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

‘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 sur

Animal Perception of Seasonal Thresholds: Changes in Elephant Movement in Relation to Rainfall Patterns

Background: The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal\u2019s behaviour, which contributes to an understanding of species\u2019 responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana), in relation to local and regional rainfall patterns. Methodology/Principal Findings: We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007\u20132009). Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. Conclusions/Significance: By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal\u2019s perspective, for delineating seasons or other extrinsic shifts in ecological studies, rather than arbitrarily fixed definitions based on convention or common practice

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

What is the state of the art on traditional medicine interventions for zoonotic diseases in the Indian subcontinent? A scoping review of the peer-reviewed evidence base

•Background: Traditional medicine (TM) interventions are plausible therapeutic alternatives to conventional medical interventions against emerging and endemic zoonotic diseases, particularly in low-and middle-income countries that may lack resources and infrastructure. Despite the growing popularity in the usage of TM interventions, their clinical safety and effectiveness are still contested within conventional healthcare in many countries. •Methods: We conducted a scoping review of the peer-reviewed literature that synthesises and maps the evidence on TM interventions for the treatment and prevention of zoonoses on the Indian subcontinent. The region, a global hotspot of biodiversity and emerging infections, is characterised by high prevalence of TM use. Based on the scientific literature (mostly case study research, n=l06 studies), our review (1) maps the scope of the literature, (2) synthesises the evidence on the application of TM interventions for zoonoses, and (3) critically reflects on the state of TM and identifies areas for future research focus. •Results: The evidence synthesis confirmed widespread usage of TM interventions for zoonoses on the subcontinent, with the majority of research reported from India (n=99 studies, 93.4%), followed by Pakistan (n=3 studies, 2.8%), Bangladesh (n=2 studies, 1.9%), and Sri Lanka (n=1, 0.9%). Most of the reviewed studies reported on ethno-medicinal uses of plant species, primarily for treating dengue (n=20 studies), tuberculosis (n=18 studies), Escherichia coli infection (n=16 studies), lymphatic filariasis and cholera (n=9 apiece). However, the evidence on the safety and effectiveness of these reported TM interventions is limited, indicating that these data are rarely collected and/or shared within the peer-reviewed literature. •Conclusion: This review thus highlights that, whilst TMs are already being used and could offer more widely accessible interventions against emerging and endemic zoonoses and ectoparasites, there is an urgent need for rigorous clinical testing and validation of the safety and effectiveness of these interventions

Hippobosca longipennis - a potential intermediate host of a species of Acanthocheilonema in dogs in northern India

Background Hippobosca longipennis (the 'dog louse fly') is a blood sucking ectoparasite found on wild carnivores such as cheetahs and lions and domesticated and feral dogs in Africa, the Middle East and Asia, including China. Known as an intermediate host for Acanthocheilonema dracunculoides and a transport host for Cheyletiella yasguri, it has also been suggested that H. longipennis may be a vector for other pathogens, including Acanthocheilonema sp.? nov., which was recently reported to infect up to 48% of dogs in northern India where this species of fly is known to commonly infest dogs. To test this hypothesis, hippoboscid flies feeding on dogs in Ladakh in northern India were collected and subjected to microscopic dissection. Results A total of 12 infective larvae were found in 10 out of 65 flies dissected; 9 from the head, 2 from the thorax and 1 from the abdomen. The larvae averaged 2, 900 (± 60) μm in length and 34 (± 5) μm in width and possessed morphological features characteristic of the family Onchocercidae. Genetic analysis and comparison of the 18S, ITS-2, 12S and cox-1 genes confirmed the identity of the larvae as the Acanthocheilonema sp.? nov. reported in dogs in Ladakh. Conclusion This study provides evidence for a potential intermediate host-parasite relationship between H. longipennis and the canine Acanthocheilonema sp.? nov. in northern India

Effects of body size on estimation of mammalian area requirements.

Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied blockcross validation to quantify bias in empirical home range estimates. Area requirements of mammals 1, meaning the scaling of the relationship changedsubstantially at the upper end of the mass spectrum

Uniting statistical and individual-based approaches for animal movement modelling

<div><p>The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.</p></div