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BackgroundOne Health is defined as an integrated, unifying approach that aims to sustainably balance and optimize the health of people, animals and ecosystems; this approach attracts stakeholders from multiple sectors, academic disciplines, and professional practices. The diversity of expertise and interest groups is frequently and simultaneously framed as (1) a strength of the One Health approach in the process of understanding and solving complex problems associated with health challenges such as pathogen spillovers and pandemics and (2) a challenge regarding consensus on essential functions of One Health and the sets of knowledge, skills, and perspectives unique to a workforce adopting this approach. Progress in developing competency-based training in One Health has revealed coverage of various topics across fundamental, technical, functional, and integrative domains. Ensuring that employers value the unique characteristics of personnel trained in One Health will likely require demonstration of its usefulness, accreditation, and continuing professional development. These needs led to the conceptual framework of a One Health Workforce Academy (OHWA) for use as a platform to deliver competency-based training and assessment for an accreditable credential in One Health and opportunities for continuing professional development.MethodsTo gather information about the desirability of an OHWA, we conducted a survey of One Health stakeholders. The IRB-approved research protocol used an online tool to collect individual responses to the survey questions. Potential respondents were recruited from partners of One Health University Networks in Africa and Southeast Asia and international respondents outside of these networks. Survey questions collected demographic information, measured existing or projected demand and the relative importance of One Health competencies, and determined the potential benefits and barriers of earning a credential. Respondents were not compensated for participation.ResultsRespondents (N = 231) from 24 countries reported differences in their perspectives on the relative importance of competency domains of the One Health approach. More than 90% of the respondents would seek to acquire a competency-based certificate in One Health, and 60% of respondents expected that earning such a credential would be rewarded by employers. Among potential barriers, time and funding were the most cited.ConclusionThis study showed strong support from potential stakeholders for a OHWA that hosts competency-based training with opportunities for certification and continuing professional development.

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.

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.

The straw-colored fruit bat (Eidolon helvum) is a pteropodid whose conservation is crucial for maintaining functional connectivity of plant populations in tropical Africa. Land conversion has pushed this species to adapt to roosting in urban centers across its range. These colonies often host millions of individuals, creating intensive human-bat contact interfaces that could facilitate the spillover of coronaviruses shed by these bats. A better understanding of coronavirus dynamics in these roosts is needed to identify peak times of exposure risk in order to propose evidence-based management that supports safe human-bat coexistence, as well as the conservation of this chiropteran. We studied the temporal patterns of coronavirus shedding in E. helvum, by testing thousands of longitudinally-collected fecal samples from two spatially distant urban roosts in Ghana and Tanzania. Shedding of coronaviruses peaked during the second part of pup weaning in both roosts. Assuming that coronavirus shedding is directly related to spillover risk, our results indicate that exposure mitigation should target reducing contact between people and E. helvum roosts during the pup "weaning" period. This recommendation can be applied across the many highly-populated urban sites occupied by E. helvum across Africa.

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development's (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security.

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.

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.

BackgroundBats provide important ecosystem services; however, current evidence supports that they host several zoonotic viruses, including species of the Coronaviridae family. If bats in close interaction with humans host and shed coronaviruses with zoonotic potential, such as the Severe Acute Respiratory Syndrome virus, spillover may occur. Therefore, strategies aiming to mitigate potential spillover and disease emergence, while supporting the conservation of bats and their important ecological roles are needed. Past research suggests that coronavirus shedding in bats varies seasonally following their reproductive cycle; however, shedding dynamics have been assessed in only a few species, which does not allow for generalization of findings across bat taxa and geographic regions.MethodsTo assess the generalizability of coronavirus shedding seasonality, we sampled hundreds of bats belonging to several species with different life history traits across East Africa at different times of the year. We assessed, via Bayesian modeling, the hypothesis that chiropterans, across species and spatial domains, experience seasonal trends in coronavirus shedding as a function of the reproductive cycle.ResultsWe found that, beyond spatial, taxonomic, and life history differences, coronavirus shedding is more expected when pups are becoming independent from the dam and that juvenile bats are prone to shed these viruses.ConclusionsThese findings could guide policy aimed at the prevention of spillover in limited-resource settings, where longitudinal surveillance is not feasible, by identifying high-risk periods for coronavirus shedding. In these periods, contact with bats should be avoided (for example, by impeding or forbidding people access to caves). Our proposed strategy provides an alternative to culling - an ethically questionable practice that may result in higher pathogen levels - and supports the conservation of bats and the delivery of their key ecosystem services.

Recurring outbreaks of emerging and re-emerging zoonoses, such as Ebola virus disease, avian influenza, and Nipah virus, serve as a reminder that the health of humans, animals, and the environment are interconnected and that early response to emerging zoonotic pathogens requires a coordinated, interdisciplinary, cross-sectoral approach. As our world becomes increasingly connected, emerging diseases pose a greater threat, requiring coordination at local, regional, and global levels. One Health is a multisectoral, transdisciplinary, and collaborative approach promoted to more effectively address these complex health threats. Despite strong advocacy for One Health, challenges for practical implementation remain. Here we discuss the value of the One Health approach for addressing global health challenges. We also share strategies applied to achieve successful outcomes through the USAID Emerging Pandemic Threats Program PREDICT project, which serve as useful case studies for implementing One Health approaches. Lastly, we explore methods for promoting more formal One Health implementation to capitalize on the added value of shared knowledge and leveraged resources.

