Potential Biases in Test-Negative Design Studies of COVID-19 Vaccine Effectiveness Arising from the Inclusion of Asymptomatic Individuals.

The test-negative design (TND) is a popular method for evaluating vaccine effectiveness (VE). A "classical" TND study includes symptomatic individuals tested for the disease targeted by the vaccine to estimate VE against symptomatic infection. However, recent applications of the TND have attempted to estimate VE against infection by including all tested individuals, regardless of their symptoms.

Generalizability of anti-SARS-CoV-2 seroprevalence estimates to the Montréal pediatric population: a comparison between two weighting methods.

Seroprevalence studies on SARS-CoV-2 infections have been often based on study populations with non-random and non-representative samples, limiting the generalizability of their results. In this study, we investigated the representativity and the generalizability of the baseline (collected from October 16th, 2020, to April 18th, 2021) estimate of a pediatric seroprevalence study based in Montréal. We compared the change in the estimates of seroprevalence for two different weighting methods: marginal standardization and raking.

Zika emergence, persistence, and transmission rate in Colombia: a nationwide application of a space-time Markov switching model.

Zika, a viral disease transmitted to humans by Aedes mosquitoes, emerged in the Americas in 2015, causing large-scale epidemics. Colombia alone reported over 72,000 Zika cases between 2015 and 2016. Using national surveillance data from 1121 municipalities over 70 weeks, we identified sociodemographic and environmental factors associated with Zika's emergence, re-emergence, persistence, and transmission intensity in Colombia.

Characterizing Trends in the Use of Food Donations and Other Food-Related Community-Based Social Assistance Programs in a Cohort of New Food Bank Users in Quebec, Canada.

To characterize 12-month trends in the use of food donations and other food-related community-based social assistance programs (CB-SAPs) during the first year following the enrollment of new food bank (FB) users in Quebec, Canada. A cohort of 1,001 newly registered FB-users in Quebec from the Pathways Study were followed-up during 12-month following baseline assessment. Outcomes were monthly use of food donations and other food-related CB-SAPs.

How to plan and manage an individual participant data meta-analysis. An illustrative toolkit.

Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognostic model development and evaluation. However, IPD-MAs are resource-intensive and require careful budgeting of time from data contributing groups, a dedicated management team, diversity of expertise, clearly documented data sharing and authorship agreements, and consistent and clear communication. We present a toolkit to facilitate the implementation and management of IPD-MAs, from study recruitment to retrospective harmonization.

The Pathways study: a cohort study of new food-aid users in rural, semi urban, and urban areas of Quebec, Canada.

Background: While considerable research has been conducted on household food insecurity (HFI), little research has examined the effects of food donation programs on users' living conditions. The Pathways study was established to investigate the long-term effects of food donation programs on food insecurity as well as other critical outcomes, such as diet, health, and social support. Herein, we describe the design of the Pathways Study and the participants' characteristics at baseline.

Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses.

Background: Individual participant data meta-analyses (IPD-MAs), which involve harmonising and analysing participant-level data from related studies, provide several advantages over aggregate data meta-analyses, which pool study-level findings. IPD-MAs are especially important for building and evaluating diagnostic and prognostic models, making them an important tool for informing the research and public health responses to COVID-19.

Methods: We conducted a rapid systematic review of protocols and publications from planned, ongoing, or completed COVID-19-related IPD-MAs to identify areas of overlap and maximise data request and harmonisation efforts.

Traffic-Calming Measures and Road Traffic Collisions and Injuries: A Spatiotemporal Analysis.

Traffic-calming measures (TCMs) are physical modifications of the road network aimed at making the roads safer. Although researchers have reported reductions in numbers of road crashes and injuries tied to the presence of TCMs, such studies have been criticized for their pre-/post- designs. In this study, we aimed to complement our knowledge of TCMs' effectiveness by assessing their impact using a longitudinal design.

Heterogeneity of Zika virus exposure and outcome ascertainment across cohorts of pregnant women, their infants and their children: a metadata survey.

