<!DOCTYPE article
PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.3 20210610//EN" "JATS-archivearticle1-3-mathml3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" xml:lang="en" article-type="research-article"><?properties manuscript?><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-journal-id">9203213</journal-id><journal-id journal-id-type="pubmed-jr-id">1135</journal-id><journal-id journal-id-type="nlm-ta">Clin Infect Dis</journal-id><journal-id journal-id-type="iso-abbrev">Clin Infect Dis</journal-id><journal-title-group><journal-title>Clinical infectious diseases : an official publication of the Infectious Diseases Society of America</journal-title></journal-title-group><issn pub-type="ppub">1058-4838</issn><issn pub-type="epub">1537-6591</issn></journal-meta><article-meta><article-id pub-id-type="pmid">40184184</article-id><article-id pub-id-type="pmc">12353082</article-id><article-id pub-id-type="doi">10.1093/cid/ciaf178</article-id><article-id pub-id-type="manuscript">HHSPA2074003</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Patterns in prescribing and dispensing of influenza antivirals among adults with influenza presenting to urgent care and emergency department settings, VISION Network, 2023&#x02013;2024</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Adams</surname><given-names>Katherine</given-names></name><degrees>MPH</degrees><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Garg</surname><given-names>Shikha</given-names></name><degrees>MD, MPH</degrees><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Tartof</surname><given-names>Sara Y.</given-names></name><degrees>PhD, MPH</degrees><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Irving</surname><given-names>Stephanie A.</given-names></name><degrees>MHS</degrees><xref rid="A3" ref-type="aff">3</xref></contrib><contrib contrib-type="author"><name><surname>DeSilva</surname><given-names>Malini B.</given-names></name><degrees>MD, MPH</degrees><xref rid="A4" ref-type="aff">4</xref></contrib><contrib contrib-type="author"><name><surname>Klein</surname><given-names>Nicola P.</given-names></name><degrees>MD, PhD</degrees><xref rid="A5" ref-type="aff">5</xref></contrib><contrib contrib-type="author"><name><surname>Natarajan</surname><given-names>Karthik</given-names></name><degrees>PhD</degrees><xref rid="A6" ref-type="aff">6</xref><xref rid="A7" ref-type="aff">7</xref></contrib><contrib contrib-type="author"><name><surname>Dascomb</surname><given-names>Kristin</given-names></name><degrees>MD, PhD</degrees><xref rid="A8" ref-type="aff">8</xref></contrib><contrib contrib-type="author"><name><surname>Grannis</surname><given-names>Shaun J.</given-names></name><degrees>MD, MS</degrees><xref rid="A9" ref-type="aff">9</xref></contrib><contrib contrib-type="author"><name><surname>Ong</surname><given-names>Toan C.</given-names></name><degrees>PhD</degrees><xref rid="A10" ref-type="aff">10</xref></contrib><contrib contrib-type="author"><name><surname>Salas</surname><given-names>S. Bianca</given-names></name><degrees>MPH</degrees><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Sy</surname><given-names>Lina S.</given-names></name><degrees>MPH</degrees><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Lewin</surname><given-names>Bruno</given-names></name><degrees>MD</degrees><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Qian</surname><given-names>Lei</given-names></name><degrees>PhD</degrees><xref rid="A2" ref-type="aff">2</xref></contrib><contrib contrib-type="author"><name><surname>Naleway</surname><given-names>Allison L.</given-names></name><degrees>PhD</degrees><xref rid="A3" ref-type="aff">3</xref></contrib><contrib contrib-type="author"><name><surname>Koppolu</surname><given-names>Padma D.</given-names></name><degrees>MPH</degrees><xref rid="A3" ref-type="aff">3</xref></contrib><contrib contrib-type="author"><name><surname>McEvoy</surname><given-names>Charlene E.</given-names></name><degrees>MD, MPH</degrees><xref rid="A4" ref-type="aff">4</xref></contrib><contrib contrib-type="author"><name><surname>Akinsete</surname><given-names>Omobosola</given-names></name><degrees>MBBS, MPH</degrees><xref rid="A4" ref-type="aff">4</xref></contrib><contrib contrib-type="author"><name><surname>Essien</surname><given-names>Inih</given-names></name><degrees>OD, MPH</degrees><xref rid="A4" ref-type="aff">4</xref></contrib><contrib contrib-type="author"><name><surname>Fireman</surname><given-names>Bruce</given-names></name><degrees>MA</degrees><xref rid="A5" ref-type="aff">5</xref></contrib><contrib contrib-type="author"><name><surname>Zerbo</surname><given-names>Ousseny</given-names></name><degrees>PhD</degrees><xref rid="A5" ref-type="aff">5</xref></contrib><contrib contrib-type="author"><name><surname>Jacobson</surname><given-names>Karen B.</given-names></name><degrees>MD, MPH</degrees><xref rid="A5" ref-type="aff">5</xref></contrib><contrib contrib-type="author"><name><surname>Timbol</surname><given-names>Julius</given-names></name><degrees>MS</degrees><xref rid="A5" ref-type="aff">5</xref></contrib><contrib contrib-type="author"><name><surname>Neelam</surname><given-names>Varsha</given-names></name><degrees>MPH</degrees><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Reeves</surname><given-names>Emily L.</given-names></name><degrees>MPH</degrees><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Dickerson</surname><given-names>Monica</given-names></name><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Ray</surname><given-names>Caitlin</given-names></name><degrees>MPH</degrees><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Link-Gelles</surname><given-names>Ruth</given-names></name><degrees>PhD, MPH</degrees><xref rid="A11" ref-type="aff">11</xref></contrib><contrib contrib-type="author"><name><surname>Mak</surname><given-names>Josephine</given-names></name><degrees>MPH</degrees><xref rid="A11" ref-type="aff">11</xref></contrib><contrib contrib-type="author"><name><surname>Ball</surname><given-names>Sarah W.</given-names></name><degrees>ScD</degrees><xref rid="A12" ref-type="aff">12</xref></contrib><contrib contrib-type="author"><name><surname>O'Reilly</surname><given-names>Michael</given-names></name><degrees>MD, MPH</degrees><xref rid="A13" ref-type="aff">13</xref></contrib><contrib contrib-type="author"><name><surname>Olsen</surname><given-names>Sonja J.</given-names></name><degrees>PhD</degrees><xref rid="A1" ref-type="aff">1</xref></contrib><contrib contrib-type="author"><name><surname>Tenforde</surname><given-names>Mark W.</given-names></name><degrees>MD, PhD</degrees><xref rid="A1" ref-type="aff">1</xref><xref rid="FN1" ref-type="author-notes">*</xref></contrib></contrib-group><aff id="A1"><label>1</label>Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States</aff><aff id="A2"><label>2</label>Department of Research &#x00026; Evaluation, Kaiser Permanente Southern California, Pasadena, California, United States</aff><aff id="A3"><label>3</label>Kaiser Permanente Center for Health Research, Portland, Oregon, United States</aff><aff id="A4"><label>4</label>HealthPartners Institute, Minneapolis, Minnesota, United States</aff><aff id="A5"><label>5</label>Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States</aff><aff id="A6"><label>6</label>Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States</aff><aff id="A7"><label>7</label>Medical Informatics Services, New York-Presbyterian Hospital, New York, New York, United States</aff><aff id="A8"><label>8</label>Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, United States</aff><aff id="A9"><label>9</label>Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, United States</aff><aff id="A10"><label>10</label>School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States</aff><aff id="A11"><label>11</label>Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States</aff><aff id="A12"><label>12</label>Westat, Rockville, Maryland, United States</aff><aff id="A13"><label>13</label>Rollins School of Public Health, Emory University, Atlanta, Georgia, United States</aff><author-notes><corresp id="CR1"><bold>Corresponding Author:</bold> Katherine Adams, MPH, 1600 Clifton Road, Mailstop H24-7 , Atlanta, GA 30329-4027, United States, Fax: 404.639.3866, <email>rqx6@cdc.gov</email></corresp><fn id="FN1"><label>*</label><p id="P1">Senior author</p></fn></author-notes><pub-date pub-type="nihms-submitted"><day>25</day><month>4</month><year>2025</year></pub-date><pub-date pub-type="ppub"><day>06</day><month>11</month><year>2025</year></pub-date><pub-date pub-type="pmc-release"><day>16</day><month>8</month><year>2025</year></pub-date><volume>81</volume><issue>4</issue><fpage>e172</fpage><lpage>e183</lpage><permissions><license><license-p>This work is written by (a) US Government employee(s) and is in the public domain in the US.</license-p></license></permissions><abstract id="ABS1"><sec id="S1"><title>Background:</title><p id="P2">We describe prescribing and dispensing patterns of influenza antivirals among patients with laboratory-confirmed influenza within U.S. urgent care and emergency department settings.</p></sec><sec id="S2"><title>Methods:</title><p id="P3">A retrospective cross-sectional study was conducted for encounters from four large, integrated health systems participating in the VISION network of adult patients presenting with acute respiratory illness to urgent cares or emergency departments and with positive influenza virus test results during the 2023&#x02013;2024 influenza season. The analysis was restricted to adult patients at higher risk of influenza complications based on presence of underlying medical conditions, older age, pregnancy, and severe obesity. We calculated proportions and odds of prescribed and dispensed antivirals by demographic and clinical characteristics.</p></sec><sec id="S3"><title>Results:</title><p id="P4">A total of 10,700 patient encounters were eligible for analysis. Among encounters with a positive standard molecular influenza test result (N=5,231), 58% (range across sites: 47&#x02013;64%) were prescribed antivirals, with 67% of prescribing occurring on the encounter date. Among those prescribed antivirals (N=3,050), 80% (range across sites: 75&#x02013;91%) had them dispensed, with 65% of dispensing occurring on the prescription date. Encounters among persons aged &#x02265;65 years had lower odds of same-day prescribing (0.57 [95% CI: 0.42&#x02013;0.78]) and lower odds of same-day dispensing (0.58 [95% CI: 0.36&#x02013;0.94]) compared to those 18&#x02013;49 years.</p></sec><sec id="S4"><title>Conclusions:</title><p id="P5">Gaps in antiviral treatment within urgent care and emergency department settings remain for patients at higher risk of influenza complications, notably among older adults. Strategies to improve earlier initiation of antiviral treatment may help reduce the risk of influenza-associated complications.</p></sec></abstract><kwd-group><kwd>influenza</kwd><kwd>antivirals</kwd><kwd>oseltamivir</kwd><kwd>prescribing</kwd><kwd>dispensing</kwd></kwd-group></article-meta></front><body><sec id="S5"><title>INTRODUCTION</title><p id="P6">Seasonal influenza produces considerable disease burden, with preliminary estimates of 15&#x02013;33 million medical visits, 380,000&#x02013;900,000 hospitalizations, and 17,000&#x02013;100,000 deaths in the United States during the 2023&#x02013;2024 season.<sup><xref rid="R1" ref-type="bibr">1</xref></sup> Antiviral treatment is a complementary tool to vaccination in the prevention, control, and management of seasonal influenza. Early treatment with antivirals can reduce influenza symptom duration as well as risk of some influenza-associated complications, hospitalizations, and mortality.<sup><xref rid="R2" ref-type="bibr">2</xref>-<xref rid="R5" ref-type="bibr">5</xref></sup> While appropriate use of influenza antivirals depends on multiple factors including symptom duration and illness severity, treatment is recommended as soon as possible in the United States for adult outpatients at higher risk of influenza complications who present with suspected or laboratory-confirmed influenza.<sup><xref rid="R3" ref-type="bibr">3</xref>, <xref rid="R6" ref-type="bibr">6</xref></sup></p><p id="P7">Gaps have been identified in seasonal influenza vaccine coverage by demographic characteristics such as age and race and ethnicity; however, less is known about use of influenza antivirals.<sup><xref rid="R7" ref-type="bibr">7</xref>-<xref rid="R9" ref-type="bibr">9</xref></sup> Prior research suggests regional gaps in influenza treatment, but recent evidence is limited.<sup><xref rid="R10" ref-type="bibr">10</xref></sup> Moreover, no study to date has described both influenza antiviral prescribing and dispensing practices and patient characteristics at each of these stages. Unequal structural and systemic drivers can lead to health care access and outcome differences across characteristics including age, race, ethnicity, and sex.<sup><xref rid="R11" ref-type="bibr">11</xref></sup> Prior analyses showed differences in COVID-19 antiviral treatment across demographic groups, suggesting the influence of factors such as access to care, negative interactions with healthcare services, limited dissemination of public health messaging on treatment benefits, provider bias, and educational, financial, and cultural barriers.<sup><xref rid="R12" ref-type="bibr">12</xref>, <xref rid="R13" ref-type="bibr">13</xref></sup></p><p id="P8">The VIrtual Sars-cov-2, Influenza, and Other respiratory viruses Network (VISION) is a Centers for Disease Control and Prevention (CDC)-sponsored network of health systems with integrated clinical, laboratory, and treatment data that performs studies on the epidemiology of medically attended illness related to respiratory virus infections. Using electronic health record (EHR) data from the 2023&#x02013;2024 influenza season, the primary study objective was to characterize influenza antiviral prescribing and dispensing practices among adults with laboratory-confirmed influenza presenting to emergency department (ED) and urgent care (UC) settings based on patient demographics and clinical characteristics. As a secondary objective, patterns in prescribing and dispensing were explored by influenza test type at one VISION partner healthcare system.</p></sec><sec id="S6"><title>METHODS</title><sec id="S7"><title>Setting and design</title><p id="P9">Four participating VISION partner healthcare systems (HealthPartners, Kaiser Permanente Northwest, Kaiser Permanente Northern California, and Kaiser Permanente Southern California) in five U.S. states (California, Minnesota, Oregon, Washington, and Wisconsin) contributed data to this retrospective cross-sectional study (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 1</xref>). EHR data were included from 94 urgent cares and 142 emergency departments. VISION partners performed geocoding of patient address to assign census tract-based 2020 Social Vulnerability Index (SVI) rankings.