Ecological countermeasures to prevent pathogen spillover and subsequent pandemics.

Substantial global attention is focused on how to reduce the risk of future pandemics. Reducing this risk requires investment in prevention, preparedness, and response. Although preparedness and response have received significant focus, prevention, especially the prevention of zoonotic spillover, remains largely absent from global conversations. This oversight is due in part to the lack of a clear definition of prevention and lack of guidance on how to achieve it. To address this gap, we elucidate the mechanisms linking environmental change and zoonotic spillover using spillover of viruses from bats as a case study. We identify ecological interventions that can disrupt these spillover mechanisms and propose policy frameworks for their implementation. Recognizing that pandemics originate in ecological systems, we advocate for integrating ecological approaches alongside biomedical approaches in a comprehensive and balanced pandemic prevention strategy.

Producing context specific land cover and land use maps of human-modified tropical forest landscapes for infectious disease applications.

Satellite-based land cover mapping plays an important role in understanding changes in ecosystems and biodiversity. There are global land cover products available, however for region specific studies of drivers of infectious disease patterns, these can lack the spatial and thematic detail or accuracy required to capture key ecological processes. To overcome this, we produced our own Landsat derived 30 m maps for three districts in India's Western Ghats (Wayanad, Shivamogga and Sindhudurg). The maps locate natural vegetation types, plantation types, agricultural areas, water bodies and settlements in the landscape, all relevant to functional resource use of species involved in infectious disease dynamics. The maps represent the mode of 50 classification iterations and include a spatial measure of class stability derived from these iterations. Overall accuracies for Wayanad, Shivamogga and Sindhudurg are 94.7 % (SE 1.2 %), 88.9 % (SE 1.2 %) and 88.8 % (SE 2 %) respectively. Class classification stability was high across all three districts and the individual classes that matter for defining key interfaces between human habitation, forests, crop, and plantation cultivation, were generally well separated. A comparison with the 300 m global ESA CCI land cover map highlights lower ESA CCI class accuracies and the importance of increased spatial resolution when dealing with complex landscape mosaics. A comparison with the 30 m Global Forest Change product reveals an accurate mapping of forest loss and different dynamics between districts (i.e., Forests lost to Built-up versus Forests lost to Plantations), demonstrating an interesting complementarity between our maps and the % tree cover Global Forest Change product. When studying infectious disease responses to land use change in tropical forest ecosystems, we recommend using bespoke land cover/use classifications reflecting functional resource use by relevant vectors, reservoirs, and people. Alternatively, global products should be carefully validated with ground reference points representing locally relevant habitats.

Citizen science facilitates first ever genetic detection of wolf-dog hybridization in Indian savannahs.

Human demographic expansion has confined wildlife to fragmented habitats, often in proximity to human-modified landscapes. Such interfaces facilitate increased interactions between feral or domesticated animals and wildlife, posing a high risk to wild species. This is especially relevant for free-ranging dogs (Canis lupus familiaris) and wild canids like gray wolves (Canis lupus) and golden jackals (Canis aureus). Wolf-dog hybridization may lead to a significant reduction of specific adaptations in wolves that could result in the decline of wolf populations. Detection and genetic discrimination of hybrids between dogs and wolves are challenging because of their complex demographic history and close ancestry. Citizen scientists identified two phenotypically different-looking individuals and subsequently collected non-invasive samples that were used by geneticists to test wolf-dog hybridization. Genomic data from shed hair samples of suspected hybrid individuals using double-digest restriction-site-associated DNA (ddRAD) sequencing resulted in 698 single nucleotide polymorphism (SNP) markers. We investigated the genetic origin of these two individuals analyzed with genetically known dogs, wolves, and other canid species including jackals and dholes (Cuon alpinus). Our results provide the first genetic evidence of one F2 hybrid and the other individual could be a complex hybrid between dogs and wolves. Our results re-iterate the power of next-generation sequencing (NGS) for non-invasive samples as an efficient tool for detecting hybrids. Our results suggest the need for more robust monitoring of wolf populations and highlight the tremendous potential for collaborative approaches between citizens and conservation scientists to detect and monitor threats to biodiversity.

