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Abstract Background The severity of COVID-19 outbreaks is disproportionate across settings (e.g., long-term care facilities (LTCF), schools) across Canada. Few studies have examined factors associated with outbreak severity to inform prevention and response. Our study objective was to assess how outbreak severity, as measured using outbreak intensity and defined as number of outbreak-associated cases divided by outbreak duration, differed by setting and factors known to influence SARS-CoV-2 transmission. Methods We described outbreak intensity trends in 2021 using data from the Canadian COVID-19 Outbreak Surveillance System from seven provinces/territories, representing 93% of the Canadian population. A negative binomial fixed-effects model was used to assess for associations between the outcome, outbreak intensity, and characteristics of outbreaks: setting type, median age of cases, number at risk, and vaccination coverage of at least 1 dose. Also included were variables previously reported to influence SARS-CoV-2 transmission: stringency of non-pharmaceutical interventions (NPI) and the predominant SARS-CoV-2 variant detected by surveillance. Results The longest outbreaks occurred in LTCF (mean = 25.4 days) and correctional facilities (mean = 20.6 days) which also reported the largest outbreaks (mean = 29.6 cases per outbreak). Model results indicated that outbreak intensity was highest in correctional facilities. Relative to correctional facilities (referent), the second highest adjusted intensity ratio was in childcare centres (intensity ratio = 0.58 [95% CI: 0.51–0.66]), followed by LTCF (0.56 [95% CI: 0.51–0.66]). Schools had the lowest adjusted intensity ratio (0.46 [95% CI: 0.40–0.53]) despite having the highest proportion of outbreaks (37.5%). An increase in outbreak intensity was associated with increases in median age, the number at risk, and stringency of NPI. Greater vaccination coverage with at least 1 dose was associated with reduced outbreak intensity. Conclusion Descriptive and multivariable model results indicated that in Canada during 2021, outbreak intensity was greatest in closed congregate living facilities: correctional facilities and LTCF. Findings from this study support the importance of vaccination in reducing outbreak intensity when vaccines are effective against infection with circulating variants, which is especially important for closed congregate living facilities where NPIs are more challenging to implement.

Abstract Objectives In Canada, substance-related accidental acute toxicity deaths (AATDs) continue to rise at the national and sub-national levels. However, it is unknown if, where, when, and to what degree AATDs cluster in space, time, and space–time across the country. The objectives of this study were to 1) assess for clusters of AATDs that occurred in Canada during 2016 and 2017 at the national and provincial/territorial (P/T) levels, and 2) examine the substance types detected in AATD cases within each cluster. Methods Two years of person-level data on AATDs were abstracted from coroner and medical examiner files using a standardized data collection tool, including the decedent's postal code and municipality information on the places of residence, acute toxicity (AT) event, and death, and the substances detected in the death. Data were combined with Canadian census information to create choropleth maps depicting AATD rates by census division. Spatial scan statistics were used to build Poisson models to identify clusters of high rates (p

Abstract Background With increased attention to the importance of integrating the One Health approach into zoonotic disease surveillance and response, a greater understanding of the mechanisms to support effective communication and information sharing across animal and human health sectors is needed. The objectives of this qualitative case study were to describe the communication channels used between human and animal health stakeholders and to identify the elements that have enabled the integration of the One Health approach. Methods We combined documentary research with interviews with fifteen stakeholders to map the communication channels used in human and swine influenza surveillance in Alberta, Canada, as well as in the response to a human case of H1N2v in 2020. A thematic analysis of the interviews was also used to identify the barriers and facilitators to communication among stakeholders from the animal and human health sectors. Results When a human case of swine influenza emerged, the response led by the provincial Chief Medical Officer of Health involved players at various levels of government and in the human and animal health sectors. The collaboration of public and animal health laboratories and of the swine sector, in addition to the information available through the surveillance systems in place, was swift and effective. Elements identified as enabling smooth communication between the human and animal health systems included preexisting relationships between the various stakeholders, a relationship of trust between them (e.g., the swine sector and their perception of government structures), the presence of stakeholders acting as permanent liaisons between the ministries of health and agriculture, and stakeholders' understanding of the importance of the One Health approach. Conclusions Information flows through formal and informal channels and both structural and relational features that can support rapid and effective communication in infectious disease surveillance and outbreak response.

