Jesse is a third-year PhD student working with Sharmistha (NSERC CGS-D). Jesse first joined the team in April 2018 as research staff (data scientist: mathematical modeler), after a background in biomedical engineering (MASc 2017, BEng 2015; University of Guelph). His previous work focused on automated segmentation of brain MRI and analysis of digital histopathology, using a combination of classic image processing techniques and machine learning algorithms.
Jesse’s PhD work examines how different representations of sex work in deterministic models of HIV transmission can influence the outputs of those models, applied to Southern/Eastern Africa. More generally, Jesse is interested in developing new mathematical models of epidemiologic phenomena and incorporating them into transmission models. Previously, Jesse has examined: how turnover of individuals between risk groups could influence the importance of reaching key populations with care; how assumptions about who is reached by the ART cascade of care can influence the epidemic impact of achieving “90-90-90”; what have been the structural characteristics of deterministic HIV transmission models applied to assess ART scale-up in Sub-Saharan Africa (systematic review); and has helped support other similar work within the team.
Jesse also helps support the team’s COVID-19 modelling work, including developing new methods for: recovering the period of infectiousness from more commonly available infectious disease data; and modelling complex age-geographic contact patterns associated with recurrent mobility (e.g. to/from work).
In his spare time, Jesse likes to go backcountry camping, pester you to try LaTeX, and tweet at politicians about the climate crisis.
Jesse’s publications with the team include research related to heterogeneity and HIV/STI epidemic dynamics
- Knight J, Kaul R, Mishra S. (2021). Risk heterogeneity in compartmental HIV transmission models of ART as prevention in Sub-Saharan Africa: A scoping review. [Preprint available].
- Knight J, Baral S, Schwartz S, Wang L, Ma H, Young K, Hausler H, Mishra S. (2020). Contribution of high risk groups’ unmet needs may be underestimated in epidemic models without risk turnover: a mechanistic modelling analysis. Infect Dis Model, 5, 549-562. doi: 10.1016/j.idm.2020.07.004.
- Mishra S, Silhol R, Knight J, Phaswanamafuya N, Diouf D, Wang L, Schwartz S, Boily MC, Baral S. Estimating the epidemic consequences of HIV prevention gaps among key populations. J Int AIDS Soc. 2021.
- 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. (2021). Mathematical modelling of the influence of serosorting on the population-level HIV transmission impact of pre-exposure prophylaxis. AIDS. doi: 10.1097/QAD.0000000000002826.
- Wang L, Moqueet N, Lambert G, Grace D, Rodrigues R, Cox J, Lachowsky NJ, Noor SW, Armstrong HL, Tan DH, Burchell AN, Ma H, Apelian H, Knight J, Messier-Peet M, Jollimore J, Baral SD, Hart TA, Moore DM, Mishra S. (2019). 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. Epub ahead of print. doi:10.1093/aje/kwz231.
Research related to SARS-CoV-2 transmission modeling and epidemiology
- Knight J, Mishra S. (2020). Estimating effective reproduction number using generation time versus serial interval, with application to COVID-19 in the Greater Toronto Area, Canada. Infect dis model, 5, 889-896. doi: 10.1016/j.idm.2020.10.009.
Other research with the lab
- Landsman D, Ma H, Knight J, Gough K, Mishra S. (2019). A flexible integer linear programming formulation for scheduling clinician on-call service in hospitals. [Preprint available].