Surveillance for TB drug resistance using routine rapid diagnostic testing data: Methodological development and application in Brazil

Effectively responding to drug-resistant tuberculosis (TB) requires accurate and timely information on resistance levels and trends. In contexts where use of drug susceptibility testing has not been universal, surveillance for rifampicin-resistance — one of the core drugs in the TB treatment regimen — has relied on resource-intensive and infrequent nationally-representative prevalence surveys. The expanded availability of rapid diagnostic tests (RDTs) over the past decade has increased testing coverage in many settings, however, RDT data collected in the course of routine (but not universal) use may provide biased estimates of resistance. Here, we developed a method that attempts to correct for non-random use of RDT testing in the context of routine TB diagnosis to recover unbiased estimates of resistance among new and previously treated TB cases. Specifically, we employed statistical corrections to model rifampicin resistance among TB notifications with observed Xpert MTB/RIF (a WHO-recommended RDT) results using a hierarchical generalized additive regression model, and then used model output to impute results for untested individuals. We applied this model to case-level data from Brazil. Modeled estimates of the prevalence of rifampicin resistance were substantially higher than naïve estimates, with estimated prevalence ranging between 28-44% higher for new cases and 2-17% higher for previously treated cases. Our estimates of RR-TB incidence were considerably more precise than WHO estimates for the same time period, and were robust to alternative model specifications. Our approach provides a generalizable method to leverage routine RDT data to derive timely estimates of RR-TB prevalence among notified TB cases in settings where testing for TB drug resistance is not universal. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement S.E.B was supported by a T32 National Research Service Award (T32 A1007535). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Secondary and de-identified data from SINAN are available online on the official webpage of the Ministry of Health (MoH) of Brazil. These data can be accessed through the link: https://datasus.saude.gov.br/transferencia-de-arquivos/. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Secondary and de-identified data from SINAN are available online on the official webpage of the Ministry of Health (MoH) of Brazil. These data can be accessed through the link: https://datasus.saude.gov.br/transferencia-de-arquivos/.