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The spatial and temporal variability inherent in malaria transmission within countries implies that targeted interventions for malaria control in high-burden settings and subnational elimination are a practical necessity. Identifying the spatio-temporal incidence, risk, and trends at different administrative geographies within malaria-endemic countries and monitoring them in near real-time as change occurs is crucial for developing and introducing cost-effective, subnational control and elimination intervention strategies.
HIV, tuberculosis (TB) and malaria are the three most important infectious diseases in Ethiopia, and sub-Saharan Africa. Understanding the spatial codistribution of these diseases is critical for designing geographically targeted and integrated disease control programmes. This study investigated the spatial overlap and drivers of HIV, TB and malaria prevalence in Ethiopia.
As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low-prevalence areas are increasingly needed. For low-burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons.
Global efforts led by The Kids Research Institute Australia’s Child Health Analytics program will see nations impacted by high rates of malaria empowered to develop their own controls and solutions.
Since their first detection in 2010, Plasmodium falciparum malaria parasites lacking the P. falciparum histidine-rich protein 2 gene (pfhrp2) have been observed in 40 of 47 surveyed countries, as documented by the World Health Organization. These genetic deletions reduce detection by the most widely used rapid diagnostic tests, prompting three countries to switch to alternative diagnostics.
Malaria remains a leading cause of morbidity and mortality and is responsible for over 0.5 million annual deaths globally. During the first two decades of this century, scale-up of a range of tools was associated with significant reductions in malaria mortality in the primary risk group, young African children.
Malaria is a focal disease and more localized in low endemic areas. The disease is increasingly becoming a concern in urban areas in most sub-Saharan African countries. The growing threats of Anopheles stephensi and insecticide resistance magnify this concern and hamper elimination efforts. It is, therefore, imperative to identify areas, within urban settings, of high-risk of malaria to help better target interventions.
The World Health Organization recommends perennial malaria chemoprevention (PMC), generally using sulfadoxine-pyrimethamine (SP) to children at high risk of severe Plasmodium falciparum malaria. Currently, PMC is given up to age two in perennial transmission settings. However, no recommendation exists for perennial settings with seasonal variation in transmission intensity, recently categorized as 'sub-perennial'.
Malaria incidence (MI) has significantly declined in Nepal, and this study aimed to investigate the spatiotemporal distribution and drivers of MI at the ward level. Data for malaria cases were obtained from the National Surveillance System from 2013 to 2021. Data for covariates, including annual mean temperature, annual mean precipitation, and distance to the nearest city, were obtained from publicly available sources. A Bayesian spatial model was used to identify factors associated with the spatial distribution of MI.
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.