A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia.
Cecilia A SánchezHongying LiKendra L PhelpsCarlos Zambrana-TorrelioLin-Fa WangPeng ZhouZheng-Li ShiKevin J OlivalPeter DaszakPublished in: Nature communications (2022)
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.
Keyphrases
- sars cov
- endothelial cells
- respiratory syndrome coronavirus
- public health
- risk assessment
- global health
- induced pluripotent stem cells
- pluripotent stem cells
- coronavirus disease
- electronic health record
- big data
- dna methylation
- heavy metals
- deep learning
- machine learning
- artificial intelligence
- current status
- resting state
- functional connectivity