Sharmistha Mishra

MD, PhD, MSc



Dr. Sharmistha Mishra is an infectious disease physician and mathematical modeler and holds a Tier 2 Canadian Research Chair in Mathematical Modeling and Program Science. 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 (IMS)
  2. Dalla Lana School of Public Health Institute of Health Policy, Management, and Evaluation (IHPME)

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 Options Lab, 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, 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 also engage in operational, clinical, and mathematical modeling studies on Ebola transmission and health-systems effects in Sierra Leone, and more recently, on SARS-CoV-2 transmission in Canada.

Mathematical modeling and epidemiology of COVID-19

Our research focuses on supporting the COVID-19 epidemic responses in Canada through detailed investigation of the sources and epidemic consequences of heterogeneity in acquisition, spread and severity. The research is conducted as part of an inter-provincial collaboration with BC Centre for Disease Control, Manitoba Centre for Health Policy, Université McGill, Université Laval, Université de Montréal, and University of Calgary. We also work closely with the Knowledge Translation Program Wellness Hub, Public Health Ontario, ICES, and Johns Hopkins University.

Our objectives are to:

1) identify individual- and neighbourhood-level sources of heterogeneity in the relative risk of COVID testing, diagnoses, and severity;

2) estimate the relative contribution of individual- and neighbourhood-level heterogeneity in onward transmission over time;

3) assess the potential impact of past and existing public health measures on transmissions, detected cases, hospitalizations, and death across subsets of the population; and

4) determine the incremental impact of an adaptive suite of feasible, population-specific, nonpharmacological interventions to mitigate spread and prevent re-emergence at different levels of relaxation of universal physical distancing measures.

Our research is funded by Canadian Institutes of Health Research, Ontario HIV Treatment Network, COVID-19 Immunity Task Force, St. Michael’s Hospital Foundation, National Institute of Health, and United States Agency for International Development.  Learn more about what we do via the IMS Raw Talk Podcast.


The team is recruiting analysts and modelers, post-doctoral fellows, and welcomes graduate students at from diverse fields (health economics, epidemiology, biostatistics, physics, engineering, mathematics, geography, ecology, computer science, etc.) for potential supervision and co-supervision as part of IMS, IHPME/DLSPH. Students with quantitative and computer programming skills (in scripting and/or programming languages) and strong interest in mathematical modeling of HIV/STIs, Ebola, or SARS-CoV-2, and in complex adaptive systems, infectious disease epidemiology, classical epidemiology, statistics, data science, data visualization; or students 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 additional summer students in 2022


  1. Wang L, Moqueet N, Simkin A, Knight J, Ma H, Lachowsky NJ, Armstrong HL, Tan DHS, Burchell AN, Hart TA, Moore DM, Adam BD, MacFadden DR, Baral S, Mishra S. Mathematical modelling of the influence of serosorting on the population-level HIV transmission impact of pre-exposure prophylaxis. AIDS. 2021 Jun;35(7):1113-1125. Available from:
  2. Knight J, Mishra S. Estimating effective reproduction number using generation time versus serial interval, with application to COVID-19 in the Greater Toronto Area, Canada. Infect Dis Model. 2020 Nov;5:889-896. Available from:
  3. Wang L, Ma H, Yiu KCY, Calzavara A, Landsman D, Luong L, Chan AK, Kustra R, Kwong JC, Boily MC, Hwang S, Straus S, Baral SD, Mishra S. Heterogeneity in testing, diagnosis and outcome in SARSCoV-2 infection across outbreak settings in the Greater Toronto Area, Canada: an observational study. CMAJ Open. 2020 Oct;8(4):E627-E636. Available from:
  4. Mishra S, Wang L, Ma H, Yiu K, Paterson JM, Kim E, Schull MJ, Pequegnat V, Lee A, Ishiguro L, Coomes E, Chan A, Downing M, Landsman D, Straus S, Muller M. Estimated surge in hospital and intensive care admission because of the coronavirus disease 2019 pandemic in the Greater Toronto Area, Canada: a mathematical modelling study. CMAJ Open. 2020 Sep;8(3):E593-E604. Available from:
  5. Wang L, Moqueet N, Lambert G, Grace D, Rodrigues R, Cox J, Lachowsky NJ, Noor SW, Armstrong HL, Tan DHS, Burchell AN, Ma H, Apelian H, Knight J, Messier-Peet M, Jollimore J, Baral S, Hart TA, Moore DM, Mishra S. Population-level sexual mixing by HIV status and pre-exposure prophylaxis use among men who have sex with men in Montreal, Canada: implications for HIV prevention. Am J Epidemiol. 2020 Jan;189(1):44-54. Available from:
  6. MacFadden D, Tan D, Mishra S. Optimizing HIV pre-exposure prophylaxis implementation among men who have sex with men in a large urban centre: a dynamic modelling study. J Int AIDS Soc. 2016 Sep;19(1):20791. Available from:
  7. Mishra S, Boily MC, Schwartz S, Beyrer C, Blanchard JF, Moses S, Castor D, Phaswana-Mafuya N, Vickerman P, Drame F, Alary M, Baral SD. Data and methods to characterize the role of sex work and to inform sex work programs in generalized HIV epidemics: evidence to challenge assumptions. Ann Epidemiol. 2016 Aug;26(8):557-569. Available from:
  8. Mattia JG, Vandy MJ, Chang JC, Platt DE, Dierberg K, Bausch DG, Brooks T, Conteh S, Crozier I, Fowler RA, Kamara AP, Kang C, Mahadevan S, Mansaray Y, Marcell L, McKay G, O’Dempsey T, Parris V, Pinto R, Rangel A, Salam AP, Shantha J, Wolfman V, Yeh S, Chan AK, Mishra S. Early clinical sequelae of Ebola virus disease in Sierra Leone: a cross sectional study. Lancet Infect Dis. 2016 Mar;16(3):331-338. Available from:
  9. Mishra S, Pickles M, Blanchard JF, Moses S, Shubber Z, Boily MC. Validation of the modes of transmission model as a tool to guide HIV prevention targets: a comparative modeling analysis. PLoS One. 2014 Jul;9(7):e101690. Available from:

Affiliations & Other Activities

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