SARS-CoV-2 seroprevalence among public school staff in Metro Vancouver after the first Omicron wave in British Columbia, Canada

ObjectiveTo determine the SARS-CoV-2 seroprevalence among school workers in the setting of full in-person schooling and the highly transmissible Omicron variants of concern. DesignCross-sectional study among school staff, comparing to period-, age-, sex- and postal code-weighted data from Canadian blood donors from the same community. SettingThree large school districts in the greater Vancouver metropolitan area, British Columbia, Canada, with serology sampling done between January 26, 2022 and April 8, 2022. ParticipantsSchool staff actively working in the Vancouver, Richmond and Delta School Districts. Main outcome measureSARS-CoV-2 seroprevalence based on nucleocapsid (N)-protein testing, adjusted for the sensitivity and specificity of the assay. ResultsA majority (65.8%) of the 1845 school staff enrolled reported close contact with a COVID-19 case outside the household. Of those, about half reported close contact with a COVID-19 case at school either in a student (51.5%) or co-worker (54.9%). In a representative sample of 1620 (87.8%) school staff, the adjusted seroprevalence was 26.5% [95%CrI: 23.9 - 29.3%]. This compared to an age, sex and residency area-weighted seroprevalence of 32.4% [95%CrI: 30.6 - 34.5%] among 7164 blood donors. ConclusionDespite frequent COVID-19 exposures, the prevalence of SARS-CoV-2 infections among the staff of three main school districts in the Vancouver metropolitan area was no greater than a reference group of blood donors, even after the emergence of the more transmissible Omicron variant. What is already known on this subject?O_LIEarlier studies indicate that COVID-19 infection rates are not increased among school staff at previous stages of the pandemic compared to the community, yet controversy remains whether this will remain true after the emergence of the highly transmissible Omicron variant. C_LI What this study adds?O_LIDespite frequent COVID-19 exposures, this study identified no detectable increase in SARS-CoV-2 seroprevalence among school staff working in three metro Vancouver public school districts after the first Omicron wave in British Columbia, compared to a reference group of blood donors from the same age, sex and community area. C_LI

Symptomatic and asymptomatic transmission of SARS-CoV-2 in K-12 schools, British Columbia, April to June 2021

We prospectively studied SARS-CoV-2 transmission at schools in an era of Variants of Concern (VoCs), offering all close contacts serial viral asymptomatic testing up to 14 days. Of 229 school close contacts, 3 tested positive (1.3%), of which 2 were detected through asymptomatic testing. Most secondary transmission (90%) occurred in households. Routine asymptomatic testing of close contacts should be examined in the context of local testing rates, preventive measures, programmatic costs, and health impacts of asymptomatic transmission.

Mathematical modeling of COVID-19 in British Columbia:an age-structured model with time-dependent contact rates

Following the emergence of COVID-19 at the end of 2019, several mathematical models have been developed to study the transmission dynamics of this disease. Many of these models assume homogeneous mixing in the underlying population. However, contact rates and mixing patterns can vary dramatically among individuals depending on their age and activity level. Variation in contact rates among age groups and over time can significantly impact how well a model captures observed trends. To properly model the age-dependent dynamics of COVID-19 and understand the impacts of interventions, it is essential to consider heterogeneity arising from contact rates and mixing patterns. We developed an age-structured model that incorporates time-varying contact rates and population mixing computed from the ongoing BC Mix COVID-19 survey to study transmission dynamics of COVID-19 in British Columbia (BC), Canada. Using a Bayesian inference framework, we fit four versions of our model to weekly reported cases of COVID-19 in BC, with each version allowing different assumptions of contact rates. We show that in addition to incorporating age-specific contact rates and mixing patterns, time-dependent (weekly) contact rates are needed to adequately capture the observed transmission dynamics of COVID-19. Our approach provides a framework for explicitly including empirical contact rates in a transmission model, which removes the need to otherwise model the impact of many non-pharmaceutical interventions. Further, this approach allows projection of future cases based on clear assumptions of age-specific contact rates, as opposed to less tractable assumptions regarding transmission rates.

Severity of SARS-CoV-2 reinfections in second wave determines likelihood of mild endemicity

Immunity to SARS-CoV-2 is building up globally, but will this be sufficient to prevent future COVID-19 epidemics in the face of variants and waning immunity? Manaus, Brazil offers a concerning glimpse of what may come: six months after the majority of the citys population experienced primary infection, a second wave with a new strain resulted in more deaths than the first wave. Current hypotheses for this surge rely on prior immunity waning due to time and antigenic distance. Here we show this hypothesis predicts a severe endemic state. We propose an alternative hypothesis in which individuals infected in the first wave lose protection against transmission but retain immunity against severe disease and show this hypothesis is equally compatible with existing data. In this scenario, the increased number of deaths is due to an increased infection fatality ratio (IFR) for primary infections with the new variant. This alternative predicts a mild endemic state will be reached within decades. Collecting data on the severity of reinfections and infections post-vaccination as a function of time and antigenic distance from the original exposure is crucial for optimizing control strategies.

SARS-CoV-2 seroprevalence among Vancouver public school staff in British Columbia, Canada

ImportanceContact-tracing studies suggest minimal secondary transmission in schools. However, there are limited school data accounting for asymptomatic cases, particularly late in the 2020/21 school year, and in the context of uninterrupted in-person schooling and widespread community transmission. ObjectivesTo determine the SARS-CoV-2 seroprevalence in a sample of school staff, compared to the community, and to COVID-19 rates among all students and staff within the same school population. DesignIncident COVID-19 cases among students and school staff using public health data, with an embedded cross-sectional serosurvey among school staff sampled from February 10 to May 15, 2021, comparing to age, sex and geographic location-matched blood donors sampled in January 2021. SettingVancouver School District (British Columbia, Canada) from kindergarten to grade 12. ParticipantsActive school staff enrolled from February 3 to April 23, 2021. Main outcome measuresSARS-CoV-2 antibodies in a sample of school staff using spike (S)-based testing (unvaccinated staff) or N-based serology testing (vaccinated staff). ResultsThe incidence of COVID-19 cases among students attending in-person was 9.8 per 1,000 students during the 2020/21 school year (N = 47,280 students), and among staff was 13 per 1,000 since the beginning of the pandemic (N = 7,071 active school staff). In total, 1,689 school staff (64% elementary, 28% secondary, 8.3% school board staff or multiple grades) completed the questionnaire, 78.2% had classroom responsibilities, and spent a median of 17.6 hours in class per week [IQR: 5.0 - 25 hours]. Although 21.5% (363/1,686) reported close contact with a COVID-19 case, only 1.4% (24/1688) of the school staff reported having had a positive viral nucleic acid test. Of this group, five believed they acquired the infection at school. The adjusted seroprevalence in staff who gave blood (1,556/1,689, 92.1%) was 2.3% [95%CI: 1.6 - 3.2%] compared to 2.3% [95%CI: 1.7 - 3.0%] in blood donors. Conclusion and relevanceDespite high reported COVID-19 cases among students and staff, and frequent within-school exposures, we found no detectable increase in seroprevalence among school staff above the community seroprevalence. These findings corroborate claims that, with appropriate mitigation strategies, in-person schooling is not associated with significantly increased risk for school staff. Key PointsO_ST_ABSQuestionC_ST_ABSWhat was the prevalence of COVID-19 infections in school staff who maintained in-person schooling during the 2020/21 school year in Vancouver, British Columbia, and how does it compare to the risk of COVID-19 infection in the community. FindingsAs of March 4, 2021, the incidence of COVID-19 cases among school staff was 13 per 1,000 (N = 7,071 school staff) since the beginning of the pandemic. In a cross-sectional seroprevalence analysis from February 10 to May 15, 2021, the adjusted seroprevalence among a sample of school staff (N = 1,556) was 2.3% [95%CI: 1.6 - 3.2%], compared to 2.3% [95%CI: 1.7 - 3.0%] in 1:2 age, sex and geographical location (by postal code)-matched reference group of blood donors. MeaningWe found no detectable increase in seroprevalence among school staff above the community seroprevalence. These findings corroborate claims that, with appropriate mitigation strategies in place, in-person schooling is not associated with significantly higher risk for school staff.

Quantifying transmissibility of COVID-19 and impact of intervention within long-term health care facilities

Estimates of the basic reproduction number (R0) for Coronavirus disease 2019 (COVID-19) are particularly variable in the context of transmission within locations such as long-term health care (LTHC) facilities. We sought to characterise the heterogeneity of R0 across known outbreaks within these facilities. We used a unique comprehensive dataset of all outbreaks that have occurred within LTHC facilities in British Columbia, Canada. We estimated R0 with a Bayesian hierarchical dynamic model of susceptible, exposed, infected, and recovered individuals, that incorporates heterogeneity of R0 between facilities. We further compared these estimates to those obtained with standard methods that utilize the exponential growth rate and maximum likelihood. The total size of an outbreak varied dramatically, with a range of attack rates of 2%-86%. The Bayesian analysis provides more constrained overall estimates of R0 = 2.19 (90% CrI [credible interval] 0.19-6.69) than standard methods, with a range within facilities of 0.48-10.08. We further estimated that intervention led to 57% (47%-66%) of all cases being averted within the LTHC facilities, or 73% (63%-78%) when using a model with multi-level intervention effect. Understanding the risks and impact of intervention are essential in planning during the ongoing global pandemic, particularly in high-risk environments such as LTHC facilities.

How much leeway is there to relax COVID-19 control measures?

Following successful widespread non-pharmaceutical interventions aiming to control COVID-19, many jurisdictions are moving towards reopening economies and borders. Given that little immunity has developed in most populations, re-establishing higher contact rates within and between populations carries substantial risks. Using a Bayesian epidemiological model, we estimate the leeway to reopen in a range of national and regional jurisdictions that have experienced different COVID-19 epidemics. We estimate the risks associated with different levels of reopening and the likely burden of new cases due to introductions from other jurisdictions. We find widely varying leeway to reopen, high risks of exceeding past peak sizes, and high possible burdens per introduced case per week, up to hundreds in some jurisdictions. We recommend a cautious approach to reopening economies and borders, coupled with strong monitoring for changes in transmission.

Estimating the impact of COVID-19 control measures using a Bayesian model of physical distancing

Extensive physical distancing measures are currently the primary intervention against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing measures, with the timing of these measures informed by survey data on attitudes to distancing and COVID-19. We fit our model to reported COVID-19 cases in British Columbia, Canada, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimate the impact that physical distancing (also known as social distancing) has had on the contact rate and examine the projected impact of relaxing distancing measures. We find that distancing has had a strong impact, consistent with declines in reported cases and in hospitalization and intensive care unit numbers. We estimate that approximately 0.78 (0.66-0.89 90% CI) of contacts have been removed for individuals in British Columbia practising physical distancing and that this fraction is above the threshold of 0.45 at which prevalence is expected to grow. However, relaxing distancing measures beyond this threshold re-starts rapid exponential growth. Because the extent of underestimation is unknown, the data are consistent with a wide range in the prevalence of COVID-19 in the population; changes to testing criteria over time introduce additional uncertainty. Our projections indicate that intermittent distancing measures--if sufficiently strong and robustly followed-- could control COVID-19 transmission, but that if distancing measures are relaxed too much, the epidemic curve would grow to high prevalence.