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Simons, D.

Publications and source records attributed to Simons, D..

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Molecular and ecological determinants of effective reassortment in orthohantaviruses

A central unsolved problem in RNA virus evolution is understanding why some viral reassortants establish and persist while others do not. To answer this question, we reconstructed reassortant histories across 553 viral genomes from seven orthohantavirus species between 1983 and 2024 using phylogenetic reconciliation and molecular dating. We found that the frequency of retained reassortants varied among orthohantaviruses. For example, reassortment ranged from absent in Andes virus to frequent in Dobrava-Belgrade, Sin Nombre, Seoul, Puumala, and Tula viruses, showing that effective reassortment is not a genus-wide constant. Our Bayesian hierarchical models identified local host overlap as the strongest ecological factor associated with viral reassortment, while cross-segment linkage and terminal RNA structure serve as a molecular filter. We found that the probability of reassortment establishment is highest when ecological opportunity is paired with molecular permissiveness, with their interaction term inferred as the strongest signal in our establishment models (posterior probability = 0.97). These results suggest that reassortment in orthohantaviruses is a sequentially filtered evolutionary process in which divergent lineages must first meet in a host through ecological overlap, exchange segments that are molecularly compatible, and do so within a lineage background permissive to establishment in the host population.

evolutionary biology↗

Viral reservoir status in small mammals emerges as a predictable life-history trait after correcting for surveillance bias

Small mammals, particularly rodents and shrews, act as primary reservoirs for Arenaviruses and Hantaviruses, zoonotic pathogens causing substantial global morbidity. However, our understanding of reservoir ecology is obscured by biased surveillance efforts, where sampling preferentially targets synanthropic species and high-income regions. It remains unclear whether observed patterns of reservoir competence, such as the association with synanthropy, are biological realities or artefacts of surveillance bias. We conducted a systematic review and data synthesis of global surveillance efforts (1960-2023), creating a harmonised database of over 590,000 recorded small mammals contributing 716,000 assay results. We then integrated this with macroecological trait data and phylogenetics to model reservoir probability using Bayesian phylogenetic dyadic generalised linear mixed models. We identified substantial taxonomic and geographic biases; surveillance is heavily skewed towards the Palearctic and widespread, large-bodied species, while 46% of host genera remain entirely unsampled. Geographically, surveillance intensity correlates strongly with accessibility and night-light intensity rather than host biodiversity. After statistically correcting for historical sampling volume, we demonstrate that reservoir status is a predictable biological trait. A fast pace of life (e.g., early maturity, large litters) is associated with an increased probability of reservoir status, independent of sampling effort. Synanthropy also remains a strong, independent predictor, indicating that commensal species act as genuine biological amplifiers in modified landscapes. Evolutionary analyses reveal a mosaic of broad lineage-level co-divergence punctuated by frequent, reactive host-switching. By projecting these models globally, we demonstrate that anthropogenic disturbance acts as an ecological filter, fundamentally challenging the assumption that pristine tropical ecosystems represent the highest intrinsic hazard for viral emergence.

ecology↗

Contact networks of small mammals highlight potential transmission foci of Lassa mammarenavirus.

Lassa fever (Mammarenavirus lassaense; LASV), is an endemic zoonosis in West Africa. Human infections arise from rodent-to-human transmission, mainly from the synanthropic reservoir Mastomys natalensis. In Sierra Leone, small-mammal communities vary across land use gradients, shaping LASV transmission risk. How anthropogenic environments facilitate the rodent-rodent interactions remains poorly understood. We sampled small mammals over 43,266 trap nights in Sierra Leones LASV-endemic Eastern Province, detecting 684 rodents and shrews. To assess potential transmission, we constructed space-sharing networks from co-trapping events within species-specific home range radii. These networks approximated shared space use, allowing comparison of encounter patterns across habitats. Network topology varied significantly by land use. Village networks were the most connected (highest average degree), whereas agricultural communities supported the most species (higher rarefied richness) and were the most fragmented (higher modularity). Notably, the probability of intraspecific space sharing among M. natalensis was highest in agriculture, suggesting land use modulates key intra-specific transmission pathways. LASV seroprevalence was 5.7% community-wide, with antibodies in nine species. We found no statistically significant association between overall seroprevalence and land use or aggregate network structure (mean degree). However, predictive modeling for M. natalensis indicated that higher individual degree is associated with seropositivity, suggesting complex, scale-dependent relationships. These findings show that simple ecological drivers do not fully explain LASV exposure, highlighting the importance of species-specific behaviors (i.e., M. natalensis clustering in agriculture) and the multi-host serological landscape in assessing transmission risk.

ecology↗

Protocol for the production of an Arenavirus and Hantavirus host-pathogen database: Project ArHa.

1Arenaviruses and Hantaviruses, primarily hosted by rodents and shrews, represent significant public health threats due to their potential for zoonotic spillover into human populations. Despite their global distribution, the full impact of these viruses on human health remains poorly understood, particularly in regions like Africa, where data is sparse. Both virus families continue to emerge, with pathogen evolution and spillover driven by anthropogenic factors such as land use change, climate change, and biodiversity loss. Recent research highlights the complex interactions between ecological dynamics, host species, and environmental factors in shaping the risk of pathogen transmission and spillover. This underscores the need for integrated ecological and genomic approaches to better understand these zoonotic diseases. A comprehensive, spatially and temporally explicit dataset, incorporating host-pathogen dynamics and human disease data, is crucial for improving risk assessments, enhancing disease surveillance, and guiding public health interventions. Such a dataset (ArHa) would also support predictive modelling efforts aimed at mitigating future spillover events. This paper proposes the development of this unified database for small-mammal hosts of Arenaviruses and Hantaviruses, identifying gaps in current research and promoting a more comprehensive understanding of pathogen prevalence, spillover risk, and viral evolution. 2 Strengths and Limitations of this studyO_LIThis dataset combines detailed spatial and temporal information, providing a unique resource for understanding geographic and temporal trends in Arenavirus and Hantavirus host-pathogen relationships. C_LIO_LIBy explicitly quantifying sampling biases and detection efforts, the dataset allows more robust and accurate asssessments of pathogen prevalence and distribution. C_LIO_LIThe dataset offers a platform for linking ecological data with human health outcomes, supporting the identification of spillover hotspots. C_LIO_LIThe dataset relies on published material, which may vary in terms of detail, accuracy and completeness. Missing or imprecise information may limit the reliability of subsequent analyses. C_LIO_LIThe dataset will be produced as a static resource which could limit its relevance over time as emerging data will not be added. C_LI

microbiology↗

Rodent trapping studies as an overlooked information source for understanding endemic and novel zoonotic spillover.

1.Rodents a diverse, globally distributed and ecologically important order of mammals are nevertheless important reservoirs of known and novel zoonotic pathogens. Ongoing anthropogenic land use change is altering the composition of these species abundance and distribution which among zoonotic host species may alter the risk of zoonoses spillover events. These changes demand that a better understanding of the current distribution of rodent species is vital for mitigating potential zoonotic disease hazard and managing risk. However, available species distribution and host-pathogen association datasets (e.g. IUCN, GBIF, CLOVER) are often taxonomically and spatially biased. Here, we synthesise data from West Africa from 127 rodent trapping studies, published between 1964-2022, as an additional source of information to characterise the range and presence of rodent species and identify the subgroup of species that are potential or known pathogen hosts. We identify that these rodent trapping studies, although biased towards human dominated landscapes across West Africa, can usefully complement current rodent species distribution datasets and we calculate the discrepancies between these datasets. For five regionally important zoonotic pathogens (Arenaviridae spp., Borrelia spp., Lassa mammarenavirus, Leptospira spp. and Toxoplasma gondii), we identify host-pathogen associations that have not been previously reported in host-association datasets. Finally, for these five pathogen groups, we find that the proportion of a rodent hosts range that has been sampled remains small with geographic clustering. A priority should be to sample rodent hosts across a greater geographic range to better characterise current and future risk of zoonotic spillover events. In the interim, studies of spatial pathogen risk informed by rodent distributions must incorporate a measure of the current sampling biases. The current synthesis of contextually rich rodent trapping data enriches available information from IUCN, GBIF and CLOVER which can support a more complete understanding of the hazard of zoonotic spillover events. 2. Author SummaryEmerging and endemic zoonotic diseases are projected to have increasing health impacts, particularly under changing climate and land-use scenarios. Rodents, an ecologically vital order of mammals carry a disproportionate number of zoonotic pathogens and are abundant across West Africa. Prior modelling studies rely on large, consolidated data sources which do not incorporate high resolution spatial and temporal data from rodent trapping studies. Here, we synthesise these studies to quantify the bias in the sampling of rodent hosts and their pathogens across West Africa. We find that rodent trapping studies are complementary to these datasets and can provide additional, high-resolution data on the distribution of hosts and their pathogens. Further, rodent trapping studies have identified additional potential host-pathogen associations than are recorded in consolidated host-pathogen association datasets. This can help to understand the risk of zoonotic diseases based on host distributions. Finally, we quantify the current extent of known rodent presence and pathogen sampling within a species range, highlighting that current knowledge is limited across much of the region. We hope that this will support work to study rodent hosts and their pathogens in currently under sampled regions to better understand the risk of emerging and endemic zoonoses in West Africa.

ecology↗