Linking mathematical models and trap data to infer the proliferation, abundance, and control of Aedes aegypti

Jing Chen; Xi Huo; André B B Wilke; John C Beier; Chalmers Vasquez; William Petrie; Robert Stephen Cantrell; Chris Cosner; Shigui Ruan

doi:10.1016/j.actatropica.2023.106837

Linking mathematical models and trap data to infer the proliferation, abundance, and control of Aedes aegypti

Acta Trop. 2023 Mar:239:106837. doi: 10.1016/j.actatropica.2023.106837. Epub 2023 Jan 16.

Authors

Jing Chen¹, Xi Huo², André B B Wilke³, John C Beier⁴, Chalmers Vasquez⁵, William Petrie⁵, Robert Stephen Cantrell², Chris Cosner², Shigui Ruan⁶

Affiliations

¹ Department of Mathematics, Nova Southeastern University, 3301 College Ave, Fort Lauderdale, FL 33314, USA.
² Department of Mathematics, University of Miami, 1365 Memorial Drive, Coral Gables, FL 33146, USA.
³ Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN 47405, USA.
⁴ Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA.
⁵ Miami-Dade County Mosquito Control Division, Miami, FL 33178, USA.
⁶ Department of Mathematics, University of Miami, 1365 Memorial Drive, Coral Gables, FL 33146, USA. Electronic address: ruan@math.miami.edu.

PMID: 36657506
DOI: 10.1016/j.actatropica.2023.106837

Abstract

Aedes aegypti is one of the most dominant mosquito species in the urban areas of Miami-Dade County, Florida, and is responsible for the local arbovirus transmissions. Since August 2016, mosquito traps have been placed throughout the county to improve surveillance and guide mosquito control and arbovirus outbreak response. In this paper, we develop a deterministic mosquito population model, estimate model parameters by using local entomological and temperature data, and use the model to calibrate the mosquito trap data from 2017 to 2019. We further use the model to compare the Ae. aegypti population and evaluate the impact of rainfall intensity in different urban built environments. Our results show that rainfall affects the breeding sites and the abundance of Ae. aegypti more significantly in tourist areas than in residential places. In addition, we apply the model to quantitatively assess the effectiveness of vector control strategies in Miami-Dade County.

Keywords: Aedes aegypti; mathematical modeling; mosquito control; population dynamics; vector-borne disease.

MeSH terms

Aedes*
Animals
Arboviruses*
Cell Proliferation
Models, Theoretical
Mosquito Control / methods
Mosquito Vectors