Characteristics of the Sexual Networks of Men Who Have Sex With Men in Montréal, Toronto, and Vancouver: Insights from Canada's 2022 Mpox Outbreak.

BACKGROUND: The 2022-2023 global mpox outbreak disproportionately affected gay, bisexual, and other men who have sex with men (GBM). We investigated differences in GBM's sexual partner distributions across Canada's 3 largest cities and over time, and how they shaped transmission. METHODS: The Engage Cohort Study (2017-2023) recruited GBM via respondent-driven sampling in Montréal, Toronto, and Vancouver (n = 2449). We compared reported sexual partner distributions across cities and periods: before COVID-19 (2017-2019), pandemic (2020-2021), and after lifting of restrictions (2021-2023). We used Bayesian regression and poststratification to model partner distributions. We estimated mpox's basic reproduction number (R0) using a risk-stratified compartmental model. RESULTS: Pre-COVID-19 pandemic distributions were comparable: fitted average partners (past 6 months) were 10.4 (95% credible interval: 9.4-11.5) in Montréal, 13.1 (11.3-15.1) in Toronto, and 10.7 (9.5-12.1) in Vancouver. Sexual activity decreased during the pandemic and increased after lifting of restrictions, but remained below prepandemic levels. Based on reported cases, we estimated R0 of 2.4 to 2.7 and similar cumulative incidences (0.7%-0.9%) across cities. CONCLUSIONS: Similar sexual partner distributions may explain comparable R0 and cumulative incidence across cities. With potential for further recovery in sexual activity, mpox vaccination and surveillance strategies should be maintained.

An Ensemble Framework for Projecting the Impact of Lymphatic Filariasis Interventions Across Sub-Saharan Africa at a Fine Spatial Scale.

BACKGROUND: Lymphatic filariasis (LF) is a neglected tropical disease targeted for elimination as a public health problem by 2030. Although mass treatments have led to huge reductions in LF prevalence, some countries or regions may find it difficult to achieve elimination by 2030 owing to various factors, including local differences in transmission. Subnational projections of intervention impact are a useful tool in understanding these dynamics, but correctly characterizing their uncertainty is challenging. METHODS: We developed a computationally feasible framework for providing subnational projections for LF across 44 sub-Saharan African countries using ensemble models, guided by historical control data, to allow assessment of the role of subnational heterogeneities in global goal achievement. Projected scenarios include ongoing annual treatment from 2018 to 2030, enhanced coverage, and biannual treatment. RESULTS: Our projections suggest that progress is likely to continue well. However, highly endemic locations currently deploying strategies with the lower World Health Organization recommended coverage (65%) and frequency (annual) are expected to have slow decreases in prevalence. Increasing intervention frequency or coverage can accelerate progress by up to 5 or 6 years, respectively. CONCLUSIONS: While projections based on baseline data have limitations, our methodological advancements provide assessments of potential bottlenecks for the global goals for LF arising from subnational heterogeneities. In particular, areas with high baseline prevalence may face challenges in achieving the 2030 goals, extending the "tail" of interventions. Enhancing intervention frequency and/or coverage will accelerate progress. Our approach facilitates preimplementation assessments of the impact of local interventions and is applicable to other regions and neglected tropical diseases.

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.

Adverse Events Following Immunization With mRNA and Viral Vector Vaccines in Individuals With Previous Severe Acute Respiratory Syndrome Coronavirus 2 Infection From the Canadian National Vaccine Safety Network.

BACKGROUND: Adults previously infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop short-term immunity and may have increased reactogenicity to coronavirus disease 2019 (COVID-19) vaccines. This prospective, multicenter, 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 22 December 2020 and 27 November 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 (interquartile range: 2-6) months previously. After dose 1, individuals with moderate (bedridden) to severe (hospitalized) COVID-19 who received BNT162b2, mRNA-1273, 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 [95% confidence interval]: 3.96 [3.67-4.28] for BNT162b2, 5.01 [4.57-5.50] for mRNA-1273, and 1.84 [1.54-2.20] for ChAdox1-S compared with no infection). Following dose 2 and 3, the greater risk associated with previous infection was also present but was attenuated compared with dose 1. For all doses, the association was lower or absent after mild or asymptomatic infection. CONCLUSIONS: 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 dose.

Emergence of SARS-CoV-2 Delta Variant and Effect of Nonpharmaceutical Interventions, British Columbia, Canada.

In British Columbia, Canada, initial growth of the SARS-CoV-2 Delta variant was slower than that reported in other jurisdictions. Delta became the dominant variant (>50% prevalence) within ≈7-13 weeks of first detection in regions within the United Kingdom and United States. In British Columbia, it remained at <10% of weekly incident COVID-19 cases for 13 weeks after first detection on March 21, 2021, eventually reaching dominance after 17 weeks. We describe the growth of Delta variant cases in British Columbia during March 1-June 30, 2021, and apply retrospective counterfactual modeling to examine factors for the initially low COVID-19 case rate after Delta introduction, such as vaccination coverage and nonpharmaceutical interventions. Growth of COVID-19 cases in the first 3 months after Delta emergence was likely limited in British Columbia because additional nonpharmaceutical interventions were implemented to reduce levels of contact at the end of March 2021, soon after variant emergence.

Changes in emergency department use in British Columbia, Canada, during the first 3 years of the COVID-19 pandemic.

BACKGROUND: Previous studies have shown reductions in the volume of emergency department visits early in the COVID-19 pandemic, but few have evaluated the pandemic's impact over time or stratified analyses by reason for visits. We aimed to quantify such changes in British Columbia, Canada, cumulatively and during prominent nadirs, and by reason for visit, age and acuity. METHODS: We included data from the National Ambulatory Care Reporting System for 30 emergency departments across BC from January 2016 to December 2022. We fitted generalized additive models, accounting for seasonal and annual trends, to the monthly number of visits to estimate changes throughout the pandemic, compared with the expected number of visits in the absence of the pandemic. We determined absolute and relative differences at various times during the study period, and cumulatively since the start of the pandemic until the overall volume of emergency department visits returned to expected levels. RESULTS: Over the first 16 months of the pandemic, the volume of emergency department visits was reduced by about 322 300 visits, or 15% (95% confidence interval 12%-18%), compared with the expected volume. A sharp drop in pediatric visits accounted for nearly one-third of the reduction. The timing of the return to baseline volume of visits differed by subgroup. The largest and most sustained decreases were in respiratory-related emergency department visits, visits among children, visits among oldest adults and non-urgent visits. Later in the pandemic, we observed increased volumes of highest-urgency visits, visits among children and visits related to ear, nose and throat. INTERPRETATION: We have extended evidence that the impact of the COVID-19 pandemic and associated mitigation strategies on emergency department visits in Canada was substantial. Both our findings and methods are relevant in public health surveillance and capacity planning for emergency departments in pandemic and nonpandemic times.

Risk of hospital admission and death from first-ever SARS-CoV-2 infection by age group during the Delta and Omicron periods in British Columbia, Canada.

BACKGROUND: Population-based cross-sectional serosurveys within the Lower Mainland, British Columbia, Canada, showed about 10%, 40% and 60% of residents were infected with SARS-CoV-2 by the sixth (September 2021), seventh (March 2022) and eighth (July 2022) serosurveys. We conducted the ninth (December 2022) and tenth (July 2023) serosurveys and sought to assess risk of severe outcomes from a first-ever SARS-CoV-2 infection during intersurvey periods. METHODS: Using increments in cumulative infection-induced seroprevalence, population census, discharge abstract and vital statistics data sets, we estimated infection hospitalization and fatality ratios (IHRs and IFRs) by age and sex for the sixth to seventh (Delta/Omicron-BA.1), seventh to eighth (Omicron-BA.2/BA.5) and eighth to ninth (Omicron-BA.5/BQ.1) intersurvey periods. As derived, IHR and IFR estimates represent the risk of severe outcome from a first-ever SARS-CoV-2 infection acquired during the specified intersurvey period. RESULTS: The cumulative infection-induced seroprevalence was 74% by December 2022 and 79% by July 2023, exceeding 80% among adults younger than 50 years but remaining less than 60% among those aged 80 years and older. Period-specific IHR and IFR estimates were consistently less than 0.3% and 0.1% overall. By age group, IHR and IFR estimates were less than 1.0% and up to 0.1%, respectively, except among adults aged 70-79 years during the sixth to seventh intersurvey period (IHR 3.3% and IFR 1.0%) and among those aged 80 years and older during all periods (IHR 4.7%, 2.2% and 3.5%; IFR 3.3%, 0.6% and 1.3% during the sixth to seventh, seventh to eighth and eighth to ninth periods, respectively). The risk of severe outcome followed a J-shaped age pattern. During the eighth to ninth period, we estimated about 1 hospital admission for COVID-19 per 300 newly infected children younger than 5 years versus about 1 per 30 newly infected adults aged 80 years and older, with no deaths from COVID-19 among children but about 1 death per 80 newly infected adults aged 80 years and older during that period. INTERPRETATION: By July 2023, we estimated about 80% of residents in the Lower Mainland, BC, had been infected with SARS-CoV-2 overall, with low risk of hospital admission or death; about 40% of the oldest adults, however, remained uninfected and at highest risk of a severe outcome. First infections among older adults may still contribute substantial burden from COVID-19, reinforcing the need to continue to prioritize this age group for vaccination and to consider them in health care system planning.

