As part of a public health behavior change and communication strategy related to the identification of a novel ebolavirus in bats in Sierra Leone in 2016, a consortium of experts launched an effort to create a widely accessible resource for community awareness and education on reducing disease risk. The resulting picture book, Living Safely With Bats, includes technical content developed by a consortium of experts in public health, animal health, conservation, bats, and disease ecology from 30 countries. The book has now been adapted, translated, and used in more than 20 countries in Africa and Asia. We review the processes used to integrate feedback from local stakeholders and multidisciplinary experts. We also provide recommendations for One Health and other practitioners who choose to pursue the development and evaluation of this or similar zoonotic disease risk mitigation tools.
Evidence suggests that bats are important hosts of filoviruses, yet the specific species involved remain largely unidentified. Niemann-Pick C1 (NPC1) is an essential entry receptor, with amino acid variations influencing viral susceptibility and species-specific tropism. Herein, we conducted combinatorial binding studies with seven filovirus glycoproteins (GPs) and NPC1 orthologs from 81 bat species. We found that GP-NPC1 binding correlated poorly with phylogeny. By integrating binding assays with machine learning, we identified genetic factors influencing virus-receptor-binding and predicted GP-NPC1-binding avidity for additional filoviruses and bats. Moreover, combining receptor-binding avidities with bat geographic distribution and the locations of previous Ebola outbreaks allowed us to rank bats by their potential as Ebola virus hosts. This study represents a comprehensive investigation of filovirus-receptor binding in bats (1,484 GP-NPC1 pairs, 11 filoviruses, and 135 bats) and describes a multidisciplinary approach to predict susceptible species and guide filovirus host surveillance.
Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses.