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Keywords: SVM Malarial incidences Forecasting Time series FFA a b s t r a c t Accurate and reliable forecasts of malarial incidences are necessary for the health authorities to ensure the appropriate action for the control of the outbreak. In this study, a novel method based on coupling the Firefly Algorithm (FFA) and Support Vector Machines (SVM) has been(More)
BACKGROUND Climate change and associated increases in climate variability will likely further exacerbate global health disparities. More research is needed, particularly in developing countries, to accurately predict the anticipated impacts and inform effective interventions. OBJECTIVES Building on the information presented at the 2009 Joint Indo-U.S.(More)
The larvicidal activity of Mentha piperita, Cymbopogan citratus (lemongrass), Eucalyptus globulus and Citrus sinensis (orange) essential oils and their combinations was evaluated against Musca domestica (housefly) and Anopheles stephensi (mosquitoes) through contact toxicity assay. Among all the tested essential oils/combinations, Me. piperita was found to(More)
Although low-and middle-income countries are responsible for only a small percentage of global greenhouse gas emissions, the adverse health effects associated with climate change will likely fall disproportionately on their populations. This inequity will further exacerbate global health disparities (McMichael et al. High-risk areas include those already(More)
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