Beyond audit: Embracing QI methodology to drive improvements in lung-protective ventilation.

BACKGROUND: Mechanical ventilation supports patients with respiratory failure during critical illness. Evidence suggests that excessive tidal volumes (regarded as >8 mL/kg predicted body weight [PBW]) cause lung damage through increased lung stretch and alveolar inflammation. Lung-protective ventilation strategies have been shown to decrease morbidity and mortality, and that all patients should receive tidal volumes between 6 and 8 mls/kg PBW. Despite this, studies demonstrate that fewer than half of patients in critical care successfully receive lung-protective ventilation. AIM: The primary aim was to reduce tidal volumes delivered to all patients receiving mandatory ventilation, with a target of >85% of tidal volumes delivered to be compliant with lung-protective ventilation strategies by the end of November 2019. METHODS: A multidisciplinary team of nurses and doctors, based in a UK tertiary hospital, utilized the Institute for Healthcare Improvement's (IHI) quality improvement methodology to improve compliance with lung-protective ventilation. RESULTS: Baseline data demonstrated that only 60.1% of tidal volumes recorded were compliant with lung-protective ventilation. Quality improvement (QI) methodology was utilized to systematically diagnose the aetiology of poor compliance and to produce and implement solutions. Real-time data collection and reporting were utilized to monitor and report improvement. Following 8 months of continuous data collection and repeated PDSA cycles, sustainable compliance with lung-protective ventilation for >85% of tidal volumes was achieved. CONCLUSIONS: The use of QI methodology to implement low tidal volume ventilation has shown a significant improvement in the delivery of lung-protective ventilation. Using QI methodology is central to this sustained improvement and offers a useful tool to systematically approach complex clinical problems. RELEVANCE TO CLINICAL PRACTICE: Lung protective ventilation is critically important in the management of ventilated patients, although compliance in intensive care is variable. Here, we describe how quality improvement methodology can lead to consistent and sustainable improvement in the delivery of lung protective ventilation.

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.

Interactive Visualization Applications in Population Health and Health Services Research: Systematic Scoping Review.

