Lab Information

Madhukar Pai (MD/PhD)

Senior Scientist
Centre for Outcomes Research and Evaluation
Department of Epidemiology, Biostatistics and Occupational Health (McGill)

Research Profile

 Fundamental: 0%
 Clinical: 0%
 Epidemiology: 100%
 Evaluation: 0%
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Tuberculosis • diagnostics • epidemiology • global health • implementation research

Research Interests

My research focuses on tuberculosis. It is a major threat to human health, with 9 million new cases and 1.5 million deaths every year. I have focused my career on improving tuberculosis diagnosis and care, with research that includes evaluating diagnostics tests that could eventually be part of country-level policies, implementation of tools and policies, and improving tuberculosis care for vulnerable populations in different countries worldwide. For example, I have compared the accuracy and usefulness of new tests that can diagnose tuberculosis in a few hours to conventional techniques which may require days before results are known. I am also conducting a study using mystery patients to evaluate the quality of tuberculosis care offered by health providers in India. The overall goal of my research program is to use translational epidemiology and implementation science to support tuberculosis care and control, so that the products developed, knowledge and policies can translate into saved lives.

Team Members

Name Position

Latest Publications

  1. Oga-Omenka, C., Sassi, A., Vasquez, N. A., Baruwa, E., Rosapep, L., Daniels, B., Olusola-Faleye, B., Huria, L., Adamu, A., Johns, B., Das, J. & Pai, M. (2023). Tuberculosis service disruptions and adaptations during the first year of the COVID-19 pandemic in the private health sector of two urban settings in Nigeria-A mixed methods study. PLOS global public health, vol. 3, p. e0001618.
  2. Fatah, F. Z., Furin, J. & Pai, M. (2022). When it comes to stopping tuberculosis, what is actually "missing"?. PLOS global public health, vol. 2, p. e0000319.
  3. Bigio, J., MacLean, E., Vasquez, N. A., Huria, L., Kohli, M., Gore, G., Hannay, E., Pai, M. & Adam, P. (2022). Most common reasons for primary care visits in low- and middle-income countries: A systematic review. PLOS global public health, vol. 2, p. e0000196.
  4. Kasaeva, T., Dias, H. M. & Pai, M. (2023). Fast-tracking progress to End TB: high-level opportunities for investment and action. Lancet (London, England).
  5. McKenna, L., Frick, M., Angami, K., Dubula, V., Furin, J., Harrington, M., Hausler, H., Heitkamp, P., Herrera, R., Lynch, S., Mitnick, C. D., Moses, G. K., Ndjeka, N., Nyang'wa, B.-T., Palazuelos, L., Ulysse, P. & Pai, M. (2023). The 1/4/6x24 campaign to cure tuberculosis quickly. Nature medicine, vol. 29, p. 16-17.
  6. Lee, J. H., Garg, T., Lee, J., McGrath, S., Rosman, L., Schumacher, S. G., Benedetti, A., Qin, Z. Z., Gore, G., Pai, M. & Sohn, H. (2022). Impact of molecular diagnostic tests on diagnostic and treatment delays in tuberculosis: a systematic review and meta-analysis. BMC infectious diseases, vol. 22, p. 940.
  7. Daniels, B., Shah, D., Kwan, A. T., Das, R., Das, V., Puri, V., Tipre, P., Waghmare, U., Gomare, M., Keskar, P., Das, J. & Pai, M. (2022). Tuberculosis diagnosis and management in the public versus private sector: a standardised patients study in Mumbai, India. BMJ global health, vol. 7.
  8. Mannan, S., Oga-Omenka, C., Soman ThekkePurakkal, A., Huria, L., Kalra, A., Gandhi, R., Kapoor, T., Gunawardena, N., Raj, S., Kaur, M., Sassi, A., Pande, T., Shibu, V., Sarin, S., Singh Chadha, S., Heitkamp, P., Das, J., Rao, R. & Pai, M. (2022). Adaptations to the first wave of the COVID-19 pandemic by private sector tuberculosis care providers in India. Journal of clinical tuberculosis and other mycobacterial diseases, vol. 28, p. 100327.
  9. Zimmer, A. J., Ugarte-Gil, C., Pathri, R., Dewan, P., Jaganath, D., Cattamanchi, A., Pai, M. & Grandjean Lapierre, S. (2022). Making cough count in tuberculosis care. Communications medicine, vol. 2, p. 83.
  10. MacLean, E. L., Kohli, M., Köppel, L., Schiller, I., Sharma, S. K., Pai, M., Denkinger, C. M. & Dendukuri, N. (2022). Bayesian latent class analysis produced diagnostic accuracy estimates that were more interpretable than composite reference standards for extrapulmonary tuberculosis tests. Diagnostic and prognostic research, vol. 6, p. 11.
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