COVID-19 Research

Our work in modelling the COVID-19 pandemic.

An interdisciplinary and cross-institutional group was convened by Caroline Colijn and Dan Coombs (UBC), with support from PIMS, to produce real-time models of the pandemic, focusing on British Columbia and Canada. Information about the group can be found here.

Pre-symptomatic transmission

On February 18 and 19 MAGPIE research group hosted a hackathon, using data from the coronavirus outbreak to explore epidemic modelling. As a result of some of the work done by hackathon participants, a paper has now been published in eLife on the incubation period and serial interval distribution using data from clusters in Singapore and Tianjin. The paper concludes that pre-symptomatic transmission is occuring. Read the paper here and a news article on the findings here.

Citation: Evidence for transmission of COVID-19 prior to symptom onset. Lauren C. Tindale, Michelle Coombe, Jessica E. Stockdale, Emma S. Garlock, Wing Yin Venus Lau, Manu Saraswat, Yen-Hsiang Brian Lee, Louxin Zhang, Dongxuan Chen, Jacco Wallinga, Caroline Colijn. eLife 2020;9:e57149

Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing

Wondering how effective social distancing practices will be on "flattening the curve"? Several members of the MAGPIE research group are co-authors on a preprint describing a Bayesian model estimating the impact of physical distancing measures using local data from BC. Read the paper here.

You can see the effect of different social distancing scenarios, as well as create your own scenarios and see how the pandemic changes on this shiny app (Link). An article was published in the Globe and Mail containing graphs based on these models. You can read the article here.

Citation: Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing. Sean C. Anderson, Andrew M. Edwards, Madi Yerlanov, Nicola Mulberry, Jessica E. Stockdale, Sarafa A. Iyaniwura, Rebeca C. Falcao, Michael C. Otterstatter, Michael A. Irvine, Naveed Z. Janjua, Daniel Coombs, Caroline Colijn. PLoS Computational Biology. doi:

How much leeway is there to relax Covid-19 control measures?

We estimate how much leeway there is to reduce control measures in a range of national and regional jurisdictions that have experienced different COVID-19 epidemics. The article examines the risks associated with different levels of reopening and finds a high risk of exceeding past peek sizes. The authors recommend a cautious approach to reopening that incorporates strong monitoring for changes in transmission. 

Citation: How much leeway is there to relax COVID-19 control measures? Sean C. Anderson, Nicola Mulberry, Andrew M. Edwards, Jessica E. Stockdale, Sarafa A. Iyaniwura, Rebeca C. Falcao, Michael C. Otterstatter, Naveed Z. Janjua, Daniel Coombs, Caroline Colijn. Epidemics Vol 35, June 2021. doi:

Long time frames to detect the impact of changing Covid-19 control measures

We explored the time frame between a change in COVID-19 measures at the population level and the observable impact of such a change on cases. This study used data from British Columbia, Canada and found that it takes three weeks or more to detect a substantial difference in case counts after a change in population level control measures.

Citation: Long time frames to detect the impact of changing COVID-19 control measures. Jessica E Stockdale, Renny Doig, Joosung Min, Nicola Mulberry, Liangliang Wang, Lloyd T Elliott, Caroline Colijn. medRxiv 2020.06.14.20131177; doi:

Event-specific interventions to minimize COVID-19 transmission

With the lack of a Covid-19 treatment or vaccine, interventions such as hand washing, masks, social distancing, and "social bubbles" are used to limit community transmission. In a now published paper, we provide a quantitative framework to determine which interventions are likely to have the most impact in which settings and introduce the concept of "event R", the expected number of new infections due to the presence of a single infected individual at an event. We obtain a fundamental relationship between event R and four parameters: transmission intensity, duration of exposure, the proximity of individuals, and the degree of mixing. We use reports of small outbreaks to establish event R and transmission intensity in a range of settings. This information can be used to re-open economies with principled measures to reduce COVID-19 transmission.

Citation: Event-specific interventions to minimize COVID-19 transmission. Paul Tupper, Madi Yerlanov, Himani Boury, Caroline Colijn. Proceedings of the National Academy of Sciences of the United States of America Dec 2020, 117 (50) 32038-32045; DOI: 10.1073/pnas.2019324117

More COVID-19 research

Estimation of SARS-CoV-2 antibody prevalence through serological uncertainty and daily incidence

L. Wang, J. Min, R. Doig, L.T. Elliott, C. Colijn. (August 4, 2022). Canadian J. Statistics; doi:

Multi-site disease analytics with applications to estimating COVID-19 undetected cases in Canada

M.R.P. Parker, J. Cao, L.L.E. Cowen, L.T. Elliott, J. Ma. (July 12, 2022). medRxiv; doi:

Spike Mutation Profiles Associated With SARS-CoV-2 Breakthrough Infections in Delta Emerging and Predominant Time Periods in British Columbia, Canada

C.D. Fibke, Y. Joffres, J.R. Tyson, C. Colijn, N.Z. Janjua, C. Fjell, N. Prystajecky, A. Jassem, H. Sbihi. (July 4, 2022). Frontiers in Public Health, 10:915363; doi:

COVID-19 cluster size and transmission rates in schools from crowdsourced case reports

P. Tupper, S. Pai, COVID Schools Canada, C. Colijn. (June 13, 2022). medRxiv; doi:

Critical weaknesses in shielding strategies for COVID-19

C.A. Smith, C.A. Yates, B. Ashby. (April 26, 2022). PLoS Global Public Health, 2(4):e0000298; doi:

Mathematical modeling of COVID-19 in British Columbia: An age-structured model with time-dependent contact rates

S.A. Iyaniwura, R.C. Falcão, N. Ringa, P.A. Adu, M. Spencer, M. Taylor, C. Colijn, D. Coombs, N.Z. Janjua, M.A. Irvine, M. Otterstatter. (9 April 2022). Epidemics, 39, 100559.

