Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data

Justin Manjourides, Hsien Ho Lin, Sonya Shin, Caroline Jeffery, Carmen Contreras, Janeth Santa Cruz, Oswaldo Jave, Martin Yagui, Luis Asencios, Marcello Pagano, Ted Cohen

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

In most countries with large drug resistant tuberculosis epidemics, only those cases that are at highest risk of having MDRTB receive a drug sensitivity test (DST) at the time of diagnosis. Because of this prioritized testing, identification of MDRTB transmission hotspots in communities where TB cases do not receive DST is challenging, as any observed aggregation of MDRTB may reflect systematic differences in how testing is distributed in communities. We introduce a new disease mapping method, which estimates this missing information through probability-weighted locations, to identify geographic areas of increased risk of MDRTB transmission. We apply this method to routinely collected data from two districts in Lima, Peru over three consecutive years. This method identifies an area in the eastern part of Lima where previously untreated cases have increased risk of MDRTB. This may indicate an area of increased transmission of drug resistant disease, a finding that may otherwise have been missed by routine analysis of programmatic data. The risk of MDR among retreatment cases is also highest in these probable transmission hotspots, though a high level of MDR among retreatment cases is present throughout the study area. Identifying potential multidrug resistant tuberculosis (MDRTB) transmission hotspots may allow for targeted investigation and deployment of resources. © 2012 Elsevier Ltd. All rights reserved.
Original languageAmerican English
Pages (from-to)273-279
Number of pages7
JournalTuberculosis
DOIs
StatePublished - 1 May 2012
Externally publishedYes

Fingerprint Dive into the research topics of 'Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data'. Together they form a unique fingerprint.

  • Cite this

    Manjourides, J., Lin, H. H., Shin, S., Jeffery, C., Contreras, C., Cruz, J. S., Jave, O., Yagui, M., Asencios, L., Pagano, M., & Cohen, T. (2012). Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data. Tuberculosis, 273-279. https://doi.org/10.1016/j.tube.2012.02.003