Structured surveys of Australian native possum excreta predict Buruli ulcer occurrence in humans

Author:

Vandelannoote Koen,Buultjens Andrew H.,Porter Jessica L.,Velink Anita,Wallace John R.,Blasdell Kim R.,Dunn Michael,Boyd Victoria,Fyfe Janet A. M.,Tay Ee Laine,Johnson Paul D. R.,Windecker Saras,Golding Nick,Stinear Timothy P.

Abstract

ABSTRACTBuruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue withMycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne. Previous research has shown that Australian native possums are reservoirs ofM. ulceransand that they shed the bacteria in their fecal material (excreta). Field surveys show that locales where possums harborM. ulceransoverlap with human cases of BU, raising the possibility of using possum excreta surveys to predict the risk of disease occurrence in humans. We thus established a highly structured 12-month possum excreta surveillance program across an area of 350 km2in the Mornington Peninsula area 70 km south of Melbourne, Australia. The primary objective of our study was to assess ifM. ulceranssurveillance of possum excreta provided useful information for predicting future human BU case locations. Over two sampling campaigns in summer and winter, we collected 2282 possum excreta specimens of which 11% were PCR positive forM. ulcerans-specific DNA. Using the spatial scanning statistical toolSatScan, we observed non-random, co-correlated clustering of bothM. ulceranspositive possum excreta and human BU cases. We next trained a statistical model with the Mornington Peninsula excreta survey data to predict the future likelihood of human BU cases occurring in the region. By observing where human BU cases subsequently occurred, we show that the excreta model performance was superior to a null model trained using the previous year’s human BU case incidence data (AUC 0.66 vs 0.55). We then used data unseen by the excreta-informed model from a new survey of 661 possum excreta specimens in Geelong, a geographically separate BU endemic area to the southwest of Melbourne, to prospectively predict the location of human BU cases in that region. As for the Mornington Peninsula, the excreta-based BU prediction model outperformed the null model (AUC 0.75 vs 0.50) and pinpointed specific locations in Geelong where interventions could be deployed to interrupt disease spread. This study highlights theOne Healthnature of BU by confirming a quantitative relationship between possum excreta shedding ofM. ulceransand humans developing BU. The excreta survey-informed modeling we have described will be a powerful tool for efficient targeting of public health responses to stop BU.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3