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- Covid-19 Research
- Fundamental Limitations of Contact Tracing for COVID-19
- After vaccination: What happens next in BC
- High transmission variants: The benefits of being proactive
- Vaccinating essential workers
- Are there COVID variants amongst us?
- What if a high-transmission variant takes off?
- What to expect when schools reopen
- Parks and Bars
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.
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
Modelling the effect of social distancing measures on outbreak trajectory
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:https://doi.org/10.1371/journal.pcbi.1008274
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: https://doi.org/10.1016/j.epidem.2021.100453
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: https://doi.org/10.1101/2020.06.14.20131177
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
Quantifying transmissibility of COVID-19 and impact of intervention within long-term health care facilities.
J.E. Stockdale, S.C. Anderson, A.M. Edwards, S.A. Iyaniwura, N. Mulberry, M.C. Otterstatter, N.Z. Janjua, D. Coombs, C. Colijn, M.A. Irvine
medRxiv 2021.02.01.21249903; doi: https://doi.org/10.1101/2021.02.01.21249903
Estimation of SARS-CoV-2 antibody prevalence through integration of serology and incidence data.
L. Wang, J. Min, R. Doig, L.T. Elliott, C. Colijn
medRxiv 2021.03.27.21254471; doi: https://doi.org/10.1101/2021.03.27.21254471
Quantifying transmissibility of COVID-19 and impact of intervention within long-term health care facilities. J.E. Stockdale, S.C. Anderson, A.M. Edwards, S.A. Iyaniwura, N. Mulberry, M.C. Otterstatter, N.Z. Janjua, D. Coombs, C. Colijn, M.A. Irvine. medRxiv 2021.02.01.21249903; doi: https://doi.org/10.1101/2021.02.01.21249903
Projected spread of COVID-19’s second wave in South Africa under different levels of lockdown. E.B. Are, C. Colijn. medRxiv 2021.01.22.21250308; doi: https://doi.org/10.1101/2021.01.22.21250308
Modelling the impact of household size distribution on the transmission dynamics of COVID-19. P. Liu, L. McQuarrie, Y. Song, C. Colijn. medRxiv 2021.01.12.21249707; doi: https://doi.org/10.1101/2021.01.12.21249707
Fundamental Limitations of Contact Tracing for COVID-19. P. Tupper, S. Otto, C. Colijn. medRxiv 2020.12.15.20248299; doi: https://doi.org/10.1101/2020.12.15.20248299
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.
medRxiv 2020.11.20.20235697; doi: https://doi.org/10.1101/2020.11.20.20235697
COVID-19’s unfortunate events in schools: mitigating classroom clusters in the context of variable transmission. P. Tupper, C. Colijn. medRxiv 2020.10.20.20216267; doi: https://doi.org/10.1101/2020.10.20.20216267
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. medRxiv 2020.07.16.20155663; doi: https://doi.org/10.1101/2020.07.16.20155663