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Background: One Health is particularly relevant to the Horn of Africa where many people's livelihoods are highly dependent on livestock and their shared environment. In this context, zoonoses may have a dramatic impact on both human and animal health, but also on country economies. This scoping review aimed to characterise and evaluate the nature of zoonotic disease research in the Horn region. Specifically, it addressed the following questions: (i) what specific zoonotic diseases have been prioritised for research, (ii) what data have been reported (human, animal or environment), (iii) what methods have been applied, and (iv) who has been doing the research?, Methodology/principal Findings: We used keyword combinations to search online databases for peer-reviewed papers and theses. Screening and data extraction (disease, country, domain and method) was performed using DistillerSR. A total of 2055 studies focusing on seven countries and over 60 zoonoses were included. Brucellosis attracted the highest attention in terms of research while anthrax, Q fever and leptospirosis have been comparatively under-studied. Research efforts did not always align with zoonoses priorities identified at national levels. Despite zoonoses being a clear target for 'One Health' research, a very limited proportion of studies report data on the three domains of human, animal and environment. Descriptive and observational epidemiological studies were dominant and only a low proportion of publications were multidisciplinary. Finally, we found that a minority of international collaborations were between Global South countries with a high proportion of authors having affiliations from outside the Horn of Africa., Conclusions/significance: There is a growing interest in zoonoses research in the Horn of Africa. Recommendations arising from this scoping review include: (i) ensuring zoonoses research aligns with national and global research agendas; (ii) encouraging researchers to adopt a holistic, transdisciplinary One Health approach following high quality reporting standards (COHERE, PRISMA, etc.); and (iii) empowering local researchers supported by regional and international partnerships to engage in zoonoses research., Competing Interests: The authors have declared that no competing interests exist.

Diseases that spread to humans from animals, zoonoses, pose major threats to human health. Identifying animal reservoirs of zoonoses and predicting future outbreaks are increasingly important to human health and well-being and economic stability, particularly where research and resources are limited. Here, we integrate complex networks and machine learning approaches to develop a new approach to identifying reservoirs. An exhaustive dataset of mammal-pathogen interactions was transformed into networks where hosts are linked via their shared pathogens. We present a methodology for identifying important and influential hosts in these networks. Ensemble models linking network characteristics with phylogeny and life-history traits are then employed to predict those key hosts and quantify the roles they undertake in pathogen transmission. Our models reveal drivers explaining host importance and demonstrate how these drivers vary by pathogen taxa. Host importance is further integrated into ensemble models to predict reservoirs of zoonoses of various pathogen taxa and quantify the extent of pathogen sharing between humans and mammals. We establish predictors of reservoirs of zoonoses, showcasing host influence to be a key factor in determining these reservoirs. Finally, we provide new insight into the determinants of zoonosis-sharing, and contrast these determinants across major pathogen taxa.

Disease or pathogen risk prioritisations aid understanding of infectious agent impact within surveillance or mitigation and biosecurity work, but take significant development. Previous work has shown the H-(Hirsch-)index as an alternative proxy. We present a weighted risk analysis describing infectious pathogen impact for human health (human pathogens) and well-being (domestic animal pathogens) using an objective, evidence-based, repeatable approach; the H-index. This study established the highest H-index European pathogens. Commonalities amongst pathogens not included in previous surveillance or risk analyses were examined. Differences between host types (humans/animals/zoonotic) in pathogen H-indices were explored as a One Health impact indicator. Finally, the acceptability of the H-index proxy for animal pathogen impact was examined by comparison with other measures. 57 pathogens appeared solely in the top 100 highest H-indices (1) human or (2) animal pathogens list, and 43 occurred in both. Of human pathogens, 66 were zoonotic and 67 were emerging, compared to 67 and 57 for animals. There were statistically significant differences between H-indices for host types (humans, animal, zoonotic), and there was limited evidence that H-indices are a reasonable proxy for animal pathogen impact. This work addresses measures outlined by the European Commission to strengthen climate change resilience and biosecurity for infectious diseases. The results include a quantitative evaluation of infectious pathogen impact, and suggest greater impacts of human-only compared to zoonotic pathogens or scientific under-representation of zoonoses. The outputs separate high and low impact pathogens, and should be combined with other risk assessment methods relying on expert opinion or qualitative data for priority setting, or could be used to prioritise diseases for which formal risk assessments are not possible because of data gaps.

The rate of emergence for emerging infectious diseases has increased dramatically over the last century, and research findings have implicated wildlife as an importance source of novel pathogens. However, the role played by domestic animals as amplifiers of pathogens emerging from the wild could also be significant, influencing the human infectious disease transmission cycle. The impact of domestic hosts on human disease emergence should therefore be ascertained. Here, using three independent datasets we showed positive relationships between the time since domestication of the major domesticated mammals and the total number of parasites or infectious diseases they shared with humans. We used network analysis, to better visualize the overall interactions between humans and domestic animals (and amongst animals) and estimate which hosts are potential sources of parasites/pathogens for humans (and for all other hosts) by investigating the network architecture. We used centrality, a measure of the connection amongst each host species (humans and domestic animals) in the network, through the sharing of parasites/pathogens, where a central host (i.e. high value of centrality) is the one that is infected by many parasites/pathogens that infect many other hosts in the network. We showed that domesticated hosts that were associated a long time ago with humans are also the central ones in the network and those that favor parasites/pathogens transmission not only to humans but also to all other domesticated animals. These results urge further investigation of the diversity and origin of the infectious diseases of domesticated animals in their domestication centres and the dispersal routes associated with human activities. Such work may help us to better understand how domesticated animals have bridged the epidemiological gap between humans and wildlife., (Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.)

Japanese encephalitis (JE) is one of the most well studied arthropod zoonotic diseases with human and animal research and their integration spanning 6-7 decades. JE research and policy in some Asian countries has epitomized the 'One Health' strategy of attainment of optimal health for people, animals, and the environment. However, despite significant mitigation of JE in some Asian countries primarily due to vaccination programs and infrastructural development, JE continues to be a major disease burden in the Asian region. Arthropod-borne zoonotic infections such as JE present some of the greatest challenges to animal and human health globally. Their emergence involves a complex interplay of vectors, hosts, environment, climate, and anthropogenic factors. Therefore, the integrated management of infectious agents that affect both humans and animals is perhaps the most highly coveted strategy that public health policy makers aspire to attain in the twenty-first century. This is in response to the seemingly growing challenges of controlling the burden of emerging infectious diseases such as shrinking financial budgets and resources, increasing demand for public health deliverables, demographic shifts and mobility, global trade economies, and climate and landscape changes. Thus, while JE research and policy is an excellent example of the One Health strategy in action, further work is required to address the obstinate burden of transmission.

Assessment of the relative impact of diseases and pathogens is important for agencies and other organizations charged with providing disease surveillance, management and control. It also helps funders of disease-related research to identify the most important areas for investment. Decisions as to which pathogens or diseases to target are often made using complex risk assessment approaches; however, these usually involve evaluating a large number of hazards as it is rarely feasible to conduct an in-depth appraisal of each. Here we propose the use of the H-index (or Hirsch index) as an alternative rapid, repeatable and objective means of assessing pathogen impact. H-index scores for 1,414 human pathogens were obtained from the Institute for Scientific Information's Web of Science (WOS) in July/August 2010. Scores were compared for zoonotic/non-zoonotic, and emerging/non-emerging pathogens, and across taxonomic groups. H-indices for a subset of pathogens were compared with Disability Adjusted Life Year (DALY) estimates for the diseases they cause. H-indices ranged from 0 to 456, with a median of 11. Emerging pathogens had higher H-indices than non-emerging pathogens. Zoonotic pathogens tended to have higher H-indices than human-only pathogens, although the opposite was observed for viruses. There was a significant correlation between the DALY of a disease and the H-index of the pathogen(s) that cause it. Therefore, scientific interest, as measured by the H-index, appears to be a reflection of the true impact of pathogens. The H-index method can be utilized to set up an objective, repeatable and readily automated system for assessing pathogen or disease impact.

Diseases that spread to humans from animals, zoonoses, pose major threats to human health. Identifying animal reservoirs of zoonoses and predicting future outbreaks are increasingly important to human health and well-being and economic stability, particularly where research and resources are limited. Here, we integrate complex networks and machine learning approaches to develop a new approach to identifying reservoirs. An exhaustive dataset of mammal–pathogen interactions was transformed into networks where hosts are linked via their shared pathogens. We present a methodology for identifying important and influential hosts in these networks. Ensemble models linking network characteristics with phylogeny and life-history traits are then employed to predict those key hosts and quantify the roles they undertake in pathogen transmission. Our models reveal drivers explaining host importance and demonstrate how these drivers vary by pathogen taxa. Host importance is further integrated into ensemble models to predict reservoirs of zoonoses of various pathogen taxa and quantify the extent of pathogen sharing between humans and mammals. We establish predictors of reservoirs of zoonoses, showcasing host influence to be a key factor in determining these reservoirs. Finally, we provide new insight into the determinants of zoonosis-sharing, and contrast these determinants across major pathogen taxa. [ABSTRACT FROM AUTHOR]

During February 2018-January 2019, we conducted large-scale surveillance for the presence and prevalence of tick-borne encephalitis virus (TBEV) and louping ill virus (LIV) in sentinel animals and ticks in the United Kingdom. Serum was collected from 1,309 deer culled across England and Scotland. Overall, 4% of samples were ELISA-positive for the TBEV serocomplex. A focus in the Thetford Forest area had the highest proportion (47.7%) of seropositive samples. Ticks collected from culled deer within seropositive regions were tested for viral RNA; 5 of 2,041 ticks tested positive by LIV/TBEV real-time reverse transcription PCR, all from within the Thetford Forest area. From 1 tick, we identified a full-length genomic sequence of TBEV. Thus, using deer as sentinels revealed a potential TBEV focus in the United Kingdom. This detection of TBEV genomic sequence in UK ticks has important public health implications, especially for undiagnosed encephalitis. [ABSTRACT FROM AUTHOR]