Biomathematics & Statistics Scotland, Rowett Institute of Nutrition and Health, University of Aberdeen, AB25 2ZD, UK.
Institute for Global Food Security, Queen's University Belfast, Biological Sciences, 19, Chlorine Gardens, BT9 5DL, UK.
Int J Parasitol. 2023 Mar;53(3):133-155. doi: 10.1016/j.ijpara.2022.11.009. Epub 2023 Jan 24.
Gastrointestinal nematode (GIN) infections are ubiquitous and often cause morbidity and reduced performance in livestock. Emerging anthelmintic resistance and increasing change in climate patterns require evaluation of alternatives to traditional treatment and management practices. Mathematical models of parasite transmission between hosts and the environment have contributed towards the design of appropriate control strategies in ruminants, but have yet to account for relationships between climate, infection pressure, immunity, resources, and growth. Here, we develop a new epidemiological model of GIN transmission in a herd of grazing cattle, including host tolerance (body weight and feed intake), parasite burden and acquisition of immunity, together with weather-dependent development of parasite free-living stages, and the influence of grass availability on parasite transmission. Dynamic host, parasite and environmental factors drive a variable rate of transmission. Using literature sources, the model was parametrised for Ostertagia ostertagi, the prevailing pathogenic GIN in grazing cattle populations in temperate climates. Model outputs were validated on published empirical studies from first season grazing cattle in northern Europe. These results show satisfactory qualitative and quantitative performance of the model; they also indicate the model may approximate the dynamics of grazing systems under co-infection by O. ostertagi and Cooperia oncophora, a second GIN species common in cattle. In addition, model behaviour was explored under illustrative anthelmintic treatment strategies, considering impacts on parasitological and performance variables. The model has potential for extension to explore altered infection dynamics as a result of management and climate change, and to optimise treatment strategies accordingly. As the first known mechanistic model to combine parasitic and free-living stages of GIN with host feed-intake and growth, it is well suited to predict complex system responses under non-stationary conditions. We discuss the implications, limitations and extensions of the model, and its potential to assist in the development of sustainable parasite control strategies.
胃肠道线虫（GIN）感染普遍存在，常导致牲畜发病和生产性能下降。新兴的驱虫耐药性和不断变化的气候模式要求评估传统治疗和管理实践的替代方案。宿主与环境之间寄生虫传播的数学模型有助于为反刍动物设计适当的控制策略，但尚未考虑气候、感染压力、免疫、资源和生长之间的关系。在这里，我们开发了一种新的放牧牛群胃肠道线虫传播的流行病学模型，包括宿主耐受性（体重和采食量）、寄生虫负担和获得免疫力，以及依赖天气的寄生虫自由生活阶段的发育，以及草资源对寄生虫传播的影响。动态的宿主、寄生虫和环境因素驱动着可变的传播速度。利用文献资料，该模型针对在温带气候中放牧牛群中普遍存在的致病性胃肠道线虫——奥斯特拉格线虫（Ostertagia ostertagi）进行了参数化。模型输出结果在北欧首次放牧季节牛的已发表的实证研究中进行了验证。这些结果表明模型具有令人满意的定性和定量性能；它们还表明，该模型可能近似于在奥斯特拉格线虫和另一种常见于牛的胃肠道线虫——网尾线虫共同感染下放牧系统的动态。此外，还探讨了在说明性驱虫治疗策略下模型的行为，考虑了对寄生虫学和性能变量的影响。该模型具有扩展潜力，可以探索由于管理和气候变化而导致的感染动态变化，并相应地优化治疗策略。作为第一个将胃肠道线虫的寄生和自由生活阶段与宿主采食量和生长相结合的机制模型，它非常适合在非稳定条件下预测复杂系统的响应。我们讨论了模型的意义、局限性和扩展，以及它在协助制定可持续寄生虫控制策略方面的潜力。
