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Namibia, a low malaria transmission country targeting elimination, has made substantial progress in reducing malaria burden through improved case management, widespread indoor residual spraying and distribution of insecticidal nets. The country's diverse landscape includes regions with varying population densities and geographical niches, with the north of the country prone to periodic outbreaks.
Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control.
In recent decades, field and semi-field studies of malaria transmission have gathered geographic-specific information about mosquito ecology, behaviour and their sensitivity to interventions. Mathematical models of malaria transmission can incorporate such data to infer the likely impact of vector control interventions and hence guide malaria control strategies in various geographies.
Novel malaria vector control strategies targeting the odour-orientation of mosquitoes during host-seeking, such as 'attract-and-kill' or 'push-and-pull', have been suggested as complementary tools to indoor residual spraying and long-lasting insecticidal nets. These would be particularly beneficial if they can target vectors in the peri-domestic space where people are unprotected by traditional interventions.
Malaria is a deadly disease caused by Plasmodium spp. Several blood phenotypes have been associated with malarial resistance, which suggests a genetic component to immune protection.
As both mechanistic and geospatial malaria modeling methods become more integrated into malaria policy decisions, there is increasing demand for strategies that combine these two methods. This paper introduces a novel archetypes-based methodology for generating high-resolution intervention impact maps based on mechanistic model simulations. An example configuration of the framework is described and explored.
The study aimed to explore sociocultural factors influencing the risk of malaria and practices and beliefs towards malaria prevention, transmission and treatment in a remote village in Khatyad Rural Municipality (KRM) of Nepal. A sequential exploratory mixed methods approach was used.
The human landing catch (HLC) method, in which human volunteers collect mosquitoes that land on them before they can bite, is used to quantify human exposure to mosquito vectors of disease. Comparing HLCs in the presence and absence of interventions such as repellents is often used to measure protective efficacy (PE).
The most recent global estimates of the number of pregnancies at risk of Plasmodium falciparum and Plasmodium vivax malaria infection are from 2007. To inform global malaria prevention and control efforts, we aimed to estimate the global distribution of pregnancies at risk of malaria infection from 2007 to 2020.
Malaria imposes a significant global health burden and remains a major cause of child mortality in sub-Saharan Africa. In many countries, malaria transmission varies seasonally. The use of seasonally-deployed interventions is expanding, and the effectiveness of these control measures hinges on quantitative and geographically-specific characterisations of malaria seasonality.