Estimating The Mosquito Density In Guangzhou City,China

Mosquitoes are vectors of many diseases.Predicting the trend of mosquito density is important for early warning and control of mosquito diseases.In this paper,we fit a discrete time mosquito model developed by Gong et al.in 2011 using Breteau Index and Bite Index data for monitoring Aedes albopictus in Guangzhou city,China,in 2014 and weather data recorded during the same period including average temperature,precipitation,evaporation and day length.This discrete time mosquito model takes into account the immature stage and adult stage of mosquitoes,as well as model parameters dependent on weather factors,such as: the fecundity rate of adults related to water index,the maturation rate and survival rate of immature mosquitoes and survival rate of adults related to temperature,and diapause rate of adults related to day length.We estimate the model parameters using the Markov chain Monte Carlo(MCMC)method.We find that many model parameters are not identifiable.We revise and simplify the model so that the parameters of our model are identifiable.We then reuse the mosquito monitoring data and the weather data in Guangzhou city,China in 2014 to fit the revised and simplified model,and we find that the parameters of the model can be identifiable.We then take the estimated model parameters into our improved model,plotting the predicted mosquito density to compare with the Breteau Index and Bite Index data in Guangzhou city in 2014.Our results show that the mosquito prevalence trends predicted by the improved model are in good agreement with the Breteau Index and Bite Index data.We then validate the estimated parameter values and the improved model using the mosquito monitoring data and the weather data in Guangzhou city in 2017 and 2018,accordingly plotting the predicted mosquito density to compare with the Breteau Index and Bite Index data in Guangzhou city in 2017 and2018.The results show that the mosquito density predicted by the improved model is in good agreement with the Breteau Index and Bite Index data,which indicates that the estimated parameters and the improved model are also applicable to Guangzhou city in 2017 and 2018.