The only way for dengue to spread in the human population is through the human-mosquito-human cycle. Most research in this field discusses the dengue-mosquito or dengue-human relationships over a particular study area, but few have explored the local spatial variations of dengue-mosquito and dengue-human relationships within a study area. This study examined whether spatial heterogeneity exists in these relationships. We used Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models to analyze spatial relationships and identify the geographical heterogeneities by using the information of entomology and dengue cases in the cities of Kaohsiung and Fengshan in 2002. Our findings indicate that dengue-mosquito and dengue-human relationships were significantly spatially non-stationary. This means that in some areas higher dengue incidences were associated with higher vector/host densities, but in some areas higher incidences were related to lower vector/host densities. We demonstrated that a GWR model can be used to geographically differentiate the relationships of dengue incidence with immature mosquito and human densities. This study provides more insights into spatial targeting of intervention and control programs against dengue outbreaks within the study areas.

Travelers who acquire dengue infection are often routes for virus transmission to other regions. Nevertheless, the interplay between infected travelers, climate, vectors, and indigenous dengue incidence remains unclear. The role of foreign-origin cases on local dengue epidemics thus has been largely neglected by research. This study investigated the effect of both imported dengue and local meteorological factors on the occurrence of indigenous dengue in Taiwan. Using logistic and Poisson regression models, we analyzed bi-weekly, laboratory-confirmed dengue cases at their onset dates of illness from 1998 to 2007 to identify correlations between indigenous dengue and imported dengue cases (in the context of local meteorological factors) across different time lags. Our results revealed that the occurrence of indigenous dengue was significantly correlated with temporally-lagged cases of imported dengue (2–14 weeks), higher temperatures (6–14 weeks), and lower relative humidity (6–20 weeks). In addition, imported and indigenous dengue cases had a significant quantitative relationship in the onset of local epidemics. However, this relationship became less significant once indigenous epidemics progressed past the initial stage. These findings imply that imported dengue cases are able to initiate indigenous epidemics when appropriate weather conditions are present. Early detection and case management of imported cases through rapid diagnosis may avert large-scale epidemics of dengue/dengue hemorrhagic fever. The deployment of an early-warning surveillance system, with the capacity to integrate meteorological data, will be an invaluable tool for successful prevention and control of dengue, particularly in non-endemic countries. Dengue/dengue hemorrhagic fever is the world's most widely spread mosquito-borne arboviral disease and threatens more than two-thirds of the world's population. Cases are mainly distributed in tropical and subtropical areas in accordance with vector habitats for Aedes aegypti and Ae. albopictus. However, the role of imported cases and favorable meteorological conditions has not yet been quantitatively assessed. This study verified the correlation between the occurrence of indigenous dengue and imported cases in the context of weather variables (temperature, rainfall, relative humidity, etc.) for different time lags in southern Taiwan. Our findings imply that imported cases have a role in igniting indigenous outbreaks, in non-endemics areas, when favorable weather conditions are present. This relationship becomes insignificant in the late phase of local dengue epidemics. Therefore, early detection and case management of imported cases through timely surveillance and rapid laboratory-diagnosis may avert large scale epidemics of dengue/dengue hemorrhagic fever. An early-warning surveillance system integrating meteorological data will be an invaluable tool for successful prevention and control of dengue, particularly in non-endemic countries.

Aedes aegypti L. is the primary dengue vector in southern Taiwan. This article is the first report on a large-scale surveillance program to study the

Commuters who acquire dengue infections could be an important route for the transmission of the virus from their homes to workplaces. Understanding the effects of routine human movement on dengue transmission can be helpful in identifying high-risk areas for effective intervention. This study investigated the effects of local environmental and demographic characteristics to clarify the role of the daily commute in dengue transmission. We analyzed the clustering patterns of space–time distances between commuting and noncommuting dengue cases from June 2007 to January 2008 in Tainan City, Taiwan. We also analyzed the network topology of space–time distances to identify possible key individuals and conducted time-to-event analysis for geographic diffusion through commuting versus noncommuting dengue cases. Our significant findings indicate that most of the space–time distances of noncommuting cases clustered within 100 m and one week, whereas commuting cases clustered within 2 to 4 km and one to five weeks. Analysis of the temporality of the geographical diffusion by villages showed that commuting cases diffuse more rapidly across villages than noncommuting cases in the late epidemic period. The role of commuting was identified as a significant risk factor contributing to epidemic diffusion (hazard ratio: 3.08, p value < 0.05). Local neighborhood characteristics (number of vacant grounds and empty houses) are independent facilitating factors for diffusion through both noncommuting cases and commuting cases (hazard ratio: 1.035 and 1.022, respectively, both p < 0.05). Higher population density is a significant risk factor only for diffusion through commuters (hazard ratio: 1.174). In summary, noncommuters, mostly elderly adults and housewives, might initiate local outbreaks, whereas commuters carrying the virus to geographically distant areas cause large-scale epidemics.