title: Data informed analysis of 2014 dengue fever outbreak in Guangzhou: Impact of multiple environmental factors and vector control.
abstract: Epidemics of dengue fever in China were reported before 1940 and the outbreak of dengue fever in Guangdong province in 2014 is the most serious so far. The important question is what factors account for this serious outbreak, and how to evaluate the sensitivity of the multiple factors including weather variables and human actions on the dengue disease. Therefore, according to the relations among the temperature (daily mean temperature (DMT) and diurnal temperature range (DTR)), vector parameters and reproduction number we have proposed the analytical formula for the relative vector's capacity and effective reproduction number, and then we have the formula for the likelihood function by employing the generation interval-informed method. This allows us to estimate the unknown vector parameters by the maximum likelihood method and carry out the sensitivity analysis. The correlations between the density of mosquito vectors (the Breteau index (BI), the adult mosquito density) and the daily newly reported cases of four different districts of Guangzhou city have been studied by using the Pearson correlation and cross-correlation analyses. Our findings indicate that both the BI and the adult mosquito density are statistically significantly correlated with the daily newly reported cases, and the vector parameters are closely related to the DMT and DTR with relative complex relationships, which influence the effective reproduction number comprehensively. Moreover, the trend of the effective reproduction number is consistent with daily newly reported cases, which confirms the effectiveness of the government control measures. Sensitivity analysis results indicate that the temperature can be either an effective barrier or a facilitator of vector-borne diseases, and consequently weather variable may result in complexity of dengue disease control.
authors.affiliation: School of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710062, PR China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Jing
authors.affiliation: School of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710062, PR China. Electronic address: xiawang@snnu.edu.cn.
authors.forename: Xia
authors.initials: X
authors.lastname: Wang
authors.affiliation: School of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710062, PR China. Electronic address: sytang@snnu.edu.cn.
authors.forename: Sanyi
authors.initials: S
authors.lastname: Tang
authors.affiliation: Centre for Disease Modelling, York Institute for Health Research, York University, Toronto, Ontario, Canada.
authors.forename: Jianhong
authors.initials: J
authors.lastname: Wu
mesh_terms: D000818:Animals; D002681:China / Q000453:epidemiology; D003715:Dengue / Q000453:epidemiology* / Q000517:prevention & control; D004196:Disease Outbreaks / Q000517:prevention & control*; D006078:Government Programs; D006801:Humans; D016013:Likelihood Functions; D009032:Mosquito Control; D000072138:Mosquito Vectors; D013696:Temperature; D014887:Weather
keywords: Breteau index; Intervention; Reproduction number; Temperature; Vector-borne disease