BACKGROUND: Simple visualizations in health research data, such as scatter plots, heat maps, and bar charts, typically present relationships between 2 variables. Interactive visualization methods allow for multiple related facets such as numerous risk factors to be studied simultaneously, leading to data insights through exploring trends and patterns from complex big health care data. The technique presents a powerful tool that can be used in combination with statistical analysis for knowledge discovery, hypothesis generation and testing, and decision support. OBJECTIVE: The primary objective of this scoping review is to describe and summarize the evidence of interactive visualization applications, methods, and tools being used in population health and health services research (HSR) and their subdomains in the last 15 years, from January 1, 2005, to March 30, 2019. Our secondary objective is to describe the use cases, metrics, frameworks used, settings, target audience, goals, and co-design of applications. METHODS: We adapted standard scoping review guidelines with a peer-reviewed search strategy: 2 independent researchers at each stage of screening and abstraction, with a third independent researcher to arbitrate conflicts and validate findings. A comprehensive abstraction platform was built to capture the data from diverse bodies of literature, primarily from the computer science and health care sectors. After screening 11,310 articles, we present findings from 56 applications from interrelated areas of population health and HSR, as well as their subdomains such as epidemiologic surveillance, health resource planning, access, and use and costs among diverse clinical and demographic populations. RESULTS: In this companion review to our earlier systematic synthesis of the literature on visual analytics applications, we present findings in 6 major themes of interactive visualization applications developed for 8 major problem categories. We found a wide application of interactive visualization methods, the major ones being epidemiologic surveillance for infectious disease, resource planning, health service monitoring and quality, and studying medication use patterns. The data sources included mostly secondary administrative and electronic medical record data. In addition, at least two-thirds of the applications involved participatory co-design approaches while introducing a distinct category, embedded research, within co-design initiatives. These applications were in response to an identified need for data-driven insights into knowledge generation and decision support. We further discuss the opportunities stemming from the use of interactive visualization methods in studying global health; inequities, including social determinants of health; and other related areas. We also allude to the challenges in the uptake of these methods. CONCLUSIONS: Visualization in health has strong historical roots, with an upward trend in the use of these methods in population health and HSR. Such applications are being fast used by academic and health care agencies for knowledge discovery, hypotheses generation, and decision support. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14019.

Application of the Eosinophilic Esophagitis Histology Scoring System Grade Scores in Patients at British Columbia Children's Hospital.

INTRODUCTION: Histologic diagnosis of eosinophilic esophagitis (EoE) involves peak eosinophil counts (PEC) being greater than 15 per high power field. The EoE Histology Scoring System (EoEHSS) was developed to comprehensively evaluate biopsies to better predict symptom and endoscopy response; we aimed to validate the EoEHSS in our provincial registry, where EoEHSS had not been employed. METHODS: We reviewed 186 esophageal biopsies from 16 patients at diagnosis and follow-up. Statistical analyses were conducted to quantify how grade scores correlate with active EoE status and PEC counts, and each feature's ability to predict active disease. RESULTS: Nearly all EoEHSS variables were associated with active EoE and high PEC, with basal zone hyperplasia, eosinophil abscesses, and surface epithelial alteration being most predictive in identifying active EoE. CONCLUSIONS: We validated and demonstrated each EoEHSS variable's strength in tracking traditional PEC counts, resulting in its adoption as a standard reporting element for our research registry.

Maternal Epstein-Barr Virus-Specific Antibodies and Risk of Infection in Ugandan Infants.

BACKGROUND: Epstein-Barr virus (EBV) infection is a major cause of malignancy worldwide. Maternal antibody is thought to prevent EBV infection because it is uncommon in early infancy. Maternal HIV infection is associated with an increased incidence of EBV infection in exposed infants, which we hypothesized results from impaired transfer of EBV-neutralizing maternal antibodies. METHODS: Among Ugandan infants followed for EBV acquisition from birth, we measured antibody binding to EBV glycoproteins (gp350, gH/gL) involved in B-cell and epithelial-cell entry, as well as viral neutralization and antibody-dependent cellular cytotoxicity (ADCC) activity in plasma samples prior to infection. These serologic data were analyzed for differences between HIV-exposed uninfected (HEU) and HIV-unexposed (HUU) infants, and for associations with incident infant EBV infection. RESULTS: HEU infants had significantly higher titers than HUU infants for all EBV-binding and neutralizing antibodies measured (P < .01) but not ADCC activity, which was similar between groups. No antibody measure was associated with a decreased risk of EBV acquisition in the cohort. CONCLUSIONS: Our findings indicate that in this cohort maternal antibody did not protect infants against EBV infection through viral neutralization. The identification of protective nonneutralizing antibody functions would be invaluable for the development of an EBV vaccine.

Validation of a Clinical Prediction Rule to Predict Asymptomatic Chlamydia and Gonorrhea Infections Among Internet-Based Testers.