Abstract Background Estimating rates of disease importation by travellers is a key activity to assess both the risk to a country from an infectious disease emerging elsewhere in the world and the effectiveness of border measures. We describe a model used to estimate the number of travellers infected with SARS-CoV-2 into Canadian airports in 2021, and assess the impact of pre-departure testing requirements on importation risk. Methods A mathematical model estimated the number of essential and non-essential air travellers infected with SARS-CoV-2, with the latter requiring a negative pre-departure test result. The number of travellers arriving infected (i.e. imported cases) depended on air travel volumes, SARS-CoV-2 exposure risk in the departure country, prior infection or vaccine acquired immunity, and, for non-essential travellers, screening from pre-departure molecular testing. Importation risk was estimated weekly from July to November 2021 as the number of imported cases and percent positivity (PP; i.e. imported cases normalised by travel volume). The impact of pre-departure testing was assessed by comparing three scenarios: baseline (pre-departure testing of all non-essential travellers; most probable importation risk given the pre-departure testing requirements), counterfactual scenario 1 (no pre-departure testing of fully vaccinated non-essential travellers), and counterfactual scenario 2 (no pre-departure testing of non-essential travellers). Results In the baseline scenario, weekly imported cases and PP varied over time, ranging from 145 to 539 cases and 0.15 to 0.28%, respectively. Most cases arrived from the USA, Mexico, the United Kingdom, and France. While modelling suggested that essential travellers had a higher weekly PP (0.37 – 0.65%) than non-essential travellers (0.12 – 0.24%), they contributed fewer weekly cases (62 – 154) than non-essential travellers (84 – 398 per week) given their lower travel volume. Pre-departure testing was estimated to reduce imported cases by one third (counterfactual scenario 1) to one half (counterfactual scenario 2). Conclusions The model results highlighted the weekly variation in importation by traveller group (e.g., reason for travel and country of departure) and enabled a framework for measuring the impact of pre-departure testing requirements. Quantifying the contributors of importation risk through mathematical simulation can support the design of appropriate public health policy on border measures.

Abstract Background Zika virus (ZIKV) spread rapidly in the Americas in 2015. Targeting effective public health interventions for inhabitants of, and travellers to and from, affected countries depends on understanding the risk of ZIKV emergence (and re-emergence) at the local scale. We explore the extent to which environmental, social and neighbourhood disease intensity variables influenced emergence dynamics. Our objective was to characterise population vulnerability given the potential for sustained autochthonous ZIKV transmission and the timing of emergence. Logistic regression models estimated the probability of reporting at least one case of ZIKV in a given municipality over the course of the study period as an indicator for sustained transmission; while accelerated failure time (AFT) survival models estimated the time to a first reported case of ZIKV in week t for a given municipality as an indicator for timing of emergence. Results Sustained autochthonous ZIKV transmission was best described at the temporal scale of the study period (almost one year), such that high levels of study period precipitation and low mean study period temperature reduced the probability. Timing of ZIKV emergence was best described at the weekly scale for precipitation in that high precipitation in the current week delayed reporting. Both modelling approaches detected an effect of high poverty on reducing/slowing case detection, especially when inter-municipal road connectivity was low. We also found that proximity to municipalities reporting ZIKV had an effect to reduce timing of emergence when located, on average, less than 100 km away. Conclusions The different modelling approaches help distinguish between large temporal scale factors driving vector habitat suitability and short temporal scale factors affecting the speed of spread. We find evidence for inter-municipal movements of infected people as a local-scale driver of spatial spread. The negative association with poverty suggests reduced case reporting in poorer areas. Overall, relatively simplistic models may be able to predict the vulnerability of populations to autochthonous ZIKV transmission at the local scale.