Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19.

The outbreak of the severe acute respiratory syndrome coronavirus 2 started in Wuhan, China, towards the end of 2019 and spread worldwide. The rapid spread of the disease can be attributed to many factors including its high infectiousness and the high rate of human mobility around the world. Although travel/movement restrictions and other non-pharmaceutical interventions aimed at controlling the disease spread were put in place during the early stages of the pandemic, these interventions did not stop COVID-19 spread. To better understand the impact of human mobility on the spread of COVID-19 between regions, we propose a hybrid gravity-metapopulation model of COVID-19. Our modeling framework has the flexibility of determining mobility between regions based on the distances between the regions or using data from mobile devices. In addition, our model explicitly incorporates time-dependent human mobility into the disease transmission rate, and has the potential to incorporate other factors that affect disease transmission such as facemasks, physical distancing, contact rates, etc. An important feature of this modeling framework is its ability to independently assess the contribution of each factor to disease transmission. Using a Bayesian hierarchical modeling framework, we calibrate our model to the weekly reported cases of COVID-19 in thirteen local health areas in Metro Vancouver, British Columbia (BC), Canada, from July 2020 to January 2021. We consider two main scenarios in our model calibration: using a fixed distance matrix and time-dependent weekly mobility matrices. We found that the distance matrix provides a better fit to the data, whilst the mobility matrices have the ability to explain the variance in transmission between regions. This result shows that the mobility data provides more information in terms of disease transmission than the distances between the regions.

Observed negative vaccine effectiveness could be the canary in the coal mine for biases in observational COVID-19 studies.

Since the emergence of the SARS-CoV-2 Omicron variant, multiple observational studies have reported negative vaccine effectiveness (VE) against infection, symptomatic infection, and even severity (hospitalization), potentially leading to an interpretation that vaccines were facilitating infection and disease. However, current observations of negative VE likely stem from the presence of various biases (e.g., exposure differences, testing differences). Although negative VE is more likely to arise when true biological efficacy is generally low and biases are large, positive VE measurements can also be subject to the same mechanisms of bias. In this perspective, we first outline the different mechanisms of bias that could lead to false-negative VE measurements and then discuss their ability to potentially influence other protection measurements. We conclude by discussing the use of suspected false-negative VE measurements as a signal to interrogate the estimates (quantitative bias analysis) and to discuss potential biases when communicating real-world immunity research.

Adverse Events Following Immunization with mRNA and Viral Vector Vaccines in Individuals with Previous SARS-CoV-2 Infection from the Canadian National Vaccine Safety Network.

BACKGROUND: Adults previously infected with SARS-CoV-2 develop short-term immunity and may have increased reactogenicity to COVID-19 vaccines. This prospective, multi-center active surveillance cohort study examined the short-term safety of COVID-19 vaccines in adults with a prior history of SARS-CoV-2. METHODS: Canadian adults vaccinated between December 22, 2020 and November 27, 2021 were sent an electronic questionnaire 7 days post dose 1, dose 2 and dose 3 vaccination. The main outcome was health events occurring in the first 7 days after each vaccination that prevented daily activities, resulted in work absenteeism or required a medical consultation, including hospitalization. RESULTS: Among 684,998 vaccinated individuals, 2.6% (18,127/684,998) reported a prior history of SARS-CoV-2 infection a median of 4 months (interquartile range 2-6 months) previously. After dose 1, individuals with moderate (bedridden) to severe (hospitalized) COVID-19 who received BNT162b2, mRNA1273 or ChAdox1-S vaccines had higher odds of a health event preventing daily activities, resulting in work absenteeism or requiring medical consultation; adjusted odds ratio (AOR) 3.96 (95% CI 3.67-4.28) for BNT162b2, 5.01 (4.57-5.50) for mRNA1273 and 1.84 (1.54-2.20) for ChAdox1-S compared to no infection. Following dose 2 and 3, the greater risk associated with previous infection was also present but attenuated compared to dose 1. For all doses, the association was lower or absent after mild or asymptomatic infection. CONCLUSION: Adults with moderate or severe previous SARS-CoV-2 infection were more likely to have a health event sufficient to impact routine activities or require medical assessment in the week following each vaccine doses.

Serial cross-sectional estimation of vaccine-and infection-induced SARS-CoV-2 seroprevalence in British Columbia, Canada.

BACKGROUND: The evolving proportion of the population considered immunologically naive versus primed for more efficient immune memory response to SARS-CoV-2 has implications for risk assessment. We sought to chronicle vaccine- and infection-induced seroprevalence across the first 7 waves of the COVID-19 pandemic in British Columbia, Canada. METHODS: During 8 cross-sectional serosurveys conducted between March 2020 and August 2022, we obtained anonymized residual sera from children and adults who attended an outpatient laboratory network in the Lower Mainland (Greater Vancouver and Fraser Valley). We used at least 3 immunoassays per serosurvey to detect SARS-CoV-2 spike and nucleocapsid antibodies. We assessed any seroprevalence (vaccineor infection-induced, or both), defined by positivity on any 2 assays, and infection-induced seroprevalence, also defined by dual-assay positivity but requiring both antinucleocapsid and antispike detection. We used estimates of infection-induced seroprevalence to explore underascertainment of infections by surveillance case reports. RESULTS: By January 2021, we estimated that any seroprevalence remained less than 5%, increasing with vaccine rollout to 56% by May-June 2021, 83% by September-October 2021 and 95% by March 2022. Infection-induced seroprevalence remained less than 15% through September-October 2021, increasing across Omicron waves to 42% by March 2022 and 61% by July-August 2022. By August 2022, 70%-80% of children younger than 20 years and 60%-70% of adults aged 20-59 years had been infected, but fewer than half of adults aged 60 years and older had been infected. Compared with estimates of infection-induced seroprevalence, surveillance case reports underestimated infections 12-fold between September 2021 and March 2022 and 92-fold between March 2022 and August 2022. INTERPRETATION: By August 2022, most children and adults younger than 60 years had evidence of both SARS-CoV-2 vaccination and infection. As previous evidence suggests that a history of both exposures may induce stronger, more durable hybrid immunity than either exposure alone, older adults - who have the lowest infection rates but highest risk of severe outcomes - continue to warrant prioritized vaccination.

SARS-CoV-2 seroprevalence among Vancouver public school staff in British Columbia, Canada: a cross-sectional study.

OBJECTIVES: Few studies reported COVID-19 cases in schools during the 2020/21 academic year in a setting of uninterrupted in-person schooling. The main objective was to determine the SARS-CoV-2 seroprevalence among school staff in Vancouver public schools. DESIGN: Cumulative incident COVID-19 cases among all students and school staff based on public health data, with an embedded cross-sectional serosurvey among a school staff sample that was compared to period, age, sex and geographical location-weighted data from blood donors. SETTING: Vancouver School District (British Columbia, Canada) from kindergarten to grade 12. PARTICIPANTS: Active school staff enrolled from 3 February to 23 April 2021 with serology testing from 10 February to 15 May 2021. MAIN OUTCOME MEASURES: SARS-CoV-2 seroprevalence among school staff, based on spike (S)-based (unvaccinated staff) or N-based serology testing (vaccinated staff). RESULTS: Public health data showed the cumulative incidence of COVID-19 among students attending in-person was 9.8 per 1000 students (n=47 280), and 13 per 1000 among school staff (n=7071). In a representative sample of 1689 school staff, 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% (363/1686) of surveyed staff self-reported close contact with a COVID-19 case outside of their household (16.5% contacts were school-based), 5 cases likely acquired the infection at school based on viral testing. Sensitivity/Specificity-adjusted seroprevalence in 1556/1689 staff (92.1%) was 2.3% (95% CI: 1.6% to 3.2%), comparable to a sex, age, date and residency area-weighted seroprevalence of 2.6% (95% CI: 2.2% to 3.1%) among 5417 blood donors. CONCLUSION: Seroprevalence among staff was comparable to a reference group of blood donors from the same community. These data show that in-person schooling could be safely maintained during the 2020/21 school year with mitigation measures, in a large school district in Vancouver, Canada.

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.

Quantifying transmissibility of SARS-CoV-2 and impact of intervention within long-term healthcare facilities.

Estimates of the basic reproduction number (R 0) for COVID-19 are particularly variable in the context of transmission within locations such as long-term healthcare (LTHC) facilities. We sought to characterize the heterogeneity of R 0 across known outbreaks within these facilities. We used a unique comprehensive dataset of all outbreaks that occurred within LTHC facilities in British Columbia, Canada as of 21 September 2020. We estimated R 0 in 18 LTHC outbreaks with a novel Bayesian hierarchical dynamic model of susceptible, exposed, infected and recovered individuals, incorporating heterogeneity of R 0 between facilities. We further compared these estimates to those obtained with standard methods that use the exponential growth rate and maximum likelihood. The total size of outbreaks varied dramatically, with range of attack rates 2%-86%. The Bayesian analysis provided an overall estimate of R 0 = 2.51 (90% credible interval 0.47-9.0), with individual facility estimates ranging between 0.56 and 9.17. Uncertainty in these estimates was more constrained than standard methods, particularly for smaller outbreaks informed by the population-level model. We further estimated that intervention led to 61% (52%-69%) of all potential cases being averted within the LTHC facilities, or 75% (68%-79%) when using a model with multi-level intervention effect. Understanding of transmission risks and impact of intervention are essential in planning during the ongoing global pandemic, particularly in high-risk environments such as LTHC facilities.

Usability of Virtual Visits for the Routine Clinical Care of Trans Youth during the COVID-19 Pandemic: Youth and Caregiver Perspectives.

We evaluated families' perspectives on the usability of virtual visits for routine gender care for trans youth during the COVID-19 pandemic. An online survey, which included a validated telehealth usability questionnaire, was sent to families who had a virtual Gender Clinic visit between March and August 2020. A total of 87 participants completed the survey (28 trans youth, 59 caregivers). Overall, usability was rated highly, with mean scores between "quite a bit" and "completely" in all categories (usefulness, ease of use, interface and interaction quality, reliability, and satisfaction). Caregivers reported higher usability scores compared to trans youth [mean (SD) 3.43 (0.80) vs. 3.12 (0.93), p = 0.01]. All families felt that virtual visits provided for their healthcare needs. A total of 100% of youth and caregivers described virtual appointments as safer or as safe as in-person visits. A total of 94% of participants would like virtual visits after the pandemic; families would choose a mean of two virtual and one yearly in-person visit with a multidisciplinary team. Overall, virtual gender visits for trans youth had impressive usability. Participants perceived virtual visits to be safe. For the future, a combination of virtual and in-person multidisciplinary visits is the most desired model.

An Interrupted Time-Series Analysis of Pediatric Emergency Department Visits During the Coronavirus Disease 2019 Pandemic.

OBJECTIVE: The objective of this study was to estimate the impact of the coronavirus disease 2019 pandemic on pediatric emergency department (PED) visits after declaration of stay-at-home orders within British Columbia, Canada, and the change in cases by acuity and age for 6 months during the pandemic. METHODS: Retrospective data on PED visits at British Columbia Children's Hospital were collected between December 1, 2019, and August 31, 2020, and for 2 previous years. An interrupted time-series analysis was performed to estimate the difference in daily visits after stay-at-home orders on March 17, 2020, as well as before and after. Further analysis was performed to estimate the drop and recovery of admission and visits by age and acuity. RESULTS: After adjustment for year and seasonality, we documented a drop in the expected number of daily visits of 83 (95% confidence interval [CI], 78-89) after stay-at-home orders. Thereafter, daily visits increased by 12.9 (95% CI, 11.3-14.4) every month. Probability of admission adjusted for seasonality and acuity increased 6.9% (95% CI, 4.9%-9.0%) after stay-at-home orders and decreased in the odds of -0.7% (95% CI, -1% to -0.4%) monthly thereafter. CONCLUSIONS: The coronavirus disease 2019 pandemic has had a dramatic and lasting impact on the number of PED visits, with contracted rates 6 months into the pandemic. Further increase in acuity-adjusted rate of admissions after stay at home orders suggests that individuals may be delaying arrival to the emergency department. Further assessment is needed to determine if patients are seeking care through other venues or not seeking care altogether.

