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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.

BackgroundAs the global population soars, human behaviours are increasing the risk of epidemics. Objective performance evaluation of outbreak responses requires that metrics of timeliness, or speed in response time, be recorded and reported. We sought to evaluate how timeliness data are being conveyed for multisectoral outbreaks and make recommendations on how One Health metrics can be used to improve response success.MethodsWe conducted a scoping review of outbreaks reported January 1, 2010- March 15, 2020, in organizational reports and peer-reviewed literature on PubMed and Embase databases. We tracked 11 outbreak milestones and calculated timeliness metrics, the median time in days, between the following: 1) Predict; 2) Prevent; 3) Start; 4) Detect; 5) Notify; 6) Verify; 7) Diagnostic; 8) Respond; 9) Communication; 10) End; and 11) After-Action Review.FindingsWe identified 26783 outbreak reports, 1014 of which involved more than just the human health sector. Only six of the eleven milestones were mentioned in >50% of reports. The time between most milestones was on average shorter for outbreaks reporting both Predict (alert of a potential outbreak) and Prevent (response to predictive alert) events.InterpretationTracking progress in timeliness during outbreaks can focus efforts to prevent outbreaks from evolving into epidemics or pandemics. Response to predictive alerts demonstrated improved expediency in time to most milestones. We recommend the adoption of universally defined One Health outbreak milestones, including After Action Review, such that timeliness metrics can be used to assess outbreak response improvements over time.FundingThis study was made possible by the United States Agency for International Development's One Health Workforce-Next Generation Project (Cooperative Agreement 7200AA19CA00018).

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.

In March 2021, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by four families (Aliusviridae, Crepuscuviridae, Myriaviridae, and Natareviridae), three subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae), 42 genera, and 200 species. Thirty-nine species were renamed and/or moved and seven species were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

Forecasting the risk of pathogen spillover from reservoir populations of wild or domestic animals is essential for the effective deployment of interventions such as wildlife vaccination or culling. Due to the sporadic nature of spillover events and limited availability of data, developing and validating robust, spatially explicit, predictions is challenging. Recent efforts have begun to make progress in this direction by capitalizing on machine learning methodologies. An important weakness of existing approaches, however, is that they generally rely on combining human and reservoir infection data during the training process and thus conflate risk attributable to the prevalence of the pathogen in the reservoir population with the risk attributed to the realized rate of spillover into the human population. Because effective planning of interventions requires that these components of risk be disentangled, we developed a multi-layer machine learning framework that separates these processes. Our approach begins by training models to predict the geographic range of the primary reservoir and the subset of this range in which the pathogen occurs. The spillover risk predicted by the product of these reservoir specific models is then fit to data on realized patterns of historical spillover into the human population. The result is a geographically specific spillover risk forecast that can be easily decomposed and used to guide effective intervention. Applying our method to Lassa virus, a zoonotic pathogen that regularly spills over into the human population across West Africa, results in a model that explains a modest but statistically significant portion of geographic variation in historical patterns of spillover. When combined with a mechanistic mathematical model of infection dynamics, our spillover risk model predicts that 897,700 humans are infected by Lassa virus each year across West Africa, with Nigeria accounting for more than half of these human infections.

In March 2020, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. At the genus rank, 20 new genera were added, two were deleted, one was moved, and three were renamed. At the species rank, 160 species were added, four were deleted, ten were moved and renamed, and 30 species were renamed. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

BackgroundMany ecologically important plants are pollinated or have their seeds dispersed by fruit bats, including the widely distributed African straw-colored fruit bats (Eidolon helvum). Their ability to fly long distances makes them essential for connecting plant populations across fragmented landscapes. While bats have been implicated as a reservoir of infectious diseases, their role in disease transmission to humans is not well understood. In this pilot study, we tracked E. helvum to shed light on their movement patterns in Tanzania and possible contact with other species.MethodsTracking devices were deployed on 25 bats captured in the Morogoro Municipal and Kilombero District area near the Udzungwa Mountains of Tanzania. Nightly flight patterns, areas corresponding to foraging bouts and feeding roosts, and new day roosts were determined from bat movement data and characterized according to their proximity to urban built-up and protected areas. Sites for additional environmental surveillance using camera traps were identified via tracking data to determine species coming in contact with fruits discarded by bats.ResultsTracking data revealed variability between individual bat movements and a fidelity to foraging areas. Bats were tracked from one to six nights, with a mean cumulative nightly flight distance of 26.14 km (min: 0.33, max: 97.57) based on data from high-resolution GPS tags. While the majority of their foraging locations were in or near urban areas, bats also foraged in protected areas, of which the Udzungwa Mountains National Park was the most frequented. Camera traps in fruit orchards frequented by tracked bats showed the presence of multiple species of wildlife, with vervet monkeys (Chlorocebus pygerythrus) observed as directly handling and eating fruit discarded by bats.ConclusionsBecause we observed multiple interactions of animals with fruits discarded by bats, specifically with vervet monkeys, the possibility of disease spillover risk exists via this indirect pathway. With flight distances of up to 97 km, however, the role of E. helvum in the seed dispersal of plants across both protected and urban built-up areas in Tanzania may be even more important, especially by helping connect increasingly fragmented landscapes during this Anthropocene epoch.

