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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.

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.

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.

Therapeutic development to accelerate malaria control through intentional intervention layering

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.

A global mathematical model of climatic suitability for Plasmodium falciparum malaria

Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control.

Mapping fertility rates at national, sub-national, and local levels in Ethiopia between 2000 and 2019

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.  

Malaria in Nepal: A Spatiotemporal Study of the Disease Distribution and Challenges on the Path to Elimination

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.

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. 

The overlapping global distribution of dengue, chikungunya, Zika and yellow fever

Arboviruses transmitted mainly by Aedes (Stegomyia) aegypti and Ae. albopictus, including dengue, chikungunya, and Zika viruses, and yellow fever virus in urban settings, pose an escalating global threat. Existing risk maps, often hampered by surveillance biases, may underestimate or misrepresent the true distribution of these diseases and do not incorporate epidemiological similarities despite shared vector species.