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

Extensive non-pharmaceutical and physical distancing measures are currently the primary interventions 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, with the timing of distancing measures informed by survey data on attitudes to distancing and COVID-19. We fit our model to reported COVID-19 cases in British Columbia (BC), Canada, and five other jurisdictions, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimated the impact that physical distancing (social distancing) has had on the contact rate and examined the projected impact of relaxing distancing measures. We found that, as of April 11 2020, distancing had a strong impact in BC, consistent with declines in reported cases and in hospitalization and intensive care unit numbers; individuals practising physical distancing experienced approximately 0.22 (0.11-0.34 90% CI [credible interval]) of their normal contact rate. The threshold above which prevalence was expected to grow was 0.55. We define the "contact ratio" to be the ratio of the estimated contact rate to the threshold rate at which cases are expected to grow; we estimated this contact ratio to be 0.40 (0.19-0.60) in BC. We developed an R package 'covidseir' to make our model available, and used it to quantify the impact of distancing in five additional jurisdictions. As of May 7, 2020, we estimated that New Zealand was well below its threshold value (contact ratio of 0.22 [0.11-0.34]), New York (0.60 [0.43-0.74]), Washington (0.84 [0.79-0.90]) and Florida (0.86 [0.76-0.96]) were progressively closer to theirs yet still below, but California (1.15 [1.07-1.23]) was above its threshold overall, with cases still rising. Accordingly, we found that BC, New Zealand, and New York may have had more room to relax distancing measures than the other jurisdictions, though this would need to be done cautiously and with total case volumes in mind. Our projections indicate that intermittent distancing measures-if sufficiently strong and robustly followed-could control COVID-19 transmission. This approach provides a useful tool for jurisdictions to monitor and assess current levels of distancing relative to their threshold, which will continue to be essential through subsequent waves of this pandemic.

Severe COVID-19 Infection and Pediatric Comorbidities: A Systematic Review and Meta-Analysis.

OBJECTIVE: There is limited information on the severity of COVID-19 infection in children with comorbidities. We investigated the effects of pediatric comorbidities on COVID-19 severity by means of a systematic review and meta-analysis of published literature. METHODS: PubMed, Embase, and Medline databases were searched for publications on pediatric COVID-19 infections published January 1st to October 5th, 2020. Articles describing at least one child with and without comorbidities, COVID-19 infection, and reported outcomes were included. RESULTS: 42 studies containing 275,661 children without comorbidities and 9,353 children with comorbidities were included. Severe COVID-19 was present in 5.1% of children with comorbidities, and in 0.2% without comorbidities. Random-effects analysis revealed a higher risk of severe COVID-19 among children with comorbidities than for healthy children; relative risk ratio 1.79 (95% CI 1.27 - 2.51; I2 = 94%). Children with underlying conditions also had a higher risk of COVID-19-associated mortality; relative risk ratio 2.81 (95% CI 1.31 - 6.02; I2 = 82%). Children with obesity had a relative risk ratio of 2.87 (95% CI 1.16 - 7.07; I2 = 36%). CONCLUSIONS: Children with comorbidities have a higher risk of severe COVID-19 and associated mortality than children without underlying disease. Additional studies are required to further evaluate this relationship.

Paediatric patients seen in 18 emergency departments during the COVID-19 pandemic.

BACKGROUND: Public health mitigation strategies in British Columbia during the pandemic included stay-at-home orders and closure of non-essential services. While most primary physicians' offices were closed, hospitals prepared for a pandemic surge and emergency departments (EDs) stayed open to provide care for urgent needs. We sought to determine whether ED paediatric presentations prior and during the COVID-19 pandemic changed and review acuity compared with seasonal adjusted prior year. METHODS: We analysed records from 18 EDs in British Columbia, Canada, serving 60% of the population. We included children 0-16 years old and excluded those with no recorded acuity or discharge disposition and those left without being seen by a physician. We compared prepandemic (before the first COVID-19 case), early pandemic (after first COVID-19 case) and peak pandemic (during public health emergency) periods as well as a similar time from the previous year. RESULTS: A reduction of 57% and 70% in overall visits was recorded in the children's hospital ED and the general hospitals EDs, respectively. Average daily visits declined significantly during the peak-pandemic period (167.44±40.72) compared with prepandemic period (543.53±58.8). Admission rates increased mainly due to the decrease in the rate of visits with lower acuity. Children with complaints of 'fever' and 'gastrointestinal' symptoms had both the largest overall volume and per cent reduction in visits between peak-pandemic and prior year (79% and 74%, respectively). CONCLUSION: Paediatric emergency medicine attendances were reduced to one-third of normal numbers during the 2020 COVID-19 lockdown in British Columbia, Canada, with the reduction mainly seen in minor illnesses that do not usually require admission.