<sup><xref rid="R14" ref-type="bibr">14</xref></sup> Contributing network partners have patient memberships that have been found to be regionally representative of the general population.<sup><xref rid="R15" ref-type="bibr">15</xref>, <xref rid="R16" ref-type="bibr">16</xref></sup></p><p id="P10">These activities were reviewed and approved by institutional review boards (IRBs) at Kaiser Permanente Northwest, Kaiser Permanente Northern California, and Kaiser Permanente Southern California (45 C.F.R. part 46.101(c); 21 C.F.R. part 56). The Westat IRB determined that the activities are non-research. Patient informed consent was not required. The study followed guidelines from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).</p></sec><sec id="S8"><title>Study population</title><p id="P11">Data were analyzed from the 2023&#x02013;2024 influenza season among adult patients with acute respiratory illness (ARI)-associated ED/UC encounters and a positive influenza laboratory test. Participating VISION partners contributed complete influenza antiviral treatment data for prescribing and dispensing. Medical encounters were included if they occurred at participating partners and the patient met an ARI case definition based on <italic toggle="yes">International Classification of Diseases, 10th Revision</italic> discharge diagnosis codes (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 2</xref>). Three participating VISION partners required patient membership, and one partner included encounters from both member and non-member patients.</p><p id="P12">All patients received clinician-initiated testing for influenza and had a positive test result &#x02264;2 days before or up to 72 hours after an encounter. Influenza tests were categorized as standard molecular (reverse transcription-polymerase chain reaction [RT-PCR] and multiplex assays using nucleic acid amplification and performed on platforms associated with extended test runtimes [&#x0003e;30 minutes to several hours]), 2) rapid molecular (isothermal nucleic acid amplification and RT-PCR performed on platforms yielding results in approximately 15&#x02013;30 minutes), or 3) rapid antigen (rapid influenza diagnostic tests [RIDTs] with results available in 10&#x02013;15 minutes).<sup><xref rid="R17" ref-type="bibr">17</xref></sup> ED and UC encounters occurring within &#x02264;7 days of one another were combined by contributing partners into a single encounter (ED/UC). Data were analyzed at the encounter level to allow for unique opportunities for providers to implement influenza antiviral treatment guidelines.</p><p id="P13">Seasonal influenza vaccination data was obtained from EHRs, state immunization systems, and claims data. A person was considered to have received a 2023&#x02013;2024 seasonal influenza vaccination if they received &#x02265;1 dose on or after August 1, 2023 and at least 14 days prior to the date of the encounter.</p></sec><sec id="S9"><title>Eligibility</title><p id="P14">ARI-associated ED/UC encounters were considered eligible if the patient was aged &#x02265;18 years. Encounters were restricted to those occurring during the 2023&#x02013;2024 influenza season (October 1, 2023 to April 30, 2024).<sup><xref rid="R18" ref-type="bibr">18</xref></sup> While the Infectious Diseases Society of America (IDSA) recommends empiric antiviral treatment for adult outpatients at higher risk of influenza complications with suspected or laboratory-confirmed influenza, this analysis only included encounters with positive influenza laboratory testing.<sup><xref rid="R3" ref-type="bibr">3</xref></sup> To align with IDSA guidance on treating outpatients considered at higher risk of influenza complications, encounters were limited to patients meeting one or more of the following criteria (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 3</xref>): 1) being &#x02265;65 years old, 2) having certain underlying medical conditions documented at the encounter (hereafter, &#x0201c;higher risk-underlying medical conditions [HR-UMCs]&#x0201d;), 3) having a body mass index (BMI) indicating severe obesity (&#x02265;40 kg/m<sup>2</sup>), or 4) being pregnant on the encounter date.<sup><xref rid="R3" ref-type="bibr">3</xref></sup> Other persons considered at higher risk of influenza complications including those who were up to two weeks postpartum or residents of a nursing home/long-term care facility were not included in the criteria due to under-capture of post-partum data and because information on type of residence is not collected by VISION. Encounters were excluded if a patient received influenza antivirals prior to the encounter (within 14 days) for their current illness.</p></sec><sec id="S10"><title>Influenza antiviral treatment</title><p id="P15">VISION partners obtained antiviral treatment data by performing a search for treatment codes and text strings across electronic sources (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 1</xref>). A patient was considered to have received influenza antivirals if on or within 14 days following the encounter date they were prescribed and dispensed a medication recommended in the United States for influenza treatment (oseltamivir, zanamivir, peramivir, or baloxavir marboxil).<sup><xref rid="R6" ref-type="bibr">6</xref>, <xref rid="R19" ref-type="bibr">19</xref></sup></p></sec><sec id="S11"><title>Statistical analysis</title><p id="P16">Among all eligible encounters, demographic and clinical characteristics overall and stratified by VISION partner were described using frequencies and proportions or medians and interquartile ranges (IQRs). To assess differences across VISION partners, Chi-square tests were performed for categorical variables, and Kruskal-Wallis or Wilcoxon rank-sum tests for continuous variables (p&#x0003c;0.05 significance).</p><p id="P17">To reflect similar diagnostic practices across all contributing VISION partners, the primary analysis was restricted to encounters with positive standard molecular testing. To characterize influenza antiviral treatment practices, demographic and clinical characteristics were first described stratified into binary antiviral groups: 1) among all encounters, prescribed versus not prescribed antivirals; and 2) among those prescribed antivirals, dispensed or not dispensed antivirals. Chi-squared or Wilcoxon rank-sum tests were performed to assess significant (p&#x0003c;0.05) differences between groups. Second, to explore characteristics with evidence of an association with antiviral prescribing and/or dispensing (p&#x0003c;0.05), odds ratios (ORs) were generated using logistic regression for the following outcomes: 1) among all encounters, prescribed antivirals; 2) among those prescribed, prescribed on the same day as the encounter; 3) among those prescribed, dispensed antivirals; 4) among those dispensed, dispensed on the same day as the prescription. ORs were adjusted by VISION healthcare system, encounter setting (ED, UC, or combined ED and UC), influenza season surveillance week (to account for variation in prescribing based on influenza activity), number of HR-UMC categories, age (continuous), BMI (continuous), race and ethnicity, sex, and seasonal influenza vaccination status. Categories of race and ethnicity were included as model covariates as social constructs reflecting differences in health access and outcomes driven by structural and systemic factors.</p><p id="P18">To explore patterns in prescribing and dispensing by influenza test type, the secondary analysis was restricted to the one VISION partner performing multiple influenza test types. Descriptive results were presented by antiviral group (prescribed and dispensed, prescribed only, not prescribed), further stratified into test type performed (standard molecular, rapid molecular, or rapid antigen).</p></sec></sec><sec id="S12"><title>RESULTS</title><sec id="S13"><title>Eligibility</title><p id="P19">Among 27,081 adult ED/UC ARI encounters with positive influenza testing and occurring from October 1, 2023, to April 30, 2024, 16,381 (60%) were excluded (<xref rid="SD1" ref-type="supplementary-material">Supplementary Figure 1</xref>): 16,047 (59%) were not considered at higher risk of influenza complications, and 334 (1%) received influenza antivirals within 14 days prior to the encounter. In total, 10,700 ED/UC encounters were included.</p></sec><sec id="S14"><title>Demographic and clinical characteristics &#x02013; overall</title><p id="P20">Eligible ED/UC encounters peaked during the week starting on December 24, 2023 (<xref rid="SD1" ref-type="supplementary-material">Supplementary Figure 2</xref>). Among 10,700 eligible encounters from four VISION partners, most occurred at urban facilities (97%) and ED settings (61%) (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 4</xref>). Median age was 65 years (IQR 41&#x02013;74), with 59% female, 36% Hispanic, 37% non-Hispanic White, 16% Medicaid recipients, and 35% living in census tracts within the highest (i.e., most vulnerable) SVI quartile. Among the 7,138 eligible encounters with an antiviral medication prescription, 7,135 (99.96%) were prescribed oseltamivir while only three (&#x0003c;1%) were prescribed zanamivir (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 4</xref>).</p></sec><sec id="S15"><title>Demographic and clinical characteristics &#x02013; by VISION partner</title><p id="P21">Care setting varied across VISION partners (p&#x0003c;0.001), with one partner exclusively contributing ED encounters and three partners contributing both ED and UC encounters (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 4</xref>). Three VISION partners solely performed standard molecular influenza testing at all care settings. Across all partners, most (94&#x02013;96%) influenza testing was performed on the encounter date (<xref rid="SD1" ref-type="supplementary-material">Supplementary Figure 3</xref>). Median patient age ranged from 61&#x02013;68 years (p&#x0003c;0.001). Racial and ethnic demographics differed across VISION partners (p&#x0003c;0.001), with two partners having &#x02265;65% of encounters among non-Hispanic White patients, while another partner had a higher (49%) proportion of Hispanic patients. SVI-designated social vulnerability varied across partners (p&#x0003c;0.001), with one having higher representation of census tracts within the lowest vulnerability quartile (38%), and another having higher representation among the highest vulnerability quartile (45%). Across partners, there was significant variation in proportion of encounters with one or more categories of HR-UMCs (37&#x02013;79%, p&#x0003c;0.001).</p></sec><sec id="S16"><title>Antiviral prescribing and dispensing &#x02013; across all four contributing VISION partners</title><p id="P22">Among encounters from all contributing VISION partners with positive influenza standard molecular testing results (N=5,231), 58% were prescribed antivirals (<xref rid="T1" ref-type="table">Table 1</xref>), with 67% of prescribing occurring on the encounter date (<xref rid="F1" ref-type="fig">Figure 1</xref>). Among those prescribed antivirals (N=3,050), 80% had them dispensed (<xref rid="T1" ref-type="table">Table 1</xref>), with 65% of dispensing occurring on the prescription date (<xref rid="F2" ref-type="fig">Figure 2</xref>). Antiviral treatment practices varied across VISION partners (47&#x02013;64% prescribed, 75&#x02013;91% prescribed and dispensed, both p&#x0003c;0.001) (<xref rid="T1" ref-type="table">Table 1</xref>, <xref rid="F3" ref-type="fig">Figure 3</xref>). Encounters occurring exclusively at UCs had lower prescribing (50%) than those at EDs (61%) or combined ED/UCs (60%) (p&#x0003c;0.001); however, higher dispensing was found among UC (85%) than ED (78%) encounters (p&#x0003c;0.001).</p><p id="P23">Antiviral prescribing (p&#x0003c;0.001) and dispensing (p=0.01) varied across age groups (<xref rid="T1" ref-type="table">Table 1</xref>). Patient encounters aged &#x02265;65 years had the highest proportion prescribed antivirals (63%); however, those aged 50&#x02013;64 years had the highest proportion dispensed antivirals (85%) among those prescribed. Significant differences were also found in both prescribing and dispensing based on race and ethnicity, BMI, certain categories of HR-UMCs (cardiovascular disease, neurologic and neurodevelopment conditions), and receipt of 2023&#x02013;2024 seasonal influenza vaccination (all p&#x0003c;0.05). No significant differences in prescribing and dispensing were found among encounters with positive influenza standard molecular testing based on sex, Medicaid status, SVI, or pregnancy status (all p&#x0003e;0.05).</p></sec><sec id="S17"><title>Adjusted odds of antiviral prescribing and dispensing &#x02013; across all VISION partners</title><p id="P24">In adjusted models among patients with a positive standard influenza molecular test, patients aged 50&#x02013;64 years had higher adjusted odds (aOR 2.72 [1.63&#x02013;4.55]) of being dispensed antivirals compared with those 18&#x02013;49 years (<xref rid="F4" ref-type="fig">Figure 4</xref>). No significant differences were found in odds of prescribing and dispensing for those aged &#x02265;65 years compared to 18&#x02013;49 years. However, lower adjusted odds of being prescribed antivirals on the encounter date (aOR 0.57 [95% CI: 0.42&#x02013;0.78]) and dispensed antivirals on the prescription date (aOR 0.58 [95% CI: 0.36&#x02013;0.94]) were found for those aged &#x02265;65 years compared with those 18&#x02013;49 years (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 5</xref>).</p><p id="P25">Among other demographic and clinical characteristics, no clear patterns in prescribing and dispensing were found. Slightly higher adjusted odds of being prescribed antivirals was found for encounters among Hispanic patients (aOR 1.39 [95% CI: 1.05&#x02013;1.83]) (<xref rid="F2" ref-type="fig">Figure 2</xref>). Using BMI 18.5 to &#x0003c;25 kg/m<sup>2</sup> as the reference group, those with BMI &#x0003c;18.5 kg/m<sup>2</sup> had lower adjusted odds of dispensing (aOR 0.22 [95% CI: 0.07&#x02013;0.76]). No significant differences in adjusted odds of prescribing and dispensing were found based on number of categories of HR-UMCs.</p><p id="P26">Higher adjusted odds of prescribing (aOR 1.28 [95% CI: 1.07&#x02013;1.54]) and dispensing (aOR 1.84 [95% CI: 1.30&#x02013;2.60]) were found for those vaccinated against seasonal influenza; however, no differences were found in same-day prescribing or dispensing.</p></sec><sec id="S18"><title>Antiviral prescribing and dispensing by influenza test type within one VISION partner</title><p id="P27">In a secondary analysis among 6,142 eligible encounters from VISION partner 4, multiple types of influenza tests were performed: 19% rapid antigen (10&#x02013;15 minutes estimated test runtime), 70% rapid molecular (20 minutes), and 11% standard molecular (3&#x02013;8 hours) (<xref rid="SD1" ref-type="supplementary-material">Supplementary Tables 1</xref> and <xref rid="SD1" ref-type="supplementary-material">4</xref>).<sup><xref rid="R20" ref-type="bibr">20</xref>-<xref rid="R22" ref-type="bibr">22</xref></sup> Characteristics varied across test type, notably urbanicity, encounter setting, age, race and ethnicity, BMI, and presence of underlying medical conditions (all p&#x0003c;0.001) (<xref rid="SD1" ref-type="supplementary-material">Supplementary Table 6</xref>).</p><p id="P28">The proportion of patient encounters prescribed influenza antivirals increased as associated test runtime decreased (standard molecular 58%, rapid molecular 72%, rapid antigen 84%, p&#x0003c;0.001, <xref rid="F5" ref-type="fig">Figure 5A</xref>, <xref rid="SD1" ref-type="supplementary-material">Supplementary Table 7</xref>). Among those prescribed antivirals, proportion dispensed also increased as runtimes decreased (standard molecular 91%, rapid molecular 94%, rapid antigen 97%, p&#x0003c;0.001). These results were also consistent for same-day encounter date and prescribing (standard molecular 44%, rapid molecular 87%, rapid antigen 97%) and same-day prescribing and dispensing (standard molecular 84%, rapid molecular 90%, rapid antigen 98%) (<xref rid="F5" ref-type="fig">Figure 5B</xref>).</p></sec></sec><sec id="S19"><title>DISCUSSION</title><p id="P29">In this analysis of influenza antiviral treatment practices within four large U.S. health systems among adult patients at higher risk of influenza complications presenting with acute respiratory illness to urgent cares and emergency departments and with laboratory-confirmed influenza during the 2023&#x02013;2024 influenza season, we found heterogeneity and gaps in antiviral prescription and dispensing practices. Among all patients with positive standard molecular influenza virus test results, 58% were prescribed and 47% were dispensed antivirals. Across contributing VISION partners, antivirals were prescribed in 47&#x02013;64% of the encounters with positive influenza standard molecular testing results, and 75&#x02013;91% of those prescribed were dispensed antivirals. Treatment practices were associated with numerous factors, including encounter setting, patient age, influenza vaccination receipt, and&#x02014;at the one VISION partner performing numerous diagnostic tests&#x02014;influenza test type. Notably, no patterns in treatment practices were found based on factors such as race and ethnicity, SVI, and Medicaid status in these integrated healthcare systems.</p><p id="P30">Our analysis aligns with previous findings showing opportunities for improvement in antiviral prescribing and dispensing among outpatient populations identified at higher risk of influenza complications.<sup><xref rid="R23" ref-type="bibr">23</xref>-<xref rid="R27" ref-type="bibr">27</xref></sup> Of note in our study among older adults (&#x02265;65 years), lower odds of being prescribed antivirals on the encounter date and dispensed antivirals on the prescription date suggest barriers to early treatment initiation which could reduce antiviral therapy effectiveness. Other studies have noted challenges in treatment of older patients including lack of social and financial support, misunderstanding of appropriate medication regimens, and multiple existing prescriptions for managing chronic conditions.<sup><xref rid="R28" ref-type="bibr">28</xref>-<xref rid="R31" ref-type="bibr">31</xref></sup> Additionally, while severe obesity has been associated with higher influenza severity and mortality<sup><xref rid="R32" ref-type="bibr">32</xref>, <xref rid="R33" ref-type="bibr">33</xref></sup>, we found that only 52% of influenza patients with a BMI &#x02265;40 kg/m<sup>2</sup> were prescribed antivirals. These gaps may be driven by multiple factors, including delayed seeking of medical care and diagnosis, and provider uncertainty on treatment benefits for this population.<sup><xref rid="R34" ref-type="bibr">34</xref>, <xref rid="R35" ref-type="bibr">35</xref></sup></p><p id="P31">At a single VISION partner performing multiple influenza testing types, use of more rapid influenza diagnostic tests showed higher overall and same-day antiviral prescribing and dispensing. These results suggest a relationship between health care provider antiviral prescribing practices and earlier availability of actionable test results at the point of care. Previous studies also found that the use of antigen-based rapid influenza diagnostic tests (RIDTs) increased early prescribing of antivirals.<sup><xref rid="R36" ref-type="bibr">36</xref>-<xref rid="R39" ref-type="bibr">39</xref></sup> Other studies have suggested that rapid point-of-care testing also leads to more appropriate use of influenza treatments by reducing unnecessary antibiotics.<sup><xref rid="R40" ref-type="bibr">40</xref>, <xref rid="R41" ref-type="bibr">41</xref></sup> Despite these benefits, RIDTs have been associated with lower diagnostic sensitivity than standard molecular tests.<sup><xref rid="R42" ref-type="bibr">42</xref>-<xref rid="R44" ref-type="bibr">44</xref></sup> Consequently, IDSA recommends using higher sensitivity rapid molecular assay tests in lieu of RIDTs to balance reduced turnaround time with better performing diagnostic tests.<sup><xref rid="R3" ref-type="bibr">3</xref></sup></p><p id="P32">In our analysis, a little over half of patients presenting to emergency department or urgent care centers with symptoms of acute respiratory illness, a laboratory-confirmed influenza diagnosis, and at higher risk for influenza-associated complications due to age or presence of underlying conditions, were prescribed influenza antiviral treatment. Although we were unable to precisely characterize guideline adherence around early initiation of treatment due to lack of symptom onset dates, all patients included in our analysis had one or more risk factors for severe complications from influenza infection and many would likely have benefited clinically from antiviral treatment. Gaps found by our study in influenza antiviral utilization among patients with an indication for treatment may echo findings from other studies of the impact of geography, health insurance plans, healthcare provider characteristics, healthcare setting, health system-level policies, and patient demographics on treatment practices.<sup><xref rid="R45" ref-type="bibr">45</xref>-<xref rid="R47" ref-type="bibr">47</xref></sup> Provider perspectives may also be influenced by a lack of consensus around the benefits to influenza antiviral treatment among outpatients and those with non-severe influenza.<sup><xref rid="R4" ref-type="bibr">4</xref>, <xref rid="R48" ref-type="bibr">48</xref>-<xref rid="R50" ref-type="bibr">50</xref></sup> Additionally, our study reflects patients seen at urgent care clinics and emergency departments, where continuity of care may be lower than in primary care settings, which in turn can influence identification of higher risk patients, appropriate prescribing practices, and communication with patients on treatment benefits.<sup><xref rid="R51" ref-type="bibr">51</xref>, <xref rid="R52" ref-type="bibr">52</xref></sup></p><sec id="S20"><title>Limitations</title><p id="P33">This study has several limitations. First, this analysis reflects data captured by the VISION Network, with contributing partners predominantly comprising large, integrated managed care networks whose membership reflects populations with greater access to care. Similar analyses using expanded data sources may illuminate health disparities that are not reflected by VISION.<sup><xref rid="R10" ref-type="bibr">10</xref>, <xref rid="R12" ref-type="bibr">12</xref>, <xref rid="R53" ref-type="bibr">53</xref></sup> Second, VISION does not capture illness onset dates, precluding assessment of guideline adherence for early treatment initiation following symptom onset. These data would be particularly relevant for patients with reduced access to healthcare and delayed treatment based on demographic characteristics. Characterizing time from illness onset to encounter date may also put into context clinical decisions driving gaps in prescribing among patients with positive influenza testing and considered at higher risk of influenza complications. Additionally, VISION does not capture the time of day that medical encounters, influenza test results, and antiviral prescription and dispensing occurred, limiting diagnostic turnaround time and time-to-treatment characterization. For standard molecular diagnostic tests with shorter associated runtimes (e.g., Cepheid GeneXpert Xpress) than multi-hour tests, describing total time associated with diagnostic activities (e.g., sample collection, transportation, laboratory backlog, results interpretation) would provide a more complete understanding of diagnostic delays. Third, as influenza testing and prescribing are clinician-driven and may be influenced by site-specific guidelines, clinical presentation, illness severity, and prior testing, variation in testing and prescribing practices across VISION partners may have occurred. However, VISION does not capture data on individual medical providers or patient illness severity at presentation, limiting description of these differences. Fourth, VISION combines ED/UC encounters occurring within &#x02264;7 days of a previous encounter, limiting the ability to stratify all encounters by UC or ED setting. These settings may reflect unique populations in terms of access, care seeking, illness severity, and testing practices.</p></sec></sec><sec id="S21"><title>CONCLUSION</title><p id="P34">Gaps in antiviral prescribing and dispensing exist for adult patients at higher risk of influenza complications seen within urgent care and emergency department settings. Antiviral prescribing and dispensing practices varied by care setting, patient age, and underlying medical conditions, and&#x02014;at the one site performing different types of tests&#x02014;influenza test type. Strategies to improve earlier initiation of influenza antivirals for older, chronically ill patients along with expanded use of rapid and highly sensitive point-of-care testing in ED and UC settings could improve treatment initiation among patients with influenza.</p></sec><sec sec-type="supplementary-material" id="SM1"><title>Supplementary Material</title><supplementary-material id="SD1" position="float" content-type="local-data"><label>Supplement</label><media xlink:href="NIHMS2074003-supplement-Supplement.pdf" id="d67e720" position="anchor"/></supplementary-material></sec></body><back><ack id="S22"><title>Acknowledgements</title><p id="P35">The authors would like to recognize the CDC Health Equity Science Manuscript Development Program in partnership with Emory University for the dedicated training and collaboration that have contributed to this publication. Included we would like to acknowledge: Locola Hayes, Ian Hennessee, Jessie Hood, Corey Lipton, Naeemah Logan, Sarah Matthews, Megan O'Connor, Tony Richardson, Shawn A. Thomas, Ruiling Liu, Samantha Williams, Zefeng Zhang (CDC); Pia Valeriano, Vikki de los Reyes (Emory University, Atlanta, GA); Ed Maes.</p><sec id="S23"><title>Financial support</title><p id="P36">This study was supported by the CDC through contract 75D30121D12779 to Westat and contracts 75D30123C17595 and 75D30123C18039 to Kaiser Foundation Hospitals.</p></sec></ack><fn-group><fn fn-type="COI-statement" id="FN2"><p id="P37">Conflict of Interest Disclosures</p><p id="P38">All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. During the conduct of the study, all Westat, Kaiser Permanente Southern California Department of Research and Evaluation, and Kaiser Permanente Northern California Division of Research affiliated authors reported receiving contractual support from the CDC via payments made to their respective institutions. Additionally, all authors affiliated with Columbia University Irving Medical Center, HealthPartners Institute, Intermountain Healthcare, Kaiser Permanente Center for Health Research, Regenstrief Institute, and University of Colorado Anschutz Medical Campus reported receiving contractual support from the CDC during the conduct of the study, via subcontracts from Westat, Inc. with payments made to their respective institutions. Unrelated to the submitted work, the following disclosures were reported from the past 36 months: SYT reports contracts from GlaxoSmithKline and Pfizer. NPK reports support from Sanofi, Merck, Pfizer, Seqirus, GlaxoSmithKline, Moderna, AstraZeneca and Janssen, and is a member of Board on Population Health and Public Health Practice, National Academies of Science, Engineering, and Medicine, and was on an expert panel sponsored by International Vaccine Institute. SJG reports contracts with National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS) and NIH National Institute of Mental Health (NIHM). TCO received consulting fees from Regenstrief Institute and support for travel from Patient-Centered Outcomes Research Institute (PCORI) and Regenstrief Institute, and has a current patent: PCT/US2018/047961. LSS and LQ report contracts from GlaxoSmithKline, Moderna, and Dynavax. CEM reports support from NIH, Department of Defense (DOD), PCORI, Astra Zeneca, and GlaxoSmithKline and is a member of the American Lung Association of Minnesota Board, Minnesota Department of Health Long COVID Advisory Committee, and Minnesota Department of Health Asthma Care Advisory Committee. OZ reports grant number R01AI168373 with the National Institute of Allergy and Infectious Diseases and support from Pfizer. SWB reports contracts with University of Utah and Novavax.. No other disclosures were reported.</p></fn><fn id="FN3"><p id="P39">Disclaimer</p><p id="P40">The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the U.S. Department of Health and Human Services, the Centers for Disease Control and Prevention, or the authors&#x02019; affiliated institutions.</p></fn></fn-group><ref-list><title>References</title><ref id="R1"><label>1.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention National Center for Immunization and Respiratory Diseases</collab>. <source>Preliminary Estimated Flu Disease Burden 2023&#x02013;2024 Flu Season</source>. <year>2024</year> [<date-in-citation>accessed 2024 June 21</date-in-citation>]; Available from: <ext-link xlink:href="https://www.cdc.gov/flu-burden/php/data-vis/2023-2024.html" ext-link-type="uri">https://www.cdc.gov/flu-burden/php/data-vis/2023-2024.html</ext-link></mixed-citation></ref><ref id="R2"><label>2.</label><mixed-citation publication-type="journal"><name><surname>Hsu</surname><given-names>J</given-names></name>, <name><surname>Santesso</surname><given-names>N</given-names></name>, <name><surname>Mustafa</surname><given-names>R</given-names></name>, <etal/>
