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Spatial distribution of and socio-ecological risk factors for strongyloidiasis in Australia

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.

Estimating the potential malaria morbidity and mortality avertable by the US President's Malaria Initiative in 2025: a geospatial modelling analysis

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. 

Spatiotemporal patterns of influenza in Western Australia

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.

Mapping Bacillus Calmette-Guérin vaccination coverage in Africa from 1990 to 2022: a novel spatiotemporal modelling study

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. 

Fine-scale spatial mapping of urban malaria prevalence for microstratification in an urban area of Ghana

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.

A malaria seasonality dataset for sub-Saharan Africa

Malaria imposes a significant global health burden and remains a major cause of child mortality in sub-Saharan Africa. In many countries, malaria transmission varies seasonally. The use of seasonally-deployed interventions is expanding, and the effectiveness of these control measures hinges on quantitative and geographically-specific characterisations of malaria seasonality.

Neighborhood Places for Preschool Children's Physical Activity: A Mixed-Methods Study Using Global Positioning System, Geographic Information Systems, and Accelerometry Data

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.

Mapping the incidence rate of typhoid fever in sub-Saharan Africa

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.

Predicting immune protection against outcomes of infectious disease from population-level effectiveness data with application to COVID-19

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. 

Geospatial mapping of drug-resistant tuberculosis prevalence in Africa at national and sub-national levels

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.