Yan-Qun Sun MPH , Yuan-Yuan Zhang MSc , Mei-Chen Liu BSc , Jin-Jin Chen MSc , Ting-Ting Li BSc , Yan-Ning Liu BSc , Ling-Yu Zhang BSc , Tao Wang MPH , Lin-Jie Yu BSc , Tian-Le Che MPH , Tian Tang BSc , Qiang Xu PhD , Chen-Long Lv PhD , Bao-Gui Jiang PhD , Prof Nick Golding PhD , Max L Mehlman PhD , Prof Simon I Hay DSc , Prof Li-Qun Fang PhD , Prof Wei Liu MD
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We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia.</p></div><div><h3>Methods</h3><p>In this geospatial modelling analysis, we developed an integrated database containing information on the distribution of Nipah virus infections in humans and animals from 1998 to 2021. We conducted phylodynamic analysis to examine the evolution and migration pathways of the virus and meta-analyses to estimate the adjusted case-fatality rate. We used two boosted regression tree models to identify the potential ecological drivers of Nipah virus occurrences in spillover events and endemic areas, and mapped potential risk areas for Nipah virus endemicity.</p></div><div><h3>Findings</h3><p>749 people and eight bat species across nine countries were documented as being infected with Nipah virus. 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Specifically, intensifying zoonotic surveillance efforts, enhancing laboratory testing capacity, and implementing public health education in projected high-risk areas where no human cases have been reported to date will be crucial. Additionally, strengthening wildlife surveillance and investigating potential modes of transmission in regions with documented human cases is needed.</p></div><div><h3>Funding</h3><p>The Key Research and Development Program of China.</p></div>","PeriodicalId":48548,"journal":{"name":"Lancet Planetary Health","volume":"8 7","pages":"Pages e463-e475"},"PeriodicalIF":24.1000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2542519624001190/pdfft?md5=37666e10da3f70c4e52b558c7833b3ed&pid=1-s2.0-S2542519624001190-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Mapping the distribution of Nipah virus infections: a geospatial modelling analysis\",\"authors\":\"Yan-Qun Sun MPH , Yuan-Yuan Zhang MSc , Mei-Chen Liu BSc , Jin-Jin Chen MSc , Ting-Ting Li BSc , Yan-Ning Liu BSc , Ling-Yu Zhang BSc , Tao Wang MPH , Lin-Jie Yu BSc , Tian-Le Che MPH , Tian Tang BSc , Qiang Xu PhD , Chen-Long Lv PhD , Bao-Gui Jiang PhD , Prof Nick Golding PhD , Max L Mehlman PhD , Prof Simon I Hay DSc , Prof Li-Qun Fang PhD , Prof Wei Liu MD\",\"doi\":\"10.1016/S2542-5196(24)00119-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Nipah virus is a zoonotic paramyxovirus responsible for disease outbreaks with high fatality rates in south and southeast Asia. However, knowledge of the potential geographical extent and risk patterns of the virus is poor. We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia.</p></div><div><h3>Methods</h3><p>In this geospatial modelling analysis, we developed an integrated database containing information on the distribution of Nipah virus infections in humans and animals from 1998 to 2021. We conducted phylodynamic analysis to examine the evolution and migration pathways of the virus and meta-analyses to estimate the adjusted case-fatality rate. We used two boosted regression tree models to identify the potential ecological drivers of Nipah virus occurrences in spillover events and endemic areas, and mapped potential risk areas for Nipah virus endemicity.</p></div><div><h3>Findings</h3><p>749 people and eight bat species across nine countries were documented as being infected with Nipah virus. On the basis of 66 complete genomes of the virus, we identified two clades—the Bangladesh clade and the Malaysia clade—with the time of the most recent common ancestor estimated to be 1863. Adjusted case-fatality rates varied widely between countries and were higher for the Bangladesh clade than for the Malaysia clade. Multivariable meta-regression analysis revealed significant relationships between case-fatality rate estimates and viral clade (p=0·0021), source country (p=0·016), proportion of male patients (p=0·036), and travel time to health-care facilities (p=0·036). Temperature-related bioclimate variables and the probability of occurrence of <em>Pteropus medius</em> were important contributors to both the spillover and the endemic infection models.</p></div><div><h3>Interpretation</h3><p>The suitable niches for Nipah virus are more extensive than previously reported. Future surveillance efforts should focus on high-risk areas informed by updated projections. 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Mapping the distribution of Nipah virus infections: a geospatial modelling analysis
Background
Nipah virus is a zoonotic paramyxovirus responsible for disease outbreaks with high fatality rates in south and southeast Asia. However, knowledge of the potential geographical extent and risk patterns of the virus is poor. We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia.
Methods
In this geospatial modelling analysis, we developed an integrated database containing information on the distribution of Nipah virus infections in humans and animals from 1998 to 2021. We conducted phylodynamic analysis to examine the evolution and migration pathways of the virus and meta-analyses to estimate the adjusted case-fatality rate. We used two boosted regression tree models to identify the potential ecological drivers of Nipah virus occurrences in spillover events and endemic areas, and mapped potential risk areas for Nipah virus endemicity.
Findings
749 people and eight bat species across nine countries were documented as being infected with Nipah virus. On the basis of 66 complete genomes of the virus, we identified two clades—the Bangladesh clade and the Malaysia clade—with the time of the most recent common ancestor estimated to be 1863. Adjusted case-fatality rates varied widely between countries and were higher for the Bangladesh clade than for the Malaysia clade. Multivariable meta-regression analysis revealed significant relationships between case-fatality rate estimates and viral clade (p=0·0021), source country (p=0·016), proportion of male patients (p=0·036), and travel time to health-care facilities (p=0·036). Temperature-related bioclimate variables and the probability of occurrence of Pteropus medius were important contributors to both the spillover and the endemic infection models.
Interpretation
The suitable niches for Nipah virus are more extensive than previously reported. Future surveillance efforts should focus on high-risk areas informed by updated projections. Specifically, intensifying zoonotic surveillance efforts, enhancing laboratory testing capacity, and implementing public health education in projected high-risk areas where no human cases have been reported to date will be crucial. Additionally, strengthening wildlife surveillance and investigating potential modes of transmission in regions with documented human cases is needed.
Funding
The Key Research and Development Program of China.
期刊介绍：
The Lancet Planetary Health is a gold Open Access journal dedicated to investigating and addressing the multifaceted determinants of healthy human civilizations and their impact on natural systems. Positioned as a key player in sustainable development, the journal covers a broad, interdisciplinary scope, encompassing areas such as poverty, nutrition, gender equity, water and sanitation, energy, economic growth, industrialization, inequality, urbanization, human consumption and production, climate change, ocean health, land use, peace, and justice.
With a commitment to publishing high-quality research, comment, and correspondence, it aims to be the leading journal for sustainable development in the face of unprecedented dangers and threats.
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