Massey Research Online - Browsing by Author "Muylaert RL"

Browsing by Author "Muylaert RL"

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Community health and human-animal contacts on the edges of Bwindi Impenetrable National Park, Uganda
(PLOS, 2021-11-24) Muylaert RL; Davidson B; Ngabirano A; Kalema-Zikusoka G; MacGregor H; Lloyd-Smith JO; Fayaz A; Knox MA; Hayman DTS; Fèvre E
Cross-species transmission of pathogens is intimately linked to human and environmental health. With limited healthcare and challenging living conditions, people living in poverty may be particularly susceptible to endemic and emerging diseases. Similarly, wildlife is impacted by human influences, including pathogen sharing, especially for species in close contact with people and domesticated animals. Here we investigate human and animal contacts and human health in a community living around the Bwindi Impenetrable National Park (BINP), Uganda. We used contact and health survey data to identify opportunities for cross-species pathogen transmission, focusing mostly on people and the endangered mountain gorilla. We conducted a survey with background questions and self-reported diaries to investigate 100 participants' health, such as symptoms and behaviours, and contact patterns, including direct contacts and sightings over a week. Contacts were revealed through networks, including humans, domestic, peri-domestic, and wild animal groups for 1) contacts seen in the week of background questionnaire completion, and 2) contacts seen during the diary week. Participants frequently felt unwell during the study, reporting from one to 10 disease symptoms at different intensity levels, with severe symptoms comprising 6.4% of the diary records and tiredness and headaches the most common symptoms. After human-human contacts, direct contact with livestock and peri-domestic animals were the most common. The contact networks were moderately connected and revealed a preference in contacts within the same taxon and within their taxa groups. Sightings of wildlife were much more common than touching. However, despite contact with wildlife being the rarest of all contact types, one direct contact with a gorilla with a timeline including concerning participant health symptoms was reported. When considering all interaction types, gorillas mostly exhibited intra-species contact, but were found to interact with five other species, including people and domestic animals. Our findings reveal a local human population with recurrent symptoms of illness in a location with intense exposure to factors that can increase pathogen transmission, such as direct contact with domestic and wild animals and proximity among animal species. Despite significant biases and study limitations, the information generated here can guide future studies, such as models for disease spread and One Health interventions.
Community health and human-animal contacts on the edges of Bwindi Impenetrable National Park, Uganda (preprint)
(2021-07-23) Muylaert RL; Davidson B; Ngabirano A; Kalema-Zikusoka G; MacGregor H; Lloyd-Smith JO; Fayaz A; Knox MA; Hayman DTS
DarkCideS 1.0, a global database for bats in karsts and caves
(Springer Nature Limited, 2022-04-05) Tanalgo KC; Tabora JAG; de Oliveira HFM; Haelewaters D; Beranek CT; Otálora-Ardila A; Bernard E; Gonçalves F; Eriksson A; Donnelly M; González JM; Ramos HF; Rivas AC; Webala PW; Deleva S; Dalhoumi R; Maula J; Lizarro D; Aguirre LF; Bouillard N; Quibod MNRM; Barros J; Turcios-Casco MA; Martínez M; Ordoñez-Mazier DI; Orellana JAS; Ordoñez-Trejo EJ; Ordoñez D; Chornelia A; Lu JM; Xing C; Baniya S; Muylaert RL; Dias-Silva LH; Ruadreo N; Hughes AC
Understanding biodiversity patterns as well as drivers of population declines, and range losses provides crucial baselines for monitoring and conservation. However, the information needed to evaluate such trends remains unstandardised and sparsely available for many taxonomic groups and habitats, including the cave-dwelling bats and cave ecosystems. We developed the DarkCideS 1.0 (https://darkcides.org/), a global database of bat caves and species synthesised from publicly available information and datasets. The DarkCideS 1.0 is by far the largest database for cave-dwelling bats, which contains information for geographical location, ecological status, species traits, and parasites and hyperparasites for 679 bat species are known to occur in caves or use caves in part of their life histories. The database currently contains 6746 georeferenced occurrences for 402 cave-dwelling bat species from 2002 cave sites in 46 countries and 12 terrestrial biomes. The database has been developed to be collaborative and open-access, allowing continuous data-sharing among the community of bat researchers and conservation biologists to advance bat research and comparative monitoring and prioritisation for conservation.
Hantavirus Expansion Trends in Natural Host Populations in Brazil.
(MDPI (Basel, Switzerland), 2024-07-17) Mello JHF; Muylaert RL; Grelle CEV; Kemenesi G; Kurucz K
Hantaviruses are zoonotic agents responsible for causing Hantavirus Cardiopulmonary Syndrome (HCPS) in the Americas, with Brazil ranking first in number of confirmed HCPS cases in South America. In this study, we simulate the monthly spread of highly lethal hantavirus in natural hosts by conjugating a Kermack-McCormick SIR model with a cellular automata model (CA), therefore simultaneously evaluating both in-cell and between-cell infection dynamics in host populations, using recently compiled data on main host species abundances and confirmed deaths by hantavirus infection. For both host species, our models predict an increase in the area of infection, with 22 municipalities where no cases have been confirmed to date expected to have at least one case in the next decade, and a reduction in infection in 11 municipalities. Our findings support existing research and reveal new areas where hantavirus is likely to spread within recognized epicenters. Highlighting spatial-temporal trends and potential expansion, we emphasize the increased risk due to pervasive habitat fragmentation and agricultural expansion. Consistent prevention efforts and One Health actions are crucial, especially in newly identified high-risk municipalities.