<article-title>Antivirals for treatment of influenza: a systematic review and meta-analysis of observational studies</article-title>. <source>Ann Intern Med</source>
<year>2012</year>; <volume>156</volume>: <fpage>512</fpage>&#x02013;<lpage>24</lpage>.<pub-id pub-id-type="pmid">22371849</pub-id>
</mixed-citation></ref><ref id="R3"><label>3.</label><mixed-citation publication-type="journal"><name><surname>Uyeki</surname><given-names>TM</given-names></name>, <name><surname>Bernstein</surname><given-names>HH</given-names></name>, <name><surname>Bradley</surname><given-names>JS</given-names></name>, <etal/>
<article-title>Clinical Practice Guidelines by the Infectious Diseases Society of America: 2018 Update on Diagnosis, Treatment, Chemoprophylaxis, and Institutional Outbreak Management of Seasonal Influenza</article-title>. <source>Clin Infect Dis</source>
<year>2019</year>; <volume>68</volume>: <fpage>895</fpage>&#x02013;<lpage>902</lpage>.<pub-id pub-id-type="pmid">30834445</pub-id>
</mixed-citation></ref><ref id="R4"><label>4.</label><mixed-citation publication-type="journal"><name><surname>Dobson</surname><given-names>J</given-names></name>, <name><surname>Whitley</surname><given-names>RJ</given-names></name>, <name><surname>Pocock</surname><given-names>S</given-names></name>, <name><surname>Monto</surname><given-names>AS</given-names></name>. <article-title>Oseltamivir treatment for influenza in adults: a meta-analysis of randomised controlled trials</article-title>. <source>Lancet</source>
<year>2015</year>; <volume>385</volume>: <fpage>1729</fpage>&#x02013;<lpage>37</lpage>.<pub-id pub-id-type="pmid">25640810</pub-id>
</mixed-citation></ref><ref id="R5"><label>5.</label><mixed-citation publication-type="journal"><name><surname>Malosh</surname><given-names>RE</given-names></name>, <name><surname>Martin</surname><given-names>ET</given-names></name>, <name><surname>Heikkinen</surname><given-names>T</given-names></name>, <name><surname>Brooks</surname><given-names>WA</given-names></name>, <name><surname>Whitley</surname><given-names>RJ</given-names></name>, <name><surname>Monto</surname><given-names>AS</given-names></name>. <article-title>Efficacy and Safety of Oseltamivir in Children: Systematic Review and Individual Patient Data Meta-analysis of Randomized Controlled Trials</article-title>. <source>Clin Infect Dis</source>
<year>2018</year>; <volume>66</volume>: <fpage>1492</fpage>&#x02013;<lpage>500</lpage>.<pub-id pub-id-type="pmid">29186364</pub-id>
</mixed-citation></ref><ref id="R6"><label>6.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention National Center for Immunization and Respiratory Diseases (NCIRD)</collab>. <source>Influenza Antiviral Medications: Summary for Clinicians</source>. <year>2022</year>
<month>September</month>
<day>9</day>, 2022 [<date-in-citation>accessed 2022 December 28</date-in-citation>]; Available from: <ext-link xlink:href="https://www.cdc.gov/flu/professionals/antivirals/summary-clinicians.htm" ext-link-type="uri">https://www.cdc.gov/flu/professionals/antivirals/summary-clinicians.htm</ext-link></mixed-citation></ref><ref id="R7"><label>7.</label><mixed-citation publication-type="journal"><name><surname>Black</surname><given-names>CL</given-names></name>, <name><surname>O'Halloran</surname><given-names>A</given-names></name>, <name><surname>Hung</surname><given-names>MC</given-names></name>, <etal/>
<article-title>Vital Signs: Influenza Hospitalizations and Vaccination Coverage by Race and Ethnicity-United States, 2009-10 Through 2021-22 Influenza Seasons</article-title>. <source>MMWR - Morbidity &#x00026; Mortality Weekly Report</source>
<year>2022</year>; <volume>71</volume>: <fpage>1366</fpage>&#x02013;<lpage>73</lpage>.<pub-id pub-id-type="pmid">36302226</pub-id>
</mixed-citation></ref><ref id="R8"><label>8.</label><mixed-citation publication-type="journal"><name><surname>Grohskopf</surname><given-names>LA</given-names></name>, <name><surname>Liburd</surname><given-names>LC</given-names></name>, <name><surname>Redfield</surname><given-names>RR</given-names></name>. <article-title>Addressing Influenza Vaccination Disparities During the COVID-19 Pandemic</article-title>. <source>JAMA</source>
<year>2020</year>; <volume>324</volume>: <fpage>1029</fpage>&#x02013;<lpage>30</lpage>.<pub-id pub-id-type="pmid">32930764</pub-id>
</mixed-citation></ref><ref id="R9"><label>9.</label><mixed-citation publication-type="journal"><name><surname>Kini</surname><given-names>A</given-names></name>, <name><surname>Morgan</surname><given-names>R</given-names></name>, <name><surname>Kuo</surname><given-names>H</given-names></name>, <etal/>
<article-title>Differences and disparities in seasonal influenza vaccine, acceptance, adverse reactions, and coverage by age, sex, gender, and race</article-title>. <source>Vaccine</source>
<year>2022</year>; <volume>40</volume>: <fpage>1643</fpage>&#x02013;<lpage>54</lpage>.<pub-id pub-id-type="pmid">33933316</pub-id>
</mixed-citation></ref><ref id="R10"><label>10.</label><mixed-citation publication-type="journal"><name><surname>Leon</surname><given-names>K</given-names></name>, <name><surname>McDonald</surname><given-names>MC</given-names></name>, <name><surname>Moore</surname><given-names>B</given-names></name>, <name><surname>Rust</surname><given-names>G</given-names></name>. <article-title>Disparities in influenza treatment among disabled Medicaid patients in Georgia</article-title>. <source>Am J Public Health</source>
<year>2009</year>; <volume>99</volume>
<issue>Suppl 2</issue>: <fpage>S378</fpage>&#x02013;<lpage>82</lpage>.<pub-id pub-id-type="pmid">19461106</pub-id>
</mixed-citation></ref><ref id="R11"><label>11.</label><mixed-citation publication-type="journal"><name><surname>O'Neill</surname><given-names>J</given-names></name>, <name><surname>Tabish</surname><given-names>H</given-names></name>, <name><surname>Welch</surname><given-names>V</given-names></name>, <etal/>
<article-title>Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health</article-title>. <source>J Clin Epidemiol</source>
<year>2014</year>; <volume>67</volume>: <fpage>56</fpage>&#x02013;<lpage>64</lpage>.<pub-id pub-id-type="pmid">24189091</pub-id>
</mixed-citation></ref><ref id="R12"><label>12.</label><mixed-citation publication-type="journal"><name><surname>Boehmer</surname><given-names>TK</given-names></name>, <name><surname>Koumans</surname><given-names>EH</given-names></name>, <name><surname>Skillen</surname><given-names>EL</given-names></name>, <etal/>
<article-title>Racial and Ethnic Disparities in Outpatient Treatment of COVID-19 - United States, January-July 2022</article-title>. <source>MMWR Morb Mortal Wkly Rep</source>
<year>2022</year>; <volume>71</volume>: <fpage>1359</fpage>&#x02013;<lpage>65</lpage>.<pub-id pub-id-type="pmid">36301738</pub-id>
</mixed-citation></ref><ref id="R13"><label>13.</label><mixed-citation publication-type="journal"><name><surname>Wiltz</surname><given-names>JL</given-names></name>, <name><surname>Feehan</surname><given-names>AK</given-names></name>, <name><surname>Molinari</surname><given-names>NM</given-names></name>, <etal/>
<article-title>Racial and Ethnic Disparities in Receipt of Medications for Treatment of COVID-19 - United States, March 2020-August 2021</article-title>. <source>MMWR Morb Mortal Wkly Rep</source>
<year>2022</year>; <volume>71</volume>: <fpage>96</fpage>&#x02013;<lpage>102</lpage>.<pub-id pub-id-type="pmid">35051133</pub-id>
</mixed-citation></ref><ref id="R14"><label>14.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention Agency for Toxic Substances and Disease Registry (ATSDR)</collab>. <source>CDC SVI Documentation 2020</source>. <year>2022</year> [<date-in-citation>accessed 2023 January 9</date-in-citation>]; Available from: <ext-link xlink:href="https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2020.html" ext-link-type="uri">https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2020.html</ext-link></mixed-citation></ref><ref id="R15"><label>15.</label><mixed-citation publication-type="journal"><name><surname>Davis</surname><given-names>AC</given-names></name>, <name><surname>Voelkel</surname><given-names>JL</given-names></name>, <name><surname>Remmers</surname><given-names>CL</given-names></name>, <name><surname>Adams</surname><given-names>JL</given-names></name>, <name><surname>McGlynn</surname><given-names>EA</given-names></name>. <article-title>Comparing Kaiser Permanente Members to the General Population: Implications for Generalizability of Research</article-title>. <source>Perm J</source>
<year>2023</year>; <volume>27</volume>: <fpage>87</fpage>&#x02013;<lpage>98</lpage>.<pub-id pub-id-type="pmid">37170584</pub-id>
</mixed-citation></ref><ref id="R16"><label>16.</label><mixed-citation publication-type="journal"><name><surname>Sukumaran</surname><given-names>L</given-names></name>, <name><surname>McCarthy</surname><given-names>NL</given-names></name>, <name><surname>Li</surname><given-names>R</given-names></name>, <etal/>
<article-title>Demographic characteristics of members of the Vaccine Safety Datalink (VSD): A comparison with the United States population</article-title>. <source>Vaccine</source>
<year>2015</year>; <volume>33</volume>: <fpage>4446</fpage>&#x02013;<lpage>50</lpage>.<pub-id pub-id-type="pmid">26209836</pub-id>
</mixed-citation></ref><ref id="R17"><label>17.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention National Center for Immunization and Respiratory Diseases (NCIRD)</collab>. <source>Overview of Influenza Testing Methods</source>. <year>2020</year> [<date-in-citation>accessed 2024 July 8</date-in-citation>]; Available from: <ext-link xlink:href="https://www.cdc.gov/flu/professionals/diagnosis/overview-testing-methods.htm" ext-link-type="uri">https://www.cdc.gov/flu/professionals/diagnosis/overview-testing-methods.htm</ext-link></mixed-citation></ref><ref id="R18"><label>18.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention National Center for Immunization and Respiratory Diseases (NCIRD)</collab>. <source>Weekly U.S. Influenza Surveillance Report</source>. <year>2023</year> February 16, 2024 [<date-in-citation>accessed 2024 February 21</date-in-citation>]; Available from: <ext-link xlink:href="https://www.cdc.gov/flu/weekly/index.htm" ext-link-type="uri">https://www.cdc.gov/flu/weekly/index.htm</ext-link></mixed-citation></ref><ref id="R19"><label>19.</label><mixed-citation publication-type="webpage"><collab>U.S. Food and Drug Administration</collab>. <source>Influenza (Flu) Antiviral Drugs and Related Information</source>. <year>2022</year> December 8, 2022 [<date-in-citation>accessed 2024 February 14</date-in-citation>]; Available from: <ext-link xlink:href="https://www.fda.gov/drugs/information-drug-class/influenza-flu-antiviral-drugs-and-related-information" ext-link-type="uri">https://www.fda.gov/drugs/information-drug-class/influenza-flu-antiviral-drugs-and-related-information</ext-link></mixed-citation></ref><ref id="R20"><label>20.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention National Center for Immunization and Respiratory Diseases (NCIRD)</collab>. <source>Table 3. Nucleic Acid Detection Based Tests</source>. <year>2020</year> [<date-in-citation>accessed 2024 June 25</date-in-citation>]; Available from: <ext-link xlink:href="https://www.cdc.gov/flu/professionals/diagnosis/table-nucleic-acid-detection.html" ext-link-type="uri">https://www.cdc.gov/flu/professionals/diagnosis/table-nucleic-acid-detection.html</ext-link></mixed-citation></ref><ref id="R21"><label>21.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention National Center for Immunization and Respiratory Diseases (NCIRD)</collab>. <source>Table 4. Multiplex Assays Authorized for Simultaneous Detection of Influenza Viruses and SARS-CoV-2 by FDA</source>. <year>2020</year> [<date-in-citation>accessed 2024 June 25</date-in-citation>]; Available from: <ext-link xlink:href="https://www.cdc.gov/flu/professionals/diagnosis/table-flu-covid19-detection.html" ext-link-type="uri">https://www.cdc.gov/flu/professionals/diagnosis/table-flu-covid19-detection.html</ext-link></mixed-citation></ref><ref id="R22"><label>22.</label><mixed-citation publication-type="webpage"><collab>Centers for Disease Control and Prevention National Center for Immunization and Respiratory Diseases (NCIRD)</collab>. <source>Rapid Influenza Diagnostic Tests (RIDTs)</source>. <year>2020</year> [<date-in-citation>accessed 2024 June 25</date-in-citation>]; Available from: <ext-link xlink:href="https://www.cdc.gov/flu/professionals/diagnosis/table-ridt.html" ext-link-type="uri">https://www.cdc.gov/flu/professionals/diagnosis/table-ridt.html</ext-link></mixed-citation></ref><ref id="R23"><label>23.</label><mixed-citation publication-type="journal"><name><surname>Stewart</surname><given-names>RJ</given-names></name>, <name><surname>Flannery</surname><given-names>B</given-names></name>, <name><surname>Chung</surname><given-names>JR</given-names></name>, <etal/>
<article-title>Influenza Antiviral Prescribing for Outpatients With an Acute Respiratory Illness and at High Risk for Influenza-Associated Complications During 5 Influenza Seasons-United States, 2011-2016</article-title>. <source>Clin Infect Dis</source>
<year>2018</year>; <volume>66</volume>: <fpage>1035</fpage>&#x02013;<lpage>41</lpage>.<pub-id pub-id-type="pmid">29069334</pub-id>
</mixed-citation></ref><ref id="R24"><label>24.</label><mixed-citation publication-type="journal"><name><surname>Biggerstaff</surname><given-names>M</given-names></name>, <name><surname>Jhung</surname><given-names>MA</given-names></name>, <name><surname>Reed</surname><given-names>C</given-names></name>, <name><surname>Fry</surname><given-names>AM</given-names></name>, <name><surname>Balluz</surname><given-names>L</given-names></name>, <name><surname>Finelli</surname><given-names>L</given-names></name>. <article-title>Influenza-like illness, the time to seek healthcare, and influenza antiviral receipt during the 2010-2011 influenza season-United States</article-title>. <source>The Journal of infectious diseases</source>
<year>2014</year>; <volume>210</volume>: <fpage>535</fpage>&#x02013;<lpage>44</lpage>.<pub-id pub-id-type="pmid">24731959</pub-id>
</mixed-citation></ref><ref id="R25"><label>25.</label><mixed-citation publication-type="journal"><name><surname>Havers</surname><given-names>F</given-names></name>, <name><surname>Thaker</surname><given-names>S</given-names></name>, <name><surname>Clippard</surname><given-names>JR</given-names></name>, <etal/>
<article-title>Use of influenza antiviral agents by ambulatory care clinicians during the 2012-2013 influenza season</article-title>. <source>Clin Infect Dis</source>
<year>2014</year>; <volume>59</volume>: <fpage>774</fpage>&#x02013;<lpage>82</lpage>.<pub-id pub-id-type="pmid">25034419</pub-id>
</mixed-citation></ref><ref id="R26"><label>26.</label><mixed-citation publication-type="journal"><name><surname>Vijayan</surname><given-names>V</given-names></name>, <name><surname>Jing</surname><given-names>J</given-names></name>, <name><surname>Zangwill</surname><given-names>KM</given-names></name>. <article-title>Evaluation of diagnostic and therapeutic approaches for suspected influenza A(H1N1)pdm09 infection, 2009-2010</article-title>. <source>Emerg Infect Dis</source>
<year>2012</year>; <volume>18</volume>: <fpage>1414</fpage>&#x02013;<lpage>21</lpage>.<pub-id pub-id-type="pmid">22931909</pub-id>
</mixed-citation></ref><ref id="R27"><label>27.</label><mixed-citation publication-type="journal"><name><surname>Hsieh</surname><given-names>YH</given-names></name>, <name><surname>Kelen</surname><given-names>GD</given-names></name>, <name><surname>Dugas</surname><given-names>AF</given-names></name>, <name><surname>Chen</surname><given-names>KF</given-names></name>, <name><surname>Rothman</surname><given-names>RE</given-names></name>. <article-title>Emergency Physicians' Adherence to Center for Disease Control and Prevention Guidance During the 2009 Influenza A H1N1 Pandemic</article-title>. <source>West J Emerg Med</source>
<year>2013</year>; <volume>14</volume>: <fpage>191</fpage>&#x02013;<lpage>9</lpage>.<pub-id pub-id-type="pmid">23599869</pub-id>
</mixed-citation></ref><ref id="R28"><label>28.</label><mixed-citation publication-type="journal"><name><surname>Dusetzina</surname><given-names>SB</given-names></name>, <name><surname>Besaw</surname><given-names>RJ</given-names></name>, <name><surname>Whitmore</surname><given-names>CC</given-names></name>, <etal/>
<article-title>Cost-Related Medication Nonadherence and Desire for Medication Cost Information Among Adults Aged 65 Years and Older in the US in 2022</article-title>. <source>JAMA Netw Open</source>
<year>2023</year>; <volume>6</volume>: <fpage>e2314211</fpage>.<pub-id pub-id-type="pmid">37200029</pub-id>
</mixed-citation></ref><ref id="R29"><label>29.</label><mixed-citation publication-type="journal"><name><surname>Hargis</surname><given-names>MB</given-names></name>, <name><surname>Castel</surname><given-names>AD</given-names></name>. <article-title>Improving Medication Understanding and Adherence Using Principles of Memory and Metacognition: In Press - Policy Insights from Behavioral and Brain Sciences</article-title>. <source>Policy Insights Behav Brain Sci</source>
<year>2018</year>; <volume>5</volume>: <fpage>147</fpage>&#x02013;<lpage>54</lpage>.<pub-id pub-id-type="pmid">31552287</pub-id>
</mixed-citation></ref><ref id="R30"><label>30.</label><mixed-citation publication-type="journal"><name><surname>Morgan</surname><given-names>SG</given-names></name>, <name><surname>Lee</surname><given-names>A</given-names></name>. <article-title>Cost-related non-adherence to prescribed medicines among older adults: a cross-sectional analysis of a survey in 11 developed countries</article-title>. <source>BMJ open</source>
<year>2017</year>; <volume>7</volume>: <fpage>e014287</fpage>.</mixed-citation></ref><ref id="R31"><label>31.</label><mixed-citation publication-type="journal"><name><surname>Innes</surname><given-names>GK</given-names></name>, <name><surname>Ogden</surname><given-names>CL</given-names></name>, <name><surname>Crentsil</surname><given-names>V</given-names></name>, <name><surname>Concato</surname><given-names>J</given-names></name>, <name><surname>Fakhouri</surname><given-names>TH</given-names></name>. <article-title>Prescription Medication Use Among Older Adults in the US</article-title>. <source>JAMA Intern Med</source>
<year>2024</year>.</mixed-citation></ref><ref id="R32"><label>32.</label><mixed-citation publication-type="journal"><name><surname>Zhao</surname><given-names>X</given-names></name>, <name><surname>Gang</surname><given-names>X</given-names></name>, <name><surname>He</surname><given-names>G</given-names></name>, <etal/>
<article-title>Obesity Increases the Severity and Mortality of Influenza and COVID-19: A Systematic Review and Meta-Analysis</article-title>. <source>Front Endocrinol (Lausanne)</source>
<year>2020</year>; <volume>11</volume>: <fpage>595109</fpage>.<pub-id pub-id-type="pmid">33408692</pub-id>
</mixed-citation></ref><ref id="R33"><label>33.</label><mixed-citation publication-type="journal"><name><surname>Kwong</surname><given-names>JC</given-names></name>, <name><surname>Campitelli</surname><given-names>MA</given-names></name>, <name><surname>Rosella</surname><given-names>LC</given-names></name>. <article-title>Obesity and respiratory hospitalizations during influenza seasons in Ontario, Canada: a cohort study</article-title>. <source>Clin Infect Dis</source>
<year>2011</year>; <volume>53</volume>: <fpage>413</fpage>&#x02013;<lpage>21</lpage>.<pub-id pub-id-type="pmid">21844024</pub-id>
</mixed-citation></ref><ref id="R34"><label>34.</label><mixed-citation publication-type="journal"><name><surname>Phelan</surname><given-names>SM</given-names></name>, <name><surname>Bauer</surname><given-names>KW</given-names></name>, <name><surname>Bradley</surname><given-names>D</given-names></name>, <etal/>
<article-title>A model of weight-based stigma in health care and utilization outcomes: Evidence from the learning health systems network</article-title>. <source>Obes Sci Pract</source>
<year>2022</year>; <volume>8</volume>: <fpage>139</fpage>&#x02013;<lpage>46</lpage>.<pub-id pub-id-type="pmid">35388341</pub-id>
</mixed-citation></ref><ref id="R35"><label>35.</label><mixed-citation publication-type="journal"><name><surname>Washington</surname><given-names>TB</given-names></name>, <name><surname>Johnson</surname><given-names>VR</given-names></name>, <name><surname>Kendrick</surname><given-names>K</given-names></name>, <etal/>
<article-title>Disparities in Access and Quality of Obesity Care</article-title>. <source>Gastroenterol Clin North Am</source>
<year>2023</year>; <volume>52</volume>: <fpage>429</fpage>&#x02013;<lpage>41</lpage>.<pub-id pub-id-type="pmid">37197884</pub-id>
</mixed-citation></ref><ref id="R36"><label>36.</label><mixed-citation publication-type="journal"><name><surname>D'Heilly</surname><given-names>SJ</given-names></name>, <name><surname>Janoff</surname><given-names>EN</given-names></name>, <name><surname>Nichol</surname><given-names>P</given-names></name>, <name><surname>Nichol</surname><given-names>KL</given-names></name>. <article-title>Rapid diagnosis of influenza infection in older adults: influence on clinical care in a routine clinical setting</article-title>. <source>Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology</source>
<year>2008</year>; <volume>42</volume>: <fpage>124</fpage>&#x02013;<lpage>8</lpage>.<pub-id pub-id-type="pmid">18289930</pub-id>
</mixed-citation></ref><ref id="R37"><label>37.</label><mixed-citation publication-type="journal"><name><surname>Suryaprasad</surname><given-names>A</given-names></name>, <name><surname>Redd</surname><given-names>JT</given-names></name>, <name><surname>Ricks</surname><given-names>PM</given-names></name>, <etal/>
<article-title>Effect of rapid influenza diagnostic testing on antiviral treatment decisions for patients with influenza-like illness: southwestern U.S., May-December 2009</article-title>. <source>Public Health Rep</source>
<year>2014</year>; <volume>129</volume>: <fpage>322</fpage>&#x02013;<lpage>7</lpage>.<pub-id pub-id-type="pmid">24982534</pub-id>
</mixed-citation></ref><ref id="R38"><label>38.</label><mixed-citation publication-type="journal"><name><surname>Busson</surname><given-names>L</given-names></name>, <name><surname>Mahadeb</surname><given-names>B</given-names></name>, <name><surname>De Foor</surname><given-names>M</given-names></name>, <name><surname>Vandenberg</surname><given-names>O</given-names></name>, <name><surname>Hallin</surname><given-names>M</given-names></name>. <article-title>Contribution of a rapid influenza diagnostic test to manage hospitalized patients with suspected influenza</article-title>. <source>Diagn Microbiol Infect Dis</source>
<year>2017</year>; <volume>87</volume>: <fpage>238</fpage>&#x02013;<lpage>42</lpage>.<pub-id pub-id-type="pmid">27939284</pub-id>
</mixed-citation></ref><ref id="R39"><label>39.</label><mixed-citation publication-type="journal"><name><surname>Fowlkes</surname><given-names>AL</given-names></name>, <name><surname>Steffens</surname><given-names>A</given-names></name>, <name><surname>Reed</surname><given-names>C</given-names></name>, <name><surname>Temte</surname><given-names>JL</given-names></name>, <name><surname>Campbell</surname><given-names>AP</given-names></name>. <article-title>Influenza Antiviral Prescribing Practices and the Influence of Rapid Testing Among Primary Care Providers in the US, 2009-2016</article-title>. <source>Open Forum Infect Dis</source>
<year>2019</year>; <volume>6</volume>: <fpage>ofz192</fpage>.<pub-id pub-id-type="pmid">31205973</pub-id>
</mixed-citation></ref><ref id="R40"><label>40.</label><mixed-citation publication-type="journal"><name><surname>Falsey</surname><given-names>AR</given-names></name>, <name><surname>Murata</surname><given-names>Y</given-names></name>, <name><surname>Walsh</surname><given-names>EE</given-names></name>. <article-title>Impact of rapid diagnosis on management of adults hospitalized with influenza</article-title>. <source>Arch Intern Med</source>
<year>2007</year>; <volume>167</volume>: <fpage>354</fpage>&#x02013;<lpage>60</lpage>.<pub-id pub-id-type="pmid">17242309</pub-id>
</mixed-citation></ref><ref id="R41"><label>41.</label><mixed-citation publication-type="journal"><name><surname>Brendish</surname><given-names>NJ</given-names></name>, <name><surname>Malachira</surname><given-names>AK</given-names></name>, <name><surname>Armstrong</surname><given-names>L</given-names></name>, <etal/>
<article-title>Routine molecular point-of-care testing for respiratory viruses in adults presenting to hospital with acute respiratory illness (ResPOC): a pragmatic, open-label, randomised controlled trial</article-title>. <source>Lancet Respir Med</source>
<year>2017</year>; <volume>5</volume>: <fpage>401</fpage>&#x02013;<lpage>11</lpage>.<pub-id pub-id-type="pmid">28392237</pub-id>
</mixed-citation></ref><ref id="R42"><label>42.</label><mixed-citation publication-type="journal"><name><surname>Green</surname><given-names>DA</given-names></name>, <name><surname>StGeorge</surname><given-names>K</given-names></name>. <article-title>Rapid Antigen Tests for Influenza: Rationale and Significance of the FDA Reclassification</article-title>. <source>J Clin Microbiol</source>
<year>2018</year>; <volume>56</volume>.</mixed-citation></ref><ref id="R43"><label>43.</label><mixed-citation publication-type="journal"><name><surname>Chartrand</surname><given-names>C</given-names></name>, <name><surname>Leeflang</surname><given-names>MM</given-names></name>, <name><surname>Minion</surname><given-names>J</given-names></name>, <name><surname>Brewer</surname><given-names>T</given-names></name>, <name><surname>Pai</surname><given-names>M</given-names></name>. <article-title>Accuracy of rapid influenza diagnostic tests: a meta-analysis</article-title>. <source>Ann Intern Med</source>
<year>2012</year>; <volume>156</volume>: <fpage>500</fpage>&#x02013;<lpage>11</lpage>.<pub-id pub-id-type="pmid">22371850</pub-id>
</mixed-citation></ref><ref id="R44"><label>44.</label><mixed-citation publication-type="journal"><name><surname>Merckx</surname><given-names>J</given-names></name>, <name><surname>Wali</surname><given-names>R</given-names></name>, <name><surname>Schiller</surname><given-names>I</given-names></name>, <etal/>
<article-title>Diagnostic Accuracy of Novel and Traditional Rapid Tests for Influenza Infection Compared With Reverse Transcriptase Polymerase Chain Reaction: A Systematic Review and Meta-analysis</article-title>. <source>Ann Intern Med</source>
<year>2017</year>; <volume>167</volume>: <fpage>394</fpage>&#x02013;<lpage>409</lpage>.<pub-id pub-id-type="pmid">28869986</pub-id>
</mixed-citation></ref><ref id="R45"><label>45.</label><mixed-citation publication-type="journal"><name><surname>Steinman</surname><given-names>MA</given-names></name>, <name><surname>Yang</surname><given-names>KY</given-names></name>, <name><surname>Byron</surname><given-names>SC</given-names></name>, <name><surname>Maselli</surname><given-names>JH</given-names></name>, <name><surname>Gonzales</surname><given-names>R</given-names></name>. <article-title>Variation in outpatient antibiotic prescribing in the United States</article-title>. <source>Am J Manag Care</source>
<year>2009</year>; <volume>15</volume>: <fpage>861</fpage>&#x02013;<lpage>8</lpage>.<pub-id pub-id-type="pmid">20001167</pub-id>
</mixed-citation></ref><ref id="R46"><label>46.</label><mixed-citation publication-type="journal"><name><surname>Rosenberg</surname><given-names>A</given-names></name>, <name><surname>Fucile</surname><given-names>C</given-names></name>, <name><surname>White</surname><given-names>RJ</given-names></name>, <etal/>
<article-title>Visualizing nationwide variation in medicare Part D prescribing patterns</article-title>. <source>BMC medical informatics and decision making</source>
<year>2018</year>; <volume>18</volume>: <fpage>103</fpage>.<pub-id pub-id-type="pmid">30454029</pub-id>
</mixed-citation></ref><ref id="R47"><label>47.</label><mixed-citation publication-type="journal"><name><surname>Rothberg</surname><given-names>MB</given-names></name>, <name><surname>Bonner</surname><given-names>AB</given-names></name>, <name><surname>Rajab</surname><given-names>MH</given-names></name>, <name><surname>Kim</surname><given-names>HS</given-names></name>, <name><surname>Stechenberg</surname><given-names>BW</given-names></name>, <name><surname>Rose</surname><given-names>DN</given-names></name>. <article-title>Effects of local variation, specialty, and beliefs on antiviral prescribing for influenza</article-title>. <source>Clin Infect Dis</source>
<year>2006</year>; <volume>42</volume>: <fpage>95</fpage>&#x02013;<lpage>9</lpage>.<pub-id pub-id-type="pmid">16323098</pub-id>
</mixed-citation></ref><ref id="R48"><label>48.</label><mixed-citation publication-type="journal"><name><surname>Jefferson</surname><given-names>T</given-names></name>, <name><surname>Jones</surname><given-names>MA</given-names></name>, <name><surname>Doshi</surname><given-names>P</given-names></name>, <etal/>
<article-title>Neuraminidase inhibitors for preventing and treating influenza in adults and children</article-title>. <source>Cochrane Database Syst Rev</source>
<year>2014</year>: <fpage>CD008965</fpage>.<pub-id pub-id-type="pmid">24718923</pub-id>
</mixed-citation></ref><ref id="R49"><label>49.</label><mixed-citation publication-type="journal"><name><surname>Hanula</surname><given-names>R</given-names></name>, <name><surname>Bortolussi-Courval</surname><given-names>&#x000c9;</given-names></name>, <name><surname>Mendel</surname><given-names>A</given-names></name>, <name><surname>Ward</surname><given-names>BJ</given-names></name>, <name><surname>Lee</surname><given-names>TC</given-names></name>, <name><surname>McDonald</surname><given-names>EG</given-names></name>. <article-title>Evaluation of Oseltamivir Used to Prevent Hospitalization in Outpatients With Influenza: A Systematic Review and Meta-Analysis</article-title>. <source>JAMA Intern Med</source>
<year>2024</year>; <volume>184</volume>: <fpage>18</fpage>&#x02013;<lpage>27</lpage>.<pub-id pub-id-type="pmid">37306992</pub-id>
</mixed-citation></ref><ref id="R50"><label>50.</label><mixed-citation publication-type="journal"><name><surname>Gao</surname><given-names>Y</given-names></name>, <name><surname>Zhao</surname><given-names>Y</given-names></name>, <name><surname>Liu</surname><given-names>M</given-names></name>, <etal/>
<article-title>Antivirals for treatment of non-severe influenza: a systematic review and network meta-analysis of randomized controlled trials</article-title>. <source>medRxiv</source>
<year>2024</year>: 2024.05.28.24307936.</mixed-citation></ref><ref id="R51"><label>51.</label><mixed-citation publication-type="journal"><name><surname>Barrera</surname><given-names>SC</given-names></name>, <name><surname>Cancino</surname><given-names>RS</given-names></name>, <name><surname>Barreto</surname><given-names>TW</given-names></name>. <article-title>The impact of continuity of care on antibiotic prescribing in acute otitis media</article-title>. <source>Int J Pediatr Otorhinolaryngol</source>
<year>2019</year>; <volume>126</volume>: <fpage>109616</fpage>.<pub-id pub-id-type="pmid">31376791</pub-id>
</mixed-citation></ref><ref id="R52"><label>52.</label><mixed-citation publication-type="journal"><name><surname>Te Winkel</surname><given-names>MT</given-names></name>, <name><surname>Damoiseaux-Volman</surname><given-names>BA</given-names></name>, <name><surname>Abu-Hanna</surname><given-names>A</given-names></name>, <etal/>
<article-title>Personal Continuity and Appropriate Prescribing in Primary Care</article-title>. <source>Ann Fam Med</source>
<year>2023</year>; <volume>21</volume>: <fpage>305</fpage>&#x02013;<lpage>12</lpage>.<pub-id pub-id-type="pmid">37487715</pub-id>
</mixed-citation></ref><ref id="R53"><label>53.</label><mixed-citation publication-type="journal"><name><surname>Cocoros</surname><given-names>NM</given-names></name>, <name><surname>Panucci</surname><given-names>G</given-names></name>, <name><surname>Haug</surname><given-names>N</given-names></name>, <name><surname>Maher</surname><given-names>C</given-names></name>, <name><surname>Reichman</surname><given-names>M</given-names></name>, <name><surname>Toh</surname><given-names>S</given-names></name>. <article-title>Outpatient influenza antivirals in a distributed data network for influenza surveillance</article-title>. <source>Influenza Other Respir Viruses</source>
<year>2018</year>; <volume>12</volume>: <fpage>804</fpage>&#x02013;<lpage>7</lpage>.<pub-id pub-id-type="pmid">30053342</pub-id>
</mixed-citation></ref></ref-list></back><floats-group><fig position="float" id="F1"><label>Figure 1.</label><caption><p id="P41">Days from date of encounter to influenza antiviral prescription among adult patients at higher risk of influenza complications presenting with acute respiratory illness to urgent cares or emergency departments and with positive standard molecular influenza virus test results and prescribed influenza antivirals (N=3,050), VISION Network, October 1, 2023 through April 30, 2024</p></caption><graphic xlink:href="nihms-2074003-f0001" position="float"/></fig><fig position="float" id="F2"><label>Figure 2.</label><caption><p id="P42">Days from date of influenza antiviral prescription to influenza antiviral dispensing among adult patients at higher risk of influenza complications presenting with acute respiratory illness to urgent cares or emergency departments and with positive standard molecular influenza virus test results and dispensed influenza antivirals (N=2,434), VISION Network, October 1, 2023 through April 30, 2024</p></caption><graphic xlink:href="nihms-2074003-f0002" position="float"/></fig><fig position="float" id="F3"><label>Figure 3.</label><caption><p id="P43">Prescribing and dispensing of influenza antivirals by VISION partner, VISION Network, October 1, 2023 through April 30, 2024. Data shown are among adult patients at higher risk of influenza complications presenting with acute respiratory illness to urgent cares or emergency departments and with positive standard molecular influenza virus test results.</p></caption><graphic xlink:href="nihms-2074003-f0003" position="float"/></fig><fig position="float" id="F4"><label>Figure 4.</label><caption><p id="P44">Adjusted odds ratio of prescribing and dispensing of influenza antivirals by social and clinical characteristics among adult patients at higher risk of influenza complications presenting with acute respiratory illness to urgent cares or emergency departments and with positive standard molecular influenza virus test results, VISION Network, October 1, 2023 through April 30, 2024</p><p id="P45">Abbreviations: AI/AN = American Indian or Alaska Native; BMI = body mass index; CI = confidence interval; HR-UMCs = underlying medical conditions considered to increase risk of influenza complications; NH = Non-Hispanic; PI = Pacific Islander; SVI = Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Social Vulnerability Index (2020)</p><p id="P46"><sup>a</sup> Age group models were adjusted for VISION healthcare system, encounter setting, week of the season, number of categories of higher risk underlying medical conditions considered to increase risk of influenza complications (cardiovascular disease except hypertension alone, chronic pulmonary disease including asthma, hematologic disorders including sickle cell, hepatic disorders, immunosuppressing conditions, metabolic disorders including diabetes mellitus, neurologic and neurodevelopment conditions including stroke and other cerebrovascular diseases, and renal disease), race and ethnicity, BMI (continuous), sex, and seasonal influenza vaccination status. Models for race and ethnicity were adjusted for VISION healthcare system, encounter setting, week of the season, number of categories of underlying medical conditions considered to increase risk of influenza complications, age (continuous), BMI (continuous), sex, and seasonal influenza vaccination status. Models for BMI were adjusted for VISION healthcare system, encounter setting, week of the season, number of categories of underlying medical conditions considered to increase risk of influenza complications, race and ethnicity, age (continuous), sex, and seasonal influenza vaccination status. Models for HR-UMCs were adjusted for VISION healthcare system, encounter setting, week of the season, race and ethnicity, age (continuous), BMI (continuous), sex, and seasonal influenza vaccination status. Vaccination models were adjusted for VISION healthcare system, encounter setting, week of the season, number of categories of higher risk underlying medical conditions considered to increase risk of influenza complications, race and ethnicity, age (continuous), BMI (continuous), and sex.</p><p id="P47"><sup>b</sup> BMI missing for N=457 encounters.</p></caption><graphic xlink:href="nihms-2074003-f0004" position="float"/></fig><fig position="float" id="F5"><label>Figure 5.</label><caption><p id="P48">Prescribing and dispensing of influenza antivirals, VISION Network, October 1, 2023 through April 30, 2024. Data shown are among adult patients at higher risk of influenza complications presenting with acute respiratory illness to urgent cares or emergency departments and with positive influenza virus test results, from the VISION partner performing multiple types of influenza testing by influenza test type (A), and same-day prescribing and dispensing and influenza test type (B).</p><p id="P49">5A. By influenza test type</p><p id="P50">5B. By prescribing on same day of encounter and dispensing on same day of prescription and influenza test type</p></caption><graphic xlink:href="nihms-2074003-f0005" position="float"/></fig><table-wrap position="float" id="T1"><label>Table 1.</label><caption><p id="P51">Characteristics of encounters among adult patients at higher risk of influenza complications presenting with acute respiratory illness to urgent cares or emergency departments and with positive standard molecular influenza virus test results, stratified by antiviral prescribing and dispensing group, VISION Network, October 1, 2023 through April 30, 2024</p></caption><table frame="box" rules="all"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th rowspan="3" align="left" valign="bottom" colspan="1">Characteristic</th><th colspan="8" align="center" valign="bottom" rowspan="1">Antiviral group</th></tr><tr><th colspan="4" align="center" valign="bottom" rowspan="1">Prescribing, N (row %)</th><th colspan="4" align="center" valign="bottom" rowspan="1">Dispensing, N (row %)</th></tr><tr><th align="left" valign="bottom" rowspan="1" colspan="1">Total<break/>encounters</th><th align="left" valign="bottom" rowspan="1" colspan="1">Not<break/>prescribed</th><th align="left" valign="bottom" rowspan="1" colspan="1">Prescribed<sup><xref rid="TFN2" ref-type="table-fn">a</xref></sup></th><th align="left" valign="bottom" rowspan="1" colspan="1">p-value<sup><xref rid="TFN3" ref-type="table-fn">b</xref></sup></th><th align="left" valign="bottom" rowspan="1" colspan="1">Total<break/>prescribed</th><th align="left" valign="bottom" rowspan="1" colspan="1">Prescribed<break/>but<break/>not<break/>dispensed</th><th align="left" valign="bottom" rowspan="1" colspan="1">Prescribed<break/>and<break/>dispensed<sup><xref rid="TFN2" ref-type="table-fn">a</xref></sup></th><th align="left" valign="bottom" rowspan="1" colspan="1">p-value<sup><xref rid="TFN3" ref-type="table-fn">b</xref></sup></th></tr></thead><tbody><tr><td align="left" valign="bottom" rowspan="1" colspan="1">All ED/UC encounters</td><td align="left" valign="bottom" rowspan="1" colspan="1">5,231</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,181 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,050 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">--</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,050</td><td align="left" valign="bottom" rowspan="1" colspan="1">616 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,434 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">--</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">VISION partner</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Partner 1</td><td align="left" valign="bottom" rowspan="1" colspan="1">573</td><td align="left" valign="bottom" rowspan="1" colspan="1">241 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">332 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">332</td><td align="left" valign="bottom" rowspan="1" colspan="1">84 (25%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">248 (75%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Partner 2</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,191</td><td align="left" valign="bottom" rowspan="1" colspan="1">637 (53%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">554 (47%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">554</td><td align="left" valign="bottom" rowspan="1" colspan="1">126 (23%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">428 (77%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Partner 3</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,794</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,018 (36%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,776 (64%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,776</td><td align="left" valign="bottom" rowspan="1" colspan="1">372 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,404 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Partner 4</td><td align="left" valign="bottom" rowspan="1" colspan="1">673</td><td align="left" valign="bottom" rowspan="1" colspan="1">285 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">388 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">388</td><td align="left" valign="bottom" rowspan="1" colspan="1">34 (9%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">354 (91%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Month of encounter</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.42</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;October-November</td><td align="left" valign="bottom" rowspan="1" colspan="1">462</td><td align="left" valign="bottom" rowspan="1" colspan="1">195 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">267 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">267</td><td align="left" valign="bottom" rowspan="1" colspan="1">44 (16%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">223 (84%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;December-January</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,145</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,230 (39%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,915 (61%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,915</td><td align="left" valign="bottom" rowspan="1" colspan="1">389 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,526 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;February-March</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,283</td><td align="left" valign="bottom" rowspan="1" colspan="1">593 (46%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">690 (54%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">690</td><td align="left" valign="bottom" rowspan="1" colspan="1">147 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">543 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;April</td><td align="left" valign="bottom" rowspan="1" colspan="1">341</td><td align="left" valign="bottom" rowspan="1" colspan="1">163 (48%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">178 (52%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">178</td><td align="left" valign="bottom" rowspan="1" colspan="1">36 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">142 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Encounter setting</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Urgent care</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,161</td><td align="left" valign="bottom" rowspan="1" colspan="1">582 (50%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">579 (50%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">579</td><td align="left" valign="bottom" rowspan="1" colspan="1">88 (15%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">491 (85%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Emergency department</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,894</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,529 (39%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,365 (61%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,365</td><td align="left" valign="bottom" rowspan="1" colspan="1">514 (22%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,851 (78%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Combined ED/UC</td><td align="left" valign="bottom" rowspan="1" colspan="1">176</td><td align="left" valign="bottom" rowspan="1" colspan="1">70 (40%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">106 (60%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">106</td><td align="left" valign="bottom" rowspan="1" colspan="1">14 (13%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">92 (87%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Age, median years (IQR)</td><td align="left" valign="bottom" rowspan="1" colspan="1">66 (44&#x02013;76)</td><td align="left" valign="bottom" rowspan="1" colspan="1">64 (40&#x02013;73)</td><td align="left" valign="bottom" rowspan="1" colspan="1">68 (47&#x02013;77)</td><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1">68 (47&#x02013;77)</td><td align="left" valign="bottom" rowspan="1" colspan="1">69 (46&#x02013;80)</td><td align="left" valign="bottom" rowspan="1" colspan="1">67 (47&#x02013;76)</td><td align="left" valign="bottom" rowspan="1" colspan="1">0.02</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Age group</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.01</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;18&#x02013;49 years</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,570</td><td align="left" valign="bottom" rowspan="1" colspan="1">757 (48%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">813 (52%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">813</td><td align="left" valign="bottom" rowspan="1" colspan="1">170 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">643 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;50&#x02013;64 years</td><td align="left" valign="bottom" rowspan="1" colspan="1">758</td><td align="left" valign="bottom" rowspan="1" colspan="1">337 (44%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">421 (56%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">421</td><td align="left" valign="bottom" rowspan="1" colspan="1">62 (15%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">359 (85%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;&#x02265;65 years<sup><xref rid="TFN4" ref-type="table-fn">c</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1">2,903</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,087 (37%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,816 (63%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,816</td><td align="left" valign="bottom" rowspan="1" colspan="1">384 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,432 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Sex<sup><xref rid="TFN5" ref-type="table-fn">d</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.07</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.88</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Male</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,119</td><td align="left" valign="bottom" rowspan="1" colspan="1">846 (40%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,273 (60%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,273</td><td align="left" valign="bottom" rowspan="1" colspan="1">257 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,016 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Female</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,111</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,335 (43%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,776 (57%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,776</td><td align="left" valign="bottom" rowspan="1" colspan="1">359 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,417 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Race and ethnicity</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.02</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.02</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;American Indian or Alaska Native, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">21</td><td align="left" valign="bottom" rowspan="1" colspan="1">7 (33%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">14 (67%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">14</td><td align="left" valign="bottom" rowspan="1" colspan="1">3 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">11 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Asian, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">544</td><td align="left" valign="bottom" rowspan="1" colspan="1">189 (35%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">355 (65%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">355</td><td align="left" valign="bottom" rowspan="1" colspan="1">69 (19%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">286 (81%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Black, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">664</td><td align="left" valign="bottom" rowspan="1" colspan="1">285 (43%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">379 (57%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">379</td><td align="left" valign="bottom" rowspan="1" colspan="1">81 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">298 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Hawaiian or Pacific Islander, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">62</td><td align="left" valign="bottom" rowspan="1" colspan="1">30 (48%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">32 (52%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">32</td><td align="left" valign="bottom" rowspan="1" colspan="1">4 (12%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">28 (88%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,152</td><td align="left" valign="bottom" rowspan="1" colspan="1">465 (40%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">687 (60%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">687</td><td align="left" valign="bottom" rowspan="1" colspan="1">112 (16%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">575 (84%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Multiracial, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">128</td><td align="left" valign="bottom" rowspan="1" colspan="1">55 (43%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">73 (57%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">73</td><td align="left" valign="bottom" rowspan="1" colspan="1">23 (32%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">50 (68%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Other race, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">17</td><td align="left" valign="bottom" rowspan="1" colspan="1">7 (41%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">10 (59%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">10</td><td align="left" valign="bottom" rowspan="1" colspan="1">0 (0%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">10 (100%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Unknown race, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">5</td><td align="left" valign="bottom" rowspan="1" colspan="1">3 (60%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2 (40%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2</td><td align="left" valign="bottom" rowspan="1" colspan="1">0 (0%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2 (100%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;White, Non-Hispanic</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,498</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,071 (43%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,427 (57%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,427</td><td align="left" valign="bottom" rowspan="1" colspan="1">307 (22%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,120 (78%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Unknown race and ethnicity</td><td align="left" valign="bottom" rowspan="1" colspan="1">140</td><td align="left" valign="bottom" rowspan="1" colspan="1">69 (49%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">71 (51%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">71</td><td align="left" valign="bottom" rowspan="1" colspan="1">17 (24%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">54 (76%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Medicaid recipient<sup><xref rid="TFN6" ref-type="table-fn">e</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.15</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.45</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">4,503</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,863 (41%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,640 (59%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,640</td><td align="left" valign="bottom" rowspan="1" colspan="1">514 (19%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,126 (81%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">689</td><td align="left" valign="bottom" rowspan="1" colspan="1">305 (44%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">384 (56%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">384</td><td align="left" valign="bottom" rowspan="1" colspan="1">81 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">303 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">SVI 2020<sup><xref rid="TFN7" ref-type="table-fn">f</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.08</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.76</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Quartile 1 (low vulnerability)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,161</td><td align="left" valign="bottom" rowspan="1" colspan="1">515 (44%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">646 (56%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">646</td><td align="left" valign="bottom" rowspan="1" colspan="1">122 (19%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">524 (81%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Quartile 2</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,418</td><td align="left" valign="bottom" rowspan="1" colspan="1">594 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">824 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">824</td><td align="left" valign="bottom" rowspan="1" colspan="1">162 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">662 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Quartile 3</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,375</td><td align="left" valign="bottom" rowspan="1" colspan="1">566 (41%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">809 (59%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">809</td><td align="left" valign="bottom" rowspan="1" colspan="1">167 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">642 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Quartile 4 (high vulnerability)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,240</td><td align="left" valign="bottom" rowspan="1" colspan="1">486 (39%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">754 (61%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">754</td><td align="left" valign="bottom" rowspan="1" colspan="1">158 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">596 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">BMI category, kg/m<sup>2 <xref rid="TFN7" ref-type="table-fn">f</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;&#x0003c;18.5</td><td align="left" valign="bottom" rowspan="1" colspan="1">94</td><td align="left" valign="bottom" rowspan="1" colspan="1">34 (36%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">60 (64%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">60</td><td align="left" valign="bottom" rowspan="1" colspan="1">26 (43%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">34 (57%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;18.5 to &#x0003c;25</td><td align="left" valign="bottom" rowspan="1" colspan="1">978</td><td align="left" valign="bottom" rowspan="1" colspan="1">368 (38%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">610 (62%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">610</td><td align="left" valign="bottom" rowspan="1" colspan="1">139 (23%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">471 (77%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;25 to &#x0003c;30</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,269</td><td align="left" valign="bottom" rowspan="1" colspan="1">503 (40%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">766 (60%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">766</td><td align="left" valign="bottom" rowspan="1" colspan="1">149 (19%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">617 (81%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;30 to &#x0003c;40</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,327</td><td align="left" valign="bottom" rowspan="1" colspan="1">504 (38%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">823 (62%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">823</td><td align="left" valign="bottom" rowspan="1" colspan="1">148 (18%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">675 (82%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;&#x02265;40</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,106</td><td align="left" valign="bottom" rowspan="1" colspan="1">531 (48%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">575 (52%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">575</td><td