#Ecological #Niche #Modeling for #Filoviruses: A #Risk #Map for #Ebola and #Marburg Virus Disease #Outbreaks in #Uganda (PLoS Curr., abstract)

[Source: PLoS Currents Outbreaks, full page: (LINK). Abstract, edited.]

Ecological Niche Modeling for Filoviruses: A Risk Map for Ebola and Marburg Virus Disease Outbreaks in Uganda


AUTHORS: Luke Nyakarahuka, Samuel Ayebare, Gladys Mosomtai, Clovice Kankya, Julius Lutwama, Frank Norbert Mwiine, Eystein Skjerve




Uganda has reported eight outbreaks caused by filoviruses between 2000 to 2016, more than any other country in the world. We used species distribution modeling to predict where filovirus outbreaks are likely to occur in Uganda to help in epidemic preparedness and surveillance.


The MaxEnt software, a machine learning modeling approach that uses presence-only data was used to establish filovirus – environmental relationships. Presence-only data for filovirus outbreaks were collected from the field and online sources. Environmental covariates from Africlim that have been downscaled to a nominal resolution of 1km x 1km were used. The final model gave the relative probability of the presence of filoviruses in the study area obtained from an average of 100 bootstrap runs. Model evaluation was carried out using Receiver Operating Characteristic (ROC) plots. Maps were created using ArcGIS 10.3 mapping software.


We showed that bats as potential reservoirs of filoviruses are distributed all over Uganda. Potential outbreak areas for Ebola and Marburg virus disease areas were predicted in West, Southwest and Central parts of Uganda, which corresponds to bat distribution and previous filovirus outbreaks areas. Additionally, the models predict the Eastern Uganda region and other areas that have not reported outbreaks before to be potential outbreak hotspots. Rainfall variables were the most important in influencing model prediction compared to temperature variables.


Despite the limitations in the prediction model due to lack of adequate sample records for outbreaks, especially for the Marburg cases, the model outputs provide a risk map to the Uganda surveillance system on filovirus outbreaks. The risk maps for potential filovirus outbreaks will aid in identifying areas to focus the filovirus surveillance for early detection and responses hence curtailing a pandemic. The results from this study also confirm previous findings that suggest that Filoviruses are mainly limited by the amount of rainfall received in an area.


We are grateful for funding from Norwegian Agency for Development Cooperation (NORAD) through the Norwegian Program for Capacity Building in Higher Education and Research for Development (NORHED) project of Capacity Building in Zoonotic diseases Management using integrated approach to Ecosystems health at the human-livestock–wildlife interface in Eastern and Southern Africa. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Keywords: Filovirus; Uganda; Ebola; Marburg; Mathematical Models.



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I am an Italian blogger, active since 2005 with main focus on emerging infectious diseases such as avian influenza, SARS, antibiotics resistance, and many other global Health issues. Other fields of interest are: climate change, global warming, geological and biological sciences. My activity consists mainly in collection and analysis of news, public services updates, confronting sources and making decision about what are the 'signals' of an impending crisis (an outbreak, for example). When a signal is detected, I follow traces during the entire course of an event. I started in 2005 my blog ''A TIME'S MEMORY'', now with more than 40,000 posts and 3 millions of web interactions. Subsequently I added an Italian Language blog, then discontinued because of very low traffic and interest. I contributed for seven years to a public forum (FluTrackers.com) in the midst of the Ebola epidemic in West Africa in 2014, I left the site to continue alone my data tracking job.

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