Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.John RS

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    Spatial risk of pathogen transmission from cattle to vulnerable and endangered wild bovids in Thailand
    (Wiley Periodicals LLC on behalf of Society for Conservation Biology, 2025-08-12) Horpiencharoen W; Marshall JC; Muylaert RL; John RS; Hayman DTS
    The interaction between livestock and wildlife causes challenges for wildlife conservation and public health. Mapping interface areas is essential for prioritizing disease surveillance, implementing mitigation measures, and developing targeted control programs to protect threatened wildlife. We used spatial overlays of habitat suitability to predict interface areas with high risk of pathogen transmission for three Thai wild bovids (gaur [Bos gaurus], banteng [Bos javanicus] and wild water buffalo [Bubalus arnee]) and domestic cattle. We assumed that domestic cattle are the reservoir of important bovine infectious diseases and that high cattle density is a proxy for a higher transmission risk. We calculated the interface inside and outside Thai protected areas and classified these by land use types. Then, we counted the number of bovine infectious disease occurrences reported in high-risk areas. Our study indicated that the highest risk areas for these species are at the forest edges where high habitat suitability and cattle densities overlap. Suitable habitats for wild water buffalo had the largest proportion of high-risk areas (9%), while gaur and banteng had similar risk areas (4%). Kuiburi National Park had the largest risk area (274 km2) for gaur and banteng, whereas the largest risk area for wild water buffalo overlapped with Huai Thabthan-Had Samran by 126 km2. Cropland and unclassified forests had the highest percentage of interface areas, indicating a higher risk of pathogen transmission. Our results highlight how habitat suitability analyses could help infectious disease prevention and control strategies and may also support wild bovid conservation initiatives.
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    Land Use Change and Infectious Disease Emergence
    (John Wiley and Sons, Inc on behalf of the American Geophysical Union, 2025-06-01) Rulli MC; D’Odorico P; Galli N; John RS; Muylaert RL; Santini M; Hayman DTS
    Major infectious diseases threatening human health are transmitted to people from animals or by arthropod vectors such as insects. In recent decades, disease outbreaks have become more common, especially in tropical regions, including new and emerging infections that were previously undetected or unknown. Even though there is growing awareness that altering natural habitats can lead to disease outbreaks, the link between land use change and emerging diseases is still often overlooked and poorly understood. Land use change typically destroys natural habitat and alters landscape composition and configuration, thus altering wildlife population dynamics, including those of pathogen hosts, domesticated (often intermediary) hosts, infectious agents, and their vectors. Moreover, land use changes provide opportunities for human exposure to direct contact with wildlife, livestock, and disease-carrying vectors, thereby increasing pathogen spillover from animals to humans. Here we explore the nexus between human health and land use change, highlighting multiple pathways linking emerging disease outbreaks and deforestation, forest fragmentation, urbanization, agricultural expansion, intensified farming systems, and concentrated livestock production. We connect direct and underlying drivers of land use change to human health outcomes related to infectious disease emergence. Despite growing evidence of land-use induced spillover, strategies to reduce the risks of emerging diseases are often absent from discussions on sustainable food systems and land management. A “One Health” perspective—integrating human, animal, and environmental health—provides a critical yet often-overlooked dimension for understanding the health impacts of land use change.
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    Impact of Infectious Diseases on Wild Bovidae Populations in Thailand: Insights from Population Modelling and Disease Dynamics
    (2023-08-31) Horpiencharoen W; Marshall JC; Muylaert RL; John RS; Hayman DTS
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    Mapping threatened Thai bovids provides opportunities for improved conservation outcomes in Asia
    (2023-08-27) Horpiencharoen W; Muylaert RL; Marshall JC; John RS; Lynam AJ; Riggio A; Godfrey A; Ngoprasert D; Gale GA; Ash E; Bisi F; Cremonesi G; Clements GR; Yindee M; Shwe NM; Pin C; Gray TNE; Aung SS; Nakbun S; Manka SG; Steinmetz R; Phoonjampa R; Seuaturien N; Phumanee W; Hayman DTS
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    Mapping threatened Thai bovids provides opportunities for improved conservation outcomes in Asia.
    (The Royal Society, 2024-09-25) Horpiencharoen W; Muylaert RL; Marshall JC; John RS; Lynam AJ; Riggio A; Godfrey A; Ngoprasert D; Gale GA; Ash E; Bisi F; Cremonesi G; Clements GR; Yindee M; Shwe NM; Pin C; Gray TNE; Aung SS; Nakbun S; Manka SG; Steinmetz R; Phoonjampa R; Seuaturien N; Phumanee W; Hayman DTS
    Wild bovids provide important ecosystem functions as seed dispersers and vegetation modifiers. Five wild bovids remain in Thailand: gaur (Bos gaurus), banteng (Bos javanicus), wild water buffalo (Bubalus arnee), mainland serow (Capricornis sumatraensis) and Chinese goral (Naemorhedus griseus). Their populations and habitats have declined substantially and become fragmented by land-use change. We use ecological niche models to quantify how much potential suitable habitat for these species remains within protected areas in Asia and then specifically Thailand. We combined species occurrence data from several sources (e.g. mainly camera traps and direct observation) with environmental variables and species-specific and single, large accessible areas in ensemble models to generate suitability maps, using out-of-sample predictions to validate model performance against new independent data. Gaur, banteng and buffalo models showed reasonable model accuracy throughout the entire distribution (greater than or equal to 62%) and in Thailand (greater than or equal to 80%), whereas serow and goral models performed poorly for the entire distribution and in Thailand, though 5 km movement buffers markedly improved the performance for serow. Large suitable areas were identified in Thailand and India for gaur, Cambodia and Thailand for banteng and India for buffalo. Over 50% of suitable habitat is located outside protected areas, highlighting the need for habitat management and conflict mitigation outside protected areas.