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.
Malaria Risk Drivers in the Brazilian Amazon: Land Use-Land Cover Interactions and Biological Diversity.
(MDPI (Basel, Switzerland), 2023-08-01) Gonzalez Daza W; Muylaert RL; Sobral-Souza T; Lemes Landeiro V; Oren E; Blanco G
Malaria is a prevalent disease in several tropical and subtropical regions, including Brazil, where it remains a significant public health concern. Even though there have been substantial efforts to decrease the number of cases, the reoccurrence of epidemics in regions that have been free of cases for many years presents a significant challenge. Due to the multifaceted factors that influence the spread of malaria, influencing malaria risk factors were analyzed through regional outbreak cluster analysis and spatio-temporal models in the Brazilian Amazon, incorporating climate, land use/cover interactions, species richness, and number of endemic birds and amphibians. Results showed that high amphibian and bird richness and endemism correlated with a reduction in malaria risk. The presence of forest had a risk-increasing effect, but it depended on its juxtaposition with anthropic land uses. Biodiversity and landscape composition, rather than forest formation presence alone, modulated malaria risk in the period. Areas with low endemic species diversity and high human activity, predominantly anthropogenic landscapes, posed high malaria risk. This study underscores the importance of considering the broader ecological context in malaria control efforts.
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.
Present and future distribution of bat hosts of sarbecoviruses: implications for conservation and public health
(The Royal Society, 2022-05-25) Muylaert RL; Kingston T; Luo J; Vancine MH; Galli N; Carlson CJ; John RS; Rulli MC; Hayman DTS
Global changes in response to human encroachment into natural habitats and carbon emissions are driving the biodiversity extinction crisis and increasing disease emergence risk. Host distributions are one critical component to identify areas at risk of viral spillover, and bats act as reservoirs of diverse viruses. We developed a reproducible ecological niche modelling pipeline for bat hosts of SARS-like viruses (subgenus Sarbecovirus), given that several closely related viruses have been discovered and sarbecovirus-host interactions have gained attention since SARS-CoV-2 emergence. We assessed sampling biases and modelled current distributions of bats based on climate and landscape relationships and project future scenarios for host hotspots. The most important predictors of species distributions were temperature seasonality and cave availability. We identified concentrated host hotspots in Myanmar and projected range contractions for most species by 2100. Our projections indicate hotspots will shift east in Southeast Asia in locations greater than 2°C hotter in a fossil-fuelled development future. Hotspot shifts have implications for conservation and public health, as loss of population connectivity can lead to local extinctions, and remaining hotspots may concentrate near human populations.
Ten simple rules for reporting information on species interactions
(PLOS, 2022-08-11) Kita CA; Florez-Montero G; Montoya-Bustamante S; Muylaert RL; Zapata-Mesa N; Mello MAR; Markel S
The coevolutionary mosaic of bat betacoronavirus emergence risk
(Oxford University Press, 2024) Forero-Muñoz NR; Muylaert RL; Seifert SN; Albery GF; Becker DJ; Carlson CJ; Poisot T
Pathogen evolution is one of the least predictable components of disease emergence, particularly in nature. Here, building on principles established by the geographic mosaic theory of coevolution, we develop a quantitative, spatially explicit framework for mapping the evolutionary risk of viral emergence. Driven by interest in diseases like Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and Coronavirus disease 2019 (COVID-19), we examine the global biogeography of bat-origin betacoronaviruses, and find that coevolutionary principles suggest geographies of risk that are distinct from the hotspots and coldspots of host richness. Further, our framework helps explain patterns like a unique pool of merbecoviruses in the Neotropics, a recently discovered lineage of divergent nobecoviruses in Madagascar, and - most importantly - hotspots of diversification in southeast Asia, sub-Saharan Africa, and the Middle East that correspond to the site of previous zoonotic emergence events. Our framework may help identify hotspots of future risk that have also been previously overlooked, like West Africa and the Indian subcontinent, and may more broadly help researchers understand how host ecology shapes the evolution and diversity of pandemic threats.
The future of zoonotic risk prediction
(The Royal Society, 2021-11-08) Carlson CJ; Farrell MJ; Grange Z; Han BA; Mollentze N; Phelan AL; Rasmussen AL; Albery GF; Bett B; Brett-Major DM; Cohen LE; Dallas T; Eskew EA; Fagre AC; Forbes KM; Gibb R; Halabi S; Hammer CC; Katz R; Kindrachuk J; Muylaert RL; Nutter FB; Ogola J; Olival KJ; Rourke M; Ryan SJ; Ross N; Seifert SN; Sironen T; Standley CJ; Taylor K; Venter M; Webala PW
In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges?
