Characterizing responsiveness to the COVID-19 pandemic in the United States and Canada using mobility data

BackgroundMobile phone-derived human mobility data are a proxy for disease transmission risk and have proven useful during the COVID-19 pandemic for forecasting cases and evaluating interventions. We propose a novel metric using mobility data to characterize responsiveness to rising case rates. MethodsWe examined weekly reported COVID-19 incidence and retail and recreation mobility from Google Community Mobility Reports for 50 U.S. states and nine Canadian provinces from December 2020 to November 2021. For each jurisdiction, we calculated the responsiveness of mobility to COVID-19 incidence when cases were rising. Responsiveness across countries was summarized using subgroup meta-analysis. We also calculated the correlation between the responsiveness metric and the reported COVID-19 death rate during the study period. FindingsResponsiveness in Canadian provinces ({beta} = -1{middle dot}45; 95% CI: -2{middle dot}45, -0{middle dot}44) was approximately five times greater than in U.S. states ({beta} = -0{middle dot}30; 95% CI: -0{middle dot}38, -0{middle dot}21). Greater responsiveness was moderately correlated with a lower reported COVID-19 death rate during the study period (Spearmans{rho} = 0{middle dot}51), whereas average mobility was only weakly correlated the COVID-19 death rate (Spearmans{rho} = 0{middle dot}20). InterpretationOur study used a novel mobility-derived metric to reveal a near-universal phenomenon of reductions in mobility subsequent to rising COVID-19 incidence across 59 states and provinces of the U.S. and Canada, while also highlighting the different public health approaches taken by the two countries. FundingThis study received no funding. Research in contextO_ST_ABSEvidence before the studyC_ST_ABSThere exists a wide body of literature establishing the usefulness of mobile phone-derived human mobility data for forecasting cases and other metrics during the COVID-19 pandemic. We performed a literature search to identify studies examining the opposite relationship, attempting to quantify the responsiveness of human mobility to changes in COVID-19 incidence. We searched PubMed on October 21, 2022 using the keywords "COVID-19", "2019-nCoV", or "SARS-CoV-2" in combination with "responsiveness" and one or more of "mobility", "distancing", "lockdown", and "non-pharmaceutical interventions". We scanned 46 published studies and found one that used a mobile phone data-derived index to measure the intensity of social distancing in U.S. counties from January 2020 to January 2021. The authors of this study found that an increase in cases in the last 7 days was associated with an increase in the intensity of social distancing, and that this effect was larger during periods of lockdown/shop closures. Added value of the studyOur study developed a metric of the responsiveness of mobility to rising case rates for COVID-19 and calculated it for 59 subnational jurisdictions in the United States and Canada. While nearly all jurisdictions displayed some degree of responsiveness, average responsiveness in Canada was nearly five times greater than in the United States. Responsiveness was moderately associated with the reported COVID-19 death rate during the study period, such that jurisdictions with greater responsiveness had lower death rates, and was more strongly associated with death rates than average mobility in a jurisdiction. Implications of all the available evidenceMobile phone-derived human mobility data has proven useful in the context of infectious disease surveillance during the COVID-19 pandemic, such as for forecasting cases and evaluating non-pharmaceutical interventions. In our study, we derived a metric of responsiveness to show that mobility data may be used to track the efficiency of public health responses as the pandemic evolves. This responsiveness metric was also correlated with reported COVID-19 death rates during the study period. Together, these results demonstrate the usefulness of mobility data for making broad characterizations of public health responses across jurisdictions during the COVID-19 pandemic and reinforce the value of mobility data as an infectious disease surveillance tool for answering present and future threats.

Real-world effectiveness of nirmatrelvir/ritonavir use for COVID-19: A population-based cohort study in Ontario, Canada

BackgroundOur objective was to evaluate the real world effectiveness of nirmatrelvir/ritonavir to prevent severe COVID-19 while Omicron and its subvariants predominate. MethodsWe conducted a population based cohort study in Ontario, Canada including all residents >17 years of age who tested positive for SARS-CoV-2 by PCR between 4 April and 31 August 2022. We compared nirmatrelvir/ritonavir treated patients to unexposed patients and measured the primary outcome of hospitalization or death from COVID-19, and a secondary outcome of death 1-30 days. We used weighted logistic regression to calculate weighted odds ratios (wOR) with 95% confidence intervals (CIs) using inverse probability of treatment weighting (IPTW) to control for confounding. ResultsThe final cohort included 177,545 patients with 8,876 (5.0%) exposed and 168,669 (95.0%) unexposed individuals. The groups were well balanced with respect to demographic and clinical characteristics after applying stabilized IPTW. Hospitalization or death within 30 days was lower in the nirmatrelvir/ritonavir treated group compared to unexposed individuals (2.1% vs 3.7%, wOR 0.56; 95%CI, 0.47-0.67). In the secondary analysis, the relative odds of death was also significantly reduced (1.6% vs 3.3%, wOR 0.49; 95%CI, 0.39-0.62). The number needed to treat to prevent one case of severe COVID-19 was 62 (95%CI 43 to 80). Findings were similar across strata of age, DDIs, vaccination status, and comorbidities. InterpretationNirmatrelvir/ritonavir was associated with significantly reduced risk of hospitalization and death from COVID-19 in this observational study, supporting ongoing use of this therapeutic to treat patients with mild COVID-19 at risk for severe disease.

Effectiveness of COVID-19 vaccines against Omicron or Delta infection

BackgroundThe incidence of SARS-CoV-2 infection, including among those who have received 2 doses of COVID-19 vaccines, increased substantially following the emergence of Omicron in Ontario, Canada. MethodsApplying the test-negative study design to linked provincial databases, we estimated vaccine effectiveness (VE) against symptomatic infection and severe outcomes (hospitalization or death) caused by Omicron or Delta between December 6 and 26, 2021. We used multivariable logistic regression to estimate the effectiveness of 2 or 3 COVID-19 vaccine doses by time since the latest dose, compared to unvaccinated individuals. ResultsWe included 16,087 Omicron-positive cases, 4,261 Delta-positive cases, and 114,087 test-negative controls. VE against symptomatic Delta infection declined from 89% (95%CI, 86-92%) 7-59 days after a second dose to 80% (95%CI, 74-84%) after [≥]240 days, but increased to 97% (95%CI, 96-98%) [≥]7 days after a third dose. VE against symptomatic Omicron infection was only 36% (95%CI, 24-45%) 7-59 days after a second dose and provided no protection after [≥]180 days, but increased to 61% (95%CI, 56-65%) [≥]7 days after a third dose. VE against severe outcomes was very high following a third dose for both Delta and Omicron (99% [95%CI, 98-99%] and 95% [95%CI, 87-98%], respectively). ConclusionsIn contrast to high levels of protection against both symptomatic infection and severe outcomes caused by Delta, our results suggest that 2 doses of COVID-19 vaccines only offer modest and short-term protection against symptomatic Omicron infection. A third dose improves protection against symptomatic infection and provides excellent protection against severe outcomes for both variants.

Effectiveness of COVID-19 vaccines against variants of concern, Canada

SARS-CoV-2 variants of concern (VOC) are more transmissible and have the potential for increased disease severity and decreased vaccine effectiveness. We estimated the effectiveness of BNT162b2 (Pfizer-BioNTech Comirnaty), mRNA-1273 (Moderna Spikevax), and ChAdOx1 (AstraZeneca Vaxzevria) vaccines against symptomatic SARS-CoV-2 infection and COVID-19 hospitalization or death caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) VOCs in Ontario, Canada using a test-negative design study. Effectiveness against symptomatic infection [≥]7 days after two doses was 89-92% against Alpha, 87% against Beta, 88% against Gamma, 82-89% against Beta/Gamma, and 87-95% against Delta across vaccine products. The corresponding estimates [≥]14 days after one dose were lower. Effectiveness estimates against hospitalization or death were similar to, or higher than, against symptomatic infection. Effectiveness against symptomatic infection is generally lower for older adults ([≥]60 years) compared to younger adults (<60 years) for most of the VOC-vaccine combinations.

Comparative Household Secondary Attack Rates associated with B.1.1.7, B.1.351, and P.1 SARS-CoV-2 Variants

BackgroundThe emergence of SARS-CoV-2 variants associated with increased transmissibility are driving a 3rd global surge in COVID-19 incidence. There are currently few reliable estimates for the P.1 and B.1.351 lineages. We sought to compare the secondary attack rates of SARS-COV-2 mutations and variants in Canadas largest province of Ontario, using a previously validated household-based approach. MethodsWe identified individuals with confirmed SARS-CoV-2 infection in Ontarios provincial reportable disease surveillance system. Cases were grouped into households based on reported residential address. Index cases had the earliest of symptom onset in the household. Household secondary attack rate was defined as the percentage of household contacts identified as secondary cases within 1-14 days after the index case. ResultsWe identified 26,888 index household cases during the study period. Among these, 7,555 (28%) were wild-type, 17,058 (63%) were B.1.1.7, 1674 (6%) were B.1.351 or P.1, and 601 (2%) were non-VOC mutants (Table 1). The secondary attack rates, according to index case variant were as follows: 20.2% (wild-type), 25.1% (B.1.1.7), 27.2% (B.1.351 or P.1), and 23.3% (non-VOC mutants). In adjusted analyses, we found that B.1.1.7, B.1.351, and P.1 index cases had the highest transmissibility (presumptive B.1.1.7 ORadjusted=1.49, 95%CI 1.36, 1.64; presumptive B.1.351 or P.1 ORadjusted=1.60, 95%CI 1.37, 1.87). O_TBL View this table: org.highwire.dtl.DTLVardef@1f1a4e9org.highwire.dtl.DTLVardef@181f042org.highwire.dtl.DTLVardef@1c483fborg.highwire.dtl.DTLVardef@b4fba0org.highwire.dtl.DTLVardef@1f3d626_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONSecondary attack rates of persons infected with SARS-CoV-2, March 1 to April 17. C_TABLECAPTION C_TBL DiscussionSubstantially higher transmissibility associated with variants will make control of SARS-CoV-2 more difficult, reinforcing the urgent need to increase vaccination rates globally.

