Seasonality and pathogen transmission in pastoral cattle contact networks

Leveraging browse and grazing forage estimates to optimize index-based livestock insurance

African pastoralists suffer recurrent droughts that cause high livestock mortality and vulnerability to climate change. The index-based livestock insurance (IBLI) program offers protection against drought impacts. However, the current IBLI design relying on the normalized difference vegetation index (NDVI) may pose limitation because it does not consider the mixed composition of rangelands (including herbaceous and woody plants) and the diverse feeding habits of grazers and browsers. To enhance IBLI, we assessed the efficacy of utilizing distinct browse and grazing forage estimates from woody LAI (LAIW) and herbaceous LAI (LAIH), respectively, derived from aggregate leaf area index (LAIA), as an alternative to NDVI for refined IBLI design. Using historical livestock mortality data from northern Kenya as reference ground dataset, our analysis compared two competing models for (1) aggregate forage estimates including sub-models for NDVI, LAI (LAIA); and (2) partitioned biomass model (LAIP) comprising LAIH and LAIW. By integrating forage estimates with ancillary environmental variables, we found that LAIP, with separate forage estimates, outperformed the aggregate models. For total livestock mortality, LAIP yielded the lowest RMSE (5.9 TLUs) and higher R2 (0.83), surpassing NDVI and LAIA models RMSE (9.3 TLUs) and R2 (0.6). A similar pattern was observed for species-specific livestock mortality. The influence of environmental variables across the models varied, depending on level of mortality aggregation or separation. Overall, forage availability was consistently the most influential variable, with species-specific models showing the different forage preferences in various animal types. These results suggest that deriving distinct browse and grazing forage estimates from LAIP has the potential to reduce basis risk by enhancing IBLI index accuracy.

Higher livestock abortion burden in arid and semi-arid lands, Kenya, 2019-2020

Tracking livestock abortion patterns over time and across factors such as species and agroecological zones (AEZs) could inform policies to mitigate disease emergence, zoonoses risk, and reproductive losses. We conducted a year-long population-based active surveillance of livestock abortion between 2019 and 2020, in administrative areas covering 52% of Kenya's landmass and home to 50% of Kenya's livestock. Surveillance sites were randomly selected to represent all AEZs in the country. Local animal health practitioners electronically transmitted weekly abortion reports from each ward, the smallest administrative unit, to a central server, using a simple short messaging service (SMS). Data were analyzed descriptively by administrative unit, species, and AEZ to reveal spatiotemporal patterns and relationships with rainfall and temperature. Of 23,766 abortions reported in all livestock species, sheep and goats contributed 77%, with goats alone contributing 53%. Seventy-seven per cent (n = 18,280) of these abortions occurred in arid and semi-arid lands (ASALs) that primarily practice pastoralism production systems. While spatiotemporal clustering of cases was observed in May-July 2019 in the ASALs, there was a substantial seasonal fluctuation across AEZs. Kenya experiences high livestock abortion rates, most of which go unreported. We recommend further research to document the national true burden of abortions. In ASALs, studies linking pathogen, climate, and environmental surveillance are needed to assign livestock abortions to infectious or non-infectious aetiologies and conducting human acute febrile illnesses surveillance to detect any links with the abortions.

Knowledge, perceptions, and practices around zoonotic diseases among actors in the livestock trade in the Lake Victoria crescent ecosystem in East Africa

Background

Zoonotic diseases such as anthrax, rabies, brucellosis, and Rift Valley fever pose a direct threat to health and undercut livelihoods in the communities in which they occur. A combination of anthropogenic and animal activities like migration and interaction with wildlife and their respective parasites and vectors drives the emergence and re-emergence of zoonotic diseases. Consequently, One Health interdisciplinary approaches that incorporate social scientists can provide key insights into complex local perceptions. The approach calls for collaboration between the human and animal health sectors, including the sharing of disease surveillance data necessary to alleviate disease impacts. Livestock traders interact closely with livestock, which puts them at elevated risk of infection and creates conditions by which they may spread zoonotic disease. It is thus essential to examine practices among actors involved in the livestock trade to understand the most appropriate ways to mitigate these risks.

Methods

A qualitative study was conducted among the actors in the livestock trade in Busia County on their knowledge and perceptions of zoonotic diseases and practices that may contribute to the spread, control, and prevention of zoonotic disease transmission. A thematic analysis framework was used to categorize and synthesize data from in-depth interviews (IDIs), key informant interviews (KIIs), and structured observations.

Results

Whereas participants could list livestock diseases, they could not identify which ones were zoonoses, demonstrating insufficient knowledge of zoonosis. They identify sick animals by checking for dropped ears, excess mucus production, diarrhea, bloody urinal discharge, and general animal activity levels. To prevent the spread of these diseases, they wash their animals, isolate sick animals from the rest of the stock, and vaccinate their animals. They seek help from animal health professionals for sick animals as part of curative practices. This shows that they perceive the diseases as serious and that they need to be attended to by professionals. The results also show that they perceive animals from outside the region to be more vulnerable to diseases compared to those from within. The actors in the livestock trade engage in practices like skinning dead animals before burying them; to them, this is a normal practice. Some also consume dead carcasses. These increase the risk of zoonotic disease transmission.

Conclusion

The actors involved in the livestock trade are critical in the prevention and elimination of zoonotic diseases; hence, they need to be involved when developing intervention programs and policies for animal health extension services. Training them as a continuum of animal health workers blends lay and professional knowledge, which, alongside their intense contact with large numbers of animals, becomes a critical disease surveillance tool. Increasing awareness of zoonoses by using multi-disciplinary teams with social scientists is urgently needed so that practices like skinning dead animals before disposing of them and consumption of dead carcasses can be minimized.

Seroprevalence and risk factors of Peste des petits ruminants in different production systems in Uganda

Peste des petits ruminants (PPR) is a highly contagious and fatal disease of mostly domestic goats and sheep. First reported in Uganda in 2007, the extent of peste des petits ruminants virus (PPRV) exposure, geographical distribution and risk factors of its transmission and spread are not clearly understood. In this study, we used cluster random sampling methodology to select study villages from three districts representing three different production systems along Uganda's "cattle corridor". Between October and December 2022, 2520 goat and sheep serum samples were collected from 252 households with no history of PPR vaccination in the past one year. The household heads were interviewed to assess possible risk factors of PPRV transmission using a structured questionnaire. The serum samples were screened with a commercial competitive enzyme-linked immunosorbent assay (cELISA) for PPRV antibodies. The determined overall true seroprevalence of PPRV was 27.3% [95% CI: 25.4-29.1]. The seroprevalence of PPRV antibodies in different production systems was 44.1% [95% CI: 40.6-47.7], 31.7% [95% CI: 28.4-35.0] and 6.1% [95% CI: 4.4-7.9] for pastoral, agropastoral and mixed crop-livestock production systems respectively. A mixed-effects multivariable logistic regression model revealed strong statistical evidence of association between female animals and PPRV antibody seropositivity compared to males [OR= 2.45, 95% CI: 1.7-3.5, p < 0.001]. The likelihood of being PPRV antibody seropositive significantly increased with increasing small ruminant age. Animals older than 3 years were more than three times as likely to be PPRV seropositive compared to animals aged under 1 year [OR= 3.41, 95% CI: 2.39-4.85, p < 0.001]. There was no statistical evidence of association between small ruminant species and PPRV antibody seropositivity (p = 0.423). Village flocks that interacted with neighboring flocks daily during grazing (IRR = 1.59, 95% CI: 1.19-2.13) and watering around swamps (IRR = 1.59, 95% CI: 1.19-2.13) were highly correlated with increased number of PPRV seropositive animals as compared to flocks that were more restricted in grazing and watered around other water sources other than swamps. Flocks from pastoral and agropastoral production systems were more than 10 times more likely to have seropositive animals than mixed crop-livestock flocks. Targeting PPR control interventions (vaccination and livestock movement control) to pastoral and agro-pastoral small ruminant production systems that are very prone to PPR incursions is recommended to prevent PPRV spread to low-risk smallholder mixed crop-livestock production systems.

Mapping brucellosis risk in Kenya and its implications for control strategies in sub-Saharan Africa

In Sub-Saharan Africa (SSA), effective brucellosis control is limited, in part, by the lack of long-term commitments by governments to control the disease and the absence of reliable national human and livestock population-based data to inform policies. Therefore, we conducted a study to establish the national prevalence and develop a risk map for Brucella spp. in cattle to contribute to plans to eliminate the disease in Kenya by the year 2040. We randomly generated 268 geolocations and distributed them across Kenya, proportionate to the area of each of the five agroecological zones and the associated cattle population. Cattle herds closest to each selected geolocation were identified for sampling. Up to 25 cattle were sampled per geolocation and a semi-structured questionnaire was administered to their owners. We tested 6,593 cattle samples for Brucella immunoglobulin G (IgG) antibodies using an Enzyme-linked immunosorbent assay (ELISA). We assessed potential risk factors and performed spatial analyses and prevalence mapping using approximate Bayesian inference implemented via the integrated nested Laplace approximation (INLA) method. The national Brucella spp. prevalence was 6.8% (95% CI: 6.2-7.4%). Exposure levels varied significantly between agro-ecological zones, with a high of 8.5% in the very arid zone with the lowest agricultural potential relative to a low of 0.0% in the agro-alpine zone with the highest agricultural potential. Additionally, seroprevalence increased with herd size, and the odds of seropositivity were significantly higher for females and adult animals than for males or calves. Similarly, animals with a history of abortion, or with multiple reproductive syndromes had higher seropositivity than those without. At the herd level, the risk of Brucella spp. transmission was higher in larger herds, and herds with a history of reproductive problems such as abortion, giving birth to weak calves, or having swollen testes. Geographic localities with high Brucella seroprevalence occurred in northern, eastern, and southern regions of Kenya all primarily characterized by semi-arid or arid agro-ecological zones dominated by livestock pastoralism interspersed with vast areas with mixed livestock-wildlife systems. The large spatial extent of our survey provides compelling evidence for the widespread geographical distribution of brucellosis risk across Kenya in a manner easily understandable for policymakers. Our findings can provide a basis for risk-stratified pilot studies aiming to investigate the cost-effectiveness and efficacy of singular and combined preventive intervention strategies that seek to inform Kenya's Brucellosis Control Policy.

Identifying target areas for risk-based surveillance and control of transboundary animal diseases: a seasonal analysis of slaughter and live-trade cattle movements in Uganda

Animal movements are a major driver for the spread of Transboundary Animal Diseases (TADs). These movements link populations that would otherwise be isolated and hence create opportunities for susceptible and infected individuals to meet. We used social network analysis to describe the seasonal network structure of cattle movements in Uganda and unravel critical network features that identify districts or sub-regions for targeted risk-based surveillance and intervention. We constructed weighted, directed networks based on 2019 between-district cattle movements using official livestock mobility data; the purpose of the movement ('slaughter' vs. 'live trade') was used to subset the network and capture the risks more reliably. Our results show that cattle trade can result in local and long-distance disease spread in Uganda. Seasonal variability appears to impact the structure of the network, with high heterogeneity of node and edge activity identified throughout the seasons. These observations mean that the structure of the live trade network can be exploited to target influential district hubs within the cattle corridor and peripheral areas in the south and west, which would result in rapid network fragmentation, reducing the contact structure-related trade risks. Similar exploitable features were observed for the slaughter network, where cattle traffic serves mainly slaughter hubs close to urban centres along the cattle corridor. Critically, analyses that target the complex livestock supply value chain offer a unique framework for understanding and quantifying risks for TADs such as Foot-and-Mouth disease in a land-locked country like Uganda. These findings can be used to inform the development of risk-based surveillance strategies and decision making on resource allocation. For instance, vaccine deployment, biosecurity enforcement and capacity building for stakeholders at the local community and across animal health services with the potential to limit the socio-economic impact of outbreaks, or indeed reduce their frequency.

Seasonal changes in network connectivity and consequences for pathogen transmission in a solitary carnivore

Seasonal variation in habitat use and animal behavior can alter host contact patterns with potential consequences for pathogen transmission dynamics. The endangered Florida panther (Puma concolor coryi) has experienced significant pathogen-induced mortality and continues to be at risk of future epidemics. Prior research has found increased panther movement in Florida's dry versus wet seasons, which may affect panther population connectivity and seasonally increase potential pathogen transmission. Our objective was to determine if Florida panthers are more spatially connected in dry seasons relative to wet seasons, and test if identified connectivity differences resulted in divergent predicted epidemic dynamics. We leveraged extensive panther telemetry data to construct seasonal panther home range overlap networks over an 11 year period. We tested for differences in network connectivity, and used observed network characteristics to simulate transmission of a broad range of pathogens through dry and wet season networks. We found that panthers were more spatially connected in dry seasons than wet seasons. Further, these differences resulted in a trend toward larger and longer pathogen outbreaks when epidemics were initiated in the dry season. Our results demonstrate that seasonal variation in behavioral patterns-even among largely solitary species-can have substantial impacts on epidemic dynamics.

Prevalence and associated risk factors of intestinal parasitic infections among children in pastoralist and agro-pastoralist communities in the Adadle woreda of the Somali Regional State of Ethiopia

BACKGROUND

Intestinal parasitic infections (IPIs) can cause illness, morbidity, and occasional mortality in children. Agro-pastoralist and pastoralist children in the Somali Regional State of Ethiopia (ESRS) are especially at risk for IPIs, as access to safe water, sanitation, and health services is lacking. Minimal data on the prevalence of IPIs and associated risk factors exists in this region.

METHODOLOGY

We assessed the prevalence of IPIs and associated risk factors during the wet season from May-June 2021 in 366 children aged 2 to 5 years in four agro-pastoralist and four pastoralist kebeles (wards) in Adadle woreda (district) of the Shebelle zone, ESRS. Household information, anthropometric measurements, and stool samples were obtained from included children. Parasites were identified microscopically using Kato-Katz and direct smear methods. Risk factors were assessed using general estimating equation models accounting for clustering.

