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AbstractThe frequency and severity of floods has increased in different regions of the world due to climate change. Although the impact of floods on human health has been extensively studied, the increase in the segments of the population that are likely to be impacted by floods in the future makes it necessary to examine how adaptation measures impact the mental health of individuals affected by these natural disasters. The goal of this scoping review is to document the existing studies on flood adaptation measures and their impact on the mental health of affected populations, in order to identify the best preventive strategies as well as limitations that deserve further exploration. This study employed the methodology of the PRISMA-ScR extension for scoping reviews to systematically search the databases Medline and Web of Science to identify studies that examined the impact of adaptation measures on the mental health of flood victims. The database queries resulted in a total of 857 records from both databases. Following two rounds of screening, 9 studies were included for full-text analysis. Most of the analyzed studies sought to identify the factors that drive resilience in flood victims, particularly in the context of social capital (6 studies), whereas the remaining studies analyzed the impact of external interventions on the mental health of flood victims, either from preventive or post-disaster measures (3 studies). There is a very limited number of studies that analyze the impact of adaptation measures on the mental health of populations and individuals affected by floods, which complicates the generalizability of their findings. There is a need for public health policies and guidelines for the development of flood adaptation measures that adequately consider a social component that can be used to support the mental health of flood victims.
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Many studies have projected malaria risks with climate change scenarios by modelling one or two environmental variables and without the consideration of malaria control interventions. We aimed to predict the risk of malaria with climate change considering the influence of rainfall, humidity, temperatures, vegetation, and vector control interventions (indoor residual spraying (IRS) and long-lasting insecticidal nets (LLIN)). We used negative binomial models based on weekly malaria data from six facility-based surveillance sites in Uganda from 2010–2018, to estimate associations between malaria, environmental variables and interventions, accounting for the non-linearity of environmental variables. Associations were applied to future climate scenarios to predict malaria distribution using an ensemble of Regional Climate Models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Predictions including interaction effects between environmental variables and interventions were also explored. The results showed upward trends in the annual malaria cases by 25% to 30% by 2050s in the absence of intervention but there was great variability in the predictions (historical vs RCP 4.5 medians [Min–Max]: 16,785 [9,902–74,382] vs 21,289 [11,796–70,606]). The combination of IRS and LLIN, IRS alone, and LLIN alone would contribute to reducing the malaria burden by 76%, 63% and 35% respectively. Similar conclusions were drawn from the predictions of the models with and without interactions between environmental factors and interventions, suggesting that the interactions have no added value for the predictions. The results highlight the need for maintaining vector control interventions for malaria prevention and control in the context of climate change given the potential public health and economic implications of increasing malaria in Uganda.