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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.
Understanding the geospatial distribution of influenza infection and the risk factors associated with infection clustering can inform targeted preventive interventions. We conducted a geospatial analysis to investigate the spatial patterns and identify drivers of medically attended influenza infection across all age groups in Western Australia.
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.
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.
Bacillus Calmette-Guérin (BCG) protects children from severe tuberculosis and remains the only licensed vaccine for tuberculosis. Subnational estimates of BCG coverage are essential for identifying underserved populations across Africa. This study aimed to map BCG vaccination coverage in Africa from 1990 to 2022.
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.
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.
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.
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.
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.