PRINCIPAL FINDINGS

Overall prevalence of IPIs was 35%: 30.6% for single infections and 4.4% for poly-parasitic infections. Intestinal protozoan prevalence was 24.9%: 21.9% Giardia intestinalis, and 3.0% Entamoeba spp.. Intestinal helminth prevalence was 14.5%: 12.8% Ascaris lumbricoides, 1.4% hookworm (Ancylostoma duodenale /Necator americanus.), and 0.3% Hymenolepis nana. G. intestinalis infection was associated with drinking water sourced from the river (aOR 15.6, 95%CI 6.84, 35.4) and from collected rainwater (aOR 9.48, 95%CI 3.39, 26.5), with toilet sharing (aOR 2.93, 95%CI 1.36, 6.31) and with household ownership of cattle (1-5 cattle: aOR 1.65, 95%CI 1.13, 2.41; 6+ cattle: aOR 2.07, 95%CI 1.33, 3.21) and chickens (aOR 3.80, 95%CI 1.77, 8.17). A. lumbricoides infection was associated with children 36 to 47 months old (aOR 1.92, 95%CI 1.03, 3.58).

CONCLUSIONS/SIGNIFICANCE

Improving access to safe water, sanitation, and hygiene services in Adadle and employing a One Health approach would likely improve the health of children living in (agro-) pastoralist communities in Adadle and the ESRS; however, further studies are required.

Relationship between Vaccine Application and Climate Factors in Sheep and Goat Farms in Greece

The objectives of the present study were (a) to evaluate the importance of climate-related variables in the vaccination patterns applied in sheep and goat farms in Greece and (b) to assess potential interactions between these factors and previously established important health management- and human resources-related factors applied in the farms. Vaccination patterns against chlamydial abortion, clostridial infections, contagious agalactia, contagious ecthyma, foot-rot, paratuberculosis, pneumonia or staphylococcal mastitis were assessed. Climatic variables (2010–2019 and 2018–2019) were obtained for 444 locations with small ruminant farms throughout Greece. Patterns of vaccine administration in the farms were obtained through interviews with farmers. The following nine outcomes were considered: ‘vaccination against chlamydial abortion’, ‘vaccination against clostridial infections’, ‘vaccination against contagious agalactia’, ‘vaccination against contagious ecthyma’, ‘vaccination against foot-rot’, ‘vaccination against paratuberculosis’, ‘vaccination against bacterial pneumonia’, ‘vaccination against staphylococcal mastitis’ and ‘total number of optional vaccines administered’. Univariable and multivariable analyses were first performed to establish associations of each of the above outcomes with climatic variables. Then, the same approach was employed to assess the importance of climatic variables against health management- and human resources-related factors in the administration of vaccines in the farms of the study. Climatic variables had a higher association with vaccinations against infections in sheep flocks (26 associations) than in goat herds (9 associations) (p = 0.002) and in farms with semi-extensive or extensive management (32 associations) than in farms with intensive or semi-intensive management (8 associations) (p < 0.0001). In 26 cases (38.8% of all analyses evaluated), the climatic variables overshadowed the management- and human resources-related variables assessed as significant predictors for vaccination. In most cases, these referred to sheep flocks (nine cases) and farms with semi-extensive or extensive management (eight cases). For all eight infections, there were changes in the climatic variables found to be significant predictors from the 10-year dataset to the 2-year dataset. The results indicated that, in some cases, climate factors overshadowed factors traditionally considered for the formulation of vaccination programs. This points out the significance of taking into account climate conditions in the health management of small ruminant farms. Future studies can be focused on formulating vaccination programs in accordance with climate factors and also on setting the optimum season(s) for vaccination of animals based on the circulation of the pathogens, the risks for the development of diseases and the stage within the annual production cycle of the animals.

Descriptive network analysis and the influence of timescale on centrality and cohesion metrics from a system of between-herd dairy cow movements in Ontario, Canada

Previous research has demonstrated that static monthly networks of between-herd dairy cow movements in Ontario, Canada were highly fragmented, reducing potential for large-scale outbreaks. Extrapolating results from static networks can become problematic for diseases with an incubation period that exceeds the timescale of the network. The objectives of this research were to: 1) describe the networks of dairy cow movements in Ontario, and 2) describe the changes that occur among network analysis metrics when conducted at seven different timescales. Networks of dairy cow movements were created using Lactanet Canada milk recording data collected in Ontario between 2009 and 2018. Centrality and cohesion metrics were calculated after aggregating the data at seven timescales: weekly, monthly, semi-annual, annual, biennial, quinquennial, and decennial. There were 50,598 individual cows moved between Lactanet-enrolled farms, representing approximately 75% of provincially registered dairy herds. Most movements occurred over short distances (median = 39.18 km), with fewer long-range movements (maximum = 1150.80 km). The number of arcs increased marginally relative to the number of nodes with longer network timescales. Both mean out-degree, and mean clustering coefficients increased disproportionately with increasing timescale. Conversely, mean network density decreased with increasing timescale. The largest weak and strong components at the monthly timescale were small relative to the full network (267 and 4 nodes), whereas yearly networks had much higher values (2213 and 111 nodes). Higher relative connectivity in networks with longer timescales suggests pathogens with long incubation periods and animals with subclinical infection present increased potential for wide-spread disease transmission among dairy farms in Ontario. Careful consideration of disease-specific dynamics should be made when using static networks to model disease transmission among dairy cow populations.

A scoping review of foot-and-mouth disease risk, based on spatial and spatio-temporal analysis of outbreaks in endemic settings

Foot-and-mouth disease (FMD) is one of the most important transboundary animal diseases affecting livestock and wildlife species worldwide. Sustained viral circulation, as evidenced by serological surveys and the recurrence of outbreaks, suggests endemic transmission cycles in some parts of Africa, Asia and the Middle East. This is the result of a complex process in which multiple serotypes, multi-host interactions and numerous socio-epidemiological factors converge to facilitate disease introduction, survival and spread. Spatial and spatio-temporal analyses have been increasingly used to explore the burden of the disease by identifying high-risk areas, analysing temporal trends and exploring the factors that contribute to the outbreaks. We systematically retrieved spatial and spatial-temporal studies on FMD outbreaks to summarize variations on their methodological approaches and identify the epidemiological factors associated with the outbreaks in endemic contexts. Fifty-one studies were included in the final review. A high proportion of papers described and visualized the outbreaks (72.5%) and 49.0% used one or more approaches to study their spatial, temporal and spatio-temporal aggregation. The epidemiological aspects commonly linked to FMD risk are broadly categorizable into themes such as (a) animal demographics and interactions, (b) spatial accessibility, (c) trade, (d) socio-economic and (e) environmental factors. The consistency of these themes across studies underlines the different pathways in which the virus is sustained in endemic areas, with the potential to exploit them to design tailored evidence based-control programmes for the local needs. There was limited data linking the socio-economics of communities and modelled FMD outbreaks, leaving a gap in the current knowledge. A thorough analysis of FMD outbreaks requires a systemic view as multiple epidemiological factors contribute to viral circulation and may improve the accuracy of disease mapping. Future studies should explore the links between socio-economic and epidemiological factors as a foundation for translating the identified opportunities into interventions to improve the outcomes of FMD surveillance and control initiatives in endemic contexts.

