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Mapping residual malaria transmission in Vietnam

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.

Local progress towards achieving the End TB targets in Ethiopia: A geospatial analysis

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.

Mapping tuberculosis prevalence in Africa using a Bayesian geospatial analysis

Worldwide, tuberculosis (TB) remains the leading cause of death from infectious diseases. Africa is the second most-affected region, accounting for a quarter of the global TB burden, but there is limited evidence whether there is subnational variation of TB prevalence across the continent. Therefore, this study aimed to estimate sub-national and local TB prevalence across Africa.

Mapping the prevalence of soil-transmitted helminth infections in the Western Pacific Region: a spatial modelling study

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.

Comparison of new computational methods for spatial modelling of malaria

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.