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Background: Vaccine homophily describes non-heterogeneous vaccine uptake within contact networks. This study was performed to determine observable patterns of vaccine homophily, as well as the impact of vaccine homophily on disease transmission within and between vaccination groups under conditions of high and low vaccine efficacy., Methods: Residents of British Columbia, Canada, aged ≥ 16 years, were recruited via online advertisements between February and March 2022, and provided information about vaccination status, perceived vaccination status of household and non-household contacts, compliance with COVID-19 prevention guidelines, and history of COVID-19. A deterministic mathematical model was used to assess transmission dynamics between vaccine status groups under conditions of high and low vaccine efficacy., Results: Vaccine homophily was observed among those with 0, 2, or 3 doses of the vaccine. Greater homophily was observed among those who had more doses of the vaccine (p < 0.0001). Those with fewer vaccine doses had larger contact networks (p < 0.0001), were more likely to report prior COVID-19 (p < 0.0001), and reported lower compliance with COVID-19 prevention guidelines (p < 0.0001). Mathematical modelling showed that vaccine homophily plays a considerable role in epidemic growth under conditions of high and low vaccine efficacy. Furthermore, vaccine homophily contributes to a high force of infection among unvaccinated individuals under conditions of high vaccine efficacy, as well as to an elevated force of infection from unvaccinated to suboptimally vaccinated individuals under conditions of low vaccine efficacy., Interpretation: The uneven uptake of COVID-19 vaccines and the nature of the contact network in the population play important roles in shaping COVID-19 transmission dynamics., (© 2024. The Author(s).)

Background: COVID-19 vaccination is a key public health measure in the pandemic response. The rapid evolution of SARS-CoV-2 variants introduce new groups of spike protein mutations. These new mutations are thought to aid in the evasion of vaccine-induced immunity and render vaccines less effective. However, not all spike mutations contribute equally to vaccine escape. Previous studies associate mutations with vaccine breakthrough infections (BTI), but information at the population level remains scarce. We aimed to identify spike mutations associated with SARS-CoV-2 vaccine BTI in a community setting during the emergence and predominance of the Delta-variant., Methods: This case-control study used both genomic, and epidemiological data from a provincial COVID-19 surveillance program. Analyses were stratified into two periods approximating the emergence and predominance of the Delta-variant, and restricted to primary SARS-CoV-2 infections from either unvaccinated individuals, or those infected ≥14 days after their second vaccination dose in a community setting. Each sample's spike mutations were concatenated into a unique spike mutation profile (SMP). Penalized logistic regression was used to identify spike mutations and SMPs associated with SARS-CoV-2 vaccine BTI in both time periods., Results and Discussion: This study reports population level relative risk estimates, between 2 and 4-folds, of spike mutation profiles associated with BTI during the emergence and predominance of the Delta-variant, which comprised 19,624 and 17,331 observations, respectively. The identified mutations cover multiple spike domains including the N-terminal domain (NTD), receptor binding domain (RBD), S1/S2 cleavage region, fusion peptide and heptad regions. Mutations in these different regions imply various mechanisms contribute to vaccine escape. Our profiling method identifies naturally occurring spike mutations associated with BTI, and can be applied to emerging SARS-CoV-2 variants with novel groups of spike mutations., Competing Interests: NJ participates in Abbvie Advisory Board meeting. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Fibke, Joffres, Tyson, Colijn, Janjua, Fjell, Prystajecky, Jassem and Sbihi.)

