Use of Spatial Information to Predict Multidrug Resistance in Tuberculosis Patients, Peru

Details

• Alternative Title:
  Emerg Infect Dis
• Personal Author:
  Lin, Hsien-Ho ; Shin, Sonya S. ; Contreras, Carmen ; Asencios, Luis ; Paciorek, Christopher J. ; Cohen, Ted
• Description:
  To determine whether spatiotemporal information could help predict multidrug resistance at the time of tuberculosis diagnosis, we investigated tuberculosis patients who underwent drug susceptibility testing in Lima, Peru, during 2005-2007. We found that crude representation of spatial location at the level of the health center improved prediction of multidrug resistance.
• Subjects:
  Antitubercular Agents Demography Drug Resistance, Multiple, Bacterial Humans Logistic Models Prognosis Risk Factors Roc Curve Tuberculosis, Multidrug-Resistant
• Source:
  Emerg Infect Dis. 18(5):811-813.
• Document Type:
  Journal Article
• Funding:
  DP2 OD006663/OD/NIH HHS/United States ; K23 AI054591-01/AI/NIAID NIH HHS/United States ; U19 A1076217/PHS HHS/United States ; U54 GM088558/GM/NIGMS NIH HHS/United States ; UL1 RR025758/RR/NCRR NIH HHS/United States
• Place as Subject:
  Peru
• Volume:
  18
• Issue:
  5
• Collection(s):
  Emerging Infectious Diseases
• Main Document Checksum:
  urn:sha256:cb45536265b15cc7a1baf09b206d51f537c03a67c50fad3f13616333df6f889b
• Download URL:
  https://stacks.cdc.gov/view/cdc/23911/cdc_23911_DS1.pdf
• File Type:
  [PDF - 239.00 KB ]