BACKGROUND: Clinical prediction rules (CPRs) can be used in sexually transmitted infection (STI) testing environments to prioritize individuals at the highest risk of infection and optimize resource allocation. We previously derived a CPR to predict asymptomatic chlamydia and/or gonorrhea (CT/NG) infection among women and heterosexual men at in-person STI clinics based on 5 predictors. Population differences between clinic-based and Internet-based testers may limit the tool's application across settings. The primary objective of this study was to assess the validity, sensitivity, and overall performance of this CPR within an Internet-based testing environment (GetCheckedOnline.com). METHODS: We analyzed GetCheckedOnline online risk assessment and laboratory data from October 2015 to June 2019. We compared the STI clinic population used for CPR derivation (data previously published) and the GetCheckedOnline validation population using χ2 tests. Calibration and discrimination were assessed using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating curve, respectively. Sensitivity and the fraction of total screening tests offered were quantified for CPR-predicted risk scores. RESULTS: Asymptomatic CT/NG infection prevalence in the GetCheckedOnline population (n = 5478) was higher than in the STI clinic population (n = 10,437; 2.4% vs. 1.8%, P = 0.007). When applied to GetCheckedOnline, the CPR had reasonable calibration (Hosmer-Lemeshow, P = 0.90) and discrimination (area under the receiver operating characteristic, 0.64). By screening only individuals with total risk scores ≥4, we would detect 97% of infections and reduce screening by 14%. CONCLUSIONS: The application of an existing CPR to detect asymptomatic CT/NG infection is valid within an Internet-based STI testing environment. Clinical prediction rules applied online can reduce unnecessary STI testing and optimize resource allocation within publicly funded health systems.

The use of mixture density networks in the emulation of complex epidemiological individual-based models.

Complex, highly-computational, individual-based models are abundant in epidemiology. For epidemics such as macro-parasitic diseases, detailed modelling of human behaviour and pathogen life-cycle are required in order to produce accurate results. This can often lead to models that are computationally-expensive to analyse and perform model fitting, and often require many simulation runs in order to build up sufficient statistics. Emulation can provide a more computationally-efficient output of the individual-based model, by approximating it using a statistical model. Previous work has used Gaussian processes (GPs) in order to achieve this, but these can not deal with multi-modal, heavy-tailed, or discrete distributions. Here, we introduce the concept of a mixture density network (MDN) in its application in the emulation of epidemiological models. MDNs incorporate both a mixture model and a neural network to provide a flexible tool for emulating a variety of models and outputs. We develop an MDN emulation methodology and demonstrate its use on a number of simple models incorporating both normal, gamma and beta distribution outputs. We then explore its use on the stochastic SIR model to predict the final size distribution and infection dynamics. MDNs have the potential to faithfully reproduce multiple outputs of an individual-based model and allow for rapid analysis from a range of users. As such, an open-access library of the method has been released alongside this manuscript.

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.

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.

Anti-Thymocyte Globulin Prophylaxis Induces a Decrease in Naive Th Cells to Inhibit the Onset of Chronic Graft-versus-Host Disease: Results from the Canadian Bone Marrow Transplant Group (CBMTG) 0801 Study.

Anti-thymocyte globulin (ATG) is an established approach to decrease chronic GVHD (cGVHD), yet the exact mechanism is uncertain. To better understand the mechanism of action of ATG in preventing cGVHD, we evaluated the day 100 immune reconstitution of known cGVHD cellular biomarkers using patients from the randomized Canadian Bone Marrow Transplant Group (CBMTG) 0801 trial, which demonstrated a significant impact of ATG on cGVHD. In a separate companion biology study, we evaluated the impact of ATG prophylaxis on cGVHD cellular markers at day 100 in 40 CBMTG 0801 patients. Analysis focused on previously identified cGVHD cellular biomarkers, including naive helper T (Th) cells, recent thymic emigrant (RTE) Th cells, CD21low B cells, CD56bright NKreg cells, and Treg cells ST2, osteopontin, soluble B-cell activating factor (sBAFF), Interleukin-2 receptor alpha (sCD25), T-cell immunoglobulin and mucin domain-3 (TIM-3), matrix metallopeptidase 3, ICAM-1, C-X-C motif chemokine 10 (CXCL10), and soluble aminopeptidase N. The ATG-treated group had a >10-fold decrease in both RTE naive Th and naive Th cells (P < .0001) and a 10-fold increase in CD56bright NKreg cells (P < .0001). Treg cells, conventional Th cells, CD21low B cells, and all plasma markers were not affected. In the populations most affected by ATG, changes in naive Th cells were associated with the later development of cGVHD. This analysis suggests that ATG primarily impacts on cGVHD through suppression of naive Th cell expansion after transplantation. These associations need to be validated in additional studies.

