A qualitative study of zoonotic risk factors among rural communities in southern China.

BACKGROUND: Strategies are urgently needed to mitigate the risk of zoonotic disease emergence in southern China, where pathogens with zoonotic potential are known to circulate in wild animal populations. However, the risk factors leading to emergence are poorly understood, which presents a challenge in developing appropriate mitigation strategies for local communities. METHODS: Residents in rural communities of Yunnan, Guangxi and Guangdong provinces were recruited and enrolled in this study. Data were collected through ethnographic interviews and field observations, and thematically coded and analysed to identify both risk and protective factors for zoonotic disease emergence at the individual, community and policy levels. RESULTS: Eighty-eight ethnographic interviews and 55 field observations were conducted at nine selected sites. Frequent human-animal interactions and low levels of environmental biosecurity in local communities were identified as risks for zoonotic disease emergence. Policies and programmes existing in the communities provide opportunities for zoonotic risk mitigation. CONCLUSIONS: This study explored the relationship among zoonotic risk and human behaviour, environment and policies in rural communities in southern China. It identifies key behavioural risk factors that can be targeted for development of tailored risk-mitigation strategies to reduce the threat of novel zoonoses.

Wild animal and zoonotic disease risk management and regulation in China: Examining gaps and One Health opportunities in scope, mandates, and monitoring systems.

Emerging diseases of zoonotic origin such as COVID-19 are a continuing public health threat in China that lead to a significant socioeconomic burden. This study reviewed the current laws and regulations, government reports and policy documents, and existing literature on zoonotic disease preparedness and prevention across the forestry, agriculture, and public health authorities in China, to articulate the current landscape of potential risks, existing mandates, and gaps. A total of 55 known zoonotic diseases (59 pathogens) are routinely monitored under a multi-sectoral system among humans and domestic and wild animals in China. These diseases have been detected in wild mammals, birds, reptiles, amphibians, and fish or other aquatic animals, the majority of which are transmitted between humans and animals via direct or indirect contact and vectors. However, this current monitoring system covers a limited scope of disease threats and animal host species, warranting expanded review for sources of disease and pathogen with zoonotic potential. In addition, the governance of wild animal protection and utilization and limited knowledge about wild animal trade value chains present challenges for zoonotic disease risk assessment and monitoring, and affect the completeness of mandates and enforcement. A coordinated and collaborative mechanism among different departments is required for the effective monitoring and management of disease emergence and transmission risks in the animal value chains. Moreover, pathogen surveillance among wild animal hosts and human populations outside of the routine monitoring system will fill the data gaps and improve our understanding of future emerging zoonotic threats to achieve disease prevention. The findings and recommendations will advance One Health collaboration across government and non-government stakeholders to optimize monitoring and surveillance, risk management, and emergency responses to known and novel zoonotic threats, and support COVID-19 recovery efforts.

Origin and cross-species transmission of bat coronaviruses in China.

Bats are presumed reservoirs of diverse coronaviruses (CoVs) including progenitors of Severe Acute Respiratory Syndrome (SARS)-CoV and SARS-CoV-2, the causative agent of COVID-19. However, the evolution and diversification of these coronaviruses remains poorly understood. Here we use a Bayesian statistical framework and a large sequence data set from bat-CoVs (including 630 novel CoV sequences) in China to study their macroevolution, cross-species transmission and dispersal. We find that host-switching occurs more frequently and across more distantly related host taxa in alpha- than beta-CoVs, and is more highly constrained by phylogenetic distance for beta-CoVs. We show that inter-family and -genus switching is most common in Rhinolophidae and the genus Rhinolophus. Our analyses identify the host taxa and geographic regions that define hotspots of CoV evolutionary diversity in China that could help target bat-CoV discovery for proactive zoonotic disease surveillance. Finally, we present a phylogenetic analysis suggesting a likely origin for SARS-CoV-2 in Rhinolophus spp. bats.