Animal movement ecology in India: insights from 2011-2021 and prospective for the future.

The field of animal movement ecology has advanced by leaps and bounds in the past few decades with the advent of sophisticated technology, advanced analytical tools, and multiple frameworks and paradigms to address key ecological problems. Unlike the longer history and faster growth of the field in North America, Europe, and Africa, movement ecology in Asia has only recently been gaining momentum. Here, we provide a review of the field from studies based in India over the last 11 years (2011-2021) curated from the database, Scopus, and search engine, Google Scholar. We identify current directions in the research objectives, taxa studied, tracking technology and the biogeographic regions in which animals were tracked, considering the years since the last systematic review of movement ecology research in the country. As an indication of the growing interest in this field, there has been a rapid increase in the number of publications over the last decade. Class Mammalia continues to dominate the taxa tracked, with tiger and leopard being the most common species studied across publications. Invertebrates and other small and medium-sized animals, as well as aquatic animals, in comparison, are understudied and remain among the important target taxa for tracking in future studies. As in the previous three decades, researchers have focussed on characterising home ranges and habitat use of animals. There is, however, a notable shift to examine the movement decision of animals in human-modified landscapes, although efforts to use movement ecology to understand impacts of climate change remain missing. Given the biogeographic and taxonomic diversity of India, and the fact that the interface between anthropogenic activity and wildlife interactions is increasing, we suggest ways in which the field of movement ecology can be expanded to facilitate ecological insights and conservation efforts. With the advancement of affordable technologies and the availability of analytical tools, the potential to expand the field of movement ecology, shift research foci, and gain new insights is now prime.

Seasonal range fidelity of a megaherbivore in response to environmental change.

For large herbivores living in highly dynamic environments, maintaining range fidelity has the potential to facilitate the exploitation of predictable resources while minimising energy expenditure. We evaluate this expectation by examining how the seasonal range fidelity of African elephants (Loxodonta africana) in the Kruger National Park, South Africa is affected by spatiotemporal variation in environmental conditions (vegetation quality, temperature, rainfall, and fire). Eight-years of GPS collar data were used to analyse the similarity in seasonal utilisation distributions for thirteen family groups. Elephants exhibited remarkable consistency in their seasonal range fidelity across the study with rainfall emerging as a key driver of space-use. Within years, high range fidelity from summer to autumn and from autumn to winter was driven by increased rainfall and the retention of high-quality vegetation. Across years, sequential autumn seasons demonstrated the lowest levels of range fidelity due to inter-annual variability in the wet to dry season transition, resulting in unpredictable resource availability. Understanding seasonal space use is important for determining the effects of future variability in environmental conditions on elephant populations, particularly when it comes to management interventions. Indeed, over the coming decades climate change is predicted to drive greater variability in rainfall and elevated temperatures in African savanna ecosystems. The impacts of climate change also present particular challenges for elephants living in fragmented or human-transformed habitats where the opportunity for seasonal range shifts are greatly constrained.

Environmental surveillance of antimicrobial resistance in a rapidly developing catchment.

Development and spread of AMR from various sources such as hospitals, pharmaceutical industries, animal farms and human habitations is not well understood. We conducted a pilot study to assess the prevalence of AMR by taking a case of rapidly developing catchment in Western India. For this, we selected four sub-catchments/regions with a dominant source of antibiotics, viz. areas with (a) dense poultry farms (4 farms/km2), (b) sparse number of poultry farms (2 farms/km2), (c) agricultural fields and (d) habitation (village). The environmental samples (soil, litter and water) were subjected to Kirby-Bauer/antibiotic disc susceptibility test to assess the resistance pattern in the bacterial species. Preliminary investigations showed the presence of seven multidrug-resistant bacterial species in the litter from poultry farms, with five species having a MAR index greater than 0.2. No evidence of AMR was observed in the vicinity (water and soil) of the poultry farms. This could be attributed to the rigorous disinfection protocols followed at the poultry farms to prevent infection in the fresh batch of chickens. However, in agricultural fields where the litter is used as manure, seven multiple drugs resistant with two species scoring a MAR index greater than 0.2 were observed. MAR index of less than 0.2 was observed for Escherichia coli and Enterobacter species isolated from village and control site (soil), respectively, indicating negligible contamination by antibiotics at sub-catchments. This study provides an approach to investigate the effects of multiple factors on the prevalence of AMR at the catchment scale.

Where Rabies Is Not a Disease. Bridging Healthworlds to Improve Mutual Understanding and Prevention of Rabies.

Deeply embedded in local social, cultural, and religious settings, traditional healing is part of dog bite and rabies management in many rabies endemic countries. Faith healing, which usually encompasses a more holistic approach to health including physical, mental and social dimensions, is rare in the context of rabies. In Gujarat, Western India, the Hindu goddess Hadkai Mata is worshiped by low-caste communities as the Mother of Rabies in the event of a dog bite to a person or their livestock. This belief might influence people's attitudes and behaviors toward rabies prevention but has never been investigated. Through 31 in-depth interviews with healers and staff of Hadkai Mata temples, this paper explores the system of knowledge around dog and human rabies that is built and shared in these places of worship and healing. Qualitative and quantitative data were analyzed looking for convergences and divergences with the recently launched National Action Plan for dog-mediated Rabies Elimination. Results suggest that while the etiology of human rabies as a social illness is usually explained as the goddess's wish to correct misbehaving people and restore positive interpersonal relations, there is some appreciation for the biological processes of infection that lead to rabies as a physical disease. Hadkai Mata is believed to cure rabies if her patients undergo the necessary process of moral growth. Although conventional post-exposure prophylaxis is not opposed per se, it is often delayed by patients who seek traditional treatment first. Some reluctance was expressed toward mass dog vaccination because it is seen as an interference in how the goddess controls dogs, by enraging them-hence infecting them with rabies-and sending them to bite wrongdoers. Addressing these cultural perceptions is likely to be critical in achieving effective control of dog rabies in this region. The study highlights the value of multidisciplinary approaches in the control and elimination of rabies, as well as other zoonoses. This includes the importance of understanding different culturally- and religiously- mediated ways in which humans relate to animals; and looking for points of convergence and mutual understanding, upon which context-tailored, linguistically-accurate, locally acceptable, feasible and effective strategies can be designed.

Genome Sequences of Five Indian Canine Rabies Virus Isolates Obtained Using Oxford Nanopore Technologies Sequencing.

We report five canine rabies virus genome sequences from India that were obtained from brain samples using Oxford Nanopore Technologies sequencing. The sequences will facilitate understanding of the evolution and transmission of rabies.

A Comparative Evaluation of the Estimation of Rabies Virus Antibodies among Free-Roaming, Vaccinated Dogs in Bengaluru, India.

Vaccination is the practical solution for the prevention of rabies in dogs. Assessment of the immunogenicity of vaccination includes estimation of specific rabies virus neutralizing antibodies (VNA) in the target species. We undertook a study to estimate the levels of VNA in free-roaming dogs with a history of rabies vaccination in Bengaluru city, India. We compared the rapid fluorescent focus inhibition test (RFFIT) and an in-house quantitative indirect ELISA (iELISA). The study area comprised the jurisdiction of Bruhat Bengaluru Mahanagara Palike (BBMP), the Bengaluru civic body. The BBMP, along with several non-government organizations (NGO), were conducting a trap- neuter- vaccinate- release program for the prevention of dog rabies. Serum samples were collected from 250 free-roaming dogs from representative regions of BBMP, of which 125 had a VNA titre of 0.5 IU or more by the RFFIT. Furthermore, 126 dogs showed percent positivity values (PP values) more than the cut off PP value of 57.1 by the iELISA, accounting for 50.4% of satisfactory post-vaccinal serum conversion. The sensitivity and specificity of the iELISA was 94.4% and 95.2%, respectively. Based on these data, a quantitative iELISA may be a complementary tool for sero-monitoring immune responses of free-ranging animals after rabies vaccination.

Co-production of knowledge as part of a OneHealth approach to better control zoonotic diseases.

There is increased global and national attention on the need for effective strategies to control zoonotic diseases. Quick, effective action is, however, hampered by poor evidence-bases and limited coordination between stakeholders from relevant sectors such as public and animal health, wildlife and forestry sectors at different scales, who may not usually work together. The OneHealth approach recognises the value of cross-sectoral evaluation of human, animal and environmental health questions in an integrated, holistic and transdisciplinary manner to reduce disease impacts and/or mitigate risks. Co-production of knowledge is also widely advocated to improve the quality and acceptability of decision-making across sectors and may be particularly important when it comes to zoonoses. This paper brings together OneHealth and knowledge co-production and reflects on lessons learned for future OneHealth co-production processes by describing a process implemented to understand spill-over and identify disease control and mitigation strategies for a zoonotic disease in Southern India (Kyasanur Forest Disease). The co-production process aimed to develop a joint decision-support tool with stakeholders, and we complemented our approach with a simple retrospective theory of change on researcher expectations of the system-level outcomes of the co-production process. Our results highlight that while co-production in OneHealth is a difficult and resource intensive process, requiring regular iterative adjustments and flexibility, the beneficial outcomes justify its adoption. A key future aim should be to improve and evaluate the degree of inter-sectoral collaboration required to achieve the aims of OneHealth. We conclude by providing guidelines based on our experience to help funders and decision-makers support future co-production processes.

'Stray appetites': a socio-ecological analysis of free-ranging dogs living alongside human communities in Bangalore, India.

Across the developing world, humans and free-ranging domestic dogs share common spaces. The relationship between these dogs and humans can range from one of dependence, to apathy, to conflict. Given the high number of humans attacked by dogs every year in India, and the lack of an effective population control strategy, we seek to provide insights into the conflict and propose alternative population management options based on reducing the carrying capacity of the environment. We used a mixed methods approach to understand both ecological and sociological underpinnings of free-ranging dog-human relationships in Bangalore, India. We conducted a photographic capture-recapture survey of free-ranging dogs to estimate population size and linked it to the availability of potential food sources. We also conducted a qualitative survey to assess attitudes of residents towards the dog population. We found that dog population varied from 192 to 1888 per square kilometre across a gradient of housing densities. The density of houses, bakeries and garbage piles were significant predictors of dog population size. Crucially, as low as 10 to 18% of houses supported the large population of dogs, highlighting the need for residents to act responsibly towards the dogs. Further, we found that garbage, although significant, is a secondary food source to household-maintained dogs. Since on the whole, respondents expressed the desire for a reduction in dog population, we suggest decreasing the carrying capacity of the environment by targeting these three food sources. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11252-021-01097-4.

Reviewing the ecological evidence base for management of emerging tropical zoonoses: Kyasanur Forest Disease in India as a case study.

Zoonoses disproportionately affect tropical communities and are associated with human modification and use of ecosystems. Effective management is hampered by poor ecological understanding of disease transmission and often focuses on human vaccination or treatment. Better ecological understanding of multi-vector and multi-host transmission, social and environmental factors altering human exposure, might enable a broader suite of management options. Options may include "ecological interventions" that target vectors or hosts and require good knowledge of underlying transmission processes, which may be more effective, economical, and long lasting than conventional approaches. New frameworks identify the hierarchical series of barriers that a pathogen needs to overcome before human spillover occurs and demonstrate how ecological interventions may strengthen these barriers and complement human-focused disease control. We extend these frameworks for vector-borne zoonoses, focusing on Kyasanur Forest Disease Virus (KFDV), a tick-borne, neglected zoonosis affecting poor forest communities in India, involving complex communities of tick and host species. We identify the hierarchical barriers to pathogen transmission targeted by existing management. We show that existing interventions mainly focus on human barriers (via personal protection and vaccination) or at barriers relating to Kyasanur Forest Disease (KFD) vectors (tick control on cattle and at the sites of host (monkey) deaths). We review the validity of existing management guidance for KFD through literature review and interviews with disease managers. Efficacy of interventions was difficult to quantify due to poor empirical understanding of KFDV-vector-host ecology, particularly the role of cattle and monkeys in the disease transmission cycle. Cattle are hypothesised to amplify tick populations. Monkeys may act as sentinels of human infection or are hypothesised to act as amplifying hosts for KFDV, but the spatial scale of risk arising from ticks infected via monkeys versus small mammal reservoirs is unclear. We identified 19 urgent research priorities for refinement of current management strategies or development of ecological interventions targeting vectors and host barriers to prevent disease spillover in the future.

