{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T07:24:12Z","timestamp":1786951452213,"version":"build-2736575974"},"reference-count":49,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,8,16]],"date-time":"2026-08-16T00:00:00Z","timestamp":1786838400000},"content-version":"vor","delay-in-days":227,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Tropical Medicine"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Uganda experiences recurrent Ebola disease (EBOD) outbreaks, yet national suitability maps often pool virus species or are too coarse for district\u2010level planning. We aimed to generate species\u2010resolved, 1\u2009km relative environmental suitability surfaces for reported Ebola spillover events in Uganda; quantify the contribution of environmental, anthropogenic, and reservoir\u2010related predictors to modeled suitability; and translate continuous outputs into operational prioritization tiers for district surveillance and preparedness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We compiled 71 laboratory\u2010confirmed reported Ebola event localities in Uganda from 2000 to 2023, defined as the most likely documented locality of initial human infection where available, and paired them with 11 minimally collinear predictors. Pooled and virus\u2010specific MaxEnt models were tuned in ENMeval by comparing feature\u2010class sets across\n                      <jats:italic>\u03b2<\/jats:italic>\n                      \u2009=\u20090.5 to 3.0, ranked by AICc, and screened for acceptable omission at the 10% training\u2010presence threshold. Performance was estimated using fourfold spatial block cross\u2010validation. Pooled cloglog suitability values were thresholded at the 10% training\u2010presence value and stratified into four operational prioritization tiers.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Tuning selected LQHP with\n                      <jats:italic>\u03b2<\/jats:italic>\n                      \u2009=\u20091.5 for the pooled model. Under spatial block cross\u2010validation, pooled performance was Test AUC\u2009=\u20090.845 (0.825 to 0.862) and Test Boyce\u2009=\u20090.58 (0.52 to 0.63), with Test OR10\u2009=\u20090.101 (0.092 to 0.109). The operational threshold was cloglog\u2009=\u20090.084, classifying 25.4% of Uganda as suitable within the modeling framework. Tier 1, defined as the highest\u2010suitability decile among suitable pixels (cloglog \u2265 0.65), covered 5.8% of land area yet contained approximately 12.6 million residents (29%). High\u2010suitability areas were clustered in the Albertine Rift escarpment belt, the Kampala, Wakiso, Mukono peri\u2010urban cluster extending along major corridors, and a northern Lake Kyoga shoreline crescent. Species\u2010specific outputs were interpreted as exploratory secondary analyses. SUDV broadly reproduced the pooled modeled suitability geography, EBOV showed elevated suitability along the western border corridor, and BDBV suitability was concentrated around the Albertine escarpment. Checkerboard2 sensitivity produced a small AUC increase (\u0394AUC\u2009=\u2009+0.006) and high tier agreement.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Relative environmental suitability for reported Ebola spillover localities in Uganda is concentrated in compact high\u2010priority belts where elevated modeled suitability overlaps with large resident populations. Tier 1 and Tier 2 areas provide a focused basis for strengthening event\u2010based surveillance, early detection, laboratory referral, infection prevention and control readiness, rapid response capacity, One Health field investigation, and community engagement.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/jotm\/9889973","type":"journal-article","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T06:28:58Z","timestamp":1786948138000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["High\u2010Resolution Mapping of Environmental Suitability for Reported Ebola Spillover Events in Uganda to Inform Surveillance and Preparedness"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6360-0589","authenticated-orcid":false,"given":"George","family":"Paasi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8687-0412","authenticated-orcid":false,"given":"Nancy","family":"Malaika","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8448-0301","authenticated-orcid":false,"given":"Sam","family":"Okware","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5757-609X","authenticated-orcid":false,"given":"Peter","family":"Olupot-Olupot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,16]]},"reference":[{"key":"e_1_2_14_1_2","unstructured":"Ebola Disease https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/ebola-disease."},{"key":"e_1_2_14_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/438575a"},{"key":"e_1_2_14_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/srep41613"},{"key":"e_1_2_14_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolmodel.2005.03.026"},{"key":"e_1_2_14_5_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1472-4642.2010.00725.x"},{"key":"e_1_2_14_6_2","doi-asserted-by":"publisher","DOI":"10.7554\/elife.04395"},{"key":"e_1_2_14_7_2","volume-title":"Outbreak History | Ebola"},{"key":"e_1_2_14_8_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pntd.0010205"},{"key":"e_1_2_14_9_2","doi-asserted-by":"publisher","DOI":"10.3201\/eid1607.091525"},{"key":"e_1_2_14_10_2","doi-asserted-by":"publisher","DOI":"10.1046\/j.1365-3156.2002.00944.x"},{"key":"e_1_2_14_11_2","doi-asserted-by":"publisher","DOI":"10.3201\/eid1809.111536"},{"key":"e_1_2_14_12_2","unstructured":"Ebola in Uganda\u2013Update https:\/\/www.who.int\/emergencies\/disease-outbreak-news\/item\/2012_09_03-en."},{"key":"e_1_2_14_13_2","unstructured":"Ebola Outbreak 2022-Uganda https:\/\/www.who.int\/emergencies\/situations\/ebola-uganda-2022."},{"key":"e_1_2_14_14_2","article-title":"Ecological Niche Modeling for Filoviruses: A Risk Map for Ebola and Marburg Virus Disease Outbreaks in Uganda","volume":"9","author":"Nyakarahuka L.","year":"2017","journal-title":"PLOS Currents"},{"key":"e_1_2_14_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolmodel.2013.12.012"},{"key":"e_1_2_14_16_2","doi-asserted-by":"publisher","DOI":"10.1890\/07-2153.1"},{"key":"e_1_2_14_17_2","doi-asserted-by":"publisher","DOI":"10.1002\/joc.5086"},{"key":"e_1_2_14_18_2","unstructured":"Shuttle Radar Topography Mission (SRTM) NASA Earthdata https:\/\/www.earthdata.nasa.gov\/data\/instruments\/srtm."},{"key":"e_1_2_14_19_2","unstructured":"WorldPop Population Density https:\/\/hub.worldpop.org\/geodata\/summary?id=44351."},{"key":"e_1_2_14_20_2","doi-asserted-by":"publisher","DOI":"10.3201\/eid2904.221022"},{"key":"e_1_2_14_21_2","volume-title":"Climate Physical Risk Index (CPRI)","author":"Guo K.","year":"2024"},{"key":"e_1_2_14_22_2","article-title":"Occurrence Download","author":"User G. 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