Thursday, April 25, 2024
4/25/2024
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
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