Analyzing the potential for future bat coronavirus emergence in Myanmar, Laos, and Vietnam

1过去二十年来，亚洲出现了两种主要的野生动物源性冠状病毒疾病。两者都有可能 2开始作为人畜共患病的溢出事件，导致小的病例集群，但直到显著 3社区传播使控制变得困难，并在COVID-19的情况下导致大流行。我们之前的工作和 4初步数据显示，东南亚野生动物冠状病毒（CoV）的多样性很高， 5经常在职业和环境中接触野生动物， 6.在可能开始暴发的农村地点进行监测。我们的热点风险地图直接表明， 7到中国南部;特别是缅甸，老挝和越南;包含人类与野生动物界面的地区 8和可能定期溢出的新冠病毒从蝙蝠和其他野生动物。我们初步的实地调查 在这些国家的蝙蝠和其他野生动物中发现了9种与已知人畜共患病有关的新型病毒， 10个社区有新冠病毒暴露的血清学证据。我们工作的首要目标是分析 11新型冠状病毒溢出的行为和环境风险因素，确定野生动物对人类的溢出 12起事件，评估社区传播和扩散的风险和驱动因素，并测试潜在的公共卫生 13项干预措施，以阻止溢出和传播。为此，我们提出以下建议： 1）对经常接触野生动物的人进行基于社区的调查和生物取样， 15缅甸、老挝和越南，寻找溢出的血清学证据，评估行为、社会结构， 16个导致暴露、溢出和扩散的空间连通性和流动性因素; 17具体目标2）在社区监测点对蝙蝠和其他野生动物进行采样和PCR筛查， 18确定与目标1中检测到的人类感染有关的病毒和宿主;全基因组测序和细胞 19项评估感染人类细胞能力的进入试验;机器学习方法估计人畜共患病 每种新型冠状病毒的20种潜在可能性; 21具体目标3）在诊所进行基于PCR的综合征监测，以识别“神秘”病例或引起的病例群 22例由蝙蝠冠状病毒感染;接触者追踪，以评估病例是否代表初始溢出或社区传播事件。 23我们的研究结果将提供有关未来CoV溢出和传播风险的详细信息，并将告知 24项潜在的公共卫生干预措施，以减少溢出风险和爆发可能性。他们也可以提供数据 25关于与COVID-19起源相关的野生动物水库和社区溢出事件。最后我们将 26个快速提供用于疫苗和治疗开发的病毒序列和分离物，包括 27种“原型病原体”疫苗，通过与NIAID-CREID网络的现有谅解备忘录。我们的长期目标是， 这项工作将作为一个模型，建立流行病准备战略，以更好地预测地点和社区 29野生动物源病毒可能出现的地方，并破坏世界各地EID热点的出现。 30

1 Two major coronaviral diseases of wildlife origin have emerged in Asia in the last two decades. Both likely 2 began as zoonotic spillover events, leading to small case clusters, but were not identified until significant 3 community spread made control difficult, and in the case of COVID-19, led to a pandemic. Our prior work and 4 preliminary data show that Southeast Asia has a high diversity of wildlife coronaviruses (CoVs), a large 5 proportion of the population with frequent occupational and environmental exposure to wildlife, and limited 6 surveillance at rural sites where outbreaks likely begin. Our hotspots risk mapping suggests countries directly 7 to the south of China; Myanmar, Laos and Vietnam in particular; contain regions with human-wildlife interfaces 8 and likely regular spillover of novel CoVs from bats and other wildlife. Our preliminary field studies have 9 identified novel viruses related to known zoonoses in bats and other wildlife from each of these countries and 10 communities with serological evidence of novel CoV exposure. The overarching goal of our work is to analyze 11 the behavioral and environmental risk factors for spillover of novel CoVs, identify wildlife-to-human spillover 12 events, assess the risk and drivers of community transmission and spread, and test potential public health 13 interventions to disrupt spillover and spread. To achieve this, we propose the following: 14 Specific Aim 1) community-based surveys and biological sampling of people frequently exposed to wildlife in 15 Myanmar, Laos, and Vietnam, to find serological evidence of spillover and assess behavioral, social structure, 16 spatial connectivity and mobility factors that lead to exposure, spillover, and spread; 17 Specific Aim 2) sampling and PCR screening of bats and other wildlife at community surveillance sites to 18 identify viruses and hosts related to the human infections detected in Aim 1; full genome sequencing and cell 19 entry assays to assess ability to infect human cells; machine learning approaches to estimate zoonotic 20 potential of each novel CoV; 21 Specific Aim 3) syndromic PCR-based surveillance in clinics to identify ‘cryptic’ cases or case clusters caused 22 by bat-CoVs; contact tracing to assess whether cases represent initial spillover or community spread events. 23 Our results will provide detailed information on the risk of future CoV spillover and spread and will inform 24 potential public health interventions to reduce spillover risk and outbreak potential. They may also provide data 25 on wildlife reservoirs and community spillover events of relevance to the origin of COVID-19. Finally, we will 26 rapidly supply viral sequences and isolates for use in vaccine and therapeutic development, including 27 “prototype pathogen” vaccines, via an existing MOU with the NIAID-CREID network. Our long-term goal is that 28 this work will act as a model to build pandemic preparedness strategies to better predict sites and communities 29 where wildlife-origin viruses are likely to emerge, and to disrupt emergence in EID hotspots around the world. 30