Statistical modelling based on structured surveys of Australian native possum excreta harbouring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans
- University of Melbourne, Australia
- Millersville University, United States
- CSIRO Health and Biosecurity, Australia
- Victorian Infectious Diseases Reference Laboratory, Australia
- Department of Healt, Australia
- Austin Health, Australia
- Curtin University, Australia
Abstract
Background: Buruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue with Mycobacterium 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, with most disease transmission occurring in the summer months. Previous research has shown that Australian native possums are reservoirs of M. ulcerans and that they shed the bacteria in their fecal material (excreta). Field surveys show that locales where possums harbor M. ulcerans overlap with human cases of BU, raising the possibility of using possum excreta surveys to predict the risk of disease occurrence in humans.
Methods: We thus established a highly structured 12-month possum excreta surveillance program across an area of 350 km2 in the Mornington Peninsula area 70 km south of Melbourne, Australia. The primary objective of our study was to assess using statistical modelling if M. ulcerans surveillance of possum excreta provided useful information for predicting future human BU case locations.
Results: Over two sampling campaigns in summer and winter, we collected 2282 possum excreta specimens of which 11% were PCR positive for M. ulcerans-specific DNA. Using the spatial scanning statistical tool SaTScan, we observed non-random, co-correlated clustering of both M. ulcerans positive 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.
Conclusions: This study highlights the One Health nature of BU by confirming a quantitative relationship between possum excreta shedding of M. ulcerans and 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.
Funding: This research was supported by the National Health and Medical Research Council of Australia and the Victorian Government Department of Health (GNT1152807 and GNT1196396).
Data availability
The computer code and source data used in this study are available here: https://github.com/abuultjens/Possum_scat_survey_predict_human_BU.
Article and author information
Author details
Andrew H Buultjens
Funding
National Health and Medical Research Council (GNT1152807)
- Timothy P Stinear
National Health and Medical Research Council (GNT1196396)
- Timothy P Stinear
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Bavesh D Kana, University of the Witwatersrand, South Africa
Ethics
Human subjects: Ethical approval for the use in this study of de-identified human BU case location, aggregated at mesh block level, was obtained from the Victorian Government Department of Health Human Ethics Committee under HREC/54166/DHHS-2019-179235(v3), "Spatial risk map of Buruli ulcer infection in Victoria".
Version history
- Preprint posted: November 17, 2022 (view preprint)
- Received: November 17, 2022
- Accepted: April 13, 2023
- Accepted Manuscript published: April 14, 2023 (version 1)
- Version of Record published: May 2, 2023 (version 2)
Copyright
© 2023, Vandelannoote et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,092
- views
-
- 127
- downloads
-
- 7
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Statistical modelling based on structured surveys of Australian native possum excreta harbouring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans
eLife 12:e84983.
https://doi.org/10.7554/eLife.84983
Further reading
-
- Ecology
- Epidemiology and Global Health
Zoonotic disease dynamics in wildlife hosts are rarely quantified at macroecological scales due to the lack of systematic surveys. Non-human primates (NHPs) host Plasmodium knowlesi, a zoonotic malaria of public health concern and the main barrier to malaria elimination in Southeast Asia. Understanding of regional P. knowlesi infection dynamics in wildlife is limited. Here, we systematically assemble reports of NHP P. knowlesi and investigate geographic determinants of prevalence in reservoir species. Meta-analysis of 6322 NHPs from 148 sites reveals that prevalence is heterogeneous across Southeast Asia, with low overall prevalence and high estimates for Malaysian Borneo. We find that regions exhibiting higher prevalence in NHPs overlap with human infection hotspots. In wildlife and humans, parasite transmission is linked to land conversion and fragmentation. By assembling remote sensing data and fitting statistical models to prevalence at multiple spatial scales, we identify novel relationships between P. knowlesi in NHPs and forest fragmentation. This suggests that higher prevalence may be contingent on habitat complexity, which would begin to explain observed geographic variation in parasite burden. These findings address critical gaps in understanding regional P. knowlesi epidemiology and indicate that prevalence in simian reservoirs may be a key spatial driver of human spillover risk.
-
- Epidemiology and Global Health
- Microbiology and Infectious Disease
Systematically tracking and analysing reproductive loss in livestock helps with efforts to safeguard the health and productivity of food animals by identifying causes and high-risk areas.
