Incorporating the human-Aedes mosquito interactions into measuring the spatial risk of urban dengue fever

To block human-mosquito interactions by eliminating dengue vectors, Aedes aegypti L. and Aedes albopictus Skuse have been considered the main strategies for dengue prevention. Spatial targeting of dengue risk areas is the highest priority for implementing control measures. However, the frequency of human-Aedes mosquito contacts as human factors for assessing the risk of dengue has not been taken into account by past studies. The objective of this study is to clarify the geographic effects of crowd-gathering places on the frequency of dengue vector for assessing the spatial risk of exposure to dengue in Kaohsiung City, Taiwan. A geographic information system (GIS) was used to integrate crowd-gathering places and ovitrap locations for investigating potential human-mosquito contacts. A negative binominal regression was used to estimate the spatial risk of dengue by integrating vector mosquitoes from the ovitrap survey, urban environmental risk factors and human crowd-gathering places as the surrogate of human activities. We also compared the estimated spatial risk of exposure to dengue with traditional approaches. Our results indicated that the spatial distribution of the residential populations is not consistent with the locations of social activities. Additionally, people closer to crowd-gathering places have a higher frequency of contact with Ae. aegypti than with Ae. albopictus larvae. The dengue risk is caused by the human-Aedes aegypti contacts concentrated around city centers, while the risk caused by the human-Aedes albopictus contacts is distributed around the city boundary. Our study concluded that only relying on infected human cases or the abundance of vector mosquitoes is not enough for assessing the spatial risk of dengue. This reliance could ignore the areas with frequent vector existence and; therefore, result in the underestimated risk of dengue transmission. This study demonstrates the methodological framework for estimating the potential dengue risk and identifies the crowd-gathering places that facilitate dengue transmission.