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About the Authors:
Elizabeth A. Cromwell
* E-mail: [email protected]
Affiliation: Department of Epidemiology, University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America
ORCID http://orcid.org/0000-0002-5106-0607
Steven T. Stoddard
Affiliation: Graduate School of Public Health, San Diego State University, San Diego, California, United States of America
Christopher M. Barker
Affiliation: Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of America
Annelies Van Rie
Affiliation: Department of Epidemiology, University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America
William B. Messer
Affiliation: Division of Infectious Diseases, Oregon Health and Science University, Portland, Oregon, United States of America
Steven R. Meshnick
Affiliation: Department of Epidemiology, University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America
Amy C. Morrison
Affiliation: Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of America
Thomas W. Scott
Affiliation: Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of AmericaAbstract
Routine entomological monitoring data are used to quantify the abundance of Ae. aegypti. The public health utility of these indicators is based on the assumption that greater mosquito abundance increases the risk of human DENV transmission, and therefore reducing exposure to the vector decreases incidence of infection. Entomological survey data from two longitudinal cohort studies in Iquitos, Peru, linked with 8,153 paired serological samples taken approximately six months apart were analyzed. Indicators of Ae. aegypti density were calculated from cross-sectional and longitudinal entomological data collected over a 12-month period for larval, pupal and adult Ae. aegypti. Log binomial models were used to estimate risk ratios (RR) to measure the association between Ae. aegypti abundance and the six-month risk of DENV seroconversion. RRs estimated using cross-sectional entomological data were compared to RRs estimated using longitudinal data. Higher cross-sectional Ae. aegypti densities were not associated with an increased risk of DENV seroconversion. Use of longitudinal entomological data resulted in RRs ranging from 1.01 (95% CI: 1.01, 1.02) to 1.30 (95% CI: 1.17, 1.46) for adult stage density estimates and RRs ranging from 1.21 (95% CI: 1.07, 1.37) to 1.75 (95% CI: 1.23, 2.5) for categorical immature indices. Ae....