A new scientific paper from Nature Health Global scientists identifies widespread spillover risk of a group of coronaviruses in China and Southeast Asia. SADS-related alpha-coronaviruses were first identified in 2018 in our breakthrough paper in Nature, as the cause of largescale outbreaks in pig farms in China and have been shown to infect human primary airway epithelial cells in the lab, suggesting potential for human infection. We report 186 new Rhinacovirus RdRp sequences, revealing a large, underappreciated diversity of these viruses. We analyzed all 523 known genetic sequences of these and related CoVs to identify the region and bats species in which they first evolved, and the origins of the SADS outbreak. We modeled the distribution of SADS related CoV bat host species, and their overlap with human and pig populations to produce spillover hotspot maps, identifying where public health programs could best track potential spillover and block future outbreaks.
The SADS-CoV outbreak in pigs in 2016 was thought to have originated from a group of related viruses in this horseshoe bat species, Rhinolophus affinis.
A downloadable pdf of the paper is available on this link: Diversity and spillover risk of swine acute diarrhea syndrome and related coronaviruses in China and Southeast Asia. Latinne et al. mBio 2025.
Supplementary information is available on this link: https://naturehealthglobal.org/latinne-et-al-2025-supplemental/.
Identifiying spillover risk to help prevent pandemics
Bat-origin coronaviruses are a key pandemic risk. They are the cause of COVID-19, the most significant pandemic in living memory that caused the tragic death of more than 20 million people, wiped out tens of trillions of dollars from our global economy, and continues to threaten our health through the emergence of new strains that may escape vaccine coverage. Emerging zoonotic diseases like COVID are on the rise – they’re spilling over more often and spreading more easily through our growing population via globalized travel and transport networks. How can we break free from this pandemic era? One way is by analyzing how, why and from where pandemics originate, then blocking future spillover events.
All significant outbreaks of emerging viruses are listed since the avian flu event in 1997
An under-appreciated coronavirus risk group
Coronaviruses (CoVs) have a long history of emerging via devastating outbreaks in people and livestock. They have an unusually high capacity for evolutionary adaptation that allows them to transmit more easily from one host species to another. This is why wildlife CoVs, including many from bat species have have led to recent outbreaks (SARS, MERS, COVID-19) and include now-endemic pathogens that cause ‘common colds’ (e.g. HCoV-229E, HCoV-NL-63).
All known major coronavirus disease outbreaks from historical times to present. Bats are significant CoV reservoirs responsible for emerging diseases of people and livestock, particularly pigs. Note that some of the historical spillover CoVs are still circulating in people, as ‘common cold’ pathogens. Figure from Keusch et al. PNAS 2022
Coronaviruses also cause important diseases of livestock, with devastating impact on the pork industry. Asia is a major producer of pigs, with China having the highest density of intensive pig farming in the world. In 2016, outbreaks of severe, fatal diarrheal disease killed more than 25,000 pigs in farms in south China. The cause was a novel alpha-CoV called swine acute diarrheal syndrome (SADS-CoV) which has since continued to emerge, causing outbreaks in 2021 and 2023. SADS-CoV is closely related to bat CoVs, suggesting this was yet another bat-to-pig spillover event leading to a new devastating disease. The horseshoe bats that carry these viruses are found across Southeast Asia, and as far as South Asia, indicating wide potential for future spillover, and a high risk to other pig production regions.
Outbreak locations of the original SADS-CoV spillover events identified causing pig die-offs in Guangdong Province, China, 2018. Note that bats from nearby locations were found positive for related coronaviruses.
Our collaborative group tested pig farm workers after the 2016 SADS-CoV outbreak and found no evidence any had been infected by the virus. However, SADS-CoV can grow efficiently in primary human lung and intestinal cells in the lab and can cause disease in baby mice inoculated with the virus. There is growing concern that in places where people and bats have high contact (e.g. occupational exposure in caves, or exposure of people who live near bat roosts or foraging sites) or where people and pigs have contact, it is possible that human infections or even an outbreak could occur.
Phylogeny of the outbreak strains of SADS-CoV compared with other coronaviruses, hosts denoted by symbols.
Identifying origins of rhinacoviruses and the SADS-CoV outbreak strains
We collected hundreds of fecal and other samples from bats across China and in other southeast Asian countries, sequenced the RNA in the samples and analyzed them for presence of coronaviruses. We found 186 new Rhinacovirus RdRp sequences, representing a large previously underappreciated diversity of these viruses. We analyzed these and all other known alpha-CoV (rhinacovirus) RdRp sequences – 523 sequences from 15 species of bats from 12 provinces of China and a number of countries in Southeast Asia. We found that these viruses split into two groups (clades): Clade 1 which seems to have originated in Guangxi/Guangdong Province and Clade 2, which includes the SADS-related CoVs and seems to have originated in Yunnan Province in the Southwest of China.
