Stopard Isaac J, Sherrard-Smith Ellie, Ranson Hilary, Toe Kobié Hyacinthe, Cook Jackie, Biggs Joseph, Lambert Ben, Churcher Thomas S
School of Public Health, Imperial College London, London, United Kingdom.
School of Population Health, University of New South Wales (UNSW), Sydney, New South Wales, Australia.
PLoS Comput Biol. 2025 Aug 18;21(8):e1013035. doi: 10.1371/journal.pcbi.1013035. eCollection 2025 Aug.
Entomological surveillance is an important component of mosquito-borne disease control. Mosquito abundance, infection prevalence and the entomological inoculation rate are the most widely reported entomological metrics, although these data are notoriously noisy and difficult to interpret. For many infections, only older mosquitoes are infectious, which is why, in part, vector control tools that reduce mosquito life expectancy have been so successful. The age structure of wild mosquitoes has been proposed as a metric to assess the effectiveness of interventions that kill adult mosquitoes, and age grading tools are becoming increasingly advanced. Mosquito populations show seasonal dynamics with temporal fluctuations. How seasonal changes in adult mosquito emergence and vector control could affect the mosquito age distribution or other important metrics is unclear. We develop stochastic mathematical models of mosquito population dynamics to show how variability in mosquito emergence causes substantial heterogeneity in the mosquito age distribution, with low frequency, positively autocorrelated changes in emergence being the most important driver of this variability. Fitting a population model to mosquito abundance data collected in experimental hut trials indicates these dynamics are likely to exist in wild Anopheles gambiae populations. Incorporating age structuring into an established compartmental model of mosquito dynamics and vector control, indicates that the use of mosquito age as a metric to assess the efficacy of vector-control tools will require an understanding of underlying variability in mosquito ages, with the mean age and other entomological metrics affected by short-term and seasonal fluctuations in mosquito emergence.
昆虫学监测是蚊媒疾病控制的重要组成部分。蚊虫数量、感染率和昆虫学接种率是报道最为广泛的昆虫学指标，不过这些数据的噪声很大，难以解读。对于许多感染而言，只有较老的蚊子才具有传染性，这在一定程度上解释了为何那些能够缩短蚊子寿命的病媒控制工具如此成功。野生蚊子的年龄结构已被提议作为一种指标，用于评估杀灭成蚊的干预措施的效果，而且年龄分级工具也日益先进。蚊子种群呈现出随时间波动的季节性动态。成蚊羽化和病媒控制的季节性变化如何影响蚊子的年龄分布或其他重要指标尚不清楚。我们建立了蚊子种群动态的随机数学模型，以展示蚊子羽化的变异性如何在蚊子年龄分布中导致显著的异质性，其中羽化的低频、正自相关变化是这种变异性的最重要驱动因素。将种群模型拟合到在实验小屋试验中收集的蚊虫数量数据表明，这些动态可能存在于野生冈比亚按蚊种群中。将年龄结构纳入已有的蚊子动态和病媒控制的 compartmental 模型表明，将蚊子年龄用作评估病媒控制工具效果的指标将需要了解蚊子年龄的潜在变异性，平均年龄和其他昆虫学指标会受到蚊子羽化的短期和季节性波动的影响。
