Spatial predictive risk mapping of lymphatic filariasis residual hotspots in American Samoa using demographic and environmental factors
Cadavid Restrepo, Angela M., Martin, Beatris M., Fuimaono, Saipale, Clements, Archie C.A., Graves, Patricia M., and Lau, Colleen L. (2023) Spatial predictive risk mapping of lymphatic filariasis residual hotspots in American Samoa using demographic and environmental factors. PLoS Neglected Tropical Diseases, 17 (7). e0010840.
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Abstract
Background: American Samoa successfully completed seven rounds of mass drug administration (MDA) for lymphatic filariasis (LF) from 2000–2006. The territory passed the school-based transmission assessment surveys in 2011 and 2015 but failed in 2016. One of the key challenges after the implementation of MDA is the identification of any residual hotspots of transmission.
Method: Based on data collected in a 2016 community survey in persons aged ≥8 years, Bayesian geostatistical models were developed for LF antigen (Ag), and Wb123, Bm14, Bm33 antibodies (Abs) to predict spatial variation in infection markers using demographic and environmental factors (including land cover, elevation, rainfall, distance to the coastline and distance to streams).
Results: In the Ag model, females had a 26.8% (95% CrI: 11.0–39.8%) lower risk of being Ag-positive than males. There was a 2.4% (95% CrI: 1.8–3.0%) increase in the odds of Ag positivity for every year of age. Also, the odds of Ag-positivity increased by 0.4% (95% CrI: 0.1–0.7%) for each 1% increase in tree cover. The models for Wb123, Bm14 and Bm33 Abs showed simi-lar significant associations as the Ag model for sex, age and tree coverage. After accounting for the effect of covariates, the radii of the clusters were larger for Bm14 and Bm33 Abs compared to Ag and Wb123 Ab. The predictive maps showed that Ab-positivity was more wide-spread across the territory, while Ag-positivity was more confined to villages in the north-west of the main island.
Conclusion: The findings may facilitate more specific targeting of post-MDA surveillance activities by prioritising those areas at higher risk of ongoing transmission.