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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.
Tuberculosis (TB) remains a major public health challenge in Ethiopia, despite being a preventable disease. TB preventive treatment (TPT) is a critical intervention to prevent the progression from latent TB infection to active disease, particularly among household contacts of TB patients and people living with HIV due to weakened immunity. However, the initiation and completion rates of TPT at subnational and local levels have not been thoroughly investigated. This study aims to map facility-based TPT initiation and completion rates among household contacts of TB across Ethiopia.
In the austral summer of 2021-2022, Australia experienced an unprecedented Japanese encephalitis virus (JEV) outbreak, with detections over 3000 km south of previous occurrences. Given the limited knowledge of JEV transmission ecology in Australia, we developed geospatial models of transmission risk to support the public health response. We created time-varying habitat suitability models for suspected mosquito vectors and ardeid hosts using month-scaled occurrence and covariate data from 2000-2023.
Strongyloidiasis, caused by the soil-transmitted helminth Strongyloides stercoralis, remains a neglected public health issue in Australia, particularly among remote Aboriginal and Torres Strait Islander communities. This study aimed to map the spatial distribution of strongyloidiasis and investigate associated socioecological factors to identify high-risk areas and guide targeted interventions in Australia.
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 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.
The clinical development of novel vaccines, injectable therapeutics, and oral chemoprevention drugs has the potential to deliver significant advancements in the prevention of Plasmodium falciparum malaria. These innovations could support regions in accelerating malaria control, transforming existing intervention packages by supplementing interventions with imperfect effectiveness or offering an entirely new tool.
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.
Fertility rates are key indicators of population health and demographic change, influencing economic development, healthcare planning, and social policies. Understanding subnational variation in fertility rate is important for effective geographical targeting and policy prioritization. This study aimed to identify geographic variation, trends, and determinants of fertility rates in Ethiopia over the past two decades.
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.