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，但目前学界对驱动宿主体内动态的机制认知仍较为薄弱。数学模型虽已提供若干有价值的见解，但现有模型极少经过严格检验，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，以至于由小规模种群引发的随机效应——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。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（response times）”，但这类效应在真实宿主-病原体互作中是否具有重要作用同样未被探明。本研究以舞毒蛾（gypsy moth）杆状病毒（baculovirus）的相关实验数据为基础，对宿主体内病原体增殖的各类模型开展检验。通过运用贝叶斯统计方法与正式的模型选择流程，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应答的显著影响。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，且宿主免疫系统针对感染的应答或许会对种群层面的疾病动态产生重要影响。