Modelling the challenges of managing free-ranging dog populations.

Free-ranging domestic dogs (FRD) are not only vectors of zoonoses of public health concern, but also pose direct threats to humans, livestock, and endangered wildlife. Many developing countries have struggled to control FRD, despite using both lethal and non-lethal methods. India has amongst the highest FRD populations globally and the highest incidences of dog-mediated human rabies, but only deploys Catch-Neuter-Vaccinate-Release (CNVR) for FRD control as a humane alternative to lethal methods, without evidence of it working successfully. Here, we use an agent-based dog population dynamics model to examine the time, effort, financial resources, and conditions needed to successfully control FRD in a typical urban setting. We simulate several scenarios, from an "ideal world" closed population with easily accessible dogs, to a more realistic open population with heterogeneity in catchability of dogs. In only one "best-case" scenario, CNVR resulted in a significant and lasting reduction in FRD, but with vaccination rates peaking only at 35%, which is half the WHO-recommended coverage. The customisable and portable modelling tool that we have developed allows managers to simulate real world processes and understand the expected effort needed to reduce regional dog populations, and assess methods for achieving effective anti-rabies vaccination coverage.

Rabies as a Public Health Concern in India-A Historical Perspective.

India bears the highest burden of global dog-mediated human rabies deaths. Despite this, rabies is not notifiable in India and continues to be underprioritised in public health discussions. This review examines the historical treatment of rabies in British India, a disease which has received relatively less attention in the literature on Indian medical history. Human and animal rabies was widespread in British India, and treatment of bite victims imposed a major financial burden on the colonial Government of India. It subsequently became a driver of Pasteurism in India and globally and a key component of British colonial scientific enterprise. Efforts to combat rabies led to the establishment of a wide network of research institutes in India and important breakthroughs in development of rabies vaccines. As a result of these efforts, rabies no longer posed a significant threat to the British, and it declined in administrative and public health priorities in India towards the end of colonial rule-a decline that has yet to be reversed in modern-day India. The review also highlights features of the administrative, scientific and societal approaches to dealing with this disease in British India that persist to this day.

Artificial Intelligence and One Health: Knowledge Bases for Causal Modeling.

Scientists all over the world are moving toward building database systems based on the One Health concept to prevent and manage outbreaks of zoonotic diseases. An appreciation of the process of discovery with incomplete information and a recognition of the role of observations gathered painstakingly by scientists in the field shows that simple databases will not be sufficient to build causal models of the complex relationships between human health and ecosystems. Rather, it is important also to build knowledge bases which complement databases using non-monotonic logic based artificial intelligence techniques, so that causal models can be improved as new, and sometimes contradictory, information is found from field studies.

Health Heatmap of India: An Open Data Platform.

Health Heatmap of India is an open data platform built for bringing together data from diverse sources and facilitating visualization, analysis, and insight building from such data. In this paper, we describe the context and need for such an open data platform and describe the technical aspects of building it. The beta site of the portal is available at https://healthheatmapindia.org.

Predicting disease risk areas through co-production of spatial models: The example of Kyasanur Forest Disease in India's forest landscapes.

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global "One Health" initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014-2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014-2018). Consistent with suggestions that KFD is an "ecotonal" disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings.

Author Correction: Demographic characteristics of free-roaming dogs (FRD) in rural and urban India following a photographic sight-resight survey.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.