ArticlePLoS neglected tropical diseases2022
Lymphatic filariasis in 2016 in American Samoa: Identifying clustering and hotspots using non-spatial and three spatial analytical methods.
Article in PLoS neglected tropical diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Spatial Clustering of Lymphatic Filariasis in Relation to Potential Mansonia Mosquito Habitats in Endemic Communities of Belitung Regency, Indonesia.Acta parasitologica · 2026Article
- Integrated Approaches to Surveillance of Lymphatic Filariasis and Other Infectious Diseases in the Pacific Islands.Tropical medicine and infectious disease · 2026Article
- The Utility of Infectious Disease Prevalence Studies to Inform Public Health Decision-Making in the Samoan Islands: A Systematic Review.Tropical medicine and infectious disease · 2025Review
- The effects of variable spatial aggregation on lymphatic filariasis transmission.Parasites & vectors · 2025Article
- Sensitivity of anti-filarial antibodies for lymphatic filariasis surveillance: Insights from a serological survey in Samoa in 2018.PLoS neglected tropical diseases · 2025Article
- Article
- Spatial predictive risk mapping of lymphatic filariasis residual hotspots in American Samoa using demographic and environmental factors.PLoS neglected tropical diseases · 2023Article
- Spatially Explicit Environmental Factors Associated with Lymphatic Filariasis Infection in American Samoa.Tropical medicine and infectious disease · 2022Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAmerican Samoa completed seven rounds of mass drug administration from 2000-2006 as part of the Global Programme to Eliminate Lymphatic Filariasis (LF). However, resurgence was confirmed in 2016 through WHO-recommended school-based transmission assessment survey and a community-based survey. This paper uses data from the 2016 community survey to compare different spatial and non-spatial methods to characterise clustering and hotspots of LF.
methodNon-spatial clustering of infection markers (antigen [Ag], microfilaraemia [Mf], and antibodies (Ab [Wb123, Bm14, Bm33]) was assessed using intra-cluster correlation coefficients (ICC) at household and village levels. Spatial dependence, clustering and hotspots were examined using semivariograms, Kulldorf's scan statistic and Getis-Ord Gi* statistics based on locations of surveyed households.
resultsThe survey included 2671 persons (750 households, 730 unique locations in 30 villages). ICCs were higher at household (0.20-0.69) than village levels (0.10-0.30) for all infection markers. Semivariograms identified significant spatial dependency for all markers (range 207-562 metres). Using Kulldorff's scan statistic, significant spatial clustering was observed in two previously known locations of ongoing transmission: for all markers in Fagali'i and all Abs in Vaitogi. Getis-Ord Gi* statistic identified hotspots of all markers in Fagali'i, Vaitogi, and Pago Pago-Anua areas. A hotspot of Ag and Wb123 Ab was identified around the villages of Nua-Seetaga-Asili. Bm14 and Bm33 Ab hotspots were seen in Maleimi and Vaitogi-Ili'ili-Tafuna.
conclusionOur study demonstrated the utility of different non-spatial and spatial methods for investigating clustering and hotspots, the benefits of using multiple infection markers, and the value of triangulating results between methods.
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