A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia

• Published in: Nature communications Vol. 13; no. 1; pp. 4380 - 12
• Main Authors: Sánchez, Cecilia A., Li, Hongying, Phelps, Kendra L., Zambrana-Torrelio, Carlos, Wang, Lin-Fa, Zhou, Peng, Shi, Zheng-Li, Olival, Kevin J., Daszak, Peter
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09.08.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/158/1144; 692/699/255/2514; 704/158/1469; Animals; Antibodies; Asia, Southeastern - epidemiology; Chiroptera; Coronaviridae; Coronaviruses; COVID-19; Ecological adaptation; Epidemiology; Evolution, Molecular; Geographical distribution; Geography; Global health; Human populations; Humanities and Social Sciences; Humans; multidisciplinary; Phylogeny; Prevention programs; Probabilistic risk assessment; Public health; Risk assessment; Science; Science (multidisciplinary); Seroepidemiologic Studies; Serology; Severe acute respiratory syndrome; Severe acute respiratory syndrome-related coronavirus; Viral diseases; Asia, Southeastern; Southeast Asia
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-022-31860-w

Emerging diseases caused by coronaviruses of likely bat origin (e.g., SARS, MERS, SADS, COVID-19) have disrupted global health and economies for two decades. Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this spillover may help target prevention programs. We derive current range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human viral seroprevalence, and antibody duration to estimate that a median of 66,280 people (95% CI: 65,351–67,131) are infected with SARSr-CoVs annually in Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence. Coronaviruses may spill over from bats to humans. This study uses epidemiological data, species distribution models, and probabilistic risk assessment to map overlap among people and SARSr-CoV bat hosts and estimate how many people are infected with bat-origin SARSr-CoVs in Southeast Asia annually.