Villela Daniel Antunes Maciel, Garcia Gabriela de Azambuja, Maciel-de-Freitas Rafael
Programa de Computação Científica, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
Laboratório de Transmissão de Hematozoários, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
PLoS Negl Trop Dis. 2017 Jun 26;11(6):e0005682. doi: 10.1371/journal.pntd.0005682. eCollection 2017 Jun.
Experiments involving mosquito mark-release-recapture (MRR) design are helpful to determine abundance, survival and even recruitment of mosquito populations in the field. Obstacles in mosquito MRR protocols include marking limitations due to small individual size, short lifespan, low efficiency in capturing devices such as traps, and individual removal upon capture. These limitations usually make MRR analysis restricted to only abundance estimation or a combination of abundance and survivorship, and often generate a great degree of uncertainty about the estimations.
METHODOLOGY/PRINCIPAL FINDINGS: We present a set of Bayesian biodemographic models designed to fit data from most common mosquito recapture experiments. Using both field data and simulations, we consider model features such as capture efficiency, survival rates, removal of individuals due to capturing, and collection of pupae. These models permit estimation of abundance, survivorship of both marked and unmarked mosquitoes, if different, and recruitment rate. We analyze the accuracy of estimates by varying the number of released individuals, abundance, survivorship, and capture efficiency in multiple simulations. These methods can stand capture efficiencies as low as usually reported but their accuracy depends on the number of released mosquitoes, abundance and survivorship. We also show that gathering pupal counts allows estimating differences in survivorship between released mosquitoes and the unmarked population.
CONCLUSION/SIGNIFICANCE: These models are important both to reduce uncertainty in evaluating MMR experiments and also to help planning future MRR studies.
涉及蚊子标记-释放-再捕获（MRR）设计的实验有助于确定野外蚊子种群的数量、存活率甚至补充率。蚊子MRR方案中的障碍包括由于个体尺寸小、寿命短、捕获装置（如诱捕器）效率低以及捕获时个体被移除等导致的标记限制。这些限制通常使得MRR分析仅限于数量估计或数量与存活率的组合，并且常常在估计中产生很大程度的不确定性。
方法/主要发现：我们提出了一组贝叶斯生物统计学模型，旨在拟合最常见的蚊子再捕获实验的数据。利用实地数据和模拟，我们考虑了诸如捕获效率、存活率、捕获导致的个体移除以及蛹的收集等模型特征。这些模型允许估计数量、标记和未标记蚊子（若有差异）的存活率以及补充率。我们通过在多次模拟中改变释放个体的数量、数量、存活率和捕获效率来分析估计的准确性。这些方法能够承受通常报道的低至那样的捕获效率，但其准确性取决于释放蚊子的数量、数量和存活率。我们还表明，收集蛹的数量能够估计释放蚊子与未标记种群之间的存活率差异。
结论/意义：这些模型对于减少评估MMR实验中的不确定性以及帮助规划未来的MRR研究都很重要。
