title: A climate-driven mechanistic population model of Aedes albopictus with diapause.
abstract: BACKGROUND
  The mosquito Aedes albopitus is a competent vector for the transmission of many blood-borne pathogens. An important factor that affects the mosquitoes' development and spreading is climate, such as temperature, precipitation and photoperiod. Existing climate-driven mechanistic models overlook the seasonal pattern of diapause, referred to as the survival strategy of mosquito eggs being dormant and unable to hatch under extreme weather. With respect to diapause, several issues remain unaddressed, including identifying the time when diapause eggs are laid and hatched under different climatic conditions, demarcating the thresholds of diapause and non-diapause periods, and considering the mortality rate of diapause eggs.
  
  
  METHODS
  Here we propose a generic climate-driven mechanistic population model of Ae. albopitus applicable to most Ae. albopictus-colonized areas. The new model is an improvement over the previous work by incorporating the diapause behaviors with many modifications to the stage-specific mechanism of the mosquitoes' life-cycle. monthly Container Index (CI) of Ae. albopitus collected in two Chinese cities, Guangzhou and Shanghai is used for model validation.
  
  
  RESULTS
  The simulation results by the proposed model is validated with entomological field data by the Pearson correlation coefficient r (2) in Guangzhou (r (2) = 0.84) and in Shanghai (r (2) = 0.90). In addition, by consolidating the effect of diapause-related adjustments and temperature-related parameters in the model, the improvement is significant over the basic model.
  
  
  CONCLUSIONS
  The model highlights the importance of considering diapause in simulating Ae. albopitus population. It also corroborates that temperature and photoperiod are significant in affecting the population dynamics of the mosquito. By refining the relationship between Ae. albopitus population and climatic factors, the model serves to establish a mechanistic relation to the growth and decline of the species. Understanding this relationship in a better way will benefit studying the transmission and the spatiotemporal distribution of mosquito-borne epidemics and eventually facilitating the early warning and control of the diseases.
authors.affiliation: College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China.
authors.forename: Pengfei
authors.initials: P
authors.lastname: Jia
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, China CDC, Beijing, 102206, China.
authors.forename: Liang
authors.initials: L
authors.lastname: Lu
authors.affiliation: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China. chenxiangpeter@gmail.com.|Department of Emergency Management, Arkansas Tech University, Russellville, Arkansas, 72801, USA. chenxiangpeter@gmail.com.
authors.forename: Xiang
authors.initials: X
authors.lastname: Chen
authors.affiliation: College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China.|State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Chen
authors.affiliation: College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China.
authors.forename: Li
authors.initials: L
authors.lastname: Guo
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, China CDC, Beijing, 102206, China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Yu
authors.affiliation: State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, China CDC, Beijing, 102206, China.
authors.forename: Qiyong
authors.initials: Q
authors.lastname: Liu
mesh_terms: D000330:Aedes / Q000254:growth & development*; D000818:Animals; D002681:China; D002947:Cities; D002980:Climate; D004772:Entomology / Q000379:methods*; D015233:Models, Statistical; D011157:Population Dynamics
keywords: Aedes albopictus; Climate-driven; Diapause; Mechanistic model; Population dynamics