Effectiveness of BNT162b2 and mRNA-1273 COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe COVID-19 outcomes in Ontario, Canada

ObjectivesTo estimate the effectiveness of mRNA COVID-19 vaccines against symptomatic infection and severe outcomes. DesignWe applied a test-negative design study to linked laboratory, vaccination, and health administrative databases, and used multivariable logistic regression adjusting for demographic and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness (VE) against symptomatic infection and severe outcomes. SettingOntario, Canada between 14 December 2020 and 19 April 2021. ParticipantsCommunity-dwelling adults aged [≥]16 years who had COVID-19 symptoms and were tested for SARS-CoV-2. InterventionsPfizer-BioNTechs BNT162b2 or Modernas mRNA-1273 vaccine. Main outcome measuresLaboratory-confirmed SARS-CoV-2 by RT-PCR; hospitalization/death associated with SARS-CoV-2 infection. ResultsAmong 324,033 symptomatic individuals, 53,270 (16.4%) were positive for SARS-CoV-2 and 21,272 (6.6%) received [≥]1 vaccine dose. Among test-positive cases, 2,479 (4.7%) had a severe outcome. VE against symptomatic infection [≥]14 days after receiving only 1 dose was 60% (95%CI, 57 to 64%), increasing from 48% (95%CI, 41 to 54%) at 14-20 days after the first dose to 71% (95%CI, 63 to 78%) at 35-41 days. VE [≥]7 days after 2 doses was 91% (95%CI, 89 to 93%). Against severe outcomes, VE [≥]14 days after 1 dose was 70% (95%CI, 60 to 77%), increasing from 62% (95%CI, 44 to 75%) at 14-20 days to 91% (95%CI, 73 to 97%) at [≥]35 days, whereas VE [≥]7 days after 2 doses was 98% (95%CI, 88 to 100%). For adults aged [≥]70 years, VE estimates were lower for intervals shortly after receiving 1 dose, but were comparable to younger adults for all intervals after 28 days. After 2 doses, we observed high VE against E484K-positive variants. ConclusionsTwo doses of mRNA COVID-19 vaccines are highly effective against symptomatic infection and severe outcomes. Single-dose effectiveness is lower, particularly for older adults shortly after the first dose.

Increased Interregional Travel to Shopping Malls and Restaurants in Response to Differential COVID-19 Restrictions in the Greater Toronto Area

BackgroundIn the fall of 2020, the government of Ontario, Canada adopted a 5-tier, regional framework of public health measures for the COVID-19 pandemic. During the second wave of COVID-19 in Ontario, the urban core of the Greater Toronto Area (Toronto and Peel) were the first regions in the province to enter the highest restriction tier ("lockdown") on November 23, 2020, which closed restaurants to in-person dining and limited non-essential businesses, including shopping malls, to curbside pickup. The peripheral regions of the Greater Toronto Area (York, Durham, Halton) would not enter lockdown until later the following month. In this analysis, we examine whether the implementation of differentially timed restrictions in a highly interconnected metropolitan area led to increased interregional travel, potentially driving further transmission of SARS-CoV-2. MethodsWe used anonymized smartphone data to estimate the number of visits by residents of regions in the urban core to shopping malls and restaurants in peripheral regions in the week before compared to the week after the November 23 lockdown. ResultsResidents of Toronto and Peel took fewer trips to shopping malls and restaurants in the week following lockdown. This was entirely driven by reductions in visits within the locked down regions themselves, as there was a significant increase in trips to shopping malls in peripheral regions by these residents in the same period (Toronto: +40.7%, Peel: +65.5%). Visits to restaurants in peripheral regions also increased slightly (Toronto: +6.3%, Peel: +11.8%). DiscussionHeterogeneous restrictions may undermine lockdowns in the urban core as well as driving residents from zones of higher transmission to zones of lower transmission. These concerns are likely generalizable to other major metropolitan areas, which often comprise interconnected but administratively independent regions.

Increased household secondary attacks rates with Variant of Concern SARS-CoV-2 index cases

IMPORTANCEHigher secondary attack rates related to variant of concern (VOC) index cases have been reported, but have not been explored within households, which continue to be an important source of coronavirus disease 2019 (COVID-19) transmission OBJECTIVETo compare secondary attack rates in households with VOC versus non-VOC index cases. DESIGNA retrospective cohort study of household index cases reported from February 7 - 27, 2021. A propensity-score matched cohort was derived to calculate adjusted estimates. SETTINGOntario, Canada. PARTICIPANTSA population-based cohort of all private households with index cases. We excluded cases in congregate settings, as well as households with one individual or with >1 case with the same earliest symptom onset date. EXPOSUREVOC status, defined as either individuals confirmed as B.1.1.7 using whole genome sequencing or those that screened positive for the N501Y mutation using real-time PCR. MAIN OUTCOME AND MEASUREHousehold secondary attack rate, defined as the number of household secondary cases that occurred 1-14 days after the index case divided by the total number of household secondary contacts. RESULTSWe included 1,259 index VOC and non-VOC cases in the propensity score-matched analysis. The secondary attack rate for VOC index cases in this matched cohort was 1.31 times higher than non-VOC index cases (RR=1.31, 95%CI 1.14-1.49), similar to the unadjusted estimate. In stratified analyses, the higher secondary attack rate for VOC compared to non-VOC index cases was accentuated for asymptomatic index cases (RR=1.91, 95% CI 0.96-3.80) and presymptomatic cases (RR=3.41, 95%CI 1.13-10.26) CONCLUSIONS AND RELEVANCEThis study provides strong evidence of increased transmissibility in households due to VOCs and suggests that asymptomatic and pre-symptomatic transmission may be of particular importance for VOCs. Our study suggests that more aggressive public health measures will be needed to control VOCs and that ongoing research is needed to understand mechanisms of VOC transmissibility to curb their associated morbidity and mortality.

Pediatric household transmission of SARS-CoV-2 infection

BACKGROUNDAs a result of low numbers of pediatric cases early in the COVID-19 pandemic, pediatric household transmission of SARS-CoV-2 remains an understudied topic. This study sought to determine whether there are differences in the odds of household transmission for younger children compared to older children. METHODSWe assembled a cohort of all individuals in Ontario, Canada with laboratory-confirmed SARS-CoV-2 infection between June 1 and December 31, 2020. The cohort was restricted to individuals residing in private households (N=132,232 cases in 89,191 households), identified through an address matching algorithm. Analysis focused on households in which the index case was aged <18 years. Logistic regression models were fit to estimate the association between age group of pediatric index cases (0-3, 4-8, 9-13, and 14-17 years) and odds of household transmission. RESULTSA total of 6,280 households had pediatric index cases, and 1,717 (27.3%) experienced secondary transmission. Children aged 0-3 years had the highest odds of household transmission compared to children aged 14-17 years (model adjusted for gender, month of disease onset, testing delay, and average family size: 1.43, 95% CI: 1.17-1.75). This association was similarly observed in sensitivity analyses defining secondary cases as 2-14 days or 4-14 days after the index case, and stratified analyses by presence of symptoms, association with a school/childcare outbreak, or school/childcare reopening. Children aged 4-8 years and 9-13 years also had increased odds of transmission (4-8: 1.40, 95% CI: 1.18-1.67; 9-13: 1.13, 95% CI: 0.97-1.32). CONCLUSIONSThis study suggests that younger children are more likely to transmit SARS-CoV-2 infection compared to older children, and the highest odds of transmission was observed for children aged 0-3 years. Differential infectivity of pediatric age groups has implications for infection prevention controls within households, as well as schools/childcare, to minimize risk of household secondary transmission.

Household secondary attack rate of COVID-19 by household size and index case characteristics

In this population-wide study in Ontario, Canada, we investigated the household secondary attack rate (SAR) to understand its relationship to household size and index case characteristics. We identified all patients with confirmed COVID-19 between July 1 and November 30, 2020. Cases within households were matched based on reported residential address; households were grouped based on the number of household contacts. The majority of households (68.2%) had a SAR of 0%, while 3,442 (11.7%) households had a SAR [≥]75%. Overall household SAR was 19.5% and was similar across household sizes, but varied across index case characteristics. Households where index cases had longer delays between symptom onset and test seeking, households with older index cases, households with symptomatic index cases, and larger households located in diverse neighborhoods, were associated with greater household SAR. Our findings present characteristics associated with greater household SARs and proposes immediate testing as a method to reduce household transmission and incidence of COVID-19.

Factors Associated with Timely Test Seeking, Test Turnaround, and Public Reporting of COVID-19: a retrospective analysis in Ontario, Canada

BackgroundMinimizing delays in disease identification and reporting improves the timeliness of surveillance data, and can reduce transmission of COVID-19. Our study investigates factors associated with timely testing and reporting of COVID-19 during the first pandemic wave in one province of Canada. MethodsWe identified all persons with confirmed SARS-CoV-2 infection residing in private households across the largest province of Canada, Ontario from the date of the first confirmed case in Ontario (January 25) to July 19, 2020. Our primary outcomes consisted of: (1) specimen collection within 1 day of symptom onset (test seeking), (2) test result reported to local public health within 1 day of specimen collection (test turnaround), and (3) entry of case data into the provincial database within 1 day of reporting test results (reporting). We examined 14 covariates including eight case characteristics, and six neighborhood characteristics. In addition to descriptive measures, logistic regression models were fitted. Unadjusted models included the covariate alone, while adjusted models included age, gender, month, and region. FindingsAmong 27,198 COVID-19 cases from January 25 2020 to July 19 2020, 28{middle dot}7% had timely test seeking, 40{middle dot}2% had timely test turnaround, and 75{middle dot}5% had timely reporting. Male gender had lower odds of timely test seeking (adjusted odds ratio [aOR] 0{middle dot}79 [95% CI: 0{middle dot}74-0{middle dot}85]) compared to females. Healthcare worker status (aOR 2{middle dot}77 [95% CI: 2{middle dot}52-3{middle dot}05] compared to non-healthcare workers), and age [≥]80 years (aOR 1{middle dot}59 [95% CI: 1{middle dot}33-1{middle dot}91] compared to 40-59 year olds) were associated with timely test seeking. Specimen collection on Fridays and Saturdays (aOR 0{middle dot}88 [95% CI: 0{middle dot}79-0{middle dot}98], aOR 0{middle dot}83 [95% CI: 0{middle dot}74-0{middle dot}92] respectively, compared to Wednesdays) had lower odds of timely test turnaround. Urban areas (aOR 1{middle dot}55 [95% CI: 1{middle dot}41-1{middle dot}70] compared to rural areas) were associated with timely test turnaround. Urban areas (aOR 0{middle dot}79 [95% CI: 0{middle dot}70-0{middle dot}89] compared to rural areas) were less likely to have timely reporting. InterpretationIndividual, neighborhood, and administrative factors are associated with timely testing and reporting of SARS-CoV-2 infections. These findings present considerations for developing targeted strategies to minimize delays and improve timely testing and reporting of SARS-CoV-2 infections. FundingThis study was funded by Public Health Ontario. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and medRxiv up to November 30 2020 to identify studies examining the impact of delays in the disease reporting process on the public health response to COVID-19. We used the search terms ("2019-nCoV" OR "COVID-19" OR "SARS-CoV-2") AND ("delays" OR "timely" OR "reporting" OR "test" OR "turnaround"), and reviewed reference lists of any relevant articles in the original search. Numerous modeling studies have highlighted the importance of timely testing and reporting to effectively control the spread of COVID-19. Additional studies have also identified delays of only 1 day in testing were associated with increased risk of secondary transmission within households. However no study has described the multiple delays in the disease reporting process of COVID-19 and examined factors associated with timely disease reporting using a large population cohort. Added value of this studyOur study described timely test seeking, test turnaround, and reporting for laboratory-confirmed COVID-19 cases in Ontario, Canada and identified associated individual, neighbourhood, and administrative factors. To the best of our knowledge, this study is the first to describe detailed delays in the disease reporting process of COVID-19 and identified associated factors using a large population cohort. Implications of all the available evidenceNumerous individual, neighborhood, and administrative characteristics are associated with timely testing and reporting of COVID-19. These identified factors may be used to develop strategies such as broadened test access, prioritization of vulnerable populations, and increased testing capacity to reduce delays in testing and reporting and improve the effectiveness of public health response to COVID-19.

Neighbourhood-level risk factors of COVID-19 incidence and mortality

BackgroundRacialized and low income communities face disproportionally high rates of coronavirus 2019 (COVID-19) infection and death. However, data on inequities in COVID-19 across granular categories of socio-demographic characteristics is more sparse. MethodsNeighbourhood-level counts of COVID-19 cases and deaths in Ontario, Canada recorded as of July 28th, 2020 were extracted from provincial and local reportable infectious disease surveillance systems. Associations between COVID-19 incidence and mortality and 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics were estimated with Poisson generalized linear mixed models. Housing characteristic variables were subsequently added to models to explore if housing may have a confounding influence on the relationships between immigration, race, and socio-economic status and COVID-19 incidence. ResultsThere were large inequities in COVID-19 incidence and mortality across the socio-demographic variables examined. Neighbourhoods having a higher proportion immigrants, racialized populations, large households and low socio-economic status were associated with COVID-19 risk. Adjusting for housing characteristics, especially unsuitably crowded housing, attenuated COVID-19 risks. However persistent risk remained for neighbourhoods having high proportions of immigrants, racialized populations, and proportion of Black, Latin American, and South Asian residents. ConclusionsSocio-demographic factors account for some of the neighbourhood-level differences in COVID-19 across Ontario. Housing characteristics account for a portion, but not all, of the excess burden of COVID-19 experienced by immigrant, racialized, low income and low education populations.

