Environmental and Ecological Statistics

, Volume 26, Issue 1, pp 1–16 | Cite as

Modeling Aedes aegypti trap data with unobserved components

  • Thiago Rezende dos SantosEmail author


Several models have been proposed to describe the population dynamics of Aedes aegypti. Intuitive interpretation of model parameters and simplicity are some of the main characteristics of mechanistic models. Another possibility is the use of statistical models, which have their advantages but are not easy to interpret. The state-space model (SSM), also known as a mechanistic time series model, incorporates the beneficial aspects of both mechanistic and statistical models. This study introduces a SSM for Ae. aegypti ovitrap data to estimate latent state and static parameters, making suitable analysis of the data. The estimation of static and state parameters is easy to achieve in this framework. A simulation study is performed to study some properties of the estimators for the parameters. The model is also applied to Ae. aegypti trap data and highlights its importance and potential for the real trap data sets. The results show that the proposed SSM has good performance and the parameters can be reasonably estimated.


Classical inference Dengue Ovitraps State-space models Time series 



T. R. Santos was supported by the PrPq-Universidade Federal de Minas Gerais-Brazil, CNPq-Brazil, and the FAPEMIG Foundation. The author thanks the associate editor and two anonymous reviewers for constructive comments and suggestions which substantially helped improve the quality of the paper. The author also thanks Helio Eustaquio dos Santos (in memoriam), Alzira de Rezende dos Santos, and Graciele Fernanda for their endless discussions.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of StatisticsUniversidade Federal de Minas GeraisBelo HorizonteBrazil

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