bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.02.21.639461

GLOWORM-META: Modelling gastrointestinal nematode metapopulation dynamics to inform cattle biosecurity research

Abstract

Gastrointestinal nematode (GIN) parasite infections in grazing livestock cause significant disease, and are responsible for estimated annual losses of over {euro}1.8 billion in Europe alone. The management of GINs in cattle is threatened by anthelmintic drug resistance (AR). Immediate action is needed to slow the progression of AR in cattle GINs and avoid the increasingly common scenario of multiple drug resistance seen in sheep. Although AR can arise independently on multiple farms, it may also be spread between holdings via purchased cattle. Therefore, effective biosecurity measures on cattle enterprises could help to reduce the risk of establishment of AR populations. A metapopulation model was developed and validated for two GIN species infecting cattle, Ostertagia ostertagi and Cooperia oncophora, incorporating the full parasite life cycle, weather- and immunity-dependent parasite life history traits and multiple pasture sub-populations. This allowed for complex grazing management strategies and weather influences to be simulated. The models successfully replicated the seasonal patterns and intensity of infections reported in multiple published longitudinal datasets. Global sensitivity analysis against four Quantities of Interest (QoIs) related to factors affecting the safety of the resident herd and of the purchased animals was used to quantify the influence of candidate biosecurity measures. The duration of quarantine, the date of purchase (weather/seasonal influences) and the intensity of infection on the day of purchase strongly influenced the QoIs. The outcomes for the UK were not significantly influenced by the geographic location of the purchasing farm, suggesting that the influence of weather patterns on GIN populations outweighs that of regional climate differences, and thus regional variations to GIN biosecurity recommendations are not warranted without alternative evidence to support this. The model presented here is the first full lifecycle GIN metapopulation model for O. ostertagi and C. oncophora, validated against longitudinal field data, and can be broadly used to evaluate the relative efficacy of a range of cattle GIN management strategies, as demonstrated here. These findings offer valuable insights to focus initial biosecurity recommendations for cattle enterprises, and are being used to direct qualitative and quantitative research to refine recommendations. HighlightsO_LIA metapopulation model for cattle GINs was developed C_LIO_LIThe model includes weather-dependence and complex grazing C_LIO_LIThe model replicated seasonal infection patterns from multiple datasets C_LIO_LISensitivity analysis explored influential biosecurity measures C_LIO_LIThe influence of weather outweighed that of geographic location (climate) C_LIO_LIInitial recommendations for biosecurity and further research are made C_LI

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ingle, O. K., Melville, L., Beechener, S., Hardy, C., Howell, A., Hobbs, N. P., Mahon, N., Morgan, E. R., Bartley, D., Rose Vineer, H.. 2025-02-25. GLOWORM-META: Modelling gastrointestinal nematode metapopulation dynamics to inform cattle biosecurity research. https://doi.org/10.1101/2025.02.21.639461

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Ecological opportunity and evolutionary relatedness predict parasite sharing differently across mammalian taxonomic scales

As global change brings species into new contact, understanding the ecological and evolutionary drivers of parasite sharing is essential for anticipating and mitigating disease emergence. Yet, the relative importance of geographic proximity and evolutionary relatedness among host species in predicting parasite sharing remains unresolved. We tested whether their relative importance changes across host taxonomic scale using 30,310 recorded associations between 680 mammalian and 11,107 parasite species. Geography accounted for 86.6% importance within genera, declining to 44.7% across all mammals, shifting toward evolutionary relatedness predominating. Parasite sharing increased nonlinearly with geographic proximity and host relatedness, and the overall trend varied among parasite types. Notably, accounting for host taxonomic scale improved parasite-sharing prediction accuracy. To explore the consequences of biotic homogenization, we applied a counterfactual scenario of reducing geographic distance by 99%, which increased mean predicted parasite sharing to 13.71% within genera and 1.50% at the class level. Together, these findings suggest that ecological opportunity is especially consequential among close relatives whereas evolutionary similarity is increasingly important among geographically distant species. Accounting for evolutionary scale can therefore improve sharing predictions and help identify which new host encounters warrant surveillance for cross-species transmission and disease emergence.

