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Since its inception in 2005, the US President's Malaria Initiative (PMI) has played a major role in the reductions in malaria morbidity and mortality observed across Africa. With the status of PMI funding and operations currently uncertain, we aimed to quantify the impact that a fully functioning PMI would have on malaria cases and deaths in Africa during 2025.
Nearly 170 years ago a British doctor applied geospatial mapping to identify the source of a cholera outbreak in central London. Using a street map to plot the location of the homes of the sick, Dr John Snow was able to pinpoint a ‘ground zero’ for the outbreak – a contaminated water pump.
Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods for geostatistical analysis or, more broadly, computational modelling of spatial processes.
Tuberculosis (TB) is the leading infectious cause of death globally, with approximately three million cases remaining undetected, thereby contributing to community transmission. Understanding the spatial distribution of undetected TB in high-burden settings is critical for designing and implementing geographically targeted interventions for early detection and control.
Country-level estimates can mask local geographic variations in progress toward achieving World Health Organization's End TB targets. This study aimed to identify spatial variations in progress toward achieving the TB incidence reduction target at a district level in Ethiopia.
New research highlights the long-term physical health problems faced by people who survive drug-resistant tuberculosis (TB) .
Disease spreading models such as the ubiquitous SIS compartmental model and its numerous variants are widely used to understand and predict the behavior of a given epidemic or information diffusion process. A common approach to imbue more realism to the spreading process is to constrain simulations to a network structure, where connected nodes update their disease state based on pairwise interactions along the edges of their local neighborhood.
Vietnam, as one of the countries in the Greater Mekong Subregion, has committed to eliminating all malaria by 2030. Declining case numbers highlight the country's progress, but challenges including imported cases and pockets of residual transmission remain. To successfully eliminate malaria and to prevent reintroduction of malaria transmission, geostatistical modelling of vulnerability (importation rate) and receptivity (quantified by the reproduction number) of malaria is critical.
Differential exposure and effect of malaria results from blends of biophysical, geospatial, and social determinants of health (SDoH). Likewise, effective policies and programmatic interventions against malaria must consider the complex interaction of social and spatial factors, while comprehensive health promotion approaches must simultaneously tackle SDoH and the ecological dimensions that drive malaria.
Soil-Transmitted Helminth (STH) infections are a significant health issue in the Western Pacific Region (WPR). This study aims to produce high-resolution spatial prediction STH prevalence maps for the WPR.