Identification of diffusion routes of O/EA-3 topotype of foot-and-mouth disease virus in Africa and Western Asia between 1974 and 2019 - a phylogeographic analysis

Foot-and-mouth disease (FMD) affects the livestock industry and socioeconomic sustainability of many African countries. The success of FMD control programs in Africa depends largely on understanding the dynamics of FMD virus (FMDV) spread. In light of the recent outbreaks of FMD that affected the North-Western African countries in 2018 and 2019, we investigated the evolutionary phylodynamics of the causative serotype O viral strains all belonging to the East-Africa 3 topotype (O/EA-3). We analyzed a total of 489 sequences encoding the FMDV VP1 genome region generated from samples collected from 25 African and Western Asian countries between 1974 and 2019. Using Bayesian evolutionary models on genomic and epidemiological data, we inferred the routes of introduction and migration of the FMDV O/EA-3 topotype at the inter-regional scale. We inferred a mean substitution rate of 6.64 × 10^-3  nt/site/year and we predicted that the most recent common ancestor for our panel of samples circulated between February 1967 and November 1973 in Yemen, likely reflecting the epidemiological situation in under sampled cattle-exporting East African countries. Our study also reinforces the role previously described of Sudan and South Sudan as a frequent source of FMDVs spread. In particular, we identified two transboundary routes of O/EA-3 diffusion: the first from Sudan to North-East Africa, and from the latter into Israel and Palestine AT; a second from Sudan to Nigeria, Cameroon, and from there to further into West and North-West Africa. This study highlights the necessity to reinforce surveillance at an inter-regional scale in Africa and Western Asia, in particular along the identified migration routes for the implementation of efficient control measures in the fight against FMD.

Once a reservoir, always a reservoir? Seasonality affects the pathogen maintenance potential of amphibian hosts

Host species that can independently maintain a pathogen in a host community and contribute to infection in other species are important targets for disease management. However, the potential of host species to maintain a pathogen is not fixed over time, and an important challenge is understanding how within- and across-season variability in host maintenance potential affects pathogen persistence over longer time scales relevant for disease management (e.g., years). Here, we sought to understand the causes and consequences of seasonal infection dynamics in leopard frogs (Rana sphenocephala and R. pipiens) infected with the fungal pathogen Batrachochytrium dendrobatidis (Bd). We addressed three questions broadly applicable to seasonal host-parasite systems. First, to what degree are observed seasonal patterns in infection driven by temperature-dependent infection processes compared to seasonal host demographic processes? Second, how does seasonal variation in maintenance potential affect long-term pathogen persistence in multihost communities? Third, does high deterministic maintenance potential relate to the long-term stochastic persistence of pathogens in host populations with seasonal infection dynamics? To answer these questions, we used field data collected over three years on >1400 amphibians across four geographic locations, laboratory and mesocosm experiments, and a novel mathematical model. We found that the mechanisms that drive seasonal prevalence were different than those driving seasonal infection intensity. Seasonal variation in Bd prevalence was driven primarily by changes in host contact rates associated with breeding migrations to and from aquatic habitat. In contrast, seasonal changes in infection intensity were driven by temperature-induced changes in Bd growth rate. Using our model, we found that the maintenance potential of leopard frogs varied significantly throughout the year and that seasonal troughs in infection prevalence made it unlikely that leopard frogs were responsible for long-term Bd persistence in these seasonal amphibian communities, highlighting the importance of alternative pathogen reservoirs for Bd persistence. Our results have broad implications for management in seasonal host-pathogen systems, showing that seasonal changes in host and pathogen vital rates, rather than the depletion of susceptible hosts, can lead to troughs in pathogen prevalence and stochastic pathogen extirpation.

Potential Mechanisms of Transmission of Tick-Borne Viruses at the Virus-Tick Interface

Ticks (Acari; Ixodidae) are the second most important vector for transmission of pathogens to humans, livestock, and wildlife. Ticks as vectors for viruses have been reported many times over the last 100 years. Tick-borne viruses (TBVs) belong to two orders (Bunyavirales and Mononegavirales) containing nine families (Bunyaviridae, Rhabdoviridae, Asfarviridae, Orthomyxovirida, Reoviridae, Flaviviridae, Phenuviridae, Nyamiviridae, and Nairoviridae). Among these TBVs, some are very pathogenic, causing huge mortality, and hence, deserve to be covered under the umbrella of one health. About 38 viral species are being transmitted by <10% of the tick species of the families Ixodidae and Argasidae. All TBVs are RNA viruses except for the African swine fever virus from the family Asfarviridae. Tick-borne viral diseases have also been classified as an emerging threat to public health and animals, especially in resource-poor communities of the developing world. Tick-host interaction plays an important role in the successful transmission of pathogens. The ticks' salivary glands are the main cellular machinery involved in the uptake, settlement, and multiplication of viruses, which are required for successful transmission into the final host. Furthermore, tick saliva also participates as an augmenting tool during the physiological process of transmission. Tick saliva is an important key element in the successful transmission of pathogens and contains different antimicrobial proteins, e.g., defensin, serine, proteases, and cement protein, which are key players in tick-virus interaction. While tick-virus interaction is a crucial factor in the propagation of tick-borne viral diseases, other factors (physiological, immunological, and gut flora) are also involved. Some immunological factors, e.g., toll-like receptors, scavenger receptors, Janus-kinase (JAK-STAT) pathway, and immunodeficiency (IMD) pathway are involved in tick-virus interaction by helping in virus assembly and acting to increase transmission. Ticks also harbor some endogenous viruses as internal microbial faunas, which also play a significant role in tick-virus interaction. Studies focusing on tick saliva and its role in pathogen transmission, tick feeding, and control of ticks using functional genomics all point toward solutions to this emerging threat. Information regarding tick-virus interaction is somewhat lacking; however, this information is necessary for a complete understanding of transmission TBVs and their persistence in nature. This review encompasses insight into the ecology and vectorial capacity of tick vectors, as well as our current understanding of the predisposing, enabling, precipitating, and reinforcing factors that influence TBV epidemics. The review explores the cellular, biochemical, and immunological tools which ensure and augment successful evading of the ticks' defense systems and transmission of the viruses to the final hosts at the virus-vector interface. The role of functional genomics, proteomics, and metabolomics in profiling tick-virus interaction is also discussed. This review is an initial attempt to comprehensively elaborate on the epidemiological determinants of TBVs with a focus on intra-vector physiological processes involved in the successful execution of the docking, uptake, settlement, replication, and transmission processes of arboviruses. This adds valuable data to the existing bank of knowledge for global stakeholders, policymakers, and the scientific community working to devise appropriate strategies to control ticks and TBVs.

