Location: Location not imported yet.Title: Ecology of West Nile virus across four European countries II: Empirical modelling of the dynamics of Culex pipens abundances in different regions
|GROEN, THOMAS - University Of Twente|
|L'AMBERT, GREGORY - Eid-Mediterranean|
|BELLINI, ROMEO - Caa G Nicoli|
|CHASKOPOULOU, ALEXANDRA - European Biological Control Laboratory (EBCL)|
|PETRIC, DUSAN - University Of Novi Sad|
|ZGOMBA, MARIJA - University Of Novi Sad|
|MARRAMA, LAURENCE - European Centre For Disease Control And Prevention|
|BICOUT, DOMINIQUE - University Of Lyon|
Submitted to: Parasites & Vectors
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/17/2017
Publication Date: 10/26/2017
Citation: Groen, T.A., L'Ambert, G., Bellini, R., Chaskopoulou, A., Petric, D., Zgomba, M., Marrama, L., Bicout, D.J. 2017. Ecology of West Nile virus across four European countries II: Empirical modelling of the dynamics of Culex pipens abundances in different regions. Parasites & Vectors. 10(1):524. https://doi.org/10.1186/s13071-017-2484-y.
Interpretive Summary: West Nile virus (WNV) represents a serious burden to human and animal health because of its capacity to cause unforeseen and large epidemics. In nature, the virus circulates in a forest/rural cycle, between birds and mosquitoes particularly members of the genus Culex, and under certain environmental conditions it spills over to human settlements where it infects humans and horses causing large epidemics. Precipitation, temperature and land use are among the most important environmental parameters that influence the life-cycles of the mosquito, the virus, the