Rapid estimation of Aedes aegypti population size using simulation modeling with a novel approach to calibration and field validation

Williams, Craig R., Johnson, Petrina H., Long, Sharron A., Rapley, Luke P., and Ritchie, Scott A. (2008) Rapid estimation of Aedes aegypti population size using simulation modeling with a novel approach to calibration and field validation. Journal of Medical Entomology, 45 (6). pp. 1173-1179.

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Abstract

New approaches for control of the dengue vector Aedes aegypti (L.) are being developed, including the potential introduction of life-shortening symbiont bacteria into field populations and the release of transgenic strains with reduced vector competency. With these new approaches comes the need for rapid estimations of existing field population size. Here, we describe the use of simulation modeling with container-inhabiting mosquito simulation (CIMSiM) for estimation of Ae. aegypti pupal crop size in north Queensland, Australia. CIMSiM was calibrated for local conditions by deploying “sentinel key containers” (tire, 2-liter plastic bucket, 0.6-liter pot plant base, and tarpaulin indentation) in which water flux and pupal productivity were studied for 72 d. Iterative adjustment of CIMSiM parameters was used to fit model outputs to match that of sentinel key containers. This calibrated model was then used in a blind field validation, in which breeding container and local meteorological data were used to populate CIMSiM, and model outputs were compared with a field pupal survey. Actual pupae per ha during two 10-d periods in 2007 fell within 95% confidence intervals of simulated pupal crop estimates made by 10 replicate simulations in CIMSiM, thus providing a successful field validation. Although the stochasticity of the field environment can never be wholly simulated, CIMSiM can provide field-validated estimates of pupal crop in a timely manner by using simple container surveys.

Item ID: 6624
Item Type: Article (Refereed Research - C1)
Keywords: mosquito; dengue; Aedes aegypti; CIMSiM; modeling; population; pupal crop; simulation
ISSN: 0022-2585
Date Deposited: 01 Mar 2010 00:31
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111799 Public Health and Health Services not elsewhere classified @ 50%
11 MEDICAL AND HEALTH SCIENCES > 1108 Medical Microbiology > 110804 Medical Virology @ 50%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 50%
92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920404 Disease Distribution and Transmission (incl. Surveillance and Response) @ 50%
Citation Count from Web of Science Web of Science 20
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