Details:

Alternative Title:
Emerg Infect Dis
Publisher's site:
http://dx.doi.org/10.3201/eid2804.212014
Personal Author:
Winglee, Kathryn ; Hill, Andrew N. ; Langer, Adam J. ; Self, Julie L.
Winglee, Kathryn ; Hill, Andrew N. ; Langer, Adam J. ; Self, Julie L. Less -
Description:
We analyzed a pharmacy dataset to assess the 20% decline in tuberculosis (TB) cases reported to the US National Tuberculosis Surveillance System (NTSS) during the coronavirus disease pandemic in 2020 compared with the 2016-2019 average. We examined the correlation between TB medication dispensing data to TB case counts in NTSS and used a seasonal autoregressive integrated moving average model to predict expected 2020 counts. Trends in the TB medication data were correlated with trends in NTSS data during 2006-2019. There were fewer prescriptions and cases in 2020 than would be expected on the basis of previous trends. This decrease was particularly large during April-May 2020. These data are consistent with NTSS data, suggesting that underreporting is not occurring but not ruling out underdiagnosis or actual decline. Understanding the mechanisms behind the 2020 decline in reported TB cases will help TB programs better prepare for postpandemic cases.
Subjects:
[+]
Covid-19 Humans Outpatients Pandemics Pharmacy Population Surveillance Tuberculosis
Source:
Emerg Infect Dis. 2022; 28(4):820-827
Pubmed ID:
35318920
Pubmed Central ID:
PMC8962886
Document Type:
Journal Article
Place as Subject:
United States
Collection(s):
Emerging Infectious Diseases
Main Document Checksum:
[+]
urn:sha256:a0bedb461b92b7346541c905c81eb00dd2ef6d65e93a0c7e53f4936d0beb37d6
Download URL:
https://stacks.cdc.gov/view/cdc/116334/cdc_116334_DS1.pdf
File Type:

Supporting Files

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