Modeling COVID-19 and Its Impacts on U.S. Immigration and Customs Enforcement (ICE) Detention Facilities, 2020.

U.S. Immigration and Customs Enforcement (ICE) facilities house thousands of undocumented immigrants in environments discordant with the public health recommendations to reduce the transmission of 2019 novel coronavirus (COVID-19). Using ICE detainee population data obtained from the ICE Enforcement and Removal Operations (ERO) website as of March 2, 2020, we implemented a simple stochastic susceptible-exposed-infected-recovered model to estimate the rate of COVID-19 transmission within 111 ICE detention facilities and then examined impacts on regional hospital intensive care unit (ICU) capacity. Models considered three scenarios of transmission (optimistic, moderate, pessimistic) over 30-, 60-, and 90-day time horizons across a range of facility sizes. We found that 72% of individuals are expected to be infected by day 90 under the optimistic scenario (R0 = 2.5), while nearly 100% of individuals are expected to be infected by day 90 under a more pessimistic (R0 = 7) scenario. Although asynchronous outbreaks are more likely, day 90 estimates provide an approximation of total positive cases after all ICE facility outbreaks. We determined that, in the most optimistic scenario, coronavirus outbreaks among a minimum of 65 ICE facilities (59%) would overwhelm ICU beds within a 10-mile radius and outbreaks among a minimum of 8 ICE facilities (7%) would overwhelm local ICU beds within a 50-mile radius over a 90-day period, provided every ICU bed was made available for sick detainees. As policymakers seek to rapidly implement interventions that ensure the continued availability of life-saving medical resources across the USA, they may be overlooking the pressing need to slow the spread of COVID-19 infection in ICE's detention facilities. Preventing the rapid spread necessitates intervention measures such as granting ICE detainees widespread release from an unsafe environment by returning them to the community.

Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review.

BACKGROUND: Visual analytics (VA) promotes the understanding of data with visual, interactive techniques, using analytic and visual engines. The analytic engine includes automated techniques, whereas common visual outputs include flow maps and spatiotemporal hot spots. OBJECTIVE: This scoping review aims to address a gap in the literature, with the specific objective to synthesize literature on the use of VA tools, techniques, and frameworks in interrelated health care areas of population health and health services research (HSR). METHODS: Using the 2018 PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, the review focuses on peer-reviewed journal articles and full conference papers from 2005 to March 2019. Two researchers were involved at each step, and another researcher arbitrated disagreements. A comprehensive abstraction platform captured data from diverse bodies of the literature, primarily from the computer and health sciences. RESULTS: After screening 11,310 articles, findings from 55 articles were synthesized under the major headings of visual and analytic engines, visual presentation characteristics, tools used and their capabilities, application to health care areas, data types and sources, VA frameworks, frameworks used for VA applications, availability and innovation, and co-design initiatives. We found extensive application of VA methods used in areas of epidemiology, surveillance and modeling, health services access, use, and cost analyses. All articles included a distinct analytic and visualization engine, with varying levels of detail provided. Most tools were prototypes, with 5 in use at the time of publication. Seven articles presented methodological frameworks. Toward consistent reporting, we present a checklist, with an expanded definition for VA applications in health care, to assist researchers in sharing research for greater replicability. We summarized the results in a Tableau dashboard. CONCLUSIONS: With the increasing availability and generation of big health care data, VA is a fast-growing method applied to complex health care data. What makes VA innovative is its capability to process multiple, varied data sources to demonstrate trends and patterns for exploratory analysis, leading to knowledge generation and decision support. This is the first review to bridge a critical gap in the literature on VA methods applied to the areas of population health and HSR, which further indicates possible avenues for the adoption of these methods in the future. This review is especially important in the wake of COVID-19 surveillance and response initiatives, where many VA products have taken center stage. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/14019.

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.