TY - JOUR

T1 - Explaining variation in adult Anopheles indoor resting abundance

T2 - the relative effects of larval habitat proximity and insecticide-treated bed net use

AU - McCann, Robert S.

AU - Messina, Joseph P.

AU - MacFarlane, David W.

AU - Bayoh, M. Nabie

AU - Gimnig, John E.

AU - Giorgi, Emanuele

PY - 2017/7/17

Y1 - 2017/7/17

N2 - BackgroundSpatial determinants of malaria risk within communities are associated with heterogeneity of exposure to vector mosquitoes. The abundance of adult malaria vectors inside people’s houses, where most transmission takes place, should be associated with several factors: proximity of houses to larval habitats, structural characteristics of houses, indoor use of vector control tools containing insecticides, and human behavioural and environmental factors in and near houses. While most previous studies have assessed the association of larval habitat proximity in landscapes with relatively low densities of larval habitats, in this study these relationships were analysed in a region of rural, lowland western Kenya with high larval habitat density.Methods525 houses were sampled for indoor-resting mosquitoes across an 8 by 8 km study area using the pyrethrum spray catch method. A predictive model of larval habitat location in this landscape, previously verified, provided derivations of indices of larval habitat proximity to houses. Using geostatistical regression models, the association of larval habitat proximity, long-lasting insecticidal nets (LLIN) use, house structural characteristics (wall type, roof type), and peridomestic variables (cooking in the house, cattle near the house, number of people sleeping in the house) with mosquito abundance in houses was quantified.ResultsVector abundance was low (mean, 1.1 adult Anopheles per house). Proximity of larval habitats was a strong predictor of Anopheles abundance. Houses without an LLIN had more female Anopheles gambiae s.s., Anopheles arabiensis and Anopheles funestus than houses where some people used an LLIN (rate ratios, 95% CI 0.87, 0.85–0.89; 0.84, 0.82–0.86; 0.38, 0.37–0.40) and houses where everyone used an LLIN (RR, 95% CI 0.49, 0.48–0.50; 0.39, 0.39–0.40; 0.60, 0.58–0.61). Cooking in the house also reduced Anopheles abundance across all species. The number of people sleeping in the house, presence of cattle near the house, and house structure modulated Anopheles abundance, but the effect varied with Anopheles species and sex.ConclusionsVariation in the abundance of indoor-resting Anopheles in rural houses of western Kenya varies with clearly identifiable factors. Results suggest that LLIN use continues to function in reducing vector abundance, and that larval source management in this region could lead to further reductions in malaria risk by reducing the amount of an obligatory resource for mosquitoes near people’s homes.

AB - BackgroundSpatial determinants of malaria risk within communities are associated with heterogeneity of exposure to vector mosquitoes. The abundance of adult malaria vectors inside people’s houses, where most transmission takes place, should be associated with several factors: proximity of houses to larval habitats, structural characteristics of houses, indoor use of vector control tools containing insecticides, and human behavioural and environmental factors in and near houses. While most previous studies have assessed the association of larval habitat proximity in landscapes with relatively low densities of larval habitats, in this study these relationships were analysed in a region of rural, lowland western Kenya with high larval habitat density.Methods525 houses were sampled for indoor-resting mosquitoes across an 8 by 8 km study area using the pyrethrum spray catch method. A predictive model of larval habitat location in this landscape, previously verified, provided derivations of indices of larval habitat proximity to houses. Using geostatistical regression models, the association of larval habitat proximity, long-lasting insecticidal nets (LLIN) use, house structural characteristics (wall type, roof type), and peridomestic variables (cooking in the house, cattle near the house, number of people sleeping in the house) with mosquito abundance in houses was quantified.ResultsVector abundance was low (mean, 1.1 adult Anopheles per house). Proximity of larval habitats was a strong predictor of Anopheles abundance. Houses without an LLIN had more female Anopheles gambiae s.s., Anopheles arabiensis and Anopheles funestus than houses where some people used an LLIN (rate ratios, 95% CI 0.87, 0.85–0.89; 0.84, 0.82–0.86; 0.38, 0.37–0.40) and houses where everyone used an LLIN (RR, 95% CI 0.49, 0.48–0.50; 0.39, 0.39–0.40; 0.60, 0.58–0.61). Cooking in the house also reduced Anopheles abundance across all species. The number of people sleeping in the house, presence of cattle near the house, and house structure modulated Anopheles abundance, but the effect varied with Anopheles species and sex.ConclusionsVariation in the abundance of indoor-resting Anopheles in rural houses of western Kenya varies with clearly identifiable factors. Results suggest that LLIN use continues to function in reducing vector abundance, and that larval source management in this region could lead to further reductions in malaria risk by reducing the amount of an obligatory resource for mosquitoes near people’s homes.

KW - Spatial heterogeneity

KW - Larval habitats

KW - Malaria vectors

KW - Anopheles gambiae

KW - Anopheles arabiensis

KW - Anopheles funestus

KW - Generalized linear models

KW - Geostatistical models

U2 - 10.1186/s12936-017-1938-1

DO - 10.1186/s12936-017-1938-1

M3 - Journal article

VL - 16

JO - Malaria Journal

JF - Malaria Journal

SN - 1475-2875

M1 - 288

ER -