The need for linked genomic surveillance of SARD-CoV-2

C. Colijn, D.J.D. Earn, J. Dushoff, N.H. Ogden, M. Li, N. knox, G. Van Domselaar, K. Franklin, G. Jolly, S.P. Otto. (April 6, 2022). Canadian Communicable Disease Report, 48(4):131-139; doi:

Cov2clusters: genomic clustering of SARS-CoV-2 sequences

B. Sobkowiak, K. Kamelian, J.E.A. Zlosnik, J. Tyson, A. Gonçalves da Silva, L.M.N. Hoang, N. Prystajecky, C. Colijn. (March 15, 2022). medRxiv; doi:

Genomic epidemiology offers high resolution estimates of serial intervals for COVID-19

J.E. Stockdale, K. Susvitasari, P. Tupper, B. Sobkowiak, N. Mulberry, A. Gonçalves da Silva, A.E. Watt, N. Sherry, C. Minko, B.P. Howden, C.R. Lane, C. Colijn. (March 3, 2022). medRxiv; doi:

Quantifying transmissibility of SARS-CoV-2 and impact of intervention within long-term healthcare facilities

J.E. Stockdale, S. Anderson, A. Edwards, S. Iyaniwura, N. Mulberry, M. Otterstatter, N.Z. Janjua, D. Coombs, C. Colijn, M. Irvine. (January 12, 2022). Royal Society Open Science, 9(1), 211710.

Antigenic evolution of SARS-CoV-2 in immunocompromised hosts

C.A. Smith, B. Ashby. (January 1, 2022). medRxiv; doi:

COVID-19 endgame: from pandemic to endemic? Vaccination, reopening and evolution in a well-vaccinated population

E.B. Are, Y. Song, J.E. Stockdale, P. Tupper, C. Colijn. (December 19, 2021). medRxiv; doi:

Fundamental limitations of contact tracing for COVID-19

P. Tupper, S.P. Otto, C. Colijn. (December 2, 2021). FACETS, 6(): 1993-2001.

Under-reporting of COVID-19 in the Northern Health Authority region of British Columbia

M.R.P. Parker, Y. Li, L.T. Elliott, J. Ma, L.L.E. Cowen. (November 1, 2021). The Canadian Journal of Statistics, 49(4):1018-1038; doi:

Vaccine rollout strategies: The case for vaccinating essential workers early

N. Mulberry, P. Tupper, E. Kirwin, C. McCabe, C. Colijn. (October 13, 2021). PLOS Global Public Health 1(10): e0000020

Long time frames to detect the impact of changing COVID-19 measures, Canada, March to July 2020

J.E. Stockdale, R. Doig, J. Min, N. Mulberry, L. Wang, L.T. Elliot, C. Colijn. (October 7, 2021). Eurosurveillance, 26(40):2001204; doi:

COVID-19’s unfortunate events in schools: mitigating classroom clusters in the context of variable transmission.

P. Tupper, C. Colijn. (July 8, 2021). PLOS Computational Biology 17(7): e1009120.

Modelling the impact of household size distribution on the transmission dynamics of COVID-19

P. Liu, L. McQuarrie, Y. Song, C. Colijn. (April 28, 2021). J. R. Soc. Interface.182021003620210036

Projected spread of COVID-19’s second wave in South Africa under different levels of lockdown

E.B. Are, C. Colijn. (January 26, 2021). medRxiv; doi:

Long-Term Persistence of Spike Antibody and Predictive Modeling of Antibody Dynamics Following Infection with SARS-CoV-2.

L. Grandjean, A. Saso, A.T. Ortiz, T. Lam, J. Hatcher, R. Thistlethwayte, M. Harris, T. Best, M. Johnson, H. Wagstaffe, E. Ralph, A. Mai, C. Colijn, J. Breuer, M. Buckland, K. Gilmour, D. Goldblatt, the Co-Stars Study Team. (November 23, 2020). medRxiv; doi:

Humoral Response Dynamics Following Infection with SARS-CoV-2.

L. Grandjean, A. Saso, A.T. Ortiz, T. Lam, J. Hatcher, R. Thistlethwaite, M. Harris, T. Best, M. Johnson, H. Wagstaffe, E. Ralph, A. Mai, C. Colijn, J. Breuer, M. Buckland, K. Gilmour, D. Goldblatt, The Co-Stars Study Team. (July 22, 2020). medRxiv 2020.07.16.20155663; doi: