The Journal of infection · 2026
Spatial distribution of and socio-ecological risk factors for strongyloidiasis in Australia.
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Wagnew Fasil, Shield Jennifer, Birtles Suzy J, Alene Kefyalew Addis, Gordon Catherine, Bradbury Richard, Muhi Stephen, Fernando Deepani D, Mationg Mary Lorraine, Page Wendy, Mahanty Siddhartha, Rossingh Bronwyn, Riley Tamara, Judd Jenni, Hoopes Jessica, Kelso Madeleine, Kaldor John, Lee Rogan, Watts Matthew, Biggs Beverley-Ann, Gray Darren J
Аннотация
INTRODUCTION: 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.
METHODS: We used data from a previous nationwide pathology data survey conducted between 2012 and 2016, which included 81,131 individuals across 332 statistical area level 3 (SA3) regions in Australia. Socio-ecological and environmental variables were extracted from publicly available online sources to explore their relationship with strongyloidiasis. Spatial patterns were analysed using Global Moran's I and Getis-Ord statistic to identify clusters of high and low disease prevalence. Bayesian spatial modelling was applied to investigate whether socio-climatic factors explain the spatial distribution of strongyloidiasis in Australia.
RESULTS: The predicted prevalence map showed substantial spatial heterogeneity of strongyloidiasis, with the highest prevalence identified in regions of the Northern Territory, northern Queensland, and northern Western Australia. Bayesian geospatial analysis indicated significant positive associations between strongyloidiasis prevalence and higher temperature (β: 0.080; 95% Credible Interval [CrI]: 0.043, 0.117) and higher soil pH (β: 0.231; 95% CrI: 0.038, 0.425). Conversely, a higher Socio-Economic Indexes for Areas (SEIFA) score, that is, areas with generally higher socio-economic status, was negatively associated with the strongyloidiasis prevalence (β: -0.107; 95% CrI: -0.179, -0.036).
CONCLUSION: Our findings reveal significant geographical variation in strongyloidiasis prevalence across Australia, with high prevalence observed in northern Queensland, the Northern Territory, and northern Western Australia, where climatic factors, soil characteristics, and socioeconomic conditions can shape the spatial distribution of the disease. Geographically tailored strategies targeting high prevalence areas are essential for effective prevention and control.
METHODS: We used data from a previous nationwide pathology data survey conducted between 2012 and 2016, which included 81,131 individuals across 332 statistical area level 3 (SA3) regions in Australia. Socio-ecological and environmental variables were extracted from publicly available online sources to explore their relationship with strongyloidiasis. Spatial patterns were analysed using Global Moran's I and Getis-Ord statistic to identify clusters of high and low disease prevalence. Bayesian spatial modelling was applied to investigate whether socio-climatic factors explain the spatial distribution of strongyloidiasis in Australia.
RESULTS: The predicted prevalence map showed substantial spatial heterogeneity of strongyloidiasis, with the highest prevalence identified in regions of the Northern Territory, northern Queensland, and northern Western Australia. Bayesian geospatial analysis indicated significant positive associations between strongyloidiasis prevalence and higher temperature (β: 0.080; 95% Credible Interval [CrI]: 0.043, 0.117) and higher soil pH (β: 0.231; 95% CrI: 0.038, 0.425). Conversely, a higher Socio-Economic Indexes for Areas (SEIFA) score, that is, areas with generally higher socio-economic status, was negatively associated with the strongyloidiasis prevalence (β: -0.107; 95% CrI: -0.179, -0.036).
CONCLUSION: Our findings reveal significant geographical variation in strongyloidiasis prevalence across Australia, with high prevalence observed in northern Queensland, the Northern Territory, and northern Western Australia, where climatic factors, soil characteristics, and socioeconomic conditions can shape the spatial distribution of the disease. Geographically tailored strategies targeting high prevalence areas are essential for effective prevention and control.