The role of case importation in explaining differences in early SARS-CoV-2 transmission dynamics in Canada—A mathematical modeling study of surveillance data

Godin, Arnaud; Xia, Yiqing; Buckeridge, David L.; Mishra, Sharmistha; Douwes‐Schultz, Dirk; Shen, Yannan; Lavigne, Maxime; Drolet, Mélanie; Schmidt, Alexandra M.; Brisson, Marc; Maheu‐Giroux, Mathieu

doi:10.1016/j.ijid.2020.10.046

Cited by 25 publications

(23 citation statements)

References 10 publications

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“…Québec is unique among Canadian provinces for its early spring break, which resulted in many returning travelers before border closures and quarantine measures were enacted. Our results are consistent with mathematical modelling results (Godin et al 2021) suggesting that Québec’s large and severe SARS-CoV-2 epidemic was driven by this early spring break. Even if most introduction events likely occurred well after spring break, those that arrived during or just after spring break generated the largest transmission lineages.…”

Section: Discussionsupporting

confidence: 92%

“…Before federally mandated quarantine orders for returning travelers were put in place on March 25 th , 1,544 travelers who entered Québec had tested positive with COVID-19 (Godin et al 2021). However, not all these cases were necessarily independent introduction events, nor would they all give rise to successful onward transmission of SARS-CoV-2.…”

Section: Resultsmentioning

confidence: 99%

“…1A ). It is believed that international travellers returning from spring break had a large impact on the epidemic (Godin et al 2021). The number of cases increased exponentially during March 2020 ( Fig.…”

Section: Introductionmentioning

confidence: 99%

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A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

Murall

Fournier

Galvez

et al. 2021

Preprint

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Using genomic epidemiology, we investigated the arrival of SARS-CoV-2 to Québec, the Canadian province most impacted by COVID-19, with >280,000 positive cases and >10,000 deaths in a population of 8.5 million as of March 1st, 2021. We report 2,921 high-quality SARS-CoV-2 genomes in the context of >12,000 publicly available genomes sampled globally over the first pandemic wave (up to June 1st, 2020). By combining phylogenetic and phylodynamic analyses with epidemiological data, we quantify the number of introduction events into Québec, identify their origins, and characterize the spatio-temporal spread of the virus. Conservatively, we estimated at least 500 independent introduction events, the majority of which happened from spring break until two weeks after the Canadian border closed for non-essential travel. Subsequent mass repatriations did not generate large transmission lineages (>50 cases), likely due to mandatory quarantine measures in place at the time. Consistent with common spring break and 'snowbird' destinations, most of the introductions were inferred to have originated from Europe via the Americas. Fewer than 100 viral introductions arrived during spring break, of which 5-10 led to the largest transmission lineages of the first wave (accounting for 36-58% of all sequenced infections). These successful viral transmission lineages dispersed widely across the province, consistent with founder effects and superspreading dynamics. Transmission lineage size was greatly reduced after March 11th, when a quarantine order for returning travelers was enacted. While this suggests the effectiveness of early public health measures, the biggest transmission lineages had already been ignited prior to this order. Combined, our results reinforce how, in the absence of tight travel restrictions or quarantine measures, fewer than 100 viral introductions in a week can ensure the establishment of extended transmission chains.

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Section: Discussionsupporting

confidence: 92%

Section: Resultsmentioning

confidence: 99%

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A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

Murall

Fournier

Galvez

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Limitations of our study include our use of observed cases, and thus we may underestimate the co-Gini if testing rates were lower among marginalized communities in particular, especially due to testing capacity constraints that were especially salient in the first wave (48-50). Second, although we excluded residents of long-term care homes, our definition of community-wide cases could still include other congregate-level settings such as shelters and group homes reflecting other ‘unmeasured’ determinants that could lead to geographical concentration within cities.…”

Section: Discussionmentioning

confidence: 99%

Geographical concentration of COVID-19 cases by social determinants of health in 16 large metropolitan areas in Canada – a cross-sectional study

Xia

Moloney

et al. 2021

Preprint

Self Cite

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Background: There is a growing recognition that strategies to reduce SARS-CoV-2 transmission should be responsive to local transmission dynamics. Studies have revealed inequalities along social determinants of health, but little investigation was conducted surrounding geographic concentration within cities. We quantified social determinants of geographic concentration of COVID-19 cases across sixteen census metropolitan areas (CMA) in four Canadian provinces. Methods: We used surveillance data on confirmed COVID-19 cases at the level of dissemination area. Gini (co-Gini) coefficients were calculated by CMA based on the proportion of the population in ranks of diagnosed cases and each social determinant using census data (income, education, visible minority, recent immigration, suitable housing, and essential workers) and the corresponding share of cases. Heterogeneity was visualized using Lorenz (concentration) curves. Results: Geographic concentration was observed in all CMAs (half of the cumulative cases were concentrated among 21-35% of each city's population): with the greatest geographic heterogeneity in Ontario CMAs (Gini coefficients, 0.32-0.47), followed by British Columbia (0.23-0.36), Manitoba (0.32), and Québec (0.28-0.37). Cases were disproportionately concentrated in areas with lower income, education attainment, and suitable housing; and higher proportion of visible minorities, recent immigrants, and essential workers. Although a consistent feature across CMAs was concentration by proportion visible minorities, the magnitude of concentration by social determinants varied across CMAs. Interpretation: The feature of geographical concentration of COVID-19 cases was consistent across CMAs, but the pattern by social determinants varied. Geographically-prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to SARS-CoV-2's resurgence.

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“…The identification of these triggers is important for slowing down the spread of a pathogen and is, thus, a strategy for public health security. Although imported cases are easier to manage, community transmissions are hard to trace, can grow quickly, and easily threaten local public health systems [16].…”

Section: Principal Findingsmentioning

confidence: 99%

Logistics Workers Are a Key Factor for SARS-CoV-2 Spread in Brazilian Small Towns: Case-Control Study

Bernardes‐Souza¹,

Júnior²,

Santos³

et al. 2021

JMIR Public Health Surveill

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Background Data on how SARS-CoV-2 enters and spreads in a population are essential for guiding public policies. Objective This study seeks to understand the transmission dynamics of SARS-CoV-2 in small Brazilian towns during the early phase of the epidemic and to identify core groups that can serve as the initial source of infection as well as factors associated with a higher risk of COVID-19. Methods Two population-based seroprevalence studies, one household survey, and a case-control study were conducted in two small towns in southeastern Brazil between May and June 2020. In the population-based studies, 400 people were evaluated in each town; there were 40 homes in the household survey, and 95 cases and 393 controls in the case-control study. SARS-CoV-2 serology testing was performed on participants, and a questionnaire was applied. Prevalence, household secondary infection rate, and factors associated with infection were assessed. Odds ratios (ORs) were calculated by logistic regression. Logistics worker was defined as an individual with an occupation focused on the transportation of people or goods and whose job involves traveling outside the town of residence at least once a week. Results Higher seroprevalence of SARS-CoV-2 was observed in the town with a greater proportion of logistics workers. The secondary household infection rate was 49.1% (55/112), and it was observed that in most households (28/40, 70%) the index case was a logistics worker. The case-control study revealed that being a logistics worker (OR 18.0, 95% CI 8.4-38.7) or living with one (OR 6.9, 95% CI 3.3-14.5) increases the risk of infection. In addition, having close contact with a confirmed case (OR 13.4, 95% CI 6.6-27.3) and living with more than four people (OR 2.7, 95% CI 1.1-7.1) were also risk factors. Conclusions Our study shows a strong association between logistics workers and the risk of SARS-CoV-2 infection and highlights the key role of these workers in the viral spread in small towns. These findings indicate the need to focus on this population to determine COVID-19 prevention and control strategies, including vaccination and sentinel genomic surveillance.

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The role of case importation in explaining differences in early SARS-CoV-2 transmission dynamics in Canada—A mathematical modeling study of surveillance data

Cited by 25 publications

References 10 publications

A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada

Geographical concentration of COVID-19 cases by social determinants of health in 16 large metropolitan areas in Canada – a cross-sectional study

Logistics Workers Are a Key Factor for SARS-CoV-2 Spread in Brazilian Small Towns: Case-Control Study

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