Knowing whether a patient has multidrug-resistant tuberculosis is crucial for prescribing the best treatment. The challenge is choosing the most effective drug with the fewest side effects while saving the “big guns” for the most resistant infections. The best way to find out whether a patient has this type of infection is to conduct drug-susceptibility testing. Unfortunately, this testing requires laboratory capabilities that are in short supply, so often only patients at high risk are tested. But who is at high risk? A recent study found an association between patients’ locations (health center at which they were seen) and likelihood of multidrug-resistant infection. Added to other known risk factors (young age, previous TB treatment, or contact with someone with similar infection), this information can further pinpoint who should be tested, which will ultimately lead to faster diagnoses, better treatments and less spread of multidrug-resistant TB.
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.