Ecological and Anthropogenic Spatial Gradients Shape Patterns of Dispersal of Foot-and-Mouth Disease Virus in Uganda

Using georeferenced phylogenetic trees, phylogeography allows researchers to elucidate interactions between environmental heterogeneities and patterns of infectious disease spread. Concordant with the increasing availability of pathogen genetic sequence data, there is a growing need for tools to test epidemiological hypotheses in this field. In this study, we apply tools traditionally used in ecology to elucidate the epidemiology of foot-and-mouth disease virus (FMDV) in Uganda. We analyze FMDV serotype O genetic sequences and their corresponding spatiotemporal metadata from a cross-sectional study of cattle. We apply step selection function (SSF) models, typically used to study wildlife habitat selection, to viral phylogenies to show that FMDV is more likely to be found in areas of low rainfall. Next, we use a novel approach, a resource gradient function (RGF) model, to elucidate characteristics of viral source and sink areas. An RGF model applied to our data reveals that areas of high cattle density and areas near livestock markets may serve as sources of FMDV dissemination in Uganda, and areas of low rainfall serve as viral sinks that experience frequent reintroductions. Our results may help to inform risk-based FMDV control strategies in Uganda. More broadly, these tools advance the phylogenetic toolkit, as they may help to uncover patterns of spread of other organisms for which genetic sequences and corresponding spatiotemporal metadata exist.

Spatio-temporal cluster analysis and transmission drivers for Peste des Petits Ruminants in Uganda

Peste des Petits Ruminants (PPR) is a transboundary, highly contagious, and fatal disease of small ruminants. PPR causes global annual economic losses of between USD 1.5-2.0 billion across more than 70 affected countries. Despite the commercial availability of effective PPR vaccines, lack of financial and technical commitment to PPR control coupled with a dearth of refined PPR risk profiling data in different endemic countries has perpetuated PPR virus transmission. In Uganda, over the past five years, PPR has extended from north-eastern Uganda (Karamoja) with sporadic incursions in other districts /regions. To identify disease cluster hotspot trends that would facilitate the design and implementation of PPR risk-based control methods (including vaccination), we employed the space-time cube approach to identify trends in the clustering of outbreaks in neighbouring space-time cells using confirmed PPR outbreak report data (2007-2020). We also used negative binomial and logistic regression models and identified high small ruminant density, extended road length, low annual precipitation and high soil water index as the most important drivers of PPR in Uganda. The study identified (with 90 - 99% confidence) five PPR disease hotspot trend categories across subregions of Uganda. Diminishing hotspots were identified in the Karamoja region whereas consecutive, sporadic, new, and emerging hotspots were identified in central and southwestern districts of Uganda. Inter-district and cross-border small ruminant movement facilitated by longer road stretches and animal comingling precipitate PPR outbreaks as well as PPR virus spread from its initial Karamoja focus to the central and south-western Uganda. There is therefore urgent need to prioritize considerable vaccination coverage to obtain the required herd immunity among small ruminants in the new hotspot areas to block transmission to further emerging hotspots. Findings of this study provide a basis for more robust timing and prioritization of control measures including vaccination. This article is protected by copyright. All rights reserved.

Water sources aggregate parasites with increasing effects in more arid conditions

Shifts in landscape heterogeneity and climate can influence animal movement in ways that profoundly alter disease transmission. Water sources that are foci of animal activity have great potential to promote disease transmission, but it is unknown how this varies across a range of hosts and climatic contexts. For fecal-oral parasites, water resources can aggregate many different hosts in small areas, concentrate infectious material, and function as disease hotspots. This may be exacerbated where water is scarce and for species requiring frequent water access. Working in an East African savanna, we show via experimental and observational methods that water sources increase the density of wild and domestic herbivore feces and thus, the concentration of fecal-oral parasites in the environment, by up to two orders of magnitude. We show that this effect is amplified in drier areas and drier periods, creating dynamic and heterogeneous disease landscapes across space and time. We also show that herbivore grazing behaviors that expose them to fecal-oral parasites often increase at water sources relative to background sites, increasing potential parasite transmission at these hotspots. Critically, this effect varies by herbivore species, with strongest effects for two animals of concern for conservation and development: elephants and cattle.

Livestock movement informs the risk of disease spread in traditional production systems in East Africa

In Africa, livestock are important to local and national economies, but their productivity is constrained by infectious diseases. Comprehensive information on livestock movements and contacts is required to devise appropriate disease control strategies; yet, understanding contact risk in systems where herds mix extensively, and where different pathogens can be transmitted at different spatial and temporal scales, remains a major challenge. We deployed Global Positioning System collars on cattle in 52 herds in a traditional agropastoral system in western Serengeti, Tanzania, to understand fine-scale movements and between-herd contacts, and to identify locations of greatest interaction between herds. We examined contact across spatiotemporal scales relevant to different disease transmission scenarios. Daily cattle movements increased with herd size and rainfall. Generally, contact between herds was greatest away from households, during periods with low rainfall and in locations close to dipping points. We demonstrate how movements and contacts affect the risk of disease spread. For example, transmission risk is relatively sensitive to the survival time of different pathogens in the environment, and less sensitive to transmission distance, at least over the range of the spatiotemporal definitions of contacts that we explored. We identify times and locations of greatest disease transmission potential and that could be targeted through tailored control strategies.

Examining local perspectives on the influence of climate change on the health of Hamer pastoralists and their livestock in Ethiopia

This study explores the perceived influence of climate change on the health of Hamer pastoralists and their livestock in south-western Ethiopia. A combination of focus group discussions and key informant interviews were conducted with Hamer communities as well as local health workers, animal health workers and non-governmental organisation (NGO) staff. Thematic framework analysis was used to analyse the data. Reductions in rangeland, erratic rainfall, recurrent droughts and loss of seasonality were perceived to be the biggest climate challenges influencing the health and livelihoods of the Hamer. Communities were travelling greater distances to access sufficient grazing lands, and this was leading to livestock deaths and increases in ethnic violence. Reductions in suitable rangeland were also precipitating disease outbreaks in animals due to increased mixing of different herds. Negative health impacts in the community stemmed indirectly from decreases in livestock production, uncertain crop harvests and increased water scarcity. The remoteness of grazing lands has resulted in decreased availability of animal milk, contributing to malnutrition in vulnerable groups, including children. Water scarcity in the region has led to utilisation of unsafe water sources resulting in diarrhoeal illnesses. Further, seasonal shifts in climate-sensitive diseases such as malaria were also acknowledged. Poorly resourced healthcare facilities with limited accessibility combined with an absence of health education has amplified the community’s vulnerability to health challenges. The resilience and ambition for livelihood diversification amongst the Hamer was evident. The introduction of camels, increase in permanent settlements and new commercial ideas were transforming their livelihood strategies. However, the Hamer lack a voice to express their perspectives, challenges and ambitions. There needs to be collaborative dynamic dialogue between pastoral communities and the policy-makers to drive sustainable development in the area without compromising the values, traditions and knowledge of the pastoralists.

Interactive effects of biological, human and environmental factors on tick loads in Boran cattle in tropical drylands

Background

Tick-borne diseases (TBDs) are a serious threat to humans, wildlife and livestock, and cause severe economic losses in many tropical drylands. The effective control of TBDs has been constrained by limited understanding of what determines tick loads in animals. We tested interactive effects of several biological factors (sex, age and body condition), one environmental factor (rainfall) and one human factor (management type) on tick loads in animals.

Methods

We collected ticks on animals at four sampling sites in the semi-arid savanna area of Laikipia County, Kenya, of which two are commercial ranches and the other two are open pastoral grazing areas. From 2017 to 2019, we collected a total of 2038 ticks from 619 domestic animals from various cattle and camel herds and from 79 tranquilised wild animals.