In endemic African areas, such as Tanzania, Brucella spp. cause human febrile illnesses, which often go unrecognized and misdiagnosed, resulting in delayed diagnosis, underdiagnosis, and underreporting. Although rapid and affordable point-of-care tests, such as the Rose Bengal test (RBT), are available, acceptance and adoption of these tests at the national level are hindered by a lack of local diagnostic performance data. To address this need, evidence on the diagnostic performance of RBT as a human brucellosis point-of-care test was reviewed. The review was initially focused on studies conducted in Tanzania but was later extended to worldwide because few relevant studies from Tanzania were identified. Databases including Web of Science, Embase, MEDLINE, and World Health Organization Global Index Medicus were searched for studies assessing the diagnostic performance of RBT (sensitivity and specificity) for detection of human brucellosis, in comparison to the reference standard culture. Sixteen eligible studies were identified and reviewed following screening. The diagnostic sensitivity (DSe) and specificity (DSp) of RBT compared to culture as the gold standard were 87.5% and 100%, respectively, in studies that used suitable "true positive" and "true negative" patient comparison groups and were considered to be of high scientific quality. Diagnostic DSe and DSp of RBT compared to culture in studies that also used suitable "true positive" and "true negative" patient comparison groups but were considered to be of moderate scientific quality varied from 92.5% to 100% and 94.3 to 99.9%, respectively. The good diagnostic performance of RBT combined with its simplicity, quickness, and affordability makes RBT an ideal (or close to) stand-alone point-of-care test for early clinical diagnosis and management of human brucellosis and nonmalarial fevers in small and understaffed health facilities and laboratories in endemic areas in Africa and elsewhere.

Marburg virus (MARV) causes sporadic outbreaks of severe Marburg virus disease (MVD). Most MVD outbreaks originated in East Africa and field studies in East Africa, South Africa, Zambia, and Gabon identified the Egyptian rousette bat (ERB; Rousettus aegyptiacus) as a natural reservoir. However, the largest recorded MVD outbreak with the highest case-fatality ratio happened in 2005 in Angola, where direct spillover from bats was not  shown. Here, collaborative studies by the Centers for Disease Control and Prevention, Njala University, University of California, Davis USAID-PREDICT, and the University of Makeni identify MARV circulating in ERBs in Sierra Leone. PCR, antibody and virus isolation data from 1755 bats of 42 species shows active MARV infection in approximately 2.5% of ERBs. Phylogenetic analysis identifies MARVs that are similar to the Angola strain. These results provide evidence of MARV circulation in West Africa and demonstrate the value of pathogen surveillance to identify previously undetected threats.

In the version of this Article originally published, the bat species for 12 individuals were incorrectly identified in Supplementary Table 1 and 2. After resequencing the MT-CytB and MT-CO1 segments and reviewing the data, the authors have corrected the errors for these 12 animals. In the amended version of the Supplementary Information, Supplementary Tables 1 and 2 have been replaced to include the corrected host species information. None of the 12 bats affected were positive for the Bombali virus, and the conclusions of the study are therefore unchanged.

Here we describe the complete genome of a new ebolavirus, Bombali virus (BOMV) detected in free-tailed bats in Sierra Leone (little free-tailed (Chaerephon pumilus) and Angolan free-tailed (Mops condylurus)). The bats were found roosting inside houses, indicating the potential for human transmission. We show that the viral glycoprotein can mediate entry into human cells. However, further studies are required to investigate whether exposure has actually occurred or if BOMV is pathogenic in humans.