Association between nursing home crowding and outbreak-associated respiratory infection and death prior to the COVID-19 pandemic between 2014 and 2019 in Ontario, Canada

ImportanceResident crowding in nursing homes is associated with larger SARS-CoV-2 outbreaks. However, this association has not been previously documented for non-SARS-CoV-2 respiratory infections. ObjectiveWe sought to measure the association between nursing home crowding and respiratory infections in Ontario nursing homes prior to the COVID-19 pandemic. Design, Setting, and ParticipantsWe conducted a retrospective cohort study of nursing home residents in Ontario, Canada over a five-year period prior to the COVID-19 pandemic, between September 2014 and August 2019. ExposureUsing administrative data, we estimated the crowding index equal to the mean number of residents per bedroom and bathroom (residents / [0.5*bedrooms+0.5*bathrooms]). OutcomesThe incidence of outbreak-associated infections and mortality per 100 nursing home residents per year. We also examined infection and mortality outcomes for outbreaks due to 7 specific pathogens: coronaviruses (OC43, 229E, NL63, HKU1), influenza A, influenza B, human metapneumovirus, parainfluenza virus, respiratory syncytial virus, rhinovirus/enterovirus. ResultsThere was one or more respiratory outbreak in 93.9% (588/626) nursing homes in Ontario. There were 4,921 outbreaks involving 64,829 cases of respiratory infection, and 1,969 deaths. Outbreaks attributable to a single identified pathogen were principally caused by influenza A (29%), rhinovirus (11.7%), influenza B (8.1%), and respiratory syncytial virus (6.1%). Among homes, 42.7% (251/588) homes had a high crowding index ([≥] 2.0). After adjustment, more crowded homes had higher outbreak-associated respiratory infection incidence (aRR 1.89; 95% 1.64-2.18) and mortality incidence (aRR 2.28; 95% 1.84-2.84). More crowded homes had higher adjusted estimates of the incidence of infection and mortality for each of the 7 respiratory pathogens examined. Conclusions and RelevanceResidents of crowded nursing homes experienced more respiratory-outbreak infections and mortality due to influenza and other non-SARS-CoV-2 respiratory pathogens. Decreasing crowding in nursing homes is an important patient safety target beyond the COVID-19 pandemic.

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.

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.

Healthcare Worker COVID-19 Cases in Ontario, Canada: A Cross-sectional Study

ImportanceProtecting healthcare workers (HCWs) from COVID-19 is a priority to maintain a safe and functioning healthcare system. The risk of transmitting COVID-19 to family members is a source of stress for many. ObjectiveTo describe and compare HCW and non-HCW COVID-19 cases in Ontario, Canada, as well as the frequency of COVID-19 among HCWs household members. Design, Setting, and ParticipantsUsing reportable disease data at Public Health Ontario which captures all COVID-19 cases in Ontario, Canada, we conducted a population-based cross-sectional study comparing demographic, exposure, and clinical variables between HCWs and non-HCWs with COVID-19 as of 14 May 2020. We calculated rates of infections over time and determined the frequency of within household transmissions using natural language processing based on residential address. Exposures and OutcomesWe contrasted age, gender, comorbidities, clinical presentation (including asymptomatic and presymptomatic), exposure histories including nosocomial transmission, and clinical outcomes between HCWs and non-HCWs with confirmed COVID-19. ResultsThere were 4,230 (17.5%) HCW COVID-19 cases in Ontario, of whom 20.2% were nurses, 2.3% were physicians, and the remaining 77.4% other specialties. HCWs were more likely to be between 30-60 years of age and female. HCWs were more likely to present asymptomatically (8.1% versus 7.0%, p=0.010) or with atypical symptoms (17.8% versus 10.5%, p<0.001). The mortality among HCWs was 0.2% compared to 10.5% of non-HCWs. HCWs commonly had exposures to a confirmed case or outbreak (74.1%), however only 3.1% were confirmed to be nosocomial. The rate of new infections was 5.5 times higher in HCWs than non-HCWs, but mirrored the epidemic curve. We identified 391 (9.8%) probable secondary household transmissions and 143 (3.6%) acquisitions. Children < 19 years comprised 14.6% of secondary cases compared to only 4.2% of the primary cases. Conclusions and RelevanceHCWs represent a disproportionate number of COVID-19 cases in Ontario but with low confirmed numbers of nosocomial transmission. The data support substantial testing bias and under-ascertainment of general population cases. Protecting HCWs through appropriate personal protective equipment and physical distancing from colleagues is paramount. Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the differences between healthcare workers and non-healthcare workers with COVID-19? FindingsIn this population-based cross-sectional study there were 4,230 healthcare workers comprising 17.5% of COVID-19 cases. Healthcare workers were diagnosed with COVID-19 at a rate 5.5 times higher than the general population with 0.8% of all healthcare workers, compared to 0.1% of non-healthcare workers. MeaningHigh healthcare worker COVID-19 burden highlights the importance of physical distancing from colleagues, appropriate personal protective equipment, as well as likely substantial testing bias and under-ascertainment of COVID-19 in the general population.