{"id":2086,"date":"2026-04-09T06:06:09","date_gmt":"2026-04-09T06:06:09","guid":{"rendered":"https:\/\/zoonoses-journal.org\/?p=2086"},"modified":"2026-04-09T06:06:09","modified_gmt":"2026-04-09T06:06:09","slug":"zoonotic-plague-risk-mapping","status":"publish","type":"post","link":"https:\/\/zoonoses-journal.org\/index.php\/2026\/04\/09\/zoonotic-plague-risk-mapping\/","title":{"rendered":"A High-Resolution Geospatial Framework for Zoonotic Plague Risk Mapping in Madagascar"},"content":{"rendered":"

Announcing a new article publication for Zoonoses<\/em> journal. Plague (Yersinia pestis<\/em>) remains endemic in Madagascar and causes recurrent outbreaks leading to substantial mortality. This study was aimed at developing a high-resolution spatial risk assessment integrating environmental suitability and population exposure.<\/p>\n

A total of 174 confirmed plague occurrence records (1939\u20132023) were analyzed with a Maxent ecological niche model to predict nationwide environmental suitability. Variable contributions and permutation importance were assessed. Model outputs were downscaled to 100-m resolution and integrated with LandScan ambient population data to generate a plague exposure risk index. Commune-level spatial clustering was evaluated through Getis-Ord Gi<\/sub>* hotspot analysis.<\/p>\n

Suitability was strongly associated with elevations of 1,000\u20131,750 m, moderate precipitation, and cooler temperatures in the Central Highlands. Elevation contributed 57.8% to model performance, whereas temperature seasonality showed high permutation importance (37.4%). Hotspot analysis identified 484 significant communes across 13 regions, and five highland regions accounted for 82.9% of hotspots. Approximately 14.8 million people (62.8%) reside in areas with some degree of risk, including 9.4 million people (40.1%) in high- to very-high-risk zones.<\/p>\n

Plague risk is concentrated in Madagascar\u2019s highlands, where substantial populations remain exposed, thus supporting targeted surveillance and public health planning.<\/p>\n

Read open access article: https:\/\/www.scienceopen.com\/hosted-document?doi=10.15212\/ZOONOSES-2026-0003<\/a><\/p>\n

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Zoonoses<\/em> is fully open access journal for research scientists, physicians, veterinarians, and public health professionals working on diverse disciplinaries of zoonotic diseases. Please visit https:\/\/zoonoses-journal.org\/<\/a> to learn more about the journal.<\/p>\n

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Zoonoses<\/em><\/strong> is available on ScienceOpen<\/a> (https:\/\/www.scienceopen.com\/search#collection\/839df240-327f-47dd-b636-9b728dff9700<\/a>).<\/p>\n

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eISSN <\/strong>2737-7474<\/p>\n

ISSN<\/strong> 2737-7466<\/p>\n

# # # # # #<\/strong><\/p>\n

Mark A. Deka. A High-Resolution Geospatial Framework for Zoonotic Plague Risk Mapping in Madagascar.\u00a0Zoonoses.\u00a0<\/em>2026. Vol. 6(1). DOI: 10.15212\/ZOONOSES-2026-0003<\/p>\n","protected":false},"excerpt":{"rendered":"

Announcing a new article publication for Zoonoses journal. Plague (Yersinia pestis) remains endemic in Madagascar and causes recurrent outbreaks leading to substantial mortality. This study was aimed at developing a high-resolution spatial risk assessment integrating environmental suitability and population exposure. A total of 174 confirmed plague occurrence records (1939\u20132023) were analyzed with a Maxent ecological […]<\/p>\n","protected":false},"author":6,"featured_media":2087,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[227,124,733,734,103],"class_list":["post-2086","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-events","tag-plague","tag-public-health","tag-risk-mapping","tag-targeted-surveillance","tag-zoonotic"],"yoast_head":"\nA High-Resolution Geospatial Framework for Zoonotic Plague Risk Mapping in Madagascar<\/title>\n<meta name=\"description\" content=\"This study mapped plague risk by integrating environmental suitability with population exposure\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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