Risk factors for retirement home COVID-19 outbreaks in Ontario, Canada: A population-level cohort study

BackgroundThe epidemiology of COVID-19 in retirement homes (also known as assisted living facilities) is largely unknown. We examined the association between retirement home and community level characteristics and the risk of COVID-19 outbreaks in retirement homes during the first wave of the COVID-19 epidemic. MethodsWe conducted a population-based retrospective cohort study of licensed retirement homes in Ontario, Canada, from March 1st - September 24th, 2020. Our primary outcome was a COVID-19 outbreak ([≥]1 resident or staff confirmed case by validated nucleic acid amplification assay). We used time-dependent proportional hazards methods to model the associations between retirement home and community level characteristics and COVID-19 outbreaks. ResultsOur cohort included all 770 licensed retirement homes in Ontario, which housed 56,491 residents. There were 172 (22.3%) COVID-19 retirement home outbreaks involving 1,045 (1.9%) residents and 548 staff (1.5%). COVID-19 cases were distributed unevenly across retirement homes, with 1,593 (92.2%) resident and staff cases occurring in 77 (10%) of homes. The adjusted hazard of a COVID-19 outbreak in a retirement home was positively associated with homes that had a large resident capacity, homes that were co-located with a long-term care facility, large corporate owned chains, homes that offered many services onsite, increases in regional COVID-19 incidence, and a higher community-level ethnic concentration. InterpretationReadily identifiable retirement home-level characteristics are independently associated with COVID-19 outbreaks and may support risk identification. A higher ethnic concentration of the community surrounding a retirement home is associated COVID-19 outbreaks, with an uncertain mechanism.

COVID-19 Workplace Outbreaks by Industry Sector and their Associated Household Transmission, Ontario, Canada, January to June, 2020

IntroductionWorkplaces requiring in-person attendance of employees for ongoing operations may be susceptible to SARS-CoV-2 outbreaks that impact workers as well as their close contacts. To understand industry sectors impacted by workplace outbreaks in the first wave of the pandemic, and the additional burden of illness through household transmission, we analyzed public health declared workplace outbreaks between January 21 to June 30, 2020, and their associated cases from January 21 to July 28. MethodsNumber, size and duration of outbreaks were described by sector, and outbreak cases were compared to sporadic cases in the same time frame. Address matching identified household cases with onset [≥]2 days before, [≥]2 days after, or within 1 day of the workplace outbreak case. ResultsThere were 199 outbreaks with 1245 cases, and 68% of outbreaks and 80% of cases belonged to i) Manufacturing, ii) Agriculture, Forestry, Fishing, Hunting, iii) Transportation and Warehousing. Median size of outbreaks was 3 cases (range: 1-140), and lasted median 7days (range: 0-119). Outbreak cases were significantly more likely to be male, younger, healthier, and have better outcomes. There were 608 household cases associated with 339 (31%) outbreak cases with valid addresses, increasing the burden of illness by 56%. The majority of household cases (368, 60%) occurred after the outbreak case. ConclusionsWorkplace outbreaks primarily occurred in three sectors. COVID-19 prevention measures should target industry sectors at risk by preventing introduction from exposed employees, spread in the workplace, and spread outside of the workplace. What is already known about this topic?COVID-19 outbreaks occur within workplaces and can spread to the community What is added by this report?From January 21 - June 30, 2020, there were 199 workplace outbreaks in Ontario, Canada; 68% of outbreaks and 80% of outbreak-associated COVID-19 case were in three industry sectors: Manufacturing, Agriculture/Forestry/Fishing/Hunting, and Transportation/Warehousing. Household transmission occurred among 31% of outbreak cases, resulting in a 56% increase in workplace outbreak-associated cases when burden of household transmission is considered. What are the implications for public health practice?Workplace outbreak prevention measures should be targeted to industry sectors at risk by preventing introduction from exposed employees, spread in the workplace, and transmission to the greater community.

Increased Prescribing of Psychotropic Medications to Ontario Nursing Home Residents during the COVID-19 Pandemic

In this population-based study of all Ontario nursing home residents, we found increased prescribing of psychotropic drugs at the onset of the COVID-19 pandemic that persisted through September 2020. Increases in prescribing were out of proportion to expected secular trends, and distinct from observed prescribing changes in other drugs during the pandemic. Our findings underscore the urgency of balancing infection prevention and control measures in nursing homes with the mental wellbeing of residents.

Impact of a public policy restricting staff mobility between long-term care homes in Ontario, Canada during the COVID-19 pandemic

ObjectivesTo assess changes in the mobility of staff between long-term care homes in Ontario, Canada before and after enactment of public policy restricting staff from working at multiple homes. DesignPre-post observational study. Setting and Participants623 long-term cares homes in Ontario, Canada between March 2020 and June 2020. MethodsWe used anonymized mobile device location data to approximate connectivity between all 623 long-term care homes in Ontario during the 7 weeks before (March 1 - April 21) and after (April 22 - June 13) the policy restricting staff movement was implemented. We visualized connectivity between long-term care homes in Ontario using an undirected network and calculated the number of homes that had a connection with another long-term care home and the average number of connections per home in each period. We calculated the relative difference in these mobility metrics between the two time periods and compared within-home changes using McNemars test and the Wilcoxon rank-sum test. ResultsIn the period preceding restrictions, 266 (42.7%) long-term care homes had a connection with at least one other home, compared to 79 (12.7%) homes during the period after restrictions, a drop of 70.3% (p <0.001). The average number of connections in the before period was 3.90 compared to 0.77 in after period, a drop of 80.3% (p < 0.001). In both periods, mobility between long-term care homes was higher in homes located in larger communities, those with higher bed counts, and those part of a large chain. Conclusions and ImplicationsMobility between long-term care homes in Ontario fell sharply after an emergency order by the Ontario government limiting long-term care staff to a single home, though some mobility persisted. Reducing this residual mobility should be a focus of efforts to reduce risk within the long-term care sector during the COVID-19 pandemic.

