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ABSTRACT Wastewater-based epidemiology has emerged as a promising tool to monitor pathogens in a population, particularly when clinical diagnostic capacities become overwhelmed. During the ongoing COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), several jurisdictions have tracked viral concentrations in wastewater to inform public health authorities. While some studies have also sequenced SARS-CoV-2 genomes from wastewater, there have been relatively few direct comparisons between viral genetic diversity in wastewater and matched clinical samples from the same region and time period. Here we report sequencing and inference of SARS-CoV-2 mutations and variant lineages (including variants of concern) in 936 wastewater samples and thousands of matched clinical sequences collected between March 2020 and July 2021 in the cities of Montreal, Quebec City, and Laval, representing almost half the population of the Canadian province of Quebec. We benchmarked our sequencing and variant-calling methods on known viral genome sequences to establish thresholds for inferring variants in wastewater with confidence. We found that variant frequency estimates in wastewater and clinical samples are correlated over time in each city, with similar dates of first detection. Across all variant lineages, wastewater detection is more concordant with targeted outbreak sequencing than with semi-random clinical swab sampling. Most variants were first observed in clinical and outbreak data due to higher sequencing rate. However, wastewater sequencing is highly efficient, detecting more variants for a given sampling effort. This shows the potential for wastewater sequencing to provide useful public health data, especially at places or times when sufficient clinical sampling is infrequent or infeasible.

Seasonal forecasting of spring floods in snow-covered basins is challenging due to the ambiguity in the driving processes, uncertain estimations of antecedent catchment conditions and the choice of predictor variables. In this study we attempt to improve the prediction of spring flow peaks in southern Quebec, Canada, by studying the preconditioning mechanisms of runoff generation and their impact on inter-annual variations in the timing and magnitude of spring peak flow. Historical observations and simulated data from a hydrological and snowmelt model were used to study the antecedent conditions that control flood characteristics in twelve snow-dominated catchments. Maximum snow accumulation (peak SWE), snowmelt and rainfall volume, snowmelt and rainfall intensity, and soil moisture were estimated during the pre-flood period. Stepwise multivariate linear regression analysis was used to identify the most relevant predictors and assess their relative contribution to the interannual variability of flood characteristics. Results show that interannual variations in spring peak flow are controlled differently between basins. Overall, interannual variations in peak flow were mainly governed, in order of importance, by snowmelt intensity, rainfall intensity, snowmelt volume, rainfall volume, peak SWE, and soil moisture. Variations in the timing of peak flow were controlled in most basins by rainfall volume and rainfall and snowmelt intensity. In the northernmost, snow-dominated basins, pre-flood rainfall amount and intensity mostly controlled peak flow variability, whereas in the southern, rainier basins snowpack conditions and melt dynamics controlled this variability. Snowpack interannual variations were found to be less important than variations in rainfall in forested basins, where snowmelt is more gradual. Conversely, peak flow was more sensitive to snowpack conditions in agricultural basins where snowmelt occurs faster. These results highlight the impact of land cover and use on spring flood generation mechanism, and the limited predictability potential of spring floods using simple methods and antecedent hydrological factors.

Abstract Background Climate change (CC) adaptation is considered a priority for Caribbean Small Islands Developing States (SIDS), as these territories and communities are considered particularly vulnerable to climate-related events. The primary health care (PHC) system is an important actor in contributing to climate change adaptation. However, knowledge on how PHC is prepared for CC in Caribbean SIDS is very limited. The objective of this paper is to discuss health adaptation to climate change focusing on the PHC system. Methods We explored the perspectives of PHC professionals in Dominica on climate change. Focus group discussions (FGDs) were conducted in each of the seven health districts in Dominica, a Caribbean SIDS, between November 2021 and January 2022. The semi-structured interview guide was based on the Essential Public Health Functions: assessment, access to health care services, policy development and resource allocation. Data coding was organized accordingly. Results Findings suggest that health care providers perceive climate change as contributing to an increase in NCDs and mental health problems. Climate-related events create barriers to care and exacerbate the chronic deficiencies within the health system, especially in the absence of high-level policy support. Healthcare providers need to take a holistic view of health and act accordingly in terms of disease prevention and health promotion, epidemiological surveillance, and ensuring the widest possible access to health care, with a particular focus on the ecological and social determinants of vulnerability. Conclusion The Primary Health Care system should be a key actor in designing and operationalizing adaptation and transformative resilience. The Essential Public Health Functions should integrate social and climate and ecological determinants of health to guide primary care activities to protect the health of communities. This indicates a need for improved research on the linkages between climate events and health outcomes, surveillance, and development of plans that are guided by contextual knowledge in the SIDS.

With the advent of the COVID-19 pandemic, in-person social interactions and opportunities for accessing resources that sustain health and well-being have drastically reduced. We therefore designed the pan-Canadian population-based prospective COVID-19: HEalth and Social Inequities across Neighbourhoods (COHESION) cohort to provide deeper understanding of how the COVID-19 pandemic context affects mental health and well-being, key determinants of health, and health inequities. This paper presents the design of the two-phase COHESION Study, and descriptive results from the first phase conducted between May 2020 and September 2021. During that period, the COHESION research platform collected monthly data linked to COVID-19 such as infection and vaccination status, perceptions and attitudes regarding pandemic-related measures, and information on participants’ physical and mental health, well-being, sleep, loneliness, resilience, substances use, living conditions, social interactions, activities, and mobility. The 1,268 people enrolled in the Phase 1 COHESION Study are for the most part from Ontario (47%) and Quebec (33%), aged 48 ± 16 years [mean ± standard deviation (SD)], and mainly women (78%), White (85%), with a university degree (63%), and living in large urban centers (70%). According to the 298 ± 68 (mean ± SD) prospective questionnaires completed each month in average, the first year of follow-up reveals significant temporal variations in standardized indexes of well-being, loneliness, anxiety, depression, and psychological distress. The COHESION Study will allow identifying trajectories of mental health and well-being while investigating their determinants and how these may vary by subgroup, over time, and across different provinces in Canada, in the unique context of the COVID-19 pandemic.

IntroductionCaribbean Small island developing states (SIDS) are generally qualified as disproportionately vulnerable to climate change, including extreme weather events like hurricanes. While many studies already documented the impacts of climate change on health in the wealthiest countries, there is little knowledge in this field in Caribbean SIDS. Our study aims to discuss health risks and vulnerabilities in a Caribbean context to inform future adaptation measures to climate change.MethodsOur paper is based on a qualitative study that was conducted in Dominica, a Caribbean SIDS. The data come from semi-structured interviews organized between March 2020 and January 2021 with people internally displaced following an extreme climate event, either tropical storm Erika (2015) or Hurricane Maria (2017), and with some people who migrated to Guadeloupe after Hurricane Maria. Interview guides were based on conceptual frameworks on climate change, migration and health, and vulnerability to climate change. Data were analyzed deductively based on frameworks and inductively to allow new codes to emerge.ResultsOur findings suggest that current knowledge of climate change by those who have been displaced by an extreme climate event varied greatly depending on the education level, class, and socioeconomic condition of the participant. Participants experienced various negative consequences from a storm or hurricane such as increased risk of relocation, lack of access to healthcare, and food, job, and water insecurities – all circumstances know to correlate with mental health issues. Participants suggested stronger dwellings, community preparedness committees to act sooner, and climate change sensitization and awareness campaigns to foster community unity and solidarity.ConclusionThese findings contribute to the perspectives and knowledge of climate change, highlighting that existing extreme climate event committees and government officials need to address structural and social barriers that can potentially increase social inequalities and lead to maladaptation to climate change with potential consequences on public health.