Leptospirosis in American Samoa - estimating and mapping risk using environmental data

Lau, Colleen L., Clements, Archie C. A., Skelly, Chris, Dobson, Annette J., Smythe, Lee D. and Weinstein, Philip (2012) Leptospirosis in American Samoa - estimating and mapping risk using environmental data. Plos Neglected Tropical Diseases, 6 5: e1669. 1-e1669. 11. doi:10.1371/journal.pntd.0001669

Author Lau, Colleen L.
Clements, Archie C. A.
Skelly, Chris
Dobson, Annette J.
Smythe, Lee D.
Weinstein, Philip
Total Author Count Override 6
Title Leptospirosis in American Samoa - estimating and mapping risk using environmental data
Journal name Plos Neglected Tropical Diseases   Check publisher's open access policy
ISSN 1935-2735
Publication date 2012-05
Sub-type Article (original research)
DOI 10.1371/journal.pntd.0001669
Open Access Status DOI
Volume 6
Issue 5
Start page e1669. 1
End page e1669. 11
Total pages 11
Place of publication San Francisco CA , United States
Publisher Public Library of Science
Collection year 2013
Language eng
Formatted abstract
The recent emergence of leptospirosis has been linked to many environmental drivers of disease transmission. Accurate epidemiological data are lacking because of under-diagnosis, poor laboratory capacity, and inadequate surveillance. Predictive risk maps have been produced for many diseases to identify high-risk areas for infection and guide allocation of public health resources, and are particularly useful where disease surveillance is poor. To date, no predictive risk maps have been produced for leptospirosis. The objectives of this study were to estimate leptospirosis seroprevalence at geographic locations based on environmental factors, produce a predictive disease risk map for American Samoa, and assess the accuracy of the maps in predicting infection risk.

Methodology and Principal Findings

Data on seroprevalence and risk factors were obtained from a recent study of leptospirosis in American Samoa. Data on environmental variables were obtained from local sources, and included rainfall, altitude, vegetation, soil type, and location of backyard piggeries. Multivariable logistic regression was performed to investigate associations between seropositivity and risk factors. Using the multivariable models, seroprevalence at geographic locations was predicted based on environmental variables. Goodness of fit of models was measured using area under the curve of the receiver operating characteristic, and the percentage of cases correctly classified as seropositive. Environmental predictors of seroprevalence included living below median altitude of a village, in agricultural areas, on clay soil, and higher density of piggeries above the house. Models had acceptable goodness of fit, and correctly classified ~84% of cases.

Conclusions and Significance

Environmental variables could be used to identify high-risk areas for leptospirosis. Environmental monitoring could potentially be a valuable strategy for leptospirosis control, and allow us to move from disease surveillance to environmental health hazard surveillance as a more cost-effective tool for directing public health interventions.
Keyword Infection
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published: 29 May 2012.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Public Health Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 17 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 24 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Mon, 02 Jul 2012, 07:46:08 EST by System User on behalf of School of Public Health