Sharmistha Mishra

MD, PhD, MSc

Scientist, Li Ka Shing Knowledge Institute


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.


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.



Recent Publications

  1. Wilton, J, Mishra, S, Tan, DHS. Considerations for Using the HIRI-MSM Screening Tool to Identify MSM Who Would Benefit Most From PrEP. J. Acquir. Immune Defic. Syndr. 2017;76 (2):e58-e61. doi: 10.1097/QAI.0000000000001472. PubMed PMID:28903127 .
  2. Tuite, AR, Shaw, S, Reimer, JN, Ross, CP, Fisman, DN, Mishra, S et al.. 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. 2017; :. doi: 10.1136/sextrans-2017-053201. PubMed PMID:28705938 .
  3. Rudolf, F, Damkjær, M, Lunding, S, Dornonville de la Cour, K, Young, A, Brooks, T et al.. Influence of Referral Pathway on Ebola Virus Disease Case-Fatality Rate and Effect of Survival Selection Bias. Emerging Infect. Dis. 2017;23 (4):597-600. doi: 10.3201/eid2304.160485. PubMed PMID:28322693 PubMed Central PMC5367409.
  4. Tsang, J, Mishra, S, Rowe, J, O'Campo, P, Ziegler, C, Kouyoumdjian, FG et al.. Transitional care for formerly incarcerated persons with HIV: protocol for a realist review. Syst Rev. 2017;6 (1):29. doi: 10.1186/s13643-017-0428-4. PubMed PMID:28193290 PubMed Central PMC5307639.
  5. Khan, S, Lorway, R, Chevrier, C, Dutta, S, Ramanaik, S, Roy, A et al.. Dutiful daughters: HIV/AIDS, moral pragmatics, female citizenship and structural violence among Devadasis in northern Karnataka, India. Glob Public Health. 2017; :1-16. doi: 10.1080/17441692.2017.1280070. PubMed PMID:28102112 .
  6. Damkjær, M, Rudolf, F, Mishra, S, Young, A, Storgaard, M. Clinical Features and Outcome of Ebola Virus Disease in Pediatric Patients: A Retrospective Case Series. J. Pediatr. 2017;182 :378-381.e1. doi: 10.1016/j.jpeds.2016.11.034. PubMed PMID:27939106 .
  7. MacFadden, DR, Tan, DH, 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. ;19 (1):20791. . PubMed PMID:27665722 PubMed Central PMC5035769.
  8. Ramachandran, S, Mishra, S, Condie, N, Pickles, M. How do HIV-negative individuals in sub-Saharan Africa change their sexual risk behaviour upon learning their serostatus? A systematic review. Sex Transm Infect. 2016;92 (8):571-578. doi: 10.1136/sextrans-2015-052354. PubMed PMID:27535763 PubMed Central PMC5256375.
  9. Leligdowicz, A, Fischer, WA 2nd, Uyeki, TM, Fletcher, TE, Adhikari, NK, Portella, G et al.. Ebola virus disease and critical illness. Crit Care. 2016;20 (1):217. doi: 10.1186/s13054-016-1325-2. PubMed PMID:27468829 PubMed Central PMC4965892.
  10. Mishra, S, Boily, MC, Schwartz, S, Beyrer, C, Blanchard, JF, Moses, S et al.. 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;26 (8):557-569. doi: 10.1016/j.annepidem.2016.06.004. PubMed PMID:27421700 .
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Affiliations & Other Activities

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