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.

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. We used a Bayesian statistical framework and sequence data from all known bat-CoVs (including 630 novel CoV sequences) to study their macroevolution, cross-species transmission, and dispersal in China. We find that host-switching was more frequent and across more distantly related host taxa in alpha-than beta-CoVs, and 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.

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.

The Impact of Global Environmental Changes on Infectious Disease Emergence with a Focus on Risks for Brazil

Environmental changes have a huge impact on the emergence and reemergence of certain infectious diseases, mostly in countries with high biodiversity and serious unresolved environmental, social, and economic issues. This article summarizes the most important findings with special attention to Brazil and diseases of present public health importance in the country such as Chikungunya, dengue fever, yellow fever, Zika, hantavirus pulmonary syndrome, leptospirosis, leishmaniasis, and Chagas disease. An extensive literature review revealed a relationship between infectious diseases outbreaks and climate change events (El Niño, La Niña, heatwaves, droughts, floods, increased temperature, higher rainfall, and others) or environmental changes (habitat fragmentation, deforestation, urbanization, bushmeat consumption, and others). To avoid or control outbreaks, integrated surveillance systems and effective outreach programs are essential. Due to strong global and local influence on emergence of infectious diseases, a more holistic approach is necessary to mitigate or control them in low-income nations.

Detection of diverse novel astroviruses from small mammals in China

Astroviruses infect humans and many animal species and cause gastroenteritis. To extensively understand the distribution and genetic diversity of astrovirus in small mammals, we tested 968 anal swabs from 39 animal species, most of which were bats and rodents. We detected diverse astroviruses in 10 bat species, including known bat astroviruses and a large number of novel viruses. Meanwhile, novel groups of astroviruses were identified in three wild rodent species and a remarkably high genetic diversity of astrovirus was revealed in Eothenomys cachinus. We detected astroviruses in captive-bred porcupines and a nearly full-length genome sequence was determined for one strain. Phylogenetic analysis of the complete ORF2 sequence suggested that this strain may share a common ancestor with porcine astrovirus type 2. Moreover, to our knowledge, this study reports the first discovery of astroviruses in shrews and pikas. Our results provide new insights for understanding these small mammals as natural reservoirs of astroviruses.

Using network theory to identify the causes of disease outbreaks of unknown origin

The identification of undiagnosed disease outbreaks is critical for mobilizing efforts to prevent widespread transmission of novel virulent pathogens. Recent developments in online surveillance systems allow for the rapid communication of the earliest reports of emerging infectious diseases and tracking of their spread. The efficacy of these programs, however, is inhibited by the anecdotal nature of informal reporting and uncertainty of pathogen identity in the early stages of emergence. We developed theory to connect disease outbreaks of known aetiology in a network using an array of properties including symptoms, seasonality and case-fatality ratio. We tested the method with 125 reports of outbreaks of 10 known infectious diseases causing encephalitis in South Asia, and showed that different diseases frequently form distinct clusters within the networks. The approach correctly identified unknown disease outbreaks with an average sensitivity of 76 per cent and specificity of 88 per cent. Outbreaks of some diseases, such as Nipah virus encephalitis, were well identified (sensitivity = 100%, positive predictive values = 80%), whereas others (e.g. Chandipura encephalitis) were more difficult to distinguish. These results suggest that unknown outbreaks in resource-poor settings could be evaluated in real time, potentially leading to more rapid responses and reducing the risk of an outbreak becoming a pandemic.

Preventing pandemics via international development: a systems approach

Tiffany Bogich and colleagues find that breakdown or absence of public health infrastructure is most often the driver in pandemic outbreaks, whose prevention requires mainstream development funding rather than emergency funding.

Predicting the global spread of H5N1 avian influenza

The spread of highly pathogenic H5N1 avian influenza into Asia, Europe, and Africa has resulted in enormous impacts on the poultry industry and presents an important threat to human health. The pathways by which the virus has and will spread between countries have been debated extensively, but have yet to be analyzed comprehensively and quantitatively. We integrated data on phylogenetic relationships of virus isolates, migratory bird movements, and trade in poultry and wild birds to determine the pathway for 52 individual introduction events into countries and predict future spread. We show that 9 of 21 of H5N1 introductions to countries in Asia were most likely through poultry, and 3 of 21 were most likely through migrating birds. In contrast, spread to most (20/23) countries in Europe was most likely through migratory birds. Spread in Africa was likely partly by poultry (2/8 introductions) and partly by migrating birds (3/8). Our analyses predict that H5N1 is more likely to be introduced into the Western Hemisphere through infected poultry and into the mainland United States by subsequent movement of migrating birds from neighboring countries, rather than from eastern Siberia. These results highlight the potential synergism between trade and wild animal movement in the emergence and pandemic spread of pathogens and demonstrate the value of predictive models for disease control.