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.

In Nepal, rapid urbanization and rural-to-urban migration especially due to internal civil conflict have catalyzed the development of temporary settlements, often along rivers on undeveloped land. This study conducted surveillance for viruses in small mammals and assessed potential risks for virus transmission to people in urban settlements along rivers in Kathmandu, Nepal. We collected samples from 411 small mammals (100 rodents and 311 shrews) at four riverside settlement sites and detected six viruses from four virus families including Thottapalayam virus; a strain of murine coronavirus; two new paramyxoviruses; and two new rhabdoviruses. Additionally, we conducted surveys of 264 residents to characterize animal-human contact. Forty-eight percent of individuals reported contact with wildlife, primarily with rodents and shrews (91%). Our findings confirm that rodents and shrews should be considered a health threat for residents of temporary settlements, and that assessment of disease transmission risk coupled with targeted surveillance for emerging pathogens could lead to improved disease control and health security for urban populations. Additionally, interventions focused on disease prevention should consider the unique urban ecology and social dynamics in temporary settlements, along with the importance of community engagement for identifying solutions that address specific multi-dimensional challenges that life on the urban river margins presents.

Free-ranging nonhuman primates are frequent sources of zoonotic pathogens due to their physiologic similarity and in many tropical regions, close contact with humans. Many high-risk disease transmission interfaces have not been monitored for zoonotic pathogens due to difficulties inherent to invasive sampling of free-ranging wildlife. Non-invasive surveillance of nonhuman primates for pathogens with high potential for spillover into humans is therefore critical for understanding disease ecology of existing zoonotic pathogen burdens and identifying communities where zoonotic diseases are likely to emerge in the future. We developed a non-invasive oral sampling technique using ropes distributed to nonhuman primates to target viruses shed in the oral cavity, which through bite wounds and discarded food, could be transmitted to people. Optimization was performed by testing paired rope and oral swabs from laboratory colony rhesus macaques for rhesus cytomegalovirus (RhCMV) and simian foamy virus (SFV) and implementing the technique with free-ranging terrestrial and arboreal nonhuman primate species in Uganda and Nepal. Both ubiquitous DNA and RNA viruses, RhCMV and SFV, were detected in oral samples collected from ropes distributed to laboratory colony macaques and SFV was detected in free-ranging macaques and olive baboons. Our study describes a technique that can be used for disease surveillance in free-ranging nonhuman primates and, potentially, other wildlife species when invasive sampling techniques may not be feasible.

Digital disease detection tools are technologically sophisticated, but dependent on digital information, which for many areas suffering from high disease burdens is simply not an option. In areas where news is often reported in local media with no digital counterpart, integration of local news information with digital surveillance systems, such as HealthMap (Boston Children's Hospital), is critical. Little research has been published in regards to the specific contribution of local health-related articles to digital surveillance systems. In response, the USAID PREDICT project implemented a local media surveillance (LMS) pilot study in partner countries to monitor disease events reported in print media. This research assessed the potential of LMS to enhance digital surveillance reach in five low- and middle-income countries. Over 16 weeks, select surveillance system attributes of LMS, such as simplicity, flexibility, acceptability, timeliness, and stability were evaluated to identify strengths and weaknesses in the surveillance method. Findings revealed that LMS filled gaps in digital surveillance network coverage by contributing valuable localized information on disease events to the global HealthMap database. A total of 87 health events were reported through the LMS pilot in the 16-week monitoring period, including 71 unique reports not found by the HealthMap digital detection tool. Furthermore, HealthMap identified an additional 236 health events outside of LMS. It was also observed that belief in the importance of the project and proper source selection from the participants was crucial to the success of this method. The timely identification of disease outbreaks near points of emergence and the recognition of risk factors associated with disease occurrence continue to be important components of any comprehensive surveillance system for monitoring disease activity across populations. The LMS method, with its minimal resource commitment, could be one tool used to address the information gaps seen in global 'hot spot' regions.

Digital disease detection tools are technologically sophisticated, but dependent on digital information, which for many areas suffering from high disease burdens is simply not an option. In areas where news is often reported in local media with no digital counterpart, integration of local news information with digital surveillance systems, such as HealthMap (Boston Children’s Hospital), is critical. Little research has been published in regards to the specific contribution of local health-related articles to digital surveillance systems. In response, the USAID PREDICT project implemented a local media surveillance (LMS) pilot study in partner countries to monitor disease events reported in print media. This research assessed the potential of LMS to enhance digital surveillance reach in five low- and middle-income countries. Over 16 weeks, select surveillance system attributes of LMS, such as simplicity, flexibility, acceptability, timeliness, and stability were evaluated to identify strengths and weaknesses in the surveillance method. Findings revealed that LMS filled gaps in digital surveillance network coverage by contributing valuable localized information on disease events to the global HealthMap database. A total of 87 health events were reported through the LMS pilot in the 16-week monitoring period, including 71 unique reports not found by the HealthMap digital detection tool. Furthermore, HealthMap identified an additional 236 health events outside of LMS. It was also observed that belief in the importance of the project and proper source selection from the participants was crucial to the success of this method. The timely identification of disease outbreaks near points of emergence and the recognition of risk factors associated with disease occurrence continue to be important components of any comprehensive surveillance system for monitoring disease activity across populations. The LMS method, with its minimal resource commitment, could be one tool used to address the information gaps seen in global ‘hot spot’ regions.