Early identification of a COVID-19 outbreak detected by wastewater surveillance at a large homeless shelter in Toronto, Ontario.

SETTING: Toronto (Ontario, Canada) is a large urban centre with a significant population of underhoused residents and several dozen shelters for this population with known medical and social vulnerabilities. A sizeable men's homeless shelter piloted a facility-level SARS-CoV-2 wastewater surveillance program. INTERVENTION: Wastewater surveillance was initiated at the shelter in January 2021. One-hour composite wastewater samples were collected twice weekly from a terminal sanitary clean-out pipe. The genetic material of the SARS-CoV-2 virus was extracted from the solid phase of each sample and analyzed using real-time qPCR to estimate the viral level. Wastewater results were reported to facility managers and Toronto Public Health within 4 days. OUTCOMES: There were 169 clients on-site at the time of the investigation. Wastewater surveillance alerted to the presence of COVID-19 activity at the site, prior to clinical detection. This notification acted as an early warning signal, which allowed for timely symptom screening and case finding for shelter managers and the local health unit, in preparation for the declaration of an outbreak. IMPLICATIONS: Wastewater surveillance acted as an advanced notification leading to the timely deployment of enhanced testing prior to clinical presentation in a population with known vulnerabilities. Wastewater surveillance at the facility level is beneficial, particularly in high-risk congregate living settings such as shelters that house transient populations where clinical testing and vaccination can be challenging. Open communication, established individual facility response plans, and a balanced threshold for action are essential to an effective wastewater surveillance program.

RéSUMé: LIEU: Toronto (Ontario, Canada) est un grand centre urbain qui compte une importante population de résidents mal logés et plusieurs douzaines de refuges pour cette population aux vulnérabilités médicales et sociales connues. Un assez gros refuge pour hommes sans-abri a mis à l'essai dans ses installations un programme de surveillance des eaux usées pour le SRAS-CoV-2. INTERVENTION: La surveillance des eaux usées du refuge a commencé en janvier 2021. Des échantillons composites d'une heure ont été prélevés deux fois par semaine à partir d'un regard de nettoyage à l'extrémité du drain sanitaire. Le matériel génétique du virus du SRAS-CoV-2 a été extrait du support solide de chaque échantillon et analysé par PCR quantitative en temps réel pour estimer le niveau du virus. Les résultats des eaux usées ont été déclarés aux gestionnaires du refuge et à Santé publique Toronto dans un délai de quatre jours. RéSULTATS: Il y avait 169 usagers sur place au moment de l'enquête. La surveillance des eaux usées a averti de la présence d'une activité de la COVID-19 sur les lieux avant sa détection clinique. Cet avertissement a servi de signal d'alerte précoce, ce qui a permis aux gestionnaires du refuge et au bureau de santé local de procéder au dépistage rapide des symptômes et à la recherche des cas en préparation pour la déclaration d'une éclosion. CONSéQUENCES: La surveillance des eaux usées a servi de notification préalable et entraîné le déploiement opportun d'un dépistage complémentaire avant la manifestation clinique dans une population qui présente des vulnérabilités connues. La surveillance des eaux usées d'une installation est avantageuse, surtout dans des milieux d'hébergement collectif à risque élevé comme les refuges qui hébergent des populations de passage, où le dépistage clinique et la vaccination peuvent être difficiles. Une communication ouverte, des plans d'intervention établis pour chaque installation et un seuil d'intervention équilibré sont essentiels à l'efficacité d'un programme de surveillance des eaux usées.

Neighbourhood-level socio-demographic characteristics and risk of COVID-19 incidence and mortality in Ontario, Canada: A population-based study.

OBJECTIVES: We aimed to estimate associations between COVID-19 incidence and mortality with neighbourhood-level immigration, race, housing, and socio-economic characteristics. METHODS: We conducted a population-based study of 28,808 COVID-19 cases in the provincial reportable infectious disease surveillance systems (Public Health Case and Contact Management System) which includes all known COVID-19 infections and deaths from Ontario, Canada reported between January 23, 2020 and July 28, 2020. Residents of congregate settings, Indigenous communities living on reserves or small neighbourhoods with populations <1,000 were excluded. Comparing neighbourhoods in the 90th to the 10th percentiles of socio-demographic characteristics, we estimated the associations between 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics and COVID-19 incidence and mortality using Poisson generalized linear mixed models. RESULTS: Neighbourhoods with the highest proportion of immigrants (relative risk (RR): 4.0, 95%CI:3.5-4.5) and visible minority residents (RR: 3.3, 95%CI:2.9-3.7) showed the strongest association with COVID-19 incidence in adjusted models. Among individual race groups, COVID-19 incidence was highest among neighbourhoods with the high proportions of Black (RR: 2.4, 95%CI:2.2-2.6), South Asian (RR: 1.9, 95%CI:1.8-2.1), Latin American (RR: 1.8, 95%CI:1.6-2.0) and Middle Eastern (RR: 1.2, 95%CI:1.1-1.3) residents. Neighbourhoods with the highest average household size (RR: 1.9, 95%CI:1.7-2.1), proportion of multigenerational families (RR: 1.8, 95%CI:1.7-2.0) and unsuitably crowded housing (RR: 2.1, 95%CI:2.0-2.3) were associated with COVID-19 incidence. Neighbourhoods with the highest proportion of residents with less than high school education (RR: 1.6, 95%CI:1.4-1.8), low income (RR: 1.4, 95%CI:1.2-1.5) and unaffordable housing (RR: 1.6, 95%CI:1.4-1.8) were associated with COVID-19 incidence. Similar inequities were observed across neighbourhood-level sociodemographic characteristics and COVID-19 mortality. CONCLUSIONS: Neighbourhood-level inequities in COVID-19 incidence and mortality were observed in Ontario, with excess burden experienced in neighbourhoods with a higher proportion of immigrants, racialized populations, large households and low socio-economic status.