Lymphatic filariasis in 2016 in American Samoa: Identifying clustering and hotspots using non-spatial and three spatial analytical methods

PLoS Negl Trop Dis. 2022 Mar 28;16(3):e0010262. doi: 10.1371/journal.pntd.0010262. eCollection 2022 Mar.

Abstract

Background: American 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.

Method: Non-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.

Results: The 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.

Conclusion: Our 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • American Samoa / epidemiology
  • Animals
  • Antigens, Helminth
  • Cluster Analysis
  • Elephantiasis, Filarial* / epidemiology
  • Wuchereria bancrofti

Substances

  • Antigens, Helminth

Grants and funding

This work received financial support from the Coalition for Operational Research on Neglected Tropical Diseases (COR-NTD), which is funded at The Task Force for Global Health primarily by the Bill & Melinda Gates Foundation (Grant number OPP1053230), the United Kingdom Department for International Development, and the United States Agency for International Development through its Neglected Tropical Diseases Program. M.S. was funded by a Westpac Research Fellowship. C.L.L. was funded by Australian National Health and Medical Research Council Fellowships (APP1109035 and APP1158469). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work was supported in whole or in part, by the Bill & Melinda Gates Foundation [Grant Number OPP1053230]. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission.