The relationship between entomological indicators of Aedes aegypti abundance and dengue virus infection.
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. aegypti densities calculated from longitudinal entomological data were associated with DENV seroconversion, whereas those measured cross-sectionally were not. Ae. aegypti indicators calculated from cross-sectional surveillance, as is common practice, have limited public health utility in detecting areas or populations at high risk of DENV infection.
Department of Epidemiology, University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America.
Elizabeth A
0000-0002-5106-0607
EA
Cromwell
Graduate School of Public Health, San Diego State University, San Diego, California, United States of America.
Steven T
ST
Stoddard
Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of America.
Christopher M
CM
Barker
Department of Epidemiology, University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America.
Annelies
A
Van Rie
Division of Infectious Diseases, Oregon Health and Science University, Portland, Oregon, United States of America.
William B
WB
Messer
Department of Epidemiology, University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America.
Steven R
SR
Meshnick
Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of America.
Amy C
AC
Morrison
Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of America.
Thomas W
TW
Scott
D000293:Adolescent; D000328:Adult; D000330:Aedes / Q000254:growth & development* / Q000821:virology; D000368:Aged; D000369:Aged, 80 and over; D000818:Animals; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D003715:Dengue / Q000453:epidemiology*; D003716:Dengue Virus / Q000302:isolation & purification; D004772:Entomology; D004784:Environmental Monitoring / Q000379:methods*; D005191:Family Characteristics; D005260:Female; D006801:Humans; D007814:Larva / Q000254:growth & development / Q000821:virology; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D000072138:Mosquito Vectors / Q000821:virology*; D010568:Peru; D011679:Pupa / Q000254:growth & development / Q000821:virology; D012044:Regression Analysis; D055815:Young Adult