ecology↗

Host availability, climate and pupal-stage ecology shape the predicted environmental suitability of the New World screwworm across Central and South America

Background: The New World screwworm, Cochliomyia hominivorax, causes primary myiasis in warm-blooded vertebrates. Its recent resurgence in Central America has renewed the need for spatial tools that identify environmentally suitable areas and surveillance gaps. Most previous distribution models have emphasized climate and livestock, whereas ecological constraints acting during the free-living pupal stage have rarely been incorporated. Methods: We compiled 2,461 georeferenced occurrence reports from the literature across Central and South America and linked them to climate, livestock density, forest cover and superficial soil predictors. Four sequential (nested) logistic models quantified the incremental contribution of predictor blocks, compared using likelihood-ratio tests, AIC and discrimination metrics. Logistic regression and Random Forest were then compared using five-fold spatial block cross-validation, which we treat as the primary measure of generalisation, and an independent municipality-level 70:30 train-test split. Variable importance was assessed using Random Forest Mean Decrease Accuracy together with partial-dependence profiles. Because presence and pseudo-absence classes were balanced before fitting, model outputs are interpreted as relative environmental suitability rather than absolute probability of occurrence. Results: The literature database represented 2,589 infected hosts, dominated by cattle, pigs, dogs and humans. Across the sequential models, AUC increased from 0.780 for climate alone to 0.898 with livestock density, 0.908 with forest cover and 0.918 with superficial soil properties; the increment attributable to the soil block ({Delta}AUC = 0.010) was smaller than the between-fold variability observed under spatial cross-validation (SD 0.049) and is therefore reported as suggestive rather than established. Sheep and horse density and cold-quarter soil temperature showed the highest Mean Decrease Accuracy values, while silt texture ranked above cattle density and forest cover. Under spatial block cross-validation Random Forest was markedly more stable than the GLM (mean AUC 0.926 {+/-} 0.049 versus 0.814 {+/-} 0.157) and was retained as the final model. On the independent municipality-level test set it achieved AUC 0.981, TSS 0.824, sensitivity 0.850 and specificity 0.972, values we regard as optimistic relative to the spatially blocked estimates. Predicted suitability was highest across Central America and parts of northern and tropical South America. Conclusions: C. hominivorax occurrence was associated with interacting climatic, host and landscape conditions. Superficial soil variables added a small, biologically interpretable signal consistent with constraints acting during pupation, but one that lies within the uncertainty of our spatial validation and requires confirmation with independent data. The maps estimate relative environmental suitability rather than infection incidence, and are intended to identify areas where surveillance could be strengthened rather than to guide control operations directly.

ecology↗

Phenotypic variation in divergent mitochondrial haplotypes in migratory three-spined stickleback

Mitochondria are essential components in life-sustaining organismal processes. The mitochondrial genome can be influenced by selection, and divergent mitochondrial haplotypes have substantial potential to affect interspecies variation in life-history and physiology, yet little is known about whole organism phenotypic changes that might accompany mitochondrial genomic divergence. Three-spined stickleback on the Scottish island of North Uist provide a model to study this as their populations exhibit a well-mixed nuclear genome, yet two highly diverged mitochondrial haplotypes ( trans-Atlantic and European). Three-spined stickleback were sampled from six lochs to investigate associations between mitochondrial haplotype and phenotypic traits including organ size, body size, and ovule volume/clutch size, as well as citrate synthase enzyme activity. Results showed that mitochondrial haplotype has an influence on male gonadosomatic index (GSI) and potentially citrate synthase (CS) enzyme activity. Differences in male GSI may be explained by the timing of male spermatogenesis or potentially a need for larger testes in European haplotype fish. While no other phenotypic trait showed differences between mitochondrial haplotypes, there were many differences between sexes and populations e.g. in body size and organ/muscle size.

ecology↗