Statistical modeling based of Australian native possum excreta identifies locations of Buruli ulcer occurrence in humans

In a recent article published in the eLife Journal, researchers launched a possum excreta surveillance program across 350 km2 in the Mornington Peninsula near South Melbourne, Australia.

The study aimed to gather data that could help predict future human Buruli ulcer (BU) case locations via statistical modeling. The 2022 outbreak in the Mornington Peninsula was the largest since 2010 in Australia, resulting in nearly 2,200 laboratory-confirmed BU cases.

The team launched another survey mission using the same surveying methodology between January 16 and April 2020 to make predictions upon a previously unseen excreta survey dataset in the Geelong region.

Study: Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans. Image Credit: LisaHagan/Shutterstock.comStudy: Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans. Image Credit: LisaHagan/


Earlier, BU, a bacterial infection of subcutaneous tissues by Mycobacterium ulcerans, commonly occurred in rural Central and Western Africa with a tropical and subtropical climate, which caused lifelong deformities in patients.

In the last 30 years, M. ulcerans have caused several outbreaks in Victoria, Australia, where most human BU cases occur in late summer. Across the same geographical regions of Victoria, BU also occurs in native wildlife and domestic mammal species, e.g., mountain brushtail possums (Trichosurus cunninghami).

Many surveys found that BU first occurs in local (or native) possum populations; then, these animals excrete M. ulcerans deoxyribonucleic acid (DNA) in their feces, which spills over to cause infections in humans inhabiting regions where BU is well-recognized as endemic for humans.

Despite technical challenges in culturing slow-growing M. ulcerans retrieved from microbial samples, whole genome sequencing (WGS) efforts have helped researchers discover that M. ulcerans strains isolated from human and possum skin lesions belonged to the same transmission cycles.

Thus, arboreal marsupial mammals appear to be the environmental reservoir for M. ulcerans in Australia, which makes BU a One Health issue.

Due to its opportunistic nature, M. ulcerans is expanding its endemic regions, which is why the Department of Health (DH) in Victoria state also identified BU cases within 5km of the Melbourne city center.

It raises the urgent need for an effective BU mitigation program, for which updated information on disease incidence and distribution is needed.

About the study

In the present study, researchers collected 2,282 possum excreta samples in two sampling campaigns launched in summer and winter to determine the extent of epizootic activity of M. ulcerans in the environment of the Mornington Peninsula.

Specifically, they extracted microbial genomic DNA (gDNA) from these samples for testing via M. ulcerans IS2404 real-time polymerase chain reaction (PCR).

The former survey ran between December 19, 2018, and March 14, 2019, and the latter between May 28 and September 19, 2019. The surveying team collected possum excreta samples along the Mornington Peninsula Road network covering the ground level along the fence line of residences.

Many of the residential properties in the study area were spacious holiday resorts with fenced gardens planted with trees, an ideal habitat for possums.

In this study, they used five Android budget smartphones (survey phones) in which they installed the Open Data Kit (ODK) Collect Android app.

This app converted paper survey forms into electronic forms containing all survey questions. All surveyors answered these promptly during sampling, and their phones automatically sent their responses to an ODK Aggregate running in the cloud, from where the team exported it into a tabular (CSV) or a geographical format.

The group laid out a 200 m grid pattern between adjacent points of a sampling space to prevent the re-sampling of animal excrement. The study surveyors used ODK Collect to capture the location of the new sampling point using their phone's GPS.

Surveyors logged a timepoint when they began the search for an excreta sample, restricted their search to a 50m radius, and terminated it within 5 minutes.

To revisit most of the locations sampled during the summer survey, they reprogrammed electronic distance trackers with a predetermined grid of sampling points from the summer survey.

Since 2004, the Victorian DH has collected enhanced BU surveillance data in a centralized notifiable disease database. The DH geocoded and de-identified this data to create mesh blocks encompassing 30-60 dwellings and ensured it anonymized this data effectively for this study.

In addition, they used variables, such as the mesh block of the residential address at the time of disease notification and the date of notification and symptoms onset.

It considered a confirmed human BU case as a patient with a clinical lesion(s) suggestive of BU, analysis of which via IS2404 real-time PCR detected M. ulcerans gDNA.

Furthermore, the researchers built a customized statistical model to compare its performance to null models, a conventional approach to predicting the geographical locations of BU cases that might appear in the future.


As expected, the authors noted a spatial association between M. ulcerans-positive possum excreta clusters and human BU case clusters, as assessed by SaTScan, aligning with the exposure interval of the excreta possum surveys.

The observed pattern and overlap were consistent with prior study assessments showing a positive spatial correlation between M. ulcerans-positive possum excreta and human BU cases; thus, established possums as key environmental reservoirs of M. ulcerans in Australia, with active involvement in human transmission cycles.

The frequency of M. ulcerans-positivity in possum excreta was comparable to a previous, smaller survey done in the Mornington Peninsula (13.6% vs. 9.3%). However, the variations in their seasonal distribution highlighted the need for performing these surveys during the summers when M. ulcerans pose the highest transmission risk.

Most importantly, the possum excreta-based model for the Mornington Peninsula more accurately predicted mesh blocks with human BU cases than the null model.

Likewise, models using the Geelong excreta data correctly predicted mesh blocks with human BU cases than a null model that used last year's data of BU occurrences.


The study confirmed a quantitative association between possum excreta shedding of M. ulcerans and humans BU cases; thus, such field surveys could be a powerful tool in the cumulative arsenal of public health responses to cease BU occurrences in humans.

These are practical and cost-effective because possum excreta is abundant, well-recognized, and easily accessible, which makes it an ideal environmental analyte.

Moreover, predictive modeling making geographical risk assessments could lay the foundation of targeted public health messaging. For instance, it could inform general practitioners of the elevated M. ulcerans transmission risk in their area, which, in turn, could help diagnose cases and initiate treatment early for better clinical outcomes.

In addition, targeted messaging could encourage people in high-risk areas to adopt preventive behaviors, e.g., mosquito repellents.

Null models contain more 'noise' than the excreta-informed models because they use a long incubation period (which makes it difficult to establish when and where a person might have become infected with M. ulcerans).

On the contrary, modeling based on the incubation period interquartile range (IQR) provides better predictive capacity. Thus, the authors recommended using the incubation period IQR to capture the actual incubation period in future studies.

Enhancing the diagnostic yield from the possum excreta could also refine the performance of excreta-informed models.

The excreta-informed models also performed better because possums typically move around in a range of less than 100 m, which makes their excreta samples a spatially reliable analyte. Studies using these specimens could give a more accurate pathogen distribution idea for a particular geolocation.

Several studies have shown that human BU cases do not occur in areas where possums do not harbor M. ulcerans, which confirms their role in this pathogen's transmission cycle. It also rationalizes why the possum excreta-informed model outperformed incidence-based/null models.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.


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