Faculty of Veterinary Medicine, Utrecht University, The Netherlands.
J Med Entomol. 2013 May;50(3):533-42. doi: 10.1603/me12126.
Accurate estimation of population size is key to understanding the ecology of disease vectors, as well as the epidemiology of the pathogens they carry and to plan effective control activities. Population size can be estimated through mark-release-recapture (MRR) experiments that are based on the assumption that the ratio of recaptured individuals to the total captures approximates the ratio of marked individuals released to the total population. However, methods to obtain population size estimates usually consider pooled data and are often based on the total number of marked and unmarked captures. We here present a logistic regression model, based on the principle of the well-known Fisher-Ford method, specific for MRR experiments where the information available is the number of marked mosquitoes released, the number of marked and unmarked mosquitoes caught in each trap and on each day, and the geographic coordinates of the traps. The model estimates population size, taking into consideration the distance between release points and traps, the time between release and recapture, and the loss of marked mosquitoes to death or dispersal. The performance and accuracy of the logistic regression model has been assessed using simulated data from known population sizes. We then applied the model to data from MRR experiments with Aedes albopictus Skuse performed on the campus of "Sapienza" University in Rome (Italy).
准确估计种群数量对于了解疾病媒介的生态学以及它们携带的病原体的流行病学至关重要，并且对于规划有效的控制活动也很重要。种群数量可以通过标记-释放-捕获 (MRR) 实验来估计，该实验基于这样的假设，即被重新捕获的个体与总捕获量的比例近似于释放的标记个体与总种群的比例。然而，获取种群数量估计值的方法通常考虑汇总数据，并且通常基于标记和未标记的捕获总数。我们在这里提出了一种逻辑回归模型，该模型基于著名的 Fisher-Ford 方法的原理，专门用于 MRR 实验，其中可用的信息是释放的标记蚊子数量、每个陷阱和每天捕获的标记和未标记蚊子数量以及陷阱的地理坐标。该模型考虑到释放点和陷阱之间的距离、释放和重新捕获之间的时间以及标记蚊子因死亡或扩散而损失的情况，来估计种群数量。使用已知种群数量的模拟数据评估了逻辑回归模型的性能和准确性。然后，我们将该模型应用于在意大利罗马的“萨皮恩扎”大学（Sapienza 大学）校园进行的白纹伊蚊（Aedes albopictus Skuse）MRR 实验的数据。
