Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

• Published in: The American journal of tropical medicine and hygiene Vol. 85; no. 2; pp. 257 - 264
• Main Authors: ELLIS, Alicia M, GARCIA, Andres J, FOCKS, Dana A, MORRISON, Amy C, SCOTT, Thomas W
• Format: Journal Article
• Language: English
• Published: Deerfield, IL American Society of Tropical Medecine and Hygiene 01-08-2011; The American Society of Tropical Medicine and Hygiene
• Subjects: Animals; Arboviroses; Biological and medical sciences; Computer Simulation; Culicidae; Culicidae - physiology; Dengue - transmission; Dengue fevers; Human viral diseases; Humans; Infectious diseases; Insect Vectors; Larva; Medical sciences; Models, Biological; Mosquito Control - methods; Ovum; Population Dynamics; Pupa; Tropical viral diseases; Viral diseases; Insecta; Dengue; Transmission; Check; Infection; Prevention; Sensitivity; Arthropoda; Viral disease; Arbovirus disease; Culicidae; Tropical medicine; Simulation model; Invertebrata; Diptera
• ISSN: 0002-9637; 1476-1645
• DOI: 10.4269/ajtmh.2011.10-0516

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority.