Integrating the landscape epidemiology and genetics of RNA viruses: rabies in domestic dogs as a model

Optimal Control Theory Applied to Rabies Epidemiological Model with Time-dependent Vaccination in Davao City, Mindanao Island, Philippines

Background and Objective

Rabies continues to be a challenge in Davao City despite the efforts of the city's local government to vaccinate primarily the non-stray dog population. Meanwhile, studies have shown that time-dependent vaccination strategy is considered a prime factor for a cost-effective rabies control strategy. Hence, this study aims to provide information that will determine the optimal vaccination strategy targeted to the stray dog population that minimizes the rabies-infected dog population and vaccination costs using optimal control theory (OCT).

Methods

OCT is used to identify the optimal level of key rabies control, i.e., vaccination. Here, OCT was applied to a modified Susceptible-Exposed-Infectious-Vaccinated (SEIV) compartmental model. The study's key parameters were derived from published articles on rabies in Davao City and similar regions, along with the city's rabies reports.

Results

The findings revealed that while rabies remains endemic in the city, it is possible to reduce the number of cases through consistent implementation of vaccination programs to the exposed and susceptible dog populations. Nevertheless, the feasibility of these findings relies to the effective targeting of vaccine coverage for the dog population. From the simulations performed, the exposed dog population (i.e., pre-rabid dogs) was able to reach zero observation when the transmission rate (β) is 0.001 for all values of anti-rabies vaccine coverages for exposed (α) and susceptible (b) dog populations and β = 0.01 only when α = 0.7 and b = 0.7, α = 0.7 and b = 0.5, and α = 0.5 and b = 0.7. Consequently, the number of infectious dogs will thereby decrease. Moreover, a nonlinear correspondence was also observed in all scenarios between the vaccination rate and the number of rabies-exposed dogs such that the reduction in the incidence of rabies cases becomes apparent only when the vaccination rate is at least 0.9995.

Conclusion

In high rabies transmissibility scenarios, a time-dependent vaccination strategy demonstrated a reduction in the number of rabies-infected dogs. However, this approach involves a trade-off, limiting the period during which monthly vaccinations can be relaxed. Consequently, a robust and timely vaccination program for dogs is crucial to manage high rabies transmission rates. Lastly, the model simulation underscores the importance of initiating monthly vaccinations.

Spatial Clustering of Rabies by Animal Species in New Jersey, United States, from 1989 to 2023

Identifying spatial clusters of rabies in animals aids policymakers in allocating resources for rabies prevention and control. This study aimed to investigate spatial patterns and hotspots of rabies in different animal species at the county level in New Jersey. Data on animal rabies cases from January 1989 to December 2023 were obtained from the New Jersey Department of Health and aggregated by county. Global Moran's index (I) statistics were computed for each species to detect global spatial clustering (GeoDa version 1.22). Local Moran's indicators of spatial association (LISA) were computed to identify local clusters of rabies. The results from the LISA analysis were mapped using ArcGIS Pro to pinpoint cluster locations. A total of 9637 rabies cases were analyzed among raccoons (n = 6308), skunks (n = 1225), bats (n = 1072), cats (n = 597), foxes (n = 225), and groundhogs (n = 210). A global Moran's test indicated significant global spatial clustering in raccoons (I = 0.32, p = 0.012), foxes (I = 0.29, p = 0.011), and groundhogs (I = 0.37, p = 0.005). The LISA results revealed significant spatial clustering of rabies in raccoons and foxes in southeastern New Jersey and in groundhogs in northern New Jersey. These findings could guide the development of targeted oral rabies vaccination programs in high-risk New Jersey counties, reducing rabies exposure among domestic animals and humans.

Geographic Distribution of Rabies Virus and Genomic Sequence Alignment of Wild and Vaccine Strains, Kenya

Rabies, a viral disease that causes lethal encephalitis, kills ≈59,000 persons worldwide annually, despite availability of effective countermeasures. Rabies is endemic in Kenya and is mainly transmitted to humans through bites from rabid domestic dogs. We analyzed 164 brain stems collected from rabid animals in western and eastern Kenya and evaluated the phylogenetic relationships of rabies virus (RABV) from the 2 regions. We also analyzed RABV genomes for potential amino acid changes in the vaccine antigenic sites of nucleoprotein and glycoprotein compared with RABV vaccine strains commonly used in Kenya. We found that RABV genomes from eastern Kenya overwhelmingly clustered with the Africa-1b subclade and RABV from western Kenya clustered with Africa-1a. We noted minimal amino acid variances between the wild and vaccine virus strains. These data confirm minimal viral migration between the 2 regions and that rabies endemicity is the result of limited vaccine coverage rather than limited efficacy.

Resource asynchrony and landscape homogenization as drivers of virulence evolution: The case of a directly transmitted disease in a social host

Throughout the last decades, the emergence of zoonotic diseases and the frequency of disease outbreaks have increased substantially, fuelled by habitat encroachment and vectors overlapping with more hosts due to global change. The virulence of pathogens is one key trait for successful invasion. In order to understand how global change drivers such as habitat homogenization and climate change drive pathogen virulence evolution, we adapted an established individual-based model of host-pathogen dynamics. Our model simulates a population of social hosts affected by a directly transmitted evolving pathogen in a dynamic landscape. Pathogen virulence evolution results in multiple strains in the model that differ in their transmission capability and lethality. We represent the effects of global change by simulating environmental changes both in time (resource asynchrony) and space (homogenization). We found an increase in pathogenic virulence and a shift in strain dominance with increasing landscape homogenization. Our model further indicated that lower virulence is dominant in fragmented landscapes, although pulses of highly virulent strains emerged under resource asynchrony. While all landscape scenarios favoured co-occurrence of low- and high-virulent strains, the high-virulence strains capitalized on the possibility for transmission when host density increased and were likely to become dominant. With asynchrony likely to occur more often due to global change, our model showed that a subsequent evolution towards lower virulence could lead to some diseases becoming endemic in their host populations.

Habitat connectivity and host relatedness influence virus spread across an urbanising landscape in a fragmentation-sensitive carnivore

Spatially heterogeneous landscape factors such as urbanisation can have substantial effects on the severity and spread of wildlife diseases. However, research linking patterns of pathogen transmission to landscape features remains rare. Using a combination of phylogeographic and machine learning approaches, we tested the influence of landscape and host factors on feline immunodeficiency virus (FIV_Lru) genetic variation and spread among bobcats (Lynx rufus) sampled from coastal southern California. We found evidence for increased rates of FIV_Lru lineage spread through areas of higher vegetation density. Furthermore, single-nucleotide polymorphism (SNP) variation among FIV_Lru sequences was associated with host genetic distances and geographic location, with FIV_Lru genetic discontinuities precisely correlating with known urban barriers to host dispersal. An effect of forest land cover on FIV_Lru SNP variation was likely attributable to host population structure and differences in forest land cover between different populations. Taken together, these results suggest that the spread of FIV_Lru is constrained by large-scale urban barriers to host movement. Although urbanisation at fine spatial scales did not appear to directly influence virus transmission or spread, we found evidence that viruses transmit and spread more quickly through areas containing higher proportions of natural habitat. These multiple lines of evidence demonstrate how urbanisation can change patterns of contact-dependent pathogen transmission and provide insights into how continued urban development may influence the incidence and management of wildlife disease.

Characterizing viral within-host diversity in fast and non-equilibrium demo-genetic dynamics

High-throughput sequencing has opened the route for a deep assessment of within-host genetic diversity that can be used, e.g., to characterize microbial communities and to infer transmission links in infectious disease outbreaks. The performance of such characterizations and inferences cannot be analytically assessed in general and are often grounded on computer-intensive evaluations. Then, being able to simulate within-host genetic diversity across time under various demo-genetic assumptions is paramount to assess the performance of the approaches of interest. In this context, we built an original model that can be simulated to investigate the temporal evolution of genotypes and their frequencies under various demo-genetic assumptions. The model describes the growth and the mutation of genotypes at the nucleotide resolution conditional on an overall within-host viral kinetics, and can be tuned to generate fast non-equilibrium demo-genetic dynamics. We ran simulations of this model and computed classic diversity indices to characterize the temporal variation of within-host genetic diversity (from high-throughput amplicon sequences) of virus populations under three demographic kinetic models of viral infection. Our results highlight how demographic (viral load) and genetic (mutation, selection, or drift) factors drive variations in within-host diversity during the course of an infection. In particular, we observed a non-monotonic relationship between pathogen population size and genetic diversity, and a reduction of the impact of mutation on diversity when a non-specific host immune response is activated. The large variation in the diversity patterns generated in our simulations suggests that the underlying model provides a flexible basis to produce very diverse demo-genetic scenarios and test, for instance, methods for the inference of transmission links during outbreaks.

The effects of geographical distributions of buildings and roads on the spatiotemporal spread of canine rabies: An individual-based modeling study

Rabies is a fatal disease that has been a serious health concern, especially in developing countries. Although rabies is preventable by vaccination, the spread still occurs sporadically in many countries, including Thailand. Geographical structures, habitats, and behaviors of host populations are essential factors that may result in an enormous impact on the mechanism of propagation and persistence of the disease. To investigate the role of geographical structures on the transmission dynamics of canine rabies, we developed a stochastic individual-based model that integrates the exact configuration of buildings and roads. In our model, the spatial distribution of dogs was estimated based on the distribution of buildings, with roads considered to facilitate dog movement. Two contrasting areas with high- and low-risk of rabies transmission in Thailand, namely, Hatyai and Tepha districts, were chosen as study sites. Our modeling results indicated that the distinct geographical structures of buildings and roads in Hatyai and Tepha could contribute to the difference in the rabies transmission dynamics in these two areas. The high density of buildings and roads in Hatyai could facilitate more rabies transmission. We also investigated the impacts of rabies intervention, including reducing the dog population, restricting owned dog movement, and dog vaccination on the spread of canine rabies in these two areas. We found that reducing the dog population alone might not be sufficient for preventing rabies transmission in the high-risk area. Owned dog confinement could reduce more the likelihood of rabies transmission. Finally, a higher vaccination coverage may be required for controlling rabies transmission in the high-risk area compared to the low-risk area.

Rabies control in Liberia: Joint efforts towards zero by 30

Despite declaration as a national priority disease, dog rabies remains endemic in Liberia, with surveillance systems and disease control activities still developing. The objective of these initial efforts was to establish animal rabies diagnostics, foster collaboration between all rabies control stakeholders, and develop a short-term action plan with estimated costs for rabies control and elimination in Liberia. Four rabies diagnostic tests, the direct fluorescent antibody (DFA) test, the direct immunohistochemical test (dRIT), the reverse transcriptase polymerase chain reaction (RT-PCR) assay and the rapid immunochromatographic diagnostic test (RIDT), were implemented at the Central Veterinary Laboratory (CVL) in Monrovia between July 2017 and February 2018. Seven samples (n=7) out of eight suspected animals were confirmed positive for rabies lyssavirus, and molecular analyses revealed that all isolates belonged to the Africa 2 lineage, subgroup H. During a comprehensive in-country One Health rabies stakeholder meeting in 2018, a practical workplan, a short-term action plan and an accurately costed mass dog vaccination strategy were developed. Liberia is currently at stage 1.5/5 of the Stepwise Approach towards Rabies Elimination (SARE) tool, which corresponds with countries that are scaling up local-level interventions (e.g. dog vaccination campaigns) to the national level. Overall an estimated 5.3 - 8 million USD invested over 13 years is needed to eliminate rabies in Liberia by 2030. Liberia still has a long road to become free from dog-rabies. However, the dialogue between all relevant stakeholders took place, and disease surveillance considerably improved through implementing rabies diagnosis at the CVL. The joint efforts of diverse national and international stakeholders laid important foundations to achieve the goal of zero dog-mediated human rabies deaths by 2030.

Long-range movements coupled with heterogeneous incubation period sustain dog rabies at the national scale in Africa

Dog-transmitted rabies is responsible for more than 98% of human cases worldwide, remaining a persistent problem in developing countries. Mass vaccination targets predominantly major cities, often compromising disease control due to re-introductions. Previous work suggested that areas neighboring cities may behave as the source of these re-introductions. To evaluate this hypothesis, we introduce a spatially explicit metapopulation model for rabies diffusion in Central African Republic. Calibrated on epidemiological data for the capital city, Bangui, the model predicts that long-range movements are essential for continuous re-introductions of rabies-exposed dogs across settlements, eased by the large fluctuations of the incubation period. Bangui's neighborhood, instead, would not be enough to self-sustain the epidemic, contrary to previous expectations. Our findings suggest that restricting long-range travels may be very efficient in limiting rabies persistence in a large and fragmented dog population. Our framework can be applied to other geographical contexts where dog rabies is endemic.

Movement patterns of free-roaming dogs on heterogeneous urban landscapes: Implications for rabies control

In 2015, a case of canine rabies in Arequipa, Peru indicated the re-emergence of rabies virus in the city. Despite mass dog vaccination campaigns across the city and reactive ring vaccination and other control activities around positive cases (e.g. elimination of unowned dogs), the outbreak has spread. Here we explore how the urban landscape of Arequipa affects the movement patterns of free-roaming dogs, the main reservoirs of the rabies virus in the area. We tracked 23 free-roaming dogs using Global Positioning System (GPS) collars. We analyzed the spatio-temporal GPS data using the time- local convex hull method. Dog movement patterns varied across local environments. We found that water channels, an urban feature of Arequipa that are dry most of the year, promote movement. Dogs that used the water channels extensively move on average 7 times further (p = 0.002) and 1.2 times more directionally (p = 0.027) than dogs that do not use the water channels at all. They were also 1.3 times faster on average, but this difference was not statistically significant (p = 0.197). Our findings suggest that water channels can be used by dogs as 'highways' to transverse the city and have the potential to spread disease far beyond the radius of control practices. Control efforts should focus on a robust vaccination campaign attuned to the geography of the city, and not limited to small-scale rings surrounding cases.

Pathogens in space: Advancing understanding of pathogen dynamics and disease ecology through landscape genetics

Landscape genetics has provided many insights into how heterogeneous landscape features drive processes influencing spatial genetic variation in free-living organisms. This rapidly developing field has focused heavily on vertebrates, and expansion of this scope to the study of infectious diseases holds great potential for landscape geneticists and disease ecologists alike. The potential application of landscape genetics to infectious agents has garnered attention at formative stages in the development of landscape genetics, but systematic examination is lacking. We comprehensively review how landscape genetics is being used to better understand pathogen dynamics. We characterize the field and evaluate the types of questions addressed, approaches used and systems studied. We also review the now established landscape genetic methods and their realized and potential applications to disease ecology. Lastly, we identify emerging frontiers in the landscape genetic study of infectious agents, including recent phylogeographic approaches and frameworks for studying complex multihost and host-vector systems. Our review emphasizes the expanding utility of landscape genetic methods available for elucidating key pathogen dynamics (particularly transmission and spread) and also how landscape genetic studies of pathogens can provide insight into host population dynamics. Through this review, we convey how increasing awareness of the complementarity of landscape genetics and disease ecology among practitioners of each field promises to drive important cross-disciplinary advances.

Molecular epidemiology of rabies virus circulating in domestic animals in India

Rabies is a neglected viral zoonotic disease affecting humans, domestic and wild animals and is endemic in most parts of the India. Dog mediated rabies is more predominant than other forms of rabies and molecular epidemiology is poorly understood in both reservoir and susceptible hosts. In the present study, a total of 140 rabies suspected brain samples from different species of animals from different geographical regions of India were used. The samples were parallelly tested by direct fluorescent antibody test, reverse transcriptase PCR and real-time PCR. Thirty positive samples were subjected for partial nucleoprotein gene sequencing and phylogenetic analysis. On sequence and phylogenetic analysis, it was observed that all Indian rabies viruses belonged to classical rabies virus of genotype 1 of Lyssavirus and formed two distinct groups. The majority of isolates were in group-1 and are closely related to arctic/arctic like lineage, whereas group-II isolated are closely related to cosmopolitan lineage. These results indicated there is simultaneous existence of two distinct lineages of rabies viruses in Indian subcontinent. Further whole genome studies are needed for better understanding of molecular epidemiology of rabies virus circulating in animals for control and prevention of rabies in India.

Landscape attributes governing local transmission of an endemic zoonosis: Rabies virus in domestic dogs

Landscape heterogeneity plays an important role in disease spread and persistence, but quantifying landscape influences and their scale dependence is challenging. Studies have focused on how environmental features or global transport networks influence pathogen invasion and spread, but their influence on local transmission dynamics that underpin the persistence of endemic diseases remains unexplored. Bayesian phylogeographic frameworks that incorporate spatial heterogeneities are promising tools for analysing linked epidemiological, environmental and genetic data. Here, we extend these methodological approaches to decipher the relative contribution and scale-dependent effects of landscape influences on the transmission of endemic rabies virus in Serengeti district, Tanzania (area ~4,900 km2 ). Utilizing detailed epidemiological data and 152 complete viral genomes collected between 2004 and 2013, we show that the localized presence of dogs but not their density is the most important determinant of diffusion, implying that culling will be ineffective for rabies control. Rivers and roads acted as barriers and facilitators to viral spread, respectively, and vaccination impeded diffusion despite variable annual coverage. Notably, we found that landscape effects were scale-dependent: rivers were barriers and roads facilitators on larger scales, whereas the distribution of dogs was important for rabies dispersal across multiple scales. This nuanced understanding of the spatial processes that underpin rabies transmission can be exploited for targeted control at the scale where it will have the greatest impact. Moreover, this research demonstrates how current phylogeographic frameworks can be adapted to improve our understanding of endemic disease dynamics at different spatial scales.

The lyssavirus host-specificity conundrum-rabies virus-the exception not the rule

Lyssaviruses are a diverse range of viruses which all cause the disease rabies. Of the 16 recognized species, only rabies viruses (RABV) have multiple host reservoirs. Although lyssaviruses are capable of infecting all mammals, onward transmission in a new host population requires adaptation of the virus, in a number of stages with both host and virus factors determining the outcome. Due to an absence of recorded non-RABV host shifts, RABV data is extrapolated to draw conclusions for all lyssaviruses. In this article, we have focused on evidence of host shifts in the same insectivorous bat reservoir species in North America (RABV) and Europe (EBLV-1, EBLV-2 and BBLV). How RABV has successfully crossed species barriers and established infectious cycles in new hosts to be the global multi-host pathogen it is today, whilst other lyssaviruses appear restricted in host species is explored in this review. It hypothesized that RABV is the exception, rather than the rule, in this fascinating genus of viruses.

The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges

Advances in high-throughput molecular biology and electronic health records (EHR), coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Big data require collection and analysis of data at an unprecedented scale and represents a paradigm shift in health care, offering (1) the capacity to generate new knowledge more quickly than traditional scientific approaches; (2) unbiased collection and analysis of data; and (3) a holistic understanding of biology and pathophysiology. Big data promises more personalized and precision medicine for patients with improved accuracy and earlier diagnosis, and therapy tailored to an individual’s unique combination of genes, environmental risk, and precise disease phenotype. This promise comes from data collected from numerous sources, ranging from molecules to cells, to tissues, to individuals and populations—and the integration of these data into networks that improve understanding of heath and disease. Big data-driven science should play a role in propelling comparative medicine and “one medicine” (i.e., the shared physiology, pathophysiology, and disease risk factors across species) forward. Merging of data from EHR across institutions will give access to patient data on a scale previously unimaginable, allowing for precise phenotype definition and objective evaluation of risk factors and response to therapy. High-throughput molecular data will give insight into previously unexplored molecular pathophysiology and disease etiology. Investigation and integration of big data from a variety of sources will result in stronger parallels drawn at the molecular level between human and animal disease, allow for predictive modeling of infectious disease and identification of key areas of intervention, and facilitate step-changes in our understanding of disease that can make a substantial impact on animal and human health. However, the use of big data comes with significant challenges. Here we explore the scope of “big data,” including its opportunities, its limitations, and what is needed capitalize on big data in one medicine.

Spatio-temporal Analysis of the Genetic Diversity of Arctic Rabies Viruses and Their Reservoir Hosts in Greenland

There has been limited knowledge on spatio-temporal epidemiology of zoonotic arctic fox rabies among countries bordering the Arctic, in particular Greenland. Previous molecular epidemiological studies have suggested the occurrence of one particular arctic rabies virus (RABV) lineage (arctic-3), but have been limited by a low number of available samples preventing in-depth high resolution phylogenetic analysis of RABVs at that time. However, an improved knowledge of the evolution, at a molecular level, of the circulating RABVs and a better understanding of the historical perspective of the disease in Greenland is necessary for better direct control measures on the island. These issues have been addressed by investigating the spatio-temporal genetic diversity of arctic RABVs and their reservoir host, the arctic fox, in Greenland using both full and partial genome sequences. Using a unique set of 79 arctic RABV full genome sequences from Greenland, Canada, USA (Alaska) and Russia obtained between 1977 and 2014, a description of the historic context in relation to the genetic diversity of currently circulating RABV in Greenland and neighboring Canadian Northern territories has been provided. The phylogenetic analysis confirmed delineation into four major arctic RABV lineages (arctic 1–4) with viruses from Greenland exclusively grouping into the circumpolar arctic-3 lineage. High resolution analysis enabled distinction of seven geographically distinct subclades (3.I – 3.VII) with two subclades containing viruses from both Greenland and Canada. By combining analysis of full length RABV genome sequences and host derived sequences encoding mitochondrial proteins obtained simultaneously from brain tissues of 49 arctic foxes, the interaction of viruses and their hosts was explored in detail. Such an approach can serve as a blueprint for analysis of infectious disease dynamics and virus-host interdependencies. The results showed a fine-scale spatial population structure in Greenland arctic foxes based on mitochondrial sequences, but provided no evidence for independent isolated evolutionary development of RABV in different arctic fox lineages. These data are invaluable to support future initiatives for arctic fox rabies control and elimination in Greenland.

Next to dog-mediated rabies, wildlife rabies continues to pose a public health problem, particularly in the northern hemisphere. Control of this zoonosis at the animal source has been proven the most efficient route to reduction of human rabies burden. Successful elimination of red fox-mediated rabies in Western Europe and parts of North America has demonstrated the viability of wildlife rabies control strategies. In some regions, the epidemiology of wildlife rabies is well understood; this is not the case for arctic rabies, particularly in Greenland. Previous molecular epidemiological studies demonstrated the occurrence of one particular arctic rabies virus (RABV) lineage (arctic-3) but were limited by low sample numbers and limited sequence length so as to preclude generation of high resolution phylogenetic analysis. Here, a unique set comprised of 79 complete genome sequences of RABVs from Greenland, Canada, USA (Alaska) and Russia collected over the past four decades was analysed. The use of next generation sequencing (NGS) allowed simultaneous determination of host derived sequences encoding mitochondrial proteins from the same brain tissue of 49 arctic foxes. These sequence data combined with geographical and temporal information permit the study of the genetic diversity and evolution of circulating RABVs in Greenland against the background of reservoir host genetics. The results reveal the existence of a single arctic RABV lineage (arctic-3) in Greenland, which has evolved into multiple distinct variants. These analyses provide an improved knowledge of the evolution of the circulating viruses at the molecular level and a better understanding of the historical perspective of the disease in Greenland compared to other parts of the Arctic. This knowledge will support policy on rabies control in mammalian wildlife reservoirs.

Rabies disease dynamics in naïve dog populations in Australia

Currently, Australia is free from terrestrial rabies but an incursion from nearby Indonesia, where the virus is endemic, is a feasible threat. Here, we aimed to determine whether the response to a simulated rabies incursion would vary between three extant Australian dog populations; free-roaming domestic dogs from a remote indigenous community in northern Australia, and free-roaming domestic and wild dogs in peri-urban areas of north-east New South Wales. We further sought to predict how different management strategies impacted disease dynamics in these populations. We used simple stochastic state-transition models and dog demographic and contact rate data from the three dog populations to simulate rabies spread, and used global and local sensitivity analyses to determine effects of model parameters. To identify the most effective control options, dog removal and vaccination strategies were also simulated. Responses to simulated rabies incursions varied between the dog populations. Free-roaming domestic dogs from north-east New South Wales exhibited the lowest risk for rabies maintenance and spread. Due to low containment and high contact rates, rabies progressed rapidly through free-roaming dogs from the remote indigenous community in northern Australia. In contrast, rabies remained at relatively low levels within the north-east New South Wales wild dog population for over a year prior to an epidemic. Across all scenarios, sensitivity analyses revealed that contact rates and the probability of transmission were the most important drivers of the number of infectious individuals within a population. The number of infectious individuals was less sensitive to birth and death rates. Removal of dogs as a control strategy was not effective for any population modelled, while vaccination rates in excess of 70% of the population resulted in significant reductions in disease progression. The variability in response between these distinct dog groups to a rabies incursion, suggests that a blanket approach to management would not be effective or feasible to control rabies in Australia. Control strategies that take into account the different population and behavioural characteristics of these dog groups will maximise the likelihood of effective and efficient rabies control in Australia.

Applying landscape genetics to the microbial world

Landscape genetics, which explicitly quantifies landscape effects on gene flow and adaptation, has largely focused on macroorganisms, with little attention given to microorganisms. This is despite overwhelming evidence that microorganisms exhibit spatial genetic structuring in relation to environmental variables. The increasing accessibility of genomic data has opened up the opportunity for landscape genetics to embrace the world of microorganisms, which may be thought of as 'the invisible regulators' of the macroecological world. Recent developments in bioinformatics and increased data accessibility have accelerated our ability to identify microbial taxa and characterize their genetic diversity. However, the influence of the landscape matrix and dynamic environmental factors on microorganism genetic dispersal and adaptation has been little explored. Also, because many microorganisms coinhabit or codisperse with macroorganisms, landscape genomic approaches may improve insights into how micro- and macroorganisms reciprocally interact to create spatial genetic structure. Conducting landscape genetic analyses on microorganisms requires that we accommodate shifts in spatial and temporal scales, presenting new conceptual and methodological challenges not yet explored in 'macro'-landscape genetics. We argue that there is much value to be gained for microbial ecologists from embracing landscape genetic approaches. We provide a case for integrating landscape genetic methods into microecological studies and discuss specific considerations associated with the novel challenges this brings. We anticipate that microorganism landscape genetic studies will provide new insights into both micro- and macroecological processes and expand our knowledge of species' distributions, adaptive mechanisms and species' interactions in changing environments.

Revealing the Micro-scale Signature of Endemic Zoonotic Disease Transmission in an African Urban Setting

The development of novel approaches that combine epidemiological and genomic data provides new opportunities to reveal the spatiotemporal dynamics of infectious diseases and determine the processes responsible for their spread and maintenance. Taking advantage of detailed epidemiological time series and viral sequence data from more than 20 years reported by the National Reference Centre for Rabies of Bangui, the capital city of Central African Republic, we used a combination of mathematical modeling and phylogenetic analysis to determine the spatiotemporal dynamics of rabies in domestic dogs as well as the frequency of extinction and introduction events in an African city. We show that although dog rabies virus (RABV) appears to be endemic in Bangui, its epidemiology is in fact shaped by the regular extinction of local chains of transmission coupled with the introduction of new lineages, generating successive waves of spread. Notably, the effective reproduction number during each wave was rarely above the critical value of 1, such that rabies is not self-sustaining in Bangui. In turn, this suggests that rabies at local geographic scales is driven by human-mediated dispersal of RABV among sparsely connected peri-urban and rural areas as opposed to dispersion in a relatively large homogenous urban dog population. This combined epidemiological and genomic approach enables development of a comprehensive framework for understanding disease persistence and informing control measures, indicating that control measures are probably best targeted towards areas neighbouring the city that appear as the source of frequent incursions seeding outbreaks in Bangui.

Surveillance of Canine Rabies in the Central African Republic: Impact on Human Health and Molecular Epidemiology

BACKGROUND

Although rabies represents an important public health threat, it is still a neglected disease in Asia and Africa where it causes tens of thousands of deaths annually despite available human and animal vaccines. In the Central African Republic (CAR), an endemic country for rabies, this disease remains poorly investigated.

METHODS

To evaluate the extent of the threat that rabies poses in the CAR, we analyzed data for 2012 from the National Reference Laboratory for Rabies, where laboratory confirmation was performed by immunofluorescence and PCR for both animal and human suspected cases, and data from the only anti-rabies dispensary of the country and only place where post-exposure prophylaxis (PEP) is available. Both are located in Bangui, the capital of the CAR. For positive samples, a portion of the N gene was amplified and sequenced to determine the molecular epidemiology of circulating strains.

RESULTS

In 2012, 966 exposed persons visited the anti-rabies dispensary and 632 received a post-exposure rabies vaccination. More than 90% of the exposed persons were from Bangui and its suburbs and almost 60% of them were under 15-years of age. No rabies-related human death was confirmed. Of the 82 samples from suspected rabid dogs tested, 69 were confirmed positive. Most of the rabid dogs were owned although unvaccinated. There was a strong spatiotemporal correlation within Bangui and within the country between reported human exposures and detection of rabid dogs (P<0.001). Phylogenetic analysis indicated that three variants belonging to Africa I and II lineages actively circulated in 2012.

CONCLUSIONS

These data indicate that canine rabies was endemic in the CAR in 2012 and had a detrimental impact on human health as shown by the hundreds of exposed persons who received PEP. Implementation of effective public health interventions including mass dog vaccination and improvement of the surveillance and the access to PEP are urgently needed in this country.

Elucidating the phylodynamics of endemic rabies virus in eastern Africa using whole-genome sequencing

Many of the pathogens perceived to pose the greatest risk to humans are viral zoonoses, responsible for a range of emerging and endemic infectious diseases. Phylogeography is a useful tool to understand the processes that give rise to spatial patterns and drive dynamics in virus populations. Increasingly, whole-genome information is being used to uncover these patterns, but the limits of phylogenetic resolution that can be achieved with this are unclear. Here, whole-genome variation was used to uncover fine-scale population structure in endemic canine rabies virus circulating in Tanzania. This is the first whole-genome population study of rabies virus and the first comprehensive phylogenetic analysis of rabies virus in East Africa, providing important insights into rabies transmission in an endemic system. In addition, sub-continental scale patterns of population structure were identified using partial gene data and used to determine population structure at larger spatial scales in Africa. While rabies virus has a defined spatial structure at large scales, increasingly frequent levels of admixture were observed at regional and local levels. Discrete phylogeographic analysis revealed long-distance dispersal within Tanzania, which could be attributed to human-mediated movement, and we found evidence of multiple persistent, co-circulating lineages at a very local scale in a single district, despite on-going mass dog vaccination campaigns. This may reflect the wider endemic circulation of these lineages over several decades alongside increased admixture due to human-mediated introductions. These data indicate that successful rabies control in Tanzania could be established at a national level, since most dispersal appears to be restricted within the confines of country borders but some coordination with neighbouring countries may be required to limit transboundary movements. Evidence of complex patterns of rabies circulation within Tanzania necessitates the use of whole-genome sequencing to delineate finer scale population structure that can that can guide interventions, such as the spatial scale and design of dog vaccination campaigns and dog movement controls to achieve and maintain freedom from disease.

Spatial and temporal epidemiological analysis in the Big Data era

Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle large datasets faster than classical regression approaches, are now also used to analyse spatial and spatio-temporal data. Multi-criteria decision analysis methods have gained greater acceptance, due in part, to the need to increasingly combine data from diverse sources including published scientific information and expert opinion in an attempt to fill important knowledge gaps. The opportunities for more effective prevention, detection and control of animal health threats arising from these developments are immense, but not without risks given the different types, and much higher frequency, of biases associated with these data.

Infectious disease transmission and contact networks in wildlife and livestock

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.

Assembling evidence for identifying reservoirs of infection

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We review the problem of identifying reservoirs of infection for multihost pathogens and provide an overview of current approaches and future directions.

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We provide a conceptual framework for classifying patterns of incidence and prevalence.

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We review current methods that allow us to characterise the components of reservoir-target systems.

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Ecological theory offers promising new ways to prioritise populations when designing interventions.

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We propose using interventions as quasi-experiments embedded in adaptive management frameworks.

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Integration of data and analysis provides powerful new opportunities for studying multihost systems.

Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems.

Recent emergence and spread of an Arctic-related phylogenetic lineage of rabies virus in Nepal

Rabies is a zoonotic disease that is endemic in many parts of the developing world, especially in Africa and Asia. However its epidemiology remains largely unappreciated in much of these regions, such as in Nepal, where limited information is available about the spatiotemporal dynamics of the main etiological agent, the rabies virus (RABV). In this study, we describe for the first time the phylogenetic diversity and evolution of RABV circulating in Nepal, as well as their geographical relationships within the broader region. A total of 24 new isolates obtained from Nepal and collected from 2003 to 2011 were full-length sequenced for both the nucleoprotein and the glycoprotein genes, and analysed using neighbour-joining and maximum-likelihood phylogenetic methods with representative viruses from all over the world, including new related RABV strains from neighbouring or more distant countries (Afghanistan, Greenland, Iran, Russia and USA). Despite Nepal's limited land surface and its particular geographical position within the Indian subcontinent, our study revealed the presence of a surprising wide genetic diversity of RABV, with the co-existence of three different phylogenetic groups: an Indian subcontinent clade and two different Arctic-like sub-clades within the Arctic-related clade. This observation suggests at least two independent episodes of rabies introduction from neighbouring countries. In addition, specific phylogenetic and temporal evolution analysis of viruses within the Arctic-related clade has identified a new recently emerged RABV lineage we named as the Arctic-like 3 (AL-3) sub-clade that is already widely spread in Nepal.

Rabies is endemic in most Asian countries and represents a serious public health issue, with an estimated 31,000 people dying each year of this disease. The majority of human cases are transmitted by domestic dogs, which act as the principal reservoir host and vector. However, molecular epidemiology and evolutionary dynamics of the main etiological agent, the rabies virus (RABV), remains largely unappreciated in some regions such as in Nepal. Based on a subset of 24 new Nepalese isolates collected from 2003 to 2011 and representative RABV strains at a global scale, phylogenetic analysis based on the complete nucleoprotein and glycoprotein genes sequences revealed the presence of a surprising wide genetic diversity of RABV circulating in this country. The presence of three different co-existing phylogenetic groups was identified: an Indian subcontinent clade and two different Arctic-like sub-clades within the Arctic-related clade, namely Arctic-like (AL)-1, lineage a (AL-1a), and AL-3. Among these clusters, the AL-3 sub-clade appears as the major Nepalese phylogroup which emerged relatively recently in this country, within the last 30 years. These data has raised some concerns about the exchange of RABV between different countries, and provided key elements for implementation of effective control measures of rabies in Nepal.

Towards the endgame and beyond: complexities and challenges for the elimination of infectious diseases

Successful control measures have interrupted the local transmission of human infectious diseases such as measles, malaria and polio, and saved and improved billions of lives. Similarly, control efforts have massively reduced the incidence of many infectious diseases of animals, such as rabies and rinderpest, with positive benefits for human health and livelihoods across the globe. However, disease elimination has proven an elusive goal, with only one human and one animal pathogen globally eradicated. As elimination targets expand to regional and even global levels, hurdles may emerge within the endgame when infections are circulating at very low levels, turning the last mile of these public health marathons into the longest mile. In this theme issue, we bring together recurring challenges that emerge as we move towards elimination, highlighting the unanticipated consequences of particular ecologies and pathologies of infection, and approaches to their management.

Phylogeographic dispersion and diversification of rabies virus lineages associated with dogs and crab-eating foxes (Cerdocyon thous) in Brazil

Genetic lineages of dog-associated RABV still circulate in some areas of the North and Northeast of Brazil. In parallel, another RABV lineage circulates among wild canids in the Northeast, particularly the crab-eating fox (Cerdocyon thous). Although previous studies and phylogenetic analyses have been carried out, the way in which these lineages are dispersed temporally and spatially remained to be elucidated. In this study, RABV N gene sequences isolated from canids in North and Northeast Brazil were analyzed by the Bayesian Markov Chain Monte Carlo Method, and the results were then used in a phylogeographic study. It was inferred from the findings that the most recent common ancestor became established at the end of the nineteenth century on the border of the Brazilian states of Paraíba and Pernambuco and diversified into the lineages associated with dogs and C. thous. Around 1910, the original C. thous lineage diversified into two main sublineages in the same area, one of which migrated to the south and the other to the north. The dog-associated lineage diversified around 1945 and moved toward the north and south. From the phylogeographic analysis it was possible to infer not only the movement of the virus lineages but also the probable location where dispersion and diversification occurred. The methodology used here enabled the phylogeographic history of RABV in the region to be reconstructed, and the dispersion pattern of the virus can be used to predict its movements, making it easier to stop the advance of a rabies epidemic.