Data from: Pathogen growth in insect hosts: inferring the importance of different mechanisms using stochastic models and response time data

Pathogen population dynamics within individual hosts can alter disease epidemics and pathogen evolution, but our understanding of the mechanisms driving within-host dynamics is weak. Mathematical models have provided useful insights, but existing models have only rarely been subjected to rigorous tests, and their reliability is therefore open to question. Most models assume that initial pathogen population sizes are so large that stochastic effects due to small population sizes, so-called demographic stochasticity, are negligible, but whether this assumption is reasonable is unknown. Most models also assume that the dynamic effects of a host’s immune system strongly affect pathogen incubation times or “response times,” but whether such effects are important in real host-pathogen interactions is likewise unknown. Here we use data for a baculovirus of the gypsy moth to test models of within-host pathogen growth. By using Bayesian statistical techniques and formal model-selection procedures, we are able to show that the response time of the gypsy moth virus is strongly affected by both demographic stochasticity and a dynamic response of the host immune system. Our results imply that not all response-time variability can be explained by host and pathogen variability, and that immune system responses to infection may have important effects on population-level disease dynamics.

宿主个体内的病原体种群动态可改变疾病流行态势与病原体演化进程，但当前学界对驱动宿主内动态的机制认知仍较为薄弱。数学模型虽已提供诸多有益的理论洞见，但现有模型极少经过严格的实证检验，因此其可靠性尚存争议。多数模型假定初始病原体种群规模足够庞大，以至于由种群规模过小引发的随机效应——即所谓种群统计随机性（demographic stochasticity）——可被忽略，但该假设的合理性尚未明确。此外，多数模型还假定宿主免疫系统的动态效应会显著影响病原体的潜伏期或“响应时间”，但这类效应在真实宿主-病原体互作中是否具有重要意义同样尚未明晰。本研究以舞毒蛾杆状病毒的相关数据为基础，对宿主内病原体增殖模型开展检验。通过运用贝叶斯统计技术与规范的模型选择流程，本研究证实舞毒蛾杆状病毒的响应时间同时受到种群统计随机性与宿主免疫系统动态响应的显著影响。本研究结果表明，并非所有响应时间的变异都可通过宿主与病原体的变异得到解释，宿主免疫系统针对感染的响应或对种群层面的疾病动态具有重要影响。