Temporal Variations in the Intensity of Care Provided to Community and Nursing Home Residents Who Died of COVID-19 in Ontario, Canada

Introduction - Worldwide, nursing home residents have experienced disproportionately high COVID-19 mortality due to the intersection of congregate living, multimorbidity, and advanced age. Among 12 OECD countries, Canada has had the highest proportion of COVID-19 deaths in nursing home residents (78%), raising concerns about a skewed pandemic response that averted much transmission and mortality in community-dwelling residents, but did not adequately protect those in nursing homes. To investigate this, we measured temporal variations in hospitalizations among community and nursing home-dwelling decedents with COVID-19 during the first and second waves of the pandemic. Methods - We conducted a population-based cohort study of residents of Ontario, Canada with COVID-19 who died between March 11, 2020 (first COVID-19 death in Ontario) and October 28, 2020. We examined hospitalization prior to death as a function of 4 factors: community (defined as all non-nursing home residents) vs. nursing home residence, age in years (<70, 70-79, 80-89, [≥]90), gender, and month of death (1st wave: March-April [peak], May, June-July 2020 [nadir], 2nd wave: August-October 2020). Results - A total of 3,114 people with confirmed COVID-19 died in Ontario from March to October, 2020 (Table 1), of whom 1,354 (43.5%) were hospitalized prior to death (median: 9 days before death, interquartile range: 4-19). Among nursing home decedents (N=2000), 22.4% were admitted to hospital prior to death, but this varied substantially from a low of 15.5% in March-April (peak of wave 1) to a high of 41.2% in June-July (nadir of wave 1). Among community-dwelling decedents (N=1,114), admission to acute care was higher (81.4%) and remained relatively stable throughout the first and second waves. Similar temporal trends for nursing home versus community decedents were apparent in age-stratified analyses (Figure 1). Women who died were less likely to have been hospitalized compared to men in both community (80% women vs 84% men) and nursing home (21% women vs 24% men) settings. Discussion - Only a minority of Ontario nursing home residents who died of COVID-19 were hospitalized prior to death, and that there were substantial temporal variations, with hospitalizations reaching their lowest point when overall COVID-19 incidence peaked in mid-April, 2020. While many nursing home residents had pre-pandemic advance directives precluding hospitalization, the low admission rate observed in March-April 2020 (15.5%) was inconsistent with both higher admission rates in subsequent months (>30%), and comparatively stable rates among community-dwelling adults. Our findings substantiate reports suggesting that hospitalizations for nursing home residents with COVID-19 were low during the peak of the pandemics first wave in Canada, which may have contributed to the particularly high concentration of COVID-19 mortality in Ontarios nursing homes.

Characteristics associated with household transmission of SARS-CoV-2 in Ontario, Canada

BACKGROUNDWithin-household transmission of SARS-CoV-2 infection has been identified as one of the main sources of spread of COVID-19 after lockdown restrictions and self-isolation guidelines are implemented. Secondary attack rates among household contacts are estimated to be five to ten times higher than among non-household contacts, but it is unclear which individuals are more prone to transmit infection within their households. METHODSUsing address matching, a cohort was assembled of all laboratory-confirmed cases of COVID-19 residing in private households in Ontario, Canada. Descriptive analyses were performed to compare characteristics of cases in households that experienced secondary transmission versus those that did not. Logistic regression models were fit to determine index case characteristics and neighbourhood characteristics associated with transmission. FINDINGSBetween January and July, 2020, there were 26,152 cases of COVID-19 residing in 21,226 households. Longer testing delays ([≥]5 days versus 0 days OR=3{middle dot}02, 95% CI: 2{middle dot}53 - 3{middle dot}60) and male sex (OR=1{middle dot}28, 95% CI: 1{middle dot}18 - 1{middle dot}38) were associated with greater odds of household secondary transmission, while being a healthcare worker (OR=0{middle dot}56, 95% CI: 0{middle dot}50 - 0{middle dot}62) was associated with lower odds of transmission. Neighbourhoods with larger average economic family size and a higher proportion of households with multiple persons per room were also associated with greater odds of transmission. INTERPRETATIONIt is important for individuals to get tested for SARS-CoV-2 infection as soon as symptoms appear, and to isolate away from household contacts; this is particularly important in neighbourhoods with large family sizes and/or crowded households. FUNDINGThis study was supported by Public Health Ontario. Research in ContextO_ST_ABSEVIDENCE BEFORE THIS STUDYC_ST_ABSWe searched PubMed and Google Scholar up to September 3, 2020 to identify individual-level cohort studies or meta-analyses on household transmission of COVID-19. We used the search terms ("COVID" OR "SARS-CoV-2") AND ("household" [Title]), and also reviewed the reference lists of any studies found during the search to identify additional studies. We considered studies that reported secondary attack rates and/or other measures of association (i.e., relative risk, odds ratio, or hazard ratio) for household transmission. We did not consider any modelling studies, studies that focused specifically on children, or small case studies that included less than three households. The search returned 53 studies, of which 51 were included in three meta-analyses. Pooled household secondary attack rates from the three meta-analyses were 19%, 27%, and 30%; secondary attack rates in households were estimated to be five to ten times as high as in non-household settings. Most studies were conducted in Asia and identified households from contact tracing, with individual studies reporting on fewer than 6000 households. Most studies did not consider households with no secondary transmission, and focused on a limited set of secondary case characteristics. ADDED VALUE OF THIS STUDYWe applied an address matching algorithm, which identified 21,226 private households of laboratory-confirmed cases of COVID-19 in Ontario, Canada. Ontario has the advantage of a universal healthcare system and population-wide data for the entire province. To our knowledge, this study contains the largest number of private households with at least one confirmed case of COVID-19. We compared a variety of individual- and neighbourhood-level characteristics of households with and without secondary transmission. We also applied logistic regression models to determine index case characteristics associated with transmission, which gave important insights into factors that may help reduce secondary transmission in households. IMPLICATIONS OF ALL THE AVAILABLE EVIDENCEFindings from this study and existing evidence suggest that testing delays and household crowding play important roles in whether household secondary transmission occurs. Odds of household transmission may be reduced by cases seeking testing as soon as symptoms appear, and self-isolating outside the home or in a room alone if possible. These strategies may be considered by public health officials to reduce household transmission and mitigate local spread of COVID-19. Future research should further investigate the role of children and youth in household transmission.