Phylogenetic tree showing relatedness of all known Rhinacovirus alpha-CoV RdRp sequences. Note that these form two distinct clades, with Clade 2 containing all SADSr-CoVs including outbreak strains
Analyses of the relatedness of these viral RNA sequences (phylogeny) shows that two horseshoe bat species (Rhinolophus affinis and R. sinicus/thomasi) are the most important in the evolution of these viruses. All SADS-related CoVs, including the outbreak strains come from a single evolutionary source (i.e. they form a monophyletic clade) dominated by sequences from the horseshoe bat species R. affinis and that the original outbreak in pigs was from a group of viruses that spilled over directly from bats to pigs in Guangdong, Southern China. This is also the region where SARS-CoV first emerged in 2002, and where we found bat samples positive for related viruses previously. A single sequence from a different province of China (Fujian) was identical to those from pigs in Guangdong, suggesting it was imported via the pig trade, rather than a separate spillover event from bats.
Median-joining network of rhinacoviruses for the data set with known hosts only. Colored circles correspond to distinct rhinacovirus sequences, and circle size is proportional to the number of identical sequences in the data set. Small black circles represent median vectors (ancestral or unsampled intermediate sequences).
Mapping disease risk
To map where this virus is likely to spillover in the future, we first had to estimate the total distribution of these viruses in bats across the region. We used bat location data from museum specimens and scientific reports then analyzed how these locations correlate to vegetation, habitat (e.g. limestone karst geology with high numbers of caves) and climate. We used these ‘niche models’ to predict the maximum geographic distribution of all bat species that are known to harbor rhinacoviruses. Theoretically, this provides the limit to the geographic regions where a person or pig would encounter a bat carrying these alpha-CoVs.
We then mapped the risk of spillover to pig farms. We used data on pig farm density in the region from the Gridded Livestock of the World database to identify the overlap with our maps of where bats that harbor alpha-CoVs are likely to exist. The mean pig density within suitable bat host habitat was ~42 pigs/km2. The disease risk hotspots were – areas with the highest pig density (> 500 pigs/km2) – occurred mostly in China, where Hunan, Guangxi, and Guangdong provinces contained the highest numbers of pigs (> 20 million) overlapping with suitable host habitat, as well as northern Viet Nam and central Thailand.
Hotspot map of the risk of SADS-related coronaviruses spilling over into pig populations in Southeast Asia. Areas with high pig production are mapped within the modeled ranges of the Rhinolophus spp. bats that carry these viruses.
Risk of SADSr-CoV spillover to pigs in China, broken down by province. Areas of intensive pig production in regions where Rhinolophus spp. bats that carry these viruses are the highest risk.
We then repeated the analysis with detailed data on human population density across the region where these bat hosts live. We found that mean population density here was ~281 people/km2. Spillover risk hotspots for people – areas with above-average human density within suitable host habitat – were mainly in southern China, Java, and eastern India. Regions with the highest human density (>2,000 people/km2) could be identified near cities such as Jakarta (Indonesia), Bangkok (Thailand), Hanoi (Viet Nam) and Shenzhen (China). Within China, Guangdong, Hunan, and Zhejiang provinces contained the highest number of people (> 40 million) living within areas of suitable host habitat
Hotspot map of the risk of SADS-related coronaviruses spilling over into people in Southeast Asia. Areas of high human density are mapped within the modeled ranges of the Rhinolophus spp. bats that carry these viruses.
Risk of SADSr-CoV spillover to people in China, broken down by province. Areas of high population density in regions where Rhinolophus spp. bats that carry these viruses are the highest risk.
Lessons for preventing pandemics
Our work provides can help guide strategies to prepare for and prevent future outbreaks, and reduce the potential for pandemics.
Targeting surveillance
We provide a roadmap to target surveillance to specific regions, e.g. Guangdong and Yunnan Provinces, which we find are hotspots for the evolution of this group of viruses. The finding of SADSr-CoVs in Thailand and Viet Nam, despite substantially less sampling, suggests that there are likely many more regions with these viruses, so targeting bat sampling in these and neighboring countries could provide a better understanding where these viruses are.