Objectives: To support the Zika virus (ZIKV) Individual Participant Data (IPD) Consortium's efforts to harmonise and analyse IPD from ZIKV-related prospective cohort studies and surveillance-based studies of pregnant women and their infants and children; we developed and disseminated a metadata survey among ZIKV-IPD Meta-Analysis (MA) study participants to identify and provide a comprehensive overview of study-level heterogeneity in exposure, outcome and covariate ascertainment and definitions.

Setting: Cohort and surveillance studies that measured ZIKV infection during pregnancy or at birth and measured fetal, infant, or child outcomes were identified through a systematic search and consultations with ZIKV researchers and Ministries of Health from 20 countries or territories.

Participants: Fifty-four cohort or active surveillance studies shared deidentified data for the IPD-MA and completed the metadata survey, representing 33 061 women (11 020 with ZIKV) and 18 281 children.

Spatio-temporal clusters and patterns of spread of dengue, chikungunya, and Zika in Colombia.

Background: Colombia has one of the highest burdens of arboviruses in South America. The country was in a state of hyperendemicity between 2014 and 2016, with co-circulation of several Aedes-borne viruses, including a syndemic of dengue, chikungunya, and Zika in 2015.

Methodology/principal Findings: We analyzed the cases of dengue, chikungunya, and Zika notified in Colombia from January 2014 to December 2018 by municipality and week.

A joint spatial marked point process model for dengue and severe dengue in Medellin, Colombia.

The spatial distribution of surveillance-reported dengue cases and severity are usually analyzed separately, assuming independence between the spatial distribution of non-severe and severe cases. Given the availability of data for the individual geo-location of surveillance-notified dengue cases, we conducted a spatial analysis to model non-severe and severe dengue simultaneously, using a hierarchical Bayesian model. We fit a joint model to the spatial pattern formed by dengue cases as well as to the severity status of the cases.

Decomposition of socioeconomic inequalities in arboviral diseases in Brazil and Colombia (2007-2017).

Background: We used surveillance data from Brazil and Colombia during 2007-2017 to assess the presence of socioeconomic inequalities on dengue, chikungunya and Zika at the neighborhood level in two Latin American cities.

Methods: To quantify the inequality, we estimated and decomposed the relative concentration index of inequality (RCI) accounting for the spatiotemporal distribution of the diseases.

Results: There were 281 426 arboviral cases notified in Fortaleza, Brazil, and 40 889 in Medellin, Colombia.

Dengue, Severity Paradox, and Socioeconomic Distribution Among Afro-Colombians.

Background: The clinical presentation of dengue ranges from self-limited mild illness to severe forms, including death. African ancestry is often described as protective against dengue severity. However, in the Latin American context, African ancestry has been associated with increased mortality.

Estimating force of infection from serologic surveys with imperfect tests.

Background: The force of infection, or the rate at which susceptible individuals become infected, is an important public health measure for assessing the extent of outbreaks and the impact of control programs.

Methods And Findings: We present Bayesian methods for estimating force of infection using serological surveys of infections which produce a lasting immune response, accounting for imperfections of the test, and uncertainty in such imperfections. In this estimation, the sensitivity and specificity can either be fixed, or belief distributions of their values can be elicited to allow for uncertainty.

Assessing the reporting of Dengue, Chikungunya and Zika to the National Surveillance System in Colombia from 2014-2017: A Capture-recapture analysis accounting for misclassification of arboviral diagnostics.

Background: Chikungunya, dengue, and Zika are three different arboviruses which have similar symptoms and are a major public health issue in Colombia. Despite the mandatory reporting of these arboviruses to the National Surveillance System in Colombia (SIVIGILA), it has been reported that the system captures less than 10% of diagnosed cases in some cities.

Methodology/principal Findings: To assess the scope and degree of arboviruses reporting in Colombia between 2014-2017, we conducted an observational study of surveillance data using the capture-recapture approach in three Colombian cities.

Effectiveness of trauma centre verification: a systematic review and meta-analysis.

Background: There is a growing trend toward verification of trauma centres, but its impact remains unclear. This systematic review aimed to synthesize available evidence on the effectiveness of trauma centre verification.

Methods: We conducted a systematic search of the CINAHL, Embase, HealthStar, MEDLINE and ProQuest databases, as well as the websites of key injury organizations for grey literature, from inception to June 2019, without language restrictions.

Estimating the Force of Infection for Dengue Virus Using Repeated Serosurveys, Ouagadougou, Burkina Faso.

Because of limited data on dengue virus in Burkina Faso, we conducted 4 consecutive age-stratified longitudinal serologic surveys, ≈6 months apart, among persons 1-55 years of age, during June 2015-March 2017, which included a 2016 outbreak. The seroconversion rate before the serosurvey enrollment was estimated by binomial regression, taking age as the duration of exposure, and assuming constant force of infection (FOI) over age and calendar time. We calculated FOI between consecutive surveys and rate ratios for potentially associated characteristics based on seroconversion using the duration of intervals.

Spatiotemporal distribution and socioeconomic disparities of dengue, chikungunya and Zika in two Latin American cities from 2007 to 2017.

Objective: To assess the presence, pattern and magnitude of socioeconomic inequalities on dengue, chikungunya and Zika in Latin America, accounting for their spatiotemporal distribution.

Methods: Using longitudinal surveillance data (reported arboviruses) from Fortaleza, Brazil and Medellin, Colombia (2007-2017), we fit Bayesian hierarchical models with structured random effects to estimate: (i) spatiotemporally adjusted incidence rates; (ii) Relative Concentration Index and Absolute Concentration Index of inequality; (iii) temporal trends in RCIs; and (iv) socioeconomic-specific estimates of disease distribution. The spatial analysis was conducted at the neighbourhood level (urban settings).

Treatment Switch to Dolutegravir With 2 Nucleoside Reverse-Transcriptase Inhibitors (NRTI) in Comparison to Continuation With Protease Inhibitor/Ritonavir Among Patients With Human Immunodeficiency Virus at Risk for Prior NRTI Resistance: A Cohort Analysis of Real-World Data.

Background: Switching antiretroviral regimens when human immunodeficiency virus (HIV) viremia is controlled for a new regimen is challenging when there is the potential for prior nucleoside reverse-transcriptase inhibitor (NRTI) resistance. The objective was to study virologic outcomes after switching to dolutegravir compared with remaining on a boosted protease inhibitor (protease inhibitor/ritonavir [PI/r]) regimen in people with HIV (PWH) with prior documented virologic failure and/or exposure to mono/dual NRTIs.

Methods: We used the Quebec HIV Cohort including 10 219 PWH whose data were collected at 4 sites in Montreal, Canada.

Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia.

The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level data) and department level in Colombia to predict weekly dengue cases for 12-weeks ahead. A pooled national model based on artificial neural networks (ANN) was also developed and used as a comparator to the RF models.

Vulnerable road-user deaths in Brazil: a Bayesian hierarchical model for spatial-temporal analysis.

Reducing the road traffic injuries burden is relevant to many sustainable development goals (SDG), in particular SDG3 - to establish good health and well-being. To describe the spatial-temporal trends and identify hotspot regions for fatal road traffic injuries, a Bayesian hierarchical Poisson model was used to analyze data on vulnerable road users (bicyclist, motorcyclist and pedestrians) in Brazil from 1999 to 2016. During the study period, mortality rates for bicyclists remained almost unchanged (0.

Towards a better integration of social sciences in arbovirus research and decision-making: an experience from scientific collaboration between Cuban and Quebec institutions.

In 2017, the Institute of Tropical Medicine Pedro Kourí, University of Montreal Public Health Research Institute, and McGill University joined efforts to provide scenarios for scientific exchange and knowledge dissemination about the social science contribution on arboviral research. This commentary describes the scientific collaboration between Cuban and Canadian (Quebec) institutions, illustrating the need and opportunities to facilitate research and effective decision-making processes for arboviral prevention and control, going beyond traditional biomedical aspects. We organized a set of scientific activities within three international events conducted in Cuba between 2017 and 2018.