The Global Virome in One Network (VIRION): an Atlas of Vertebrate-Virus Associations
(American Society for Microbiology, 2022-04-26) Carlson CJ; Gibb RJ; Albery GF; Brierley L; Connor RP; Dallas TA; Eskew EA; Fagre AC; Farrell MJ; Frank HK; Muylaert RL; Poisot T; Rasmussen AL; Ryan SJ; Seifert SN; Pickett BE; Jurado K
Data that catalogue viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open sharing, posing challenges for research on macroecology, evolution, and public health. Here, we solve this problem by establishing a dynamically maintained database of vertebrate-virus associations, called The Global Virome in One Network (VIRION). The VIRION database has been assembled through both reconciliation of static data sets and integration of dynamically updated databases. These data sources are all harmonized against one taxonomic backbone, including metadata on host and virus taxonomic validity and higher classification; additional metadata on sampling methodology and evidence strength are also available in a harmonized format. In total, the VIRION database is the largest open-source, open-access database of its kind, with roughly half a million unique records that include 9,521 resolved virus "species" (of which 1,661 are ICTV ratified), 3,692 resolved vertebrate host species, and 23,147 unique interactions between taxonomically valid organisms. Together, these data cover roughly a quarter of mammal diversity, a 10th of bird diversity, and ∼6% of the estimated total diversity of vertebrates, and a much larger proportion of their virome than any previous database. We show how these data can be used to test hypotheses about microbiology, ecology, and evolution and make suggestions for best practices that address the unique mix of evidence that coexists in these data. IMPORTANCE Animals and their viruses are connected by a sprawling, tangled network of species interactions. Data on the host-virus network are available from several sources, which use different naming conventions and often report metadata in different levels of detail. VIRION is a new database that combines several of these existing data sources, reconciles taxonomy to a single consistent backbone, and reports metadata in a format designed by and for virologists. Researchers can use VIRION to easily answer questions like "Can any fish viruses infect humans?" or "Which bats host coronaviruses?" or to build more advanced predictive models, making it an unprecedented step toward a full inventory of the global virome.
The risk of vector transmission of Trypanosoma cruzi remains high in the State of Paraná.
(Instituto Oswaldo Cruz, Ministério da Saúde, 2024-06-10) Trovo JVS; Weber-Lima MM; Prado-Costa B; Iunklaus GF; Andrade AJ; Sobral-Souza T; Muylaert RL; Alvarenga LM; Toledo MJO
BACKGROUND: Monitoring and analysing the infection rates of the vector of Trypanosoma cruzi, that causes Chagas disease, helps assess the risk of transmission. OBJECTIVES: A study was carried out on triatomine in the State of Paraná, Brazil, between 2012 and 2021 and a comparison was made with a previous study. This was done to assess the risk of disease transmission. METHODS: Ecological niche models based on climate and landscape variables were developed to predict habitat suitability for the vectors as a proxy for risk of occurrence. FINDINGS: A total of 1,750 specimens of triatomines were recorded, of which six species were identified. The overall infection rate was 22.7%. The areas with the highest risk transmission of T. cruzi are consistent with previous predictions in municipalities. New data shows that climate models are more accurate than landscape models. This is likely because climate suitability was higher in the previous period. MAIN CONCLUSION: Regardless of uneven sampling and potential biases, risk remains high due to the wide presence of infected vectors and high environmental suitability for vector species throughout the state and, therefore, improvements in public policies aimed at wide dissemination of knowledge about the disease are recommended to ensure the State remains free of Chagas disease.
Time lag effect on malaria transmission dynamics in an Amazonian Colombian municipality and importance for early warning systems.
(Springer Nature Limited, 2023-10-30) Gonzalez-Daza W; Vivero-Gómez RJ; Altamiranda-Saavedra M; Muylaert RL; Landeiro VL
Malaria remains a significant public health problem worldwide, particularly in low-income regions with limited access to healthcare. Despite the use of antimalarial drugs, transmission remains an issue in Colombia, especially among indigenous populations in remote areas. In this study, we used an SIR Ross MacDonald model that considered land use change, temperature, and precipitation to analyze eco epidemiological parameters and the impact of time lags on malaria transmission in La Pedrera-Amazonas municipality. We found changes in land use between 2007 and 2020, with increases in forested areas, urban infrastructure and water edges resulting in a constant increase in mosquito carrying capacity. Temperature and precipitation variables exhibited a fluctuating pattern that corresponded to rainy and dry seasons, respectively and a marked influence of the El Niño climatic phenomenon. Our findings suggest that elevated precipitation and temperature increase malaria infection risk in the following 2 months. The risk is influenced by the secondary vegetation and urban infrastructure near primary forest formation or water body edges. These results may help public health officials and policymakers develop effective malaria control strategies by monitoring precipitation, temperature, and land use variables to flag high-risk areas and critical periods, considering the time lag effect.
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.

Browsing by Author "Muylaert RL"

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