Following the emergence of COVID-19 at the end of 2019, several mathematical models have been developed to study the transmission dynamics of this disease. Many of these models assume homogeneous mixing in the underlying population. However, contact rates and mixing patterns can vary dramatically among individuals depending on their age and activity level. Variation in contact rates among age groups and over time can significantly impact how well a model captures observed trends. To properly model the age-dependent dynamics of COVID-19 and understand the impacts of interventions, it is essential to consider heterogeneity arising from contact rates and mixing patterns. We developed an age-structured model that incorporates time-varying contact rates and population mixing computed from the ongoing BC Mix COVID-19 survey to study transmission dynamics of COVID-19 in British Columbia (BC), Canada. Using a Bayesian inference framework, we fit four versions of our model to weekly reported cases of COVID-19 in BC, with each version allowing different assumptions of contact rates. We show that in addition to incorporating age-specific contact rates and mixing patterns, time-dependent (weekly) contact rates are needed to adequately capture the observed transmission dynamics of COVID-19. Our approach provides a framework for explicitly including empirical contact rates in a transmission model, which removes the need to otherwise model the impact of many non-pharmaceutical interventions. Further, this approach allows projection of future cases based on clear assumptions of age-specific contact rates, as opposed to less tractable assumptions regarding transmission rates., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Importance: An effective vaccine against SARS-CoV-2 will reduce morbidity and mortality and allow substantial relaxation of physical distancing policies. However, the ability of a vaccine to prevent infection or disease depends critically on protecting older individuals, who are at highest risk of severe disease., Objective: We quantitatively estimated the relative benefits of COVID-19 vaccines, in terms of preventing infection and death, with a particular focus on effectiveness in elderly people., Design: We applied compartmental mathematical modelling to determine the relative effects of vaccines that block infection and onward transmission, and those that prevent severe disease. We assumed that vaccines showing high efficacy in adults would be deployed, and examined the effects of lower vaccine efficacy among the elderly population., Setting and Participants: Our mathematical model was calibrated to simulate the course of an epidemic among the entire population of British Columbia, Canada. Within our model, the population was structured by age and levels of contact., Main Outcome(s) and Measure(s): We assessed the effectiveness of possible vaccines in terms of the predicted number of infections within the entire population, and deaths among people aged 65 years and over., Results: In order to reduce the overall rate of infections in the population, high rates of deployment to all age groups will be critical. However, to substantially reduce mortality among people aged 65 years and over, a vaccine must directly protect a high proportion of people in that group., Conclusions and Relevance: Effective vaccines deployed to a large fraction of the population are projected to substantially reduce infection in an otherwise susceptible population. However, even if transmission were blocked highly effectively by vaccination of children and younger adults, overall mortality would not be substantially reduced unless the vaccine is also directly protective in elderly people. We strongly recommend: (i) the inclusion of people aged 65 years and over in future trials of COVID-19 vaccine candidates; (ii) careful monitoring of vaccine efficacy in older age groups following vaccination., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Extensive non-pharmaceutical and physical distancing measures are currently the primary interventions against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing, with the timing of distancing measures informed by survey data on attitudes to distancing and COVID-19. We fit our model to reported COVID-19 cases in British Columbia (BC), Canada, and five other jurisdictions, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimated the impact that physical distancing (social distancing) has had on the contact rate and examined the projected impact of relaxing distancing measures. We found that, as of April 11 2020, distancing had a strong impact in BC, consistent with declines in reported cases and in hospitalization and intensive care unit numbers; individuals practising physical distancing experienced approximately 0.22 (0.11-0.34 90% CI [credible interval]) of their normal contact rate. The threshold above which prevalence was expected to grow was 0.55. We define the "contact ratio" to be the ratio of the estimated contact rate to the threshold rate at which cases are expected to grow; we estimated this contact ratio to be 0.40 (0.19-0.60) in BC. We developed an R package 'covidseir' to make our model available, and used it to quantify the impact of distancing in five additional jurisdictions. As of May 7, 2020, we estimated that New Zealand was well below its threshold value (contact ratio of 0.22 [0.11-0.34]), New York (0.60 [0.43-0.74]), Washington (0.84 [0.79-0.90]) and Florida (0.86 [0.76-0.96]) were progressively closer to theirs yet still below, but California (1.15 [1.07-1.23]) was above its threshold overall, with cases still rising. Accordingly, we found that BC, New Zealand, and New York may have had more room to relax distancing measures than the other jurisdictions, though this would need to be done cautiously and with total case volumes in mind. Our projections indicate that intermittent distancing measures-if sufficiently strong and robustly followed-could control COVID-19 transmission. This approach provides a useful tool for jurisdictions to monitor and assess current levels of distancing relative to their threshold, which will continue to be essential through subsequent waves of this pandemic., Competing Interests: The authors have declared that no competing interests exist.

Setting: British Columbia (BC) has a low incidence of tuberculosis (TB), with the burden of endogenously acquired disease concentrated among vulnerable populations, including the homeless. In May 2008, a TB outbreak began in a BC homeless shelter, with a single index case seeding multiple secondary cases within the shelter., Objective: To use nightly shelter records to quantify the risk of latent tuberculous infection (LTBI) among shelter clients as a function of their sleeping distance from and duration of exposure to the index case., Design: Distance and duration of exposure were visualised and assessed using logistic regression with LTBI status as outcome. We used a novel machine learning approach to establish exposure thresholds that optimally separated infected and non-infected individuals., Results: Of 161 exposed shelter clients, 58 had a recorded outcome of infected (n = 39) or non-infected (n = 19). Only duration of exposure to the index was associated with increased odds of infection (OR 1.26); stays of ⩾ 5 nights put shelter clients at higher odds of infection (OR 4.97)., Conclusion: The unique data set and analytical approach suggested that, in a shelter environment, long-term clients are at highest risk of LTBI and should be prioritised for screening during an outbreak investigation.