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o map subnational and local prevalence of drug-resistant tuberculosis (DR-TB) across Africa. We assembled a geolocated dataset from 173 sources across 31 African countries, comprising drug susceptibility test results and covariate data from publicly available databases. We used Bayesian model-based geostatistical framework with multivariate Bayesian logistic regression model to estimate DR-TB prevalence at lower administrative levels.
Although most people born this century will be educated in African schools, these schools often lack basic infrastructure, such as electricity and/or lighting. In the face of a rapidly growing school-age population in Africa, the electrification of educational facilities is not just an infrastructural challenge but also a pivotal investment in the continent’s future workforce.
Quantifying the extent to which previous infections and vaccinations confer protection against future infection or disease outcomes is critical to managing the transmission and consequences of infectious diseases. We present a general statistical model for predicting the strength of protection conferred by different immunising exposures (numbers, types, and strains of both vaccines and infections), against multiple outcomes of interest, whilst accounting for immune waning.
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.
With more than 1.2 million illnesses and 29,000 deaths in sub-Saharan Africa in 2017, typhoid fever continues to be a major public health problem. Effective control of the disease would benefit from an understanding of the subnational geospatial distribution of the disease incidence.
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.
Children who live in the outer suburbs of Australia’s four biggest cities are twice as likely to have asthma as those living in inner city areas, according to a new study based on health data captured in the last Australian Census.
New research which maps the entire global population’s travel time to their nearest healthcare facility has revealed major inequalities in access to healthcare depending on whether people have access to motorised transport or not.
This study adds to the current literature by using a novel device-based method to explore where preschool children are physically active outside of home and childcare settings. This study combined accelerometry with geospatial data to explore the influence of the environment on preschool children's physical activity by objectively identifying the locations where preschool children engage in moderate to vigorous physical activity (MVPA) within and outside of their neighborhood.
Malaria remains a leading cause of illness and death globally, with countries in sub-Saharan Africa bearing a disproportionate burden. Global high-resolution maps of malaria prevalence, incidence, and mortality are crucial for tracking spatially heterogeneous progress against the disease and to inform strategic malaria control efforts. We present the latest such maps, the first since 2019, which cover the years 2000–22. The maps are accompanied by administrative-level summaries and include estimated COVID-19 pandemic-related impacts on malaria burden.