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    Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots.
    (Springer Nature Limited, 2023-10-27) Muylaert RL; Wilkinson DA; Kingston T; D'Odorico P; Rulli MC; Galli N; John RS; Alviola P; Hayman DTS
    The emergence of SARS-like coronaviruses is a multi-stage process from wildlife reservoirs to people. Here we characterize multiple drivers-landscape change, host distribution, and human exposure-associated with the risk of spillover of zoonotic SARS-like coronaviruses to help inform surveillance and mitigation activities. We consider direct and indirect transmission pathways by modeling four scenarios with livestock and mammalian wildlife as potential and known reservoirs before examining how access to healthcare varies within clusters and scenarios. We found 19 clusters with differing risk factor contributions within a single country (N = 9) or transboundary (N = 10). High-risk areas were mainly closer (11-20%) rather than far ( < 1%) from healthcare. Areas far from healthcare reveal healthcare access inequalities, especially Scenario 3, which includes wild mammals and not livestock as secondary hosts. China (N = 2) and Indonesia (N = 1) had clusters with the highest risk. Our findings can help stakeholders in land use planning, integrating healthcare implementation and One Health actions.
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    Impact of infectious diseases on wild bovidae populations in Thailand: insights from population modelling and disease dynamics.
    (The Royal Society, 2024-07-03) Horpiencharoen W; Marshall JC; Muylaert RL; John RS; Hayman DTS
    The wildlife and livestock interface is vital for wildlife conservation and habitat management. Infectious diseases maintained by domestic species may impact threatened species such as Asian bovids, as they share natural resources and habitats. To predict the population impact of infectious diseases with different traits, we used stochastic mathematical models to simulate the population dynamics over 100 years for 100 times in a model gaur (Bos gaurus) population with and without disease. We simulated repeated introductions from a reservoir, such as domestic cattle. We selected six bovine infectious diseases; anthrax, bovine tuberculosis, haemorrhagic septicaemia, lumpy skin disease, foot and mouth disease and brucellosis, all of which have caused outbreaks in wildlife populations. From a starting population of 300, the disease-free population increased by an average of 228% over 100 years. Brucellosis with frequency-dependent transmission showed the highest average population declines (-97%), with population extinction occurring 16% of the time. Foot and mouth disease with frequency-dependent transmission showed the lowest impact, with an average population increase of 200%. Overall, acute infections with very high or low fatality had the lowest impact, whereas chronic infections produced the greatest population decline. These results may help disease management and surveillance strategies support wildlife conservation.
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    Using drivers and transmission pathways to identify SARS-like coronavirus spillover risk hotspots
    (Springer Nature Limited., 2023-05-30) Muylaert R; Wilkinson D; Kingston T; D’Odorico P; Rulli MC; Galli N; John RS; Alviola P; Hayman DTS
    The emergence of SARS-like coronaviruses is a multi-stage process from wildlife reservoirs to people. Here we characterize multiple drivers—landscape change, host distribution, and human exposure—associated with the risk of spillover of SARS-like coronaviruses to help inform surveillance and mitigation activities. We consider direct and indirect transmission pathways by modeling four scenarios with livestock and mammalian wildlife as potential and known reservoirs before examining how access to healthcare varies within clusters and scenarios. We found 19 clusters with differing risk factor contributions within a single country (N=9) or transboundary (N=10). High-risk areas were mainly closer (11-20%) rather than far (<1%) from healthcare. Areas far from healthcare reveal healthcare access inequalities, especially Scenario 3, which includes wild mammals as secondary hosts. China (N=2) and Indonesia (N=1) had clusters with the highest risk. Our findings can help stakeholders in land use planning integrating healthcare implementation and One Health actions.
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    Modelling Lassa virus dynamics in West African Mastomys natalensis and the impact of human activities.
    (The Royal Society, 2024-07-24) John RS; Fatoyinbo HO; Hayman DTS
    Lassa fever is a West African rodent-borne viral haemorrhagic fever that kills thousands of people a year, with 100 000 to 300 000 people a year probably infected by Lassa virus (LASV). The main reservoir of LASV is the Natal multimammate mouse, Mastomys natalensis. There is reported asynchrony between peak infection in the rodent population and peak Lassa fever risk among people, probably owing to differing seasonal contact rates. Here, we developed a susceptible-infected-recovered ([Formula: see text])-based model of LASV dynamics in its rodent host, M. natalensis, with a persistently infected class and seasonal birthing to test the impact of changes to seasonal birthing in the future owing to climate and land use change. Our simulations suggest shifting rodent birthing timing and synchrony will alter the peak of viral prevalence, changing risk to people, with viral dynamics mainly stable in adults and varying in the young, but with more infected individuals. We calculate the time-average basic reproductive number, [Formula: see text], for this infectious disease system with periodic changes to population sizes owing to birthing using a time-average method and with a sensitivity analysis show four key parameters: carrying capacity, adult mortality, the transmission parameter among adults and additional disease-induced mortality impact the maintenance of LASV in M. natalensis most, with carrying capacity and adult mortality potentially changeable owing to human activities and interventions.