align="left" valign="bottom" rowspan="1" colspan="1">94 (16%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">481 (84%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Number of categories of HR-UMCs<sup><xref rid="TFN4" ref-type="table-fn">c</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.32</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;0</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,898</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,248 (43%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,650 (57%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,650</td><td align="left" valign="bottom" rowspan="1" colspan="1">316 (19%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,334 (81%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;1</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,838</td><td align="left" valign="bottom" rowspan="1" colspan="1">781 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,057 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,057</td><td align="left" valign="bottom" rowspan="1" colspan="1">223 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">834 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;2</td><td align="left" valign="bottom" rowspan="1" colspan="1">314</td><td align="left" valign="bottom" rowspan="1" colspan="1">94 (30%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">220 (70%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">220</td><td align="left" valign="bottom" rowspan="1" colspan="1">53 (24%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">167 (76%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;3</td><td align="left" valign="bottom" rowspan="1" colspan="1">122</td><td align="left" valign="bottom" rowspan="1" colspan="1">40 (33%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">82 (67%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">82</td><td align="left" valign="bottom" rowspan="1" colspan="1">14 (17%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">68 (83%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;4+</td><td align="left" valign="bottom" rowspan="1" colspan="1">59</td><td align="left" valign="bottom" rowspan="1" colspan="1">18 (31%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">41 (69%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">41</td><td align="left" valign="bottom" rowspan="1" colspan="1">10 (24%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">31 (76%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Cardiovascular<sup><xref rid="TFN8" ref-type="table-fn">g</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.01</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">4,781</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,054 (43%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,727 (57%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,727</td><td align="left" valign="bottom" rowspan="1" colspan="1">533 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,194 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">450</td><td align="left" valign="bottom" rowspan="1" colspan="1">127 (28%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">323 (72%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">323</td><td align="left" valign="bottom" rowspan="1" colspan="1">83 (26%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">240 (74%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Chronic pulmonary<sup><xref rid="TFN9" ref-type="table-fn">h</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.57</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.14</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,873</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,606 (41%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,267 (59%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,267</td><td align="left" valign="bottom" rowspan="1" colspan="1">472 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,795 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,358</td><td align="left" valign="bottom" rowspan="1" colspan="1">575 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">783 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">783</td><td align="left" valign="bottom" rowspan="1" colspan="1">144 (18%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">639 (82%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Hematologic<sup><xref rid="TFN10" ref-type="table-fn">i</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.81</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.91</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">5,206</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,170 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,036 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">3,036</td><td align="left" valign="bottom" rowspan="1" colspan="1">613 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,423 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">25</td><td align="left" valign="bottom" rowspan="1" colspan="1">11 (44%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">14 (56%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">14</td><td align="left" valign="bottom" rowspan="1" colspan="1">3 (21%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">11 (79%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Hepatic</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.41</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.48</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">5,187</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,160 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,027 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">3,027</td><td align="left" valign="bottom" rowspan="1" colspan="1">610 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,417 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">44</td><td align="left" valign="bottom" rowspan="1" colspan="1">21 (48%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">23 (52%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">23</td><td align="left" valign="bottom" rowspan="1" colspan="1">6 (26%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">17 (74%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Immunosuppressing<sup><xref rid="TFN11" ref-type="table-fn">j</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.44</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.76</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">4,982</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,083 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,899 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,899</td><td align="left" valign="bottom" rowspan="1" colspan="1">587 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,312 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">249</td><td align="left" valign="bottom" rowspan="1" colspan="1">98 (39%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">151 (61%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">151</td><td align="left" valign="bottom" rowspan="1" colspan="1">29 (19%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">122 (81%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Metabolic<sup><xref rid="TFN12" ref-type="table-fn">k</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.01</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.47</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">4,687</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,983 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,704 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,704</td><td align="left" valign="bottom" rowspan="1" colspan="1">541 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,163 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">544</td><td align="left" valign="bottom" rowspan="1" colspan="1">198 (36%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">346 (64%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">346</td><td align="left" valign="bottom" rowspan="1" colspan="1">75 (22%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">271 (78%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Neurologic and neurodevelopment conditions<sup><xref rid="TFN13" ref-type="table-fn">l</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.02</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">5,003</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,103 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,900 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,900</td><td align="left" valign="bottom" rowspan="1" colspan="1">569 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,331 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">228</td><td align="left" valign="bottom" rowspan="1" colspan="1">78 (34%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">150 (66%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">150</td><td align="left" valign="bottom" rowspan="1" colspan="1">47 (31%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">103 (69%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Renal</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.01</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.33</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">5,045</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,122 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,923 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,923</td><td align="left" valign="bottom" rowspan="1" colspan="1">586 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,337 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">186</td><td align="left" valign="bottom" rowspan="1" colspan="1">59 (32%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">127 (68%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">127</td><td align="left" valign="bottom" rowspan="1" colspan="1">30 (24%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">97 (76%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Pregnant<sup><xref rid="TFN4" ref-type="table-fn">c</xref></sup></td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.08</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">0.57</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">4,942</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,075 (42%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,867 (58%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">2,867</td><td align="left" valign="bottom" rowspan="1" colspan="1">582 (20%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,285 (80%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">289</td><td align="left" valign="bottom" rowspan="1" colspan="1">106 (37%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">183 (63%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">183</td><td align="left" valign="bottom" rowspan="1" colspan="1">34 (19%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">149 (81%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Received 2023&#x02013;2024 seasonal influenza vaccination</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">&#x0003c;0.001</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;No</td><td align="left" valign="bottom" rowspan="1" colspan="1">3,150</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,406 (45%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,744 (55%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,744</td><td align="left" valign="bottom" rowspan="1" colspan="1">405 (23%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,339 (77%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Yes</td><td align="left" valign="bottom" rowspan="1" colspan="1">2,081</td><td align="left" valign="bottom" rowspan="1" colspan="1">775 (37%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,306 (63%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/><td align="left" valign="bottom" rowspan="1" colspan="1">1,306</td><td align="left" valign="bottom" rowspan="1" colspan="1">211 (16%)</td><td align="left" valign="bottom" rowspan="1" colspan="1">1,095 (84%)</td><td align="left" valign="bottom" rowspan="1" colspan="1"/></tr></tbody></table><table-wrap-foot><fn id="TFN1"><p id="P52">Abbreviations: BMI = body mass index; ED/UC = emergency department and urgent care; HR-UMCs = underlying medical conditions considered to increase risk of influenza complications; IQR = interquartile range; NH = Non-Hispanic; SVI = Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Social Vulnerability Index (2020)</p></fn><fn id="TFN2"><label>a</label><p id="P53">Includes neuraminidase inhibitors (NAIs) (Oseltamivir [Tamiflu], Peramivir [Rapivab], and Zanamivir [Relenza)]) and Baloxavir marboxil (Xofluza).</p></fn><fn id="TFN3"><label>b</label><p id="P54">Chi-square test performed for categorical and binary variables, Wilcoxon rank-sum test used for continuous variables.</p></fn><fn id="TFN4"><label>c</label><p id="P55">Criteria for being at higher risk for influenza complications. BMI was missing for N=409 standard molecular testing encounters.</p></fn><fn id="TFN5"><label>d</label><p id="P56">Sex missing for N=1 standard molecular testing encounters.</p></fn><fn id="TFN6"><label>e</label><p id="P57">Medicaid status missing for N=39 standard molecular testing encounters.</p></fn><fn id="TFN7"><label>f</label><p id="P58">SVI was missing for N=37 standard molecular testing encounters.</p></fn><fn id="TFN8"><label>g</label><p id="P59">Cardiovascular diseases include heart failure, ischemic heart disease, pulmonary embolism, heart valve, atrial fibrillation, congenital heart disease, and other heart disease, and does not include hypertension alone.</p></fn><fn id="TFN9"><label>h</label><p id="P60">Chronic pulmonary disease includes asthma, chronic obstructive pulmonary disease, and other chronic lung disease conditions.</p></fn><fn id="TFN10"><label>i</label><p id="P61">Hematologic disorders include sickle cell disease and other blood disorders.</p></fn><fn id="TFN11"><label>j</label><p id="P62">Immunosuppressing conditions include human immunodeficiency virus (HIV), hematological malignancy, other intrinsic immune condition or immunodeficiency, solid malignancy, transplant, rheumatologic/inflammatory disorders, and chronic steroid use.</p></fn><fn id="TFN12"><label>k</label><p id="P63">Metabolic disorders include diabetes mellitus and other endocrine disorders.</p></fn><fn id="TFN13"><label>l</label><p id="P64">Neurologic and neurodevelopment conditions include dementia, Down's syndrome, other neurological and musculoskeletal disorders, stroke, and other cerebrovascular disease.</p></fn></table-wrap-foot></table-wrap></floats-group></article>