Predicting malaria risk considering vector control interventions under climate change scenarios.

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.

Differential Influence of Environmental Factors on Malaria Due to Vector Control Interventions in Uganda.

BACKGROUND: Few studies have explored how vector control interventions may modify associations between environmental factors and malaria. METHODS: We used weekly malaria cases reported from six public health facilities in Uganda. Environmental variables (temperature, rainfall, humidity, and vegetation) were extracted from remote sensing sources. The non-linearity of environmental variables was investigated, and negative binomial regression models were used to explore the influence of indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) on associations between environmental factors and malaria incident cases for each site as well as pooled across the facilities, with or without considering the interaction between environmental variables and vector control interventions. RESULTS: An average of 73.3 weekly malaria cases per site (range: 0-597) occurred between 2010 and 2018. From the pooled model, malaria risk related to environmental variables was reduced by about 35% with LLINs and 63% with IRS. Significant interactions were observed between some environmental variables and vector control interventions. There was site-specific variability in the shape of the environment-malaria risk relationship and in the influence of interventions (6 to 72% reduction in cases with LLINs and 43 to 74% with IRS). CONCLUSION: The influence of vector control interventions on the malaria-environment relationship need to be considered at a local scale in order to efficiently guide control programs.

The influence of the environment and indoor residual spraying on malaria risk in a cohort of children in Uganda.

Studies have estimated the impact of the environment on malaria incidence although few have explored the differential impact due to malaria control interventions. Therefore, the objective of the study was to evaluate the effect of indoor residual spraying (IRS) on the relationship between malaria and environment (i.e. rainfall, temperatures, humidity, and vegetation) using data from a dynamic cohort of children from three sub-counties in Uganda. Environmental variables were extracted from remote sensing sources and averaged over different time periods. General linear mixed models were constructed for each sub-counties based on a log-binomial distribution. The influence of IRS was analysed by comparing marginal effects of environment in models adjusted and unadjusted for IRS. Great regional variability in the shape (linear and non-linear), direction, and magnitude of environmental associations with malaria risk were observed between sub-counties. IRS was significantly associated with malaria risk reduction (risk ratios vary from RR = 0.03, CI 95% [0.03-0.08] to RR = 0.35, CI95% [0.28-0.42]). Model adjustment for this intervention changed the magnitude and/or direction of environment-malaria associations, suggesting an interaction effect. This study evaluated the potential influence of IRS in the malaria-environment association and highlighted the necessity to control for interventions when they are performed to properly estimate the environmental influence on malaria. Local models are more informative to guide intervention program compared to national models.

How are large-scale One Health initiatives targeting infectious diseases and antimicrobial resistance evaluated? A scoping review.

While One Health initiatives are gaining in popularity, it is unclear if and how they are evaluated when implementation at scale is intended. The main purpose of this scoping review was to describe how One Health initiatives targeting infectious diseases and antimicrobial resistance at a large scale are evaluated. Secondary objectives included identifying the main facilitators and barriers to the implementation and success of these initiatives, and how their impacts were assessed. Twenty-three studies evaluating One Health initiatives were eligible. Most studies included the human (n = 22) and animal (n = 15) sectors; only four included the environment sector. The types of evaluated initiative (non-exclusive) included governance (n = 5), knowledge (n = 6), protection (n = 17), promotion (n = 16), prevention (n = 9), care (n = 8), advocacy (n = 10) and capacity (n = 10). Studies used normative (n = 4) and evaluative (n = 20) approaches to assess the One Health initiatives, the latter including impact (n = 19), implementation (n = 8), and performance (n = 7) analyses. Structural and economic, social, political, communication and coordination-related factors, as well as ontological factors, were identified as both facilitators and barriers for successful One Health initiatives. These results identified a wide range of evaluation methods and indicators used to demonstrate One Health's added values, strengths, and limitations: the inherent complexity of the One Health approach leads to the use of multiple types of evaluation. The strengths and remaining gaps in the evaluation of such initiative highlight the relevance of comprehensive, mixed-method, context-sensitive evaluation frameworks to inform and support the implementation of One Health initiatives by stakeholders in different governance settings.

Environmental and Occupational Short-Term Exposure to Airborne Particles and FEV1 and FVC in Healthy Adults: A Systematic Review and Meta-Analysis.

BACKGROUND: No study has compared the respiratory effects of environmental and occupational particulate exposure in healthy adults. METHODS: We estimated, by a systematic review and meta-analysis, the associations between short term exposures to fine particles (PM2.5 and PM4) and certain parameters of lung function (FEV1 and FVC) in healthy adults. RESULTS: In total, 33 and 14 studies were included in the qualitative synthesis and meta-analyses, respectively. In environmental studies, a 10 µg/m3 increase in PM2.5 was associated with an FEV1 reduction of 7.63 mL (95% CI: -10.62 to -4.63 mL). In occupational studies, an increase of 10 µg/m3 in PM4 was associated with an FEV1 reduction of 0.87 mL (95% CI: -1.36 to -0.37 mL). Similar results were observed with FVC. CONCLUSIONS: Both occupational and environmental short-term exposures to fine particles are associated with reductions in FEV1 and FVC in healthy adults.

Factors Associated with Seasonal Food Insecurity among Small-Scale Subsistence Farming Households in Rural Honduras.

In the context of climate change, a nutritional transition, and increased pressures to migrate internally and internationally, this study examined the relationship between seasonal food insecurity and demographic, socioeconomic, and agricultural production factors among small-scale subsistence farmers in rural northern Honduras. Anchored by a partnership with the Fundación para la Investigación Participativa con Agricultores de Honduras (FIPAH) and the Yorito Municipal Health Centre, a cross-sectional household survey was administered in Yorito, Honduras, in July 2014. The study population included 1263 individuals from 248 households across 22 rural communities. A multivariate mixed effects negative binomial regression model was built to investigate the relationship between the self-reported number of months without food availability and access from subsistence agriculture in the previous year (August 2013-July 2014) and demographic, socioeconomic, and agricultural production variables. This study found a lengthier 'lean season' among surveyed household than previously documented in Honduras. Overall, 62.2% (95% confidence interval (CI): [59.52, 64.87]) of individuals experienced at least four months of insufficient food in the previous year. Individuals from poorer and larger households were more likely to experience insufficient food compared to individuals from wealthier and smaller households. Additionally, individuals from households that produced both maize and beans were less likely to have insufficient food compared to individuals from households that did not grow these staple crops (prevalence ratio (PR) = 0.83; 95% CI: [0.69, 0.99]). Receiving remittances from a migrant family member did not significantly reduce the prevalence of having insufficient food. As unpredictable crop yields linked to climate change and extreme weather events are projected to negatively influence the food security and nutrition outcomes of rural populations, it is important to understand how demographic, socioeconomic, and agricultural production factors may modify the ability of individuals and households engaged in small-scale subsistence agriculture to respond to adverse shocks.

The Impact of Multiple Rounds of Indoor Residual Spraying on Malaria Incidence and Hemoglobin Levels in a High-Transmission Setting.

BACKGROUND: Indoor residual spraying (IRS) is widely used as a vector control measure, although there are conflicting findings of its effectiveness in reducing malaria incidence. The objective of this study was to estimate the effect of multiple IRS rounds on malaria incidence and hemoglobin levels in a cohort of children in rural southeastern Uganda. METHODS: The study was based upon a dynamic cohort of children aged 0.5-10 years enrolled from August 2011 to June 2017 in Nagongera Subcounty. Confirmed malaria infections and hemoglobin levels were recorded over time for each participant. After each of 4 rounds of IRS, malaria incidence, hemoglobin levels, and parasite density were evaluated and compared with pre-IRS levels. Analyses were carried out at the participant level while accounting for repeated measures and clustering by household. RESULTS: Incidence rate ratios comparing post-IRS to pre-IRS incidence rates for age groups 0-3, 3-5, and 5-11 were 0.108 (95% confidence interval [CI], .078-.149), 0.173 (95% CI, .136-.222), and 0.226 (95% CI, .187-.274), respectively. The mean hemoglobin levels significantly increased from 11.01 (pre-IRS) to 12.18 g/dL (post-IRS). CONCLUSIONS: Our study supports the policy recommendation of IRS usage in a stable and perennial transmission area to rapidly reduce malaria transmission.

The Montreal heat response plan: evaluation of its implementation towards healthcare professionals and vulnerable populations.

OBJECTIVES: Since 2004, the Montreal heat response plan (MHRP) has been developed and implemented on the Island of Montreal to reduce heat-related health effects in the general population. In this paper, we aimed to assess the barriers and facilitators to implementation of the MHRP and evaluate the awareness of key elements of the plan by healthcare professionals and individuals from vulnerable populations. METHODS: Data were gathered from monitoring reports and a questionnaire administered to managers of healthcare institutions and healthcare workers in Montreal-area health and social services institutions. Individual interviews and focus groups with healthcare workers and with individuals with schizophrenia or suffering from drug or alcohol dependencies were performed. Data were categorized according to predefined subthemes. Coding matrices were then used to determine the most frequently occurring elements in the subthemes. RESULTS: Our results indicate that actions are progressively implemented each year in the healthcare network. Intensification of surveillance for signs of heat-related illness is the most frequently reported measure. Identification and prioritization of clientele and homecare patients are identified as a challenge, as is ensuring the availability of sufficient personnel during a heat wave. Analysis of practice and awareness in healthcare professionals reveals that preventive measures are known and applied by the personnel. Individuals from vulnerable population groups were not uniformly aware of preventive measures, and consequently, variability was observed in their application. CONCLUSION: The framework proposed in this study revealed valuable information that can be useful to improve plans aimed at reducing heat-related health effects in the population.

The associations between malaria, interventions, and the environment: a systematic review and meta-analysis.

BACKGROUND: Malaria transmission is driven by multiple factors, including complex and multifaceted connections between malaria transmission, socioeconomic conditions, climate and interventions. Forecasting models should account for all significant drivers of malaria incidence although it is first necessary to understand the relationship between malaria burden and the various determinants of risk to inform the development of forecasting models. In this study, the associations between malaria risk, environmental factors, and interventions were evaluated through a systematic review. METHODS: Five electronic databases (CAB Abstracts, EMBASE, Global Health, MEDLINE and ProQuest Dissertations & Theses) were searched for studies that included both the effects of the environment and interventions on malaria within the same statistical model. Studies were restricted to quantitative analyses and health outcomes of malaria mortality or morbidity, outbreaks, or transmission suitability. Meta-analyses were conducted on a subset of results using random-effects models. RESULTS: Eleven studies of 2248 potentially relevant articles that met inclusion criteria were identified for the systematic review and two meta-analyses based upon five results each were performed. Normalized Difference Vegetation Index was not found to be statistically significant associated with malaria with a pooled OR of 1.10 (95% CI 0.07, 1.71). Bed net ownership was statistically associated with decreasing risk of malaria, when controlling for the effects of environment with a pooled OR of 0.75 (95% CI 0.60, 0.95). In general, environmental effects on malaria, while controlling for the effect of interventions, were variable and showed no particular pattern. Bed nets ownership, use and distribution, have a significant protective effect while controlling for environmental variables. CONCLUSIONS: There are a limited number of studies which have simultaneously evaluated both environmental and interventional effects on malaria risk. Poor statistical reporting and a lack of common metrics were important challenges for this review, which must be addressed to ensure reproducibility and quality research. A comprehensive or inclusive approach to identifying malaria determinants using standardized indicators would allow for a better understanding of its epidemiology, which is crucial to improve future malaria risk estimations.