COVID-19 seroprevalence surveys and antibody decline - A note of caution on antibody decline

We analyzed 21,676 residual specimens from Ontario, Canada collected between March-August, 2020 to investigate the effect of antibody decline on SARS-CoV-2 seroprevalence estimates. Testing specimens orthogonally using the Abbott (anti-nucleocapsid) and then the Ortho (anti-spike) assays, seroprevalence estimates ranged from 0.4%-1.4%, despite ongoing disease activity. The geometric mean concentration (GMC) of antibody-positive specimens decreased over time (p=0.015), and the GMC of antibody-negative specimens increased over time (p=0.0018). The association between the two tests decreased each month (p<0.001), suggesting anti-N antibody decline. Lowering the Abbott index cut-off from 1.4 to 0.7 resulted in a 16% increase in positive specimens.

Association Between Nursing Home Crowding and COVID-19 Infection and Mortality in Ontario, Canada

ImportanceNursing home residents have been disproportionately impacted by the COVID-19 epidemic. Prevention recommendations have emphasized frequent testing of healthcare personnel and residents, but additional strategies are needed to protect nursing home residents. ObjectiveWe developed a reproducible index of nursing home crowding and determined whether crowding was associated with incidence of COVID-19 in the first months of the COVID-19 epidemic. Design, Setting, and ParticipantsPopulation-based retrospective cohort study of over 78,000 residents of 618 distinct nursing homes in Ontario, Canada from March 29 to May 20, 2020. ExposureThe nursing home crowding index equalled the average number of residents per bedroom and bathroom. OutcomesPrimary outcomes included the cumulative incidence of COVID-19 infection and mortality, per 100 residents; introduction of COVID-19 into a home ([≥]1 resident case) was a negative tracer. ResultsOf 623 homes in Ontario, we obtained complete information on 618 homes (99%) housing 78,607 residents. A total of 5,218 residents (6.6%) developed COVID-19 infection, and 1,452 (1.8%) died with COVID-19 infection as of May 20, 2020. COVID-19 infection was distributed unevenly across nursing homes: 4,496 (86%) of infections occurred in just 63 (10%) of homes. The crowding index ranged across homes from 1.3 (mainly single-occupancy rooms) to 4.0 (exclusively quadruple occupancy rooms); 308 (50%) homes had high crowding index ([≥]2). Incidence in high crowding index homes was 9.7%, versus 4.5% in low crowding index homes (p<0.001), while COVID-19 mortality was 2.7%, versus 1.3%. The likelihood of COVID-19 introduction did not differ (31.3% vs 30.2%, p=0.79). After adjustment for regional, nursing home, and resident covariates, the crowding index remained associated with increased risk of infection (RR=1.72, 95% Confidence Interval [CI]: 1.11-2.65) and mortality (RR=1.72, 95%CI: 1.03-2.86). Propensity score analysis yielded similar conclusions for infection (RR=2.06, 95%CI: 1.34-3.17) and mortality (RR=2.09, 95%CI: 1.30-3.38). Simulations suggested that converting all 4-bed rooms to 2-bed rooms would have averted 988 (18.9%) infections of COVID-19 and 271 (18.7%) deaths. Conclusions and RelevanceCrowding was associated with higher incidence of COVID-19 infection and mortality. Reducing crowding in nursing homes could prevent future COVID-19 mortality.