Results

Generally, wild herbivores (zebras, rhinos and elephants) had higher tick loads than domestic animals. As 83% of the tick samples were taken from Boran cattle, we analysed tick load in these cattle in more detail. Boran cattle had high tick loads in the wet season, especially those animals in poor condition. No differences were found between female and male cattle, regardless of season. The calves had high tick loads during both the wet and dry seasons, whereas the sub-adult and adult cattle had less ticks during the dry season. Cattle on the intensively managed ranches had lower tick load than those in the transhumant management system.

Conclusion

These findings highlight the importance of establishing effective control of ticks on domestic animals in transhumant management systems as tick loads were high on these animals in both the wet and dry season.

Graphic abstract

Animal movement in a pastoralist population in the Maasai Mara Ecosystem in Kenya and implications for pathogen spread and control

Livestock movements are important drivers for infectious disease transmission. However, paucity of such data in pastoralist communities in rangeland ecosystems limits our understanding of their dynamics and hampers disease surveillance and control. The aim of this study was to investigate animal movement networks in a pastoralist community in Kenya, and assess network-based strategies for disease control. We used network analysis to characterize five types of between-village animal movement networks. We then evaluated implications of these networks for disease spread and control by quantifying topological changes in the network associated with targeted and random removal of nodes. To construct these networks, data were collected using standardized questionnaires (N = 165 households) from communities living within the Maasai Mara Ecosystem in southwestern Kenya. Our analyses show that the Maasai Mara National Reserve (MMNR), a protected wildlife area, was critical for maintaining village connectivity in the agistment network (dry season grazing), with MMNR-adjacent villages being highly utilized during the dry season. In terms of disease dynamics, the network-based basic reproduction number, R₀, was sufficient to allow disease invasion in all the five networks, and removal of villages based on degree or betweenness was not efficient in reducing R₀. However, we show that villages with high degree or betweenness may play an important role in maintaining network connectivity, which may not be captured by assessment of R₀ alone. Such villages may function as potential "firebreaks." For example, targeted removal of highly connected village nodes was more effective at fragmenting each network than random removal of nodes, indicating that network-based targeting of interventions such as vaccination could potentially disrupt transmission pathways in the ecosystem. In conclusion, this work shows that animal movements have the potential to shape patterns of disease transmission in this ecosystem, with targeted interventions being a practical and efficient measure for disease control.

Associations between monthly rainfall and mortality in cattle due to East Coast fever, anaplasmosis and babesiosis

Weather conditions can impact infectious disease transmission, causing mortalities in humans, wild and domestic animals. Although rainfall in dry tropical regions is highly variable over the year, rainfall is thought to play an important role in the transmission of tick-borne diseases. Whether variation in rainfall affects disease-induced mortalities, is, however, poorly understood. Here, we use long-term data on monthly rainfall and Boran cattle mortality (1998-2017) to investigate associations between within-year variation in rainfall and cattle mortalities due to East Coast fever (ECF), anaplasmosis and babesiosis in Laikipia, Kenya, using ARIMAX modelling. Results show a negative correlation between monthly rainfall and cattle mortality for ECF and anaplasmosis, with a lag effect of 2 and 6 months, respectively. There was no association between babesiosis-induced mortalities and monthly rainfall. The results of this study suggest that control of the tick-borne diseases ECF and anaplasmosis to reduce mortalities should be intensified during rainy periods after the respective estimated time lags following dry periods.

The role of African buffalo in the epidemiology of foot-and-mouth disease in sympatric cattle and buffalo populations in Kenya

Quantitative knowledge on the contribution of African buffalo to the epidemiology of foot-and-mouth disease virus (FMDV) in East Africa is lacking, and this information is essential for the design of control programs in the region. The objective of this study was to investigate the epidemiology of FMDV in buffalo, including the role of buffalo in the circulation of FMDV in livestock populations. We collected blood and oropharyngeal fluids from 92 wild buffalo and 98 sympatric cattle in central Kenya and sequenced the virus' VP1 coding region. We show that FMDV has a high seroprevalence in buffalo (~77%) and targeted cattle (~93%). In addition, we recovered 80 FMDV sequences from buffalo, all of which were serotype SAT1 and SAT2, and four serotype O and A sequences from sympatric cattle. Notably, six individual buffalo were co-infected with both SAT1 and SAT2. Amongst sympatric buffalo and cattle, the fact that no SAT1 or 2 sequences were found in cattle suggests that transmission of FMDV from buffalo to sympatric cattle is rare. Similarly, there was no evidence that serotype O and A sequences found in cattle were transmitted to buffalo. However, viruses from FMDV outbreaks in cattle elsewhere in Kenya were closely related to SAT1 and SAT2 viruses found in buffalo in this study, suggesting that FMDV in cattle and buffalo do not constitute independently evolving populations. We also show that fine-scale geographic features, such as rivers, influence the circulation of FMDV in buffalo and that social segregation amongst sympatric herds may limit between-herd transmission. These results significantly advance our understanding of the ecology and molecular epidemiology of FMDV at wildlife-livestock interfaces in East Africa and will help to inform the design of control and surveillance strategies for this disease in the region.

Trade-offs with telemetry-derived contact networks for infectious disease studies in wildlife

Network analysis of infectious disease in wildlife can reveal traits or individuals critical to pathogen transmission and help inform disease management strategies. However, estimates of contact between animals are notoriously difficult to acquire. Researchers commonly use telemetry technologies to identify animal associations; but such data may have different sampling intervals and often captures a small subset of the population. The objectives of this study were to outline best practices for telemetry sampling in network studies of infectious disease by determining (1) the consequences of telemetry sampling on our ability to estimate network structure, (2) whether contact networks can be approximated using purely spatial contact definitions, and (3) how wildlife spatial configurations may influence telemetry sampling requirements.We simulated individual movement trajectories for wildlife populations using a home range-like movement model, creating full location datasets and corresponding "complete" networks. To mimic telemetry data, we created "sample" networks by subsampling the population (10-100% of individuals) with a range of sampling intervals (every minute to every three days). We varied the definition of contact for sample networks, using either spatiotemporal or spatial overlap, and varied the spatial configuration of populations (random, lattice, or clustered). To compare complete and sample networks, we calculated seven network metrics important for disease transmission and assessed mean ranked correlation coefficients and percent error between complete and sample network metrics.Telemetry sampling severely reduced our ability to calculate global node-level network metrics, but had less impact on local and network-level metrics. Even so, in populations with infrequent associations, high intensity telemetry sampling may still be necessary. Defining contact in terms of spatial overlap generally resulted in overly connected networks, but in some instances, could compensate for otherwise coarse telemetry data.By synthesizing movement and disease ecology with computational approaches, we characterized trade-offs important for using wildlife telemetry data beyond ecological studies of individual movement, and found that careful use of telemetry data has the potential to inform network models. Thus, with informed application of telemetry data, we can make significant advances in leveraging its use for a better understanding and management of wildlife infectious disease.