Using serological assays for surveillance in bats, livestock and people could within the regions identified as bat-to-pig spillover hotspots, could provide a way to pick up evidence of spillover on the ‘frontline’ of infection risk, and help reduce the opportunity for outbreaks to take hold.
Rhinolophus affinis, the horseshoe bat species from which the original SADS-CoV outbreak spilled over into pigs, and a key reservoir host for the evolutionary origins of this group of viruses.
Specific risk to people remains uncertain, but the finding that these viruses can infect human airway cells is a red flag for action. Farmers working with pigs, particularly where diarrheal outbreaks and die-offs have been identified, could be placed under more active surveillance. Communities close to Rhinolophus spp. Horseshoe bat roosts and foraging sites are also a high priority for increased surveillance. While no human cases of SADS-CoV infection have been identified to date, the reported number of people tested by PCR or serology is low (<50) (20) compared to the population of tens of millions within this region, and the high potential for occupational exposure.
Designing Control programs
In our field investigations at two of the farms where the original SADS-CoV began, we found insectivorous bats roosting under the roof of pig barns and bat feces on the ground around them. Efforts to reduce contact between bats and pigs, by tightening up barriers around pigsties, and removing roosting bats, and fecal contamination, could reduce risk of spillover of these and other viruses. The hotspots maps provide a way to target the costly control programs to the places that would benefit the most in reducing risk. Future ecological investigations in these hotspots to understand bat behavior and bat interactions with pigs and people could be invaluable. Identifying the extent and seasonality of roosting, foraging, and other activity patterns, as well as the patterns of viral shedding over time would help identify peak seasons and locations to block transmission.
Photo from our survey of farms after the original SADS-CoV outbreak in Guangdong province, China. Outside of this pigsty shows potential for access by foraging horseshoe bats.
Photo from our survey of farms after the original SADS-CoV outbreak in Guangdong province, China. Examining for evidence of bat visitation to this pigsty.
Photo from our survey of farms after the original SADS-CoV outbreak in Guangdong province, China. Examining for evidence of bat visitation to this pigsty.
Photo from our survey of farms after the original SADS-CoV outbreak in Guangdong province, China. Assessing evidence of bat presence inside the structure.
Photo from our surveys of pigfarms involved in the original SADS-CoV outbreak reported in 2018. Evidence of bats visiting the pigsties revealed by the presence of bat feces below entry points and potential roost sites for bats.
Photo from our surveys of pigfarms involved in the original SADS-CoV outbreak reported in 2018. Evidence of insectivorous bat roost sites just under the eaves of pigsties at one farm.
Photo from our surveys of pigfarms involved in the original SADS-CoV outbreak reported in 2018. Evidence of insectivorous bat roost sites just under the eaves of pigsties at one farm. at fecal pellets found on the ground below potential entry or roost sites.
Photo from our survey of farms involved in the original SADS-CoV outbreak reported in 2018. Bat fecal pellets on the ground directly outside pigsties indicate potential roost sites and access to the pigsties by insectivorous bats.
The value of international collaboration
This work is part of a multi-decade collaboration between scientists in the USA and China that has led to dozens of important papers on coronaviruses, funded mainly by US and Chinese Governments. This work has been severely hindered during the past 5+ years, due to conspiracies surrounding the origins of COVID-19, and by efforts to block funding for EcoHealth Alliance. We are extremely grateful for the continued support and collaboration of our colleagues in China who are named as authors, as well as all those who listed in the acknowledgments section of the paper: Kai Zhao (Yunnan Key Laboratory of Biodiversity Information, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China); and Ben Hu, Bei Li, Wei Zhang, and Zheng-Li Shi (Key Laboratory of Virology and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China).
Likewise, we thank the US and Chinese public, and the government agencies that originally funded this work (NIH-NIAID R01AI110964, NIAID-CREID U01AI151797 “EID-SEARCH”; USAID Emerging Pandemic Threats PREDICT project; National Natural Science Foundation of China (31830096, 32361133556), Chinese Academy of Sciences (KJZD-SW-L11), the Major Project of Guangzhou National Laboratory (GZNL2023A01001), the Self-Supporting Program of Guangzhou Laboratory (SRPG22-001) to Z-LS, and the Guangdong Provincial Science and Technology Program (2021B1212110003, 2021B1212050021). When public funds were blocked, private donors and foundations came to our aid, including the Samuel Freeman Charitable Trust, The Wallace Fund, and an anonymous donor c/o Schwab Charitable. To them, we are particularly grateful.
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