Nasopharyngeal Angiotensin Converting Enzyme 2 (ACE2) Expression as a Risk-Factor for SARS-CoV-2 Transmission in Concurrent Hospital Associated Outbreaks (preprint)

Background: Widespread human-to-human transmission of the severe acute respiratory syndrome coronavirus two (SARS-CoV-2) stems from a strong affinity for the cellular receptor angiotensin converting enzyme two (ACE2). We investigate the relationship between a patient's nasopharyngeal ACE2 transcription and secondary transmission within a series of concurrent hospital associated SARS-CoV-2 outbreaks in British Columbia, Canada. Methods: Epidemiological case data from the outbreak investigations was merged with public health laboratory records and viral lineage calls, from whole genome sequencing, to reconstruct the concurrent outbreaks using infection tracing transmission network analysis. ACE2 transcription and RNA viral load were measured by quantitative real-time polymerase chain reaction. The transmission network was resolved to calculate the number of potential secondary cases. Bivariate and multivariable analyses using Poisson and Negative Binomial regression models was performed to estimate the association between ACE2 transcription the number of SARS-CoV-2 secondary cases. Results: The infection tracing transmission network provided n = 76 potential transmission events across n = 103 cases. Bivariate comparisons found that on average ACE2 transcription did not differ between patients and healthcare workers (P = 0.86). High ACE2 transcription was observed in 98.6% of transmission events, either the primary or secondary case had above average ACE2. Multivariable analysis found that the association between ACE2 transcription and the number of secondary transmission events differs between patients and healthcare workers. In health care workers Negative Binomial regression estimated that a one unit change in ACE2 transcription decreases the number of secondary cases (B = -0.132 (95%CI: -0.255 to -0.0181) adjusting for RNA viral load. Conversely, in patients a one unit change in ACE2 transcription increases the number of secondary cases (B = 0.187 (95% CI: 0.0101 to 0.370) adjusting for RNA viral load. Sensitivity analysis found no significant relationship between ACE2 and secondary transmission in health care workers and confirmed the positive association among patients. Conclusion: Our study suggests that ACE2 transcription has a positive association with SARS-CoV-2 secondary transmission in admitted inpatients, but not health care workers in concurrent hospital associated outbreaks, and it should be further investigated as a risk-factor for viral transmission.

Prediction of SARS-CoV-2 transmission dynamics based on population-level cycle threshold values: A Machine learning and mechanistic modeling study (preprint)

Background: Polymerase chain reaction (PCR) cycle threshold (Ct) values can be used to estimate the viral burden of Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2) and predict population-level epidemic trends. We investigated the use of machine learning (ML) and epidemic transmission modeling based on Ct value distribution for SARS-CoV-2 incidence prediction during an Omicron-predominant period. Methods: Using simulated data, we developed a ML model to predict the reproductive number based on Ct value distribution, and validated it on out-of-sample province-level data. We also developed an epidemiological model and fitted it to province-level data to accurately predict incidence. Results: Based on simulated data, the ML model predicted the reproductive number with highest performance on out-of-sample province-level data. The epidemiological model was validated on outbreak data, and fitted to province-level data, and accurately predicted incidence. Conclusions: These modeling approaches can complement traditional surveillance, especially when diagnostic testing practices change over time. The models can be tailored to different epidemiological settings and used in real time to guide public health interventions.

Serial cross-sectional estimation of vaccine and infection-induced SARS-CoV-2 sero-prevalence in children and adults, British Columbia, Canada: March 2020 to August 2022 (preprint)

BackgroundWe chronicle SARS-CoV-2 sero-prevalence through eight cross-sectional sero-surveys (snapshots) in the Lower Mainland (Greater Vancouver and Fraser Valley), British Columbia, Canada from March 2020 to August 2022. MethodsAnonymized-residual sera were obtained from children and adults attending an outpatient laboratory network. Sera were tested with at least three immuno-assays per snapshot to detect spike (S1) and/or nucleocapsid protein (NP) antibodies. Sero-prevalence was defined by dual-assay positivity, including any or infection-induced, the latter requiring S1+NP antibody detection from January 2021 owing to vaccine availability. Infection-induced estimates were used to assess the extent to which surveillance case reports under-estimated infections. ResultsSero-prevalence was [≤]1% by the 3rd snapshot in September 2020 and <5% by January 2021 (4th). Following vaccine roll-out, sero-prevalence increased to >55% by May/June 2021 (5th), [~]80% by September/October 2021 (6th), and >95% by March 2022 (7th). In all age groups, infection-induced sero-prevalence remained <15% through September/October 2021, increasing through subsequent Omicron waves to [~]40% by March 2022 (7th) and [~]60% by July/August 2022 (8th). By August 2022, at least 70-80% of children [≤]19 years, 60-70% of adults 20-59 years, but [~]40% of adults [≥]60 years had been infected. Surveillance case reports under-estimated infections by 12-fold between the 6th-7th and 92-fold between the 7th-8th snapshots. InterpretationBy August 2022, most children and adults had acquired SARS-CoV-2 vaccine and infection exposures, resulting in more robust hybrid immunity. Conversely the elderly, still at greatest risk of severe outcomes, remain largely-dependent on vaccine-induced protection alone, and should be prioritized for additional doses.

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

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

Safety of COVID-19 vaccines in pregnancy: a Canadian National Vaccine Safety (CANVAS) Network study (preprint)

BackgroundPregnant individuals have been receiving COVID-19 vaccines following pre-authorization clinical trials in non-pregnant people. This study aimed to determine significant health events amongst pregnant females after COVID-19 vaccination, compared with unvaccinated pregnant controls and vaccinated non-pregnant individuals. MethodsStudy participants were pregnant and non-pregnant females aged 15-49 years who had received any COVID-19 vaccine, and pregnant unvaccinated controls. Participants reported significant health events occurring within seven days of vaccination. We employed multivariable logistic regression to examine significant health events associated with mRNA vaccines. FindingsOverall 226/5,597(4.0%) vaccinated pregnant females reported a significant health event after dose one of an mRNA vaccine, and 227/3,108(7.3%) after dose two, compared with 11/339(3.2%) pregnant unvaccinated females. Pregnant vaccinated females had an increased odds of a significant health event after dose two of mRNA-1273 (aOR 4.4,95%CI 2.4-8.3) compared to pregnant unvaccinated controls, but not after dose one of mRNA-1273 or any dose of BNT162b2. Pregnant females had decreased odds of a significant health event compared to non-pregnant females after both dose one (aOR 0.63,95%CI 0.55-0.72) and dose two (aOR 0.62,95%CI 0.54-0.71) of mRNA vaccination. There were no significant differences in any analyses when restricted to events which led to medical attention. InterpretationCOVID-19 mRNA vaccines have a good safety profile in pregnancy. Rates of significant health events were higher after dose two of mRNA-1273 compared with unvaccinated controls, with no difference when considering events leading to medical consultation. Rates of significant health events were lower in pregnant females than similarly aged non-pregnant individuals. FundingThis work was supported by the COVID-19 Vaccine Readiness funding from the Canadian Institutes of Health Research and the Public Health Agency of Canada CANVAS grant number CVV-450980 and by funding from the Public Health Agency of Canada, through the Vaccine Surveillance Reference Group and the COVID-19 Immunity Task Force.

Impact of routine asymptomatic screening on COVID-19 incidence in a highly vaccinated university population (preprint)

Background: With the return of in-person classes, an understanding of COVID-19 transmission in vaccinated university campuses is essential. Given the context of high anticipated vaccination rates and other measures, there are outstanding questions of the potential impact of campus-based asymptomatic screening. Methods: We estimated the expected number of cases and hospitalizations in one semester using rates derived for British Columbia (BC), Canada up to September 15th, 2021 and age-standardizing to a University population. To estimate the expected number of secondary cases averted due to routine tests of unvaccinated individuals in a BC post-secondary institution, we used a probabilistic model based on the incidence, vaccination effectiveness, vaccination coverage and R0. We examined multiple scenarios of vaccine coverage, screening frequency, and pre-vaccination R0. Results: For one 12 week semester, the expected number of cases is 67 per 50,000 for 80\% vaccination coverage and 37 per 50,000 for 95\% vaccination coverage. Screening of the unvaccinated population averts an expected 6-16 cases per 50,000 at 80\% decreasing to 1-2 averted cases per 50,000 at 95\% vaccination coverage for weekly to daily screening. Further scenarios can be explored using a web-based application. Interpretation: Routine screening of unvaccinated individuals may be of limited benefit if vaccination coverage is 80\% or greater within a university setting.

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

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 = 2.83 (90% CrI [credible interval] 0.25-7.19) than standard methods, with a range within facilities of 0.66-10.06. We further estimated that intervention led to 67% (56%-73%) of all cases being averted within the LTHC facilities. 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.

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

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.