Spatial distribution and risk factors for foot and mouth disease virus in Uganda: Opportunities for strategic surveillance

Foot-and-mouth disease virus (FMDV) has a substantial impact on cattle populations in Uganda, causing short- and long-term production losses and hampering local and international trade. Although FMDV has persisted in Uganda for at least 60 years, its epidemiology there and in other endemic settings remains poorly understood. Here, we utilized a large-scale cross-sectional study of cattle to elucidate the dynamics of FMDV spread in Uganda. Sera samples (n = 14,439) from 211 herds were analyzed for non-structural protein reactivity, an indication of past FMDV exposure. Serological results were used to determine spatial patterns, and a Bayesian multivariable logistic regression mixed model was used to identify risk factors for FMDV infection. Spatial clustering of the disease was evident, with higher risk demonstrated near international borders. Additionally, high cattle density, low annual rainfall, and pastoralism were associated with increased likelihood of FMD seropositivity. These results provide insights into the complex epidemiology of FMDV in Uganda and will help inform refined control strategies in Uganda and other FMDV-endemic settings.

Rabies-induced behavioural changes are key to rabies persistence in dog populations: Investigation using a network-based model

Canine rabies was endemic pre-urbanisation, yet little is known about how it persists in small populations of dogs typically seen in rural and remote regions. By simulating rabies outbreaks in such populations (50-90 dogs) using a network-based model, our objective was to determine if rabies-induced behavioural changes influence disease persistence. Behavioural changes-increased bite frequency and increased number or duration of contacts (disease-induced roaming or paralysis, respectively)-were found to be essential for disease propagation. Spread occurred in approximately 50% of model simulations and in these, very low case rates (2.0-2.6 cases/month) over long durations (95% range 20-473 days) were observed. Consequently, disease detection is a challenge, risking human infection and spread to other communities via dog movements. Even with 70% pre-emptive vaccination, spread occurred in >30% of model simulations (in these, median case rate was 1.5/month with 95% range of 15-275 days duration). We conclude that the social disruption caused by rabies-induced behavioural change is the key to explaining how rabies persists in small populations of dogs. Results suggest that vaccination of substantially greater than the recommended 70% of dog populations is required to prevent rabies emergence in currently free rural areas.

Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies

Livestock movements are an important mechanism of infectious disease transmission. Where these are well recorded, network analysis tools have been used to successfully identify system properties, highlight vulnerabilities to transmission, and inform targeted surveillance and control. Here we highlight the main uses of network properties in understanding livestock disease epidemiology and discuss statistical approaches to infer network characteristics from biased or fragmented datasets. We use a 'hurdle model' approach that predicts (i) the probability of movement and (ii) the number of livestock moved to generate synthetic 'complete' networks of movements between administrative wards, exploiting routinely collected government movement permit data from northern Tanzania. We demonstrate that this model captures a significant amount of the observed variation. Combining the cattle movement network with a spatial between-ward contact layer, we create a multiplex, over which we simulated the spread of 'fast' ( R0 = 3) and 'slow' ( R0 = 1.5) pathogens, and assess the effects of random versus targeted disease control interventions (vaccination and movement ban). The targeted interventions substantially outperform those randomly implemented for both fast and slow pathogens. Our findings provide motivation to encourage routine collection and centralization of movement data to construct representative networks. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Network analyses of transhumance movements and simulations of foot-and-mouth disease virus transmission among mobile livestock in Cameroon

Foot-and-mouth disease (FMD) affects cloven-hoofed livestock and agricultural economies worldwide. Analyses of the 2001 FMD outbreak in the United Kingdom informed how livestock movement contributed to disease spread. However, livestock reared in other locations use different production systems that might also influence disease dynamics. Here, we investigate a livestock production system known as transhumance, which is the practice of moving livestock between seasonal grazing areas. We built mechanistic models using livestock movement data from the Far North Region of Cameroon. We represented these data as a dynamic network over which we simulated disease transmission and examined three questions. First, we asked what were characteristics of simulated FMDV transmission across a transhumant pastoralist system. Second, we asked how simulated FMDV transmission across a transhumant pastoralist system differed from transmission across this same population held artificially stationary, thereby revealing the effect of movement on disease dynamics. Third, we asked if disease simulations on well-studied theoretical networks are similar to disease simulations on this empirical dynamic network. The results show that the empirical dynamic network was sparsely connected except for an eight-week period in September and October when pastoralists move from rainy season to dry season grazing areas. The mean epidemic size across all 3,744 simulations was 99.9% and the mean epidemic duration was 1.45 years. Disease simulations across the static network showed a smaller mean epidemic size (27.6%) and a similar epidemic duration (1.5 years). Epidemics simulated on theoretical networks showed similar final epidemic sizes (100%) and different mean durations. Our simulations indicate that transhumant livestock systems have the potential to host FMDV outbreaks that affect almost all livestock and last longer than a year. Furthermore, our comparison of empirical and theoretical networks underscores the importance of using empirical data to understand the role of mobility in the transmission of infectious diseases.

Seasonal differences in baseline innate immune function are better explained by environment than annual cycle stage in a year-round breeding tropical songbird

Seasonal variation in innate immunity is often attributed to either temporal environmental variation or to life-history trade-offs that arise from specific annual cycle stages but decoupling them is difficult in natural populations. Here, we effectively decouple seasonal environmental variation from annual cycle stage effects by exploiting cross-seasonal breeding and moult in the tropical Common Bulbul Pycnonotus barbatus. We test how annual cycle stage interacts with a key seasonal environmental variable, rainfall, to determine immunity at population and individual level. If immune challenge varies with precipitation, we might expect immune function to be higher in the wet season due to increased environmental productivity. If breeding or moult imposes resource constraints on birds, depending on or independent of precipitation, we might expect lower immune indices during breeding or moult. We sampled blood from 818 birds in four annual cycle stage categories: breeding, moult, simultaneous breeding and moulting, or neither. We quantified indices of innate immunity (haptoglobin, nitric oxide (NOx ) and ovotransferrin concentrations, and haemagglutination and haemolysis titres) over two annual cycles of wet and dry seasons. Environment (but not annual cycle stage or interactions between both) explained variation in all immune indices, except NOx . NOx concentration differed between annual cycle stages but not between seasons. However, within the wet season, haptoglobin, NOx , ovotransferrin and haemolysis differed significantly between breeding and non-breeding females. Aside from some recorded inconsistencies, population level results were largely similar to results within individuals that were measured repeatedly. Unexpectedly, most immune indices were higher in the dry season and during breeding. Higher immune indices may be explained if fewer or poorer quality resources force birds to increase social contact, thereby exposing individuals to novel antigens and increased infection risk, independently of environmental productivity. Breeding birds may also show higher immunity if less immune-competent and/or infected females omit breeding. We conclude that seasonal environmental variation impacts immunity more directly in natural animal populations than via resource trade-offs. In addition, immune indices were more often variable within than among individuals, but some indices are characteristic of individuals, and so may offer selective advantages if heritable.

Molecular detection and phylogeny of bovine viral diarrhea virus 1 among cattle herds from Northeast, Southeast, and Midwest regions, Brazil

We examined the circulating BVDV species and genotypes among cattle herds from Northeast, Southeast, and Midwest regions in Brazil. A total of 77 animals tested positive through standard PCR. Phylogenetic analyses revealed the presence of BVDV-1a, highlighting the need for better surveillance strategies to prevent BVDV spread in the country.

The spread of bovine tuberculosis in Canadian shared pastures: Data, model, and simulations

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is a chronic disease typical of cattle. Nonetheless, it can affect many mammals including humans, making it one of the most widespread zoonotic diseases worldwide. In industrialized countries, the main pathways of introduction of bTB into a herd are animal trade and contact with infected wildlife. In addition, for slow-spreading diseases with a long latent period such as bTB, shared seasonal pastures might be a between-herd transmission pathway, indeed farmers might unknowingly send infected animals to the pasture, since clinical signs are rarely evident in early infection. In this study, we developed a dynamic stochastic model to represent the spread of bTB in pastures. This was tailored to Canadian cow-calf herds, as we calibrated the model with data sourced from a recent bTB outbreak in Western Canada. We built a model for a herd with seasonal management, characterized by its partition into a group staying in the main facility and the remaining group(s) moving to summer pastures. We used this model to estimate the time of the first introduction of bTB into the herd. Furthermore, we expanded the model to include herds categorized as high-risk contacts with the index herd, in order to estimate the potential for disease spread on shared pastures. Finally, we explored two control scenarios to be applied to high-risk farms after the outbreak detection. Our results showed that the first introduction likely happened 3 to 5 years prior to the detection of the index herd, and the probability of bTB spreading in pastures was low, but not negligible. Nevertheless, the surveillance system currently in place was effective to detect potential outbreaks.

The social networks of free-roaming domestic dogs in island communities in the Torres Strait, Australia

Social structure creates heterogeneity of interactions between individuals, thus influencing infectious disease spread. The objective of this study was to describe and characterise the social structure of free-roaming dog populations in three communities in the Torres Strait, Australia. Dogs in Kubin, Saibai, and Warraber communities were collared with GPS units that recorded locations at 15 s intervals for up to 1 week, and datasets were obtained from 24 (62% of the dog population), 23 (53%) and 21 (51%) dogs in each community, respectively. An association (potential contact) between dogs was defined as proximity within a spatio-temporal window of 5 m for 30 s. Networks were constructed for each dog population: 1. nodes were individual dogs, and 2. edges were weighted according to the duration of spatio-temporal association between pairs of dogs as a proportion of their simultaneous time monitored. Network statistics were calculated for each population and the robustness of networks to the duration of association between pairs of dogs was assessed in terms of efficiency, degree distribution and fragmentation (number of components). Dog social networks had 'small-world' structures, with characteristic clustering and low average shortest-path length between individuals. Overall, all three networks were highly connected in terms of degree distribution and global and local efficiency, but the median tie strength (2-13.5 min) was low. Centrality and the duration of association (tie-strength) between dogs were significantly different between communities. The Kubin network was least robust to fragmentation when ties of short duration were successively removed (14 components with minimum tie strength of 2 h). In contrast, the Warraber dog network was relatively robust with 7 components at minimum tie strength of 2 h as well as high local efficiency within components. We conclude that whilst infectious disease that requires a short duration of contact for transmission is likely to spread rapidly between and within clusters in all three networks in this study, fragmentation of networks - once ties of short duration are removed - is likely to limit spread of disease that requires a longer duration of direct contact. The network information in this study is useful as a foundation for disease spread modelling and to investigate control strategies such as movement restrictions in dog populations.

Spatial and temporal distribution of foot-and-mouth disease in four districts situated along the Uganda-Tanzania border: Implications for cross-border efforts in disease control

Foot-and-mouth disease (FMD) is one of the major trans-boundary animal diseases in East Africa causing economic loss to farmers and other stakeholders in the livestock industry. Foot-and-mouth disease occurs widely in both Uganda and Tanzania with annual outbreaks recorded. With the recent introduction of the Progressive Control Pathway for FMD control (PCP-FMD) in eastern Africa, knowledge of the spatial and temporal distribution of FMD at the border area between Uganda and Tanzania is helpful in framing engagement with the initial stages of the PCP. Retrospective data collected between 2011 and 2016 from four districts located along the border areas of Uganda and Tanzania, recorded 23 and 59 FMD outbreaks, respectively, for the entire study period. Analysis showed that 46% of the 82 recorded outbreaks occurred in 20% of sub-counties and wards immediately neighbouring the Uganda–Tanzania border and 69.5% of the outbreaks occurred during the dry months. While the serotypes of the FMD virus responsible for most outbreaks reported in this region were not known, previous research reported South African Territory (SAT) 1, SAT 2 and O to be the serotypes in circulation. The results from this study provide evidence of the endemic status of FMD on the Uganda–Tanzania border and emphasise that the border area should be given due consideration during FMD control drives and that cross-border coordination should be prioritised. With the limited data on circulating serotypes in this area, there is a need for more vigilance on FMD case detection, laboratory diagnostic confirmation and provision of more complete documentation of outbreaks. This work further recommends more studies on cross-border livestock movement coupled with phylogenetics in order to understand the spread of the FMD in the border area.

Seasonal Differences in Animal Welfare Assessment of Family Farming Dual-Purpose Cattle Raised under Tropical Conditions

Simple Summary

Family-run cattle farms in the tropics deal with two distinct seasons, the dry and the rainy, where features such as resources, diseases and climate are variable. Nevertheless, an acceptable level of animal welfare must be maintained throughout the year. The purpose of this study was to investigate whether there were animal welfare issues at farms affected by either the dry or the rainy season. Forty-five dual-purpose family farms in the Mexican tropics were assessed via the Welfare Quality^® protocol. The animal welfare assessment on these farms obtained better results during the dry season, hence the season presenting a greater risk to animal welfare of dual-purpose cattle raised under tropical conditions is the rainy season. However, there were management-related differences observed between the two seasons, and the dry season also had some animal welfare threats. The fact that farms scored higher during the dry season is possibly the result of farmer awareness, leading to modification of their systems to provide animals with the necessary inputs to meet their production needs. If these modifications, such as providing supplementary feed and water points were not fulfilled, then welfare conditions might have been jeopardized.

Abstract

Conditions on farms in the tropics can differ greatly depending on the season of the year. Characteristics such as disease prevalence, climate and availability of resources may not be constant all year around; however an acceptable level of animal welfare must be maintained throughout the year. Since it is neither practical nor economically feasible to perform several assessments per year, the purpose of this study was to define whether there were animal welfare issues at farms that were affected by the season to identify which season would present a greater risk to animal welfare, using a risk-based approach. Forty-five dual-purpose family farms in the Mexican tropics were assessed via the Welfare Quality^® protocol. During the rainy season, 2.2% of the farms were classified as excellent, 57.8% as enhanced, 31.1% as acceptable and 8.9% as unclassified. In the dry season, 31.1% were classified as excellent, 68.9% as enhanced and none of the farms were categorized as acceptable or unclassified. Consequently, the season which presented the greatest risk to animal welfare of dual-purpose cattle raised under tropical conditions was the rainy season. However, there were management-related differences observed between the two seasons and the dry season also had some animal welfare threats. The fact that farms scored higher during the dry season is possibly the result of farmer awareness, leading to modification of their systems to provide animals with the necessary inputs to meet their production needs. If these modifications were not fulfilled, then welfare conditions might have been jeopardized.