Details

Autor(en) / Beteiligte

• Cromwell, Elizabeth A
• Stoddard, Steven T
• Barker, Christopher M
• Van Rie, Annelies
• Messer, William B
• Meshnick, Steven R
• Morrison, Amy C
• Scott, Thomas W
• Gubler, Duane J.

Titel

The relationship between entomological indicators of Aedes aegypti abundance and dengue virus infection

Ist Teil von

• PLoS neglected tropical diseases, 2017-03, Vol.11 (3), p.e0005429

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2017

Quelle

MEDLINE

Beschreibungen/Notizen

• 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.