Sharmistha Mishra

MD, PhD, MSc



Dr. Sharmistha Mishra is an infectious disease physician and mathematical modeler. After completing medical school and residency training (Internal Medicine, Infectious Diseases) at the University of Toronto, she obtained a Masters of Science degree in epidemiology and a Doctor of Philosophy in mathematical modelling at Imperial College London. She joined St. Michael’s Hospital in September 2014. She was also involved in the 2014-2015 Ebola response in Sierra Leone, as a consultant with the World Health Organization, from December 2014 to July 2015.

Graduate trainee supervisory appointments:

1. Institute of Medical Sciences
2. Dalla Lana School of Public Health Institute of Health Policy, Management, and Evaluation.

Mathematical modeling and epidemiology for HIV/STI Program Science

Our research focuses on answering questions about the biological, behavioural, and environmental (health systems and structural) mechanisms that underpin HIV and other sexually transmitted infection (STI) epidemics in different geo-social contexts. We develop and integrate mathematical models with the best available data to test hypotheses and to better inform clinical, programmatic, and policy decisions under a Program Science framework. We collaborate with the Ontario HIV Applied Epidemiology Unit, Public Health Ontario, and Winnipeg Regional Health Authority. We work closely with the Toronto Clinical HIV Prevention Unit, Centre for Global Public Health (University of Manitoba), HIV Modeling Consortium and the HPTN Modeling Centre (Imperial College), Karnataka Health Promotion Trust, Kenya HIV Technical Support Unit, Ukrainian Institute of Social Research, Johns Hopkins University Center for Public Health and Human Rights Key Population Program, and with program implementers and persons living with – and communities affected by – HIV/STIs in Canada (Ontario, Manitoba), India, Kenya, South Africa, and Ukraine.

Our objectives are to:

1) Appraise HIV/STI Epidemics (“know your epidemic”): to understand why HIV/STI epidemics establish and persist where and when they do, and what leads to differences in their trajectories, size, and characteristics across regions.

2) Maximize HIV/STI Program Impact (“plan the response”): to optimize the design and delivery of HIV/STI programs by health-system and epidemic context.

3) Forecast Data Priorities (“monitor and adapt the response”): to systematically assess the influence of data uncertainty on model projections in order to prioritize future data collection.

We have recently engaged in operational, clinical, and mathematical modeling studies on Ebola transmission and health-systems effects in Sierra Leone, and on tuberculosis transmission in urban India.

Our research is funded by CIHR, OHTN, NIH, and USAID.  Learn more about what we do via the IMS Raw Talk Podcast 


The team is recruiting data scientists (analysts and modelers), post-doctoral fellows, and welcomes graduate students at all levels and from diverse fields (computer science, physics, engineering, mathematics, epidemiology, statistics, geography, ecology, medicine, etc.) for supervision as part of IMS or IHPME. Students with quantitative and computer programming skills (in scripting and/or programming languages) and strong interest in mathematical modeling of HIV/STIs, complex adaptive systems, infectious disease epidemiology, classical epidemiology, statistics, data science, data visualization, or those interested in systematic reviews and meta-analyses to better inform modeling studies, are encouraged to touch base with us anytime.

Please note: Dr. Mishra’s lab will not be able to supervise summer students.


  1. Mishra S, Boily MC, Shwartz S, Blanchard JF, Moses S, Vickerman P, Alary M, Baral SB. (2016). Data and methodological needs to characterize the role of sex work and to inform HIV programs in generalized HIV epidemics: evidence to challenge assumptions. Annals of Epidemiology. 26(8): 557-69. PMID: 27421700
  2. Mishra S, Pickles M, Blanchard JF,Moses S, Shubber Z, Boily MC (2014). Validation of the Modes of Transmission model as a tool to guide HIV prevention policies: a comparative modeling analysis. PLoS One 9(7): e101690. doi:10.1371/journal.pone.0101690 PMID: 25014543
  3. Boily MC, Pickles M, Alary M, Baral SD, Blanchard JF, Moses S, Vickerman P, Mishra S (2015). How big can a concentrated HIV epidemic get and what does it mean for West and Central Africa? Insights from mathematical modelling. JAIDS 68: 74-82. PMID: 25723994
  4. Mishra S, Pickles M, Blanchard JF, Moses S, Boily MC. (2014). Distinguishing the sources of HIV transmission from the distribution of newly acquired HIV infections: why is it important for HIV prevention planning? Sex Transm Infect. 90(1):19-25. PMID: 24056777
  5. Mishra S , Mountain E , Pickles M , Vickerman P , Shastri S , Gilks C , Dhingra NK , Washington R , Becker ML , Blanchard JF , Alary M , Boily MC, for the Strategic Epi-ART in India Modelling Team. (2014). Exploring the population-level impact of antiretroviral treatment: the influence of baseline intervention context. AIDS. 27:S307–S318 PMID: 24468948
  6. Tuite A, Shaw S, Reimer J, Ross C, Fisman D, Mishra S. (2017). Can enhanced screening of men with a history of prior syphilis infection stem the epidemic in men who have sex with men? A mathematical modelling study. Sex Transm Infect. Epub ahead of print: doi: 10.1136/sextrans-2017-053201 PMID: 28705938
  7. Wilton J, Mishra S, Tan DHS.(2017). Considerations for using the HIRI-MSM tool to identify MSM who would benefit most from PrEP. JAIDS. 76(2): e58-e61. PMID: 28903127
  8. MacFadden D, Tan D, Mishra S. (2016). Optimizing HIV pre-exposure prophylaxis implementation among men who have sex with men in large, urban cities: A dynamic modeling study. J Int AIDS Soc. 19(1): 20791. PMID: 27665722
  9. Mattia JJ, Vandy MJ, Chang J, Platt DE, Bausch DG, Brooks T, Conteh S, Fowler RA, Kamara AP, Kang C, Mahadevan S, Mansaray Y, Marcell L, McKay G, O’Dempsey T, Parris V, Rangel A, Salam AP, Shantha J, Wolfman V, Yeh S, Chan AK, Mishra S (2016). Early clinical sequelae of Ebola virus disease during in Sierra Leone. Lancet ID. 15:489-92. PMID: 26725449
  10. Kamara MH, Najjemba R, van Griensven J, Yorpoi D, Jimissa AS, Chan AK, Mishra S. (2017). Increase in acute malnutrition in children following the 2014-2015 Ebola outbreak in rural Sierra Leone. Public Health Action. 21:27-33. PMID: 28744436

Affiliations & Other Activities

  • Clinician Scientist, Division of Infectious Disease, Department of Medicine, St. Michael’s Hospital
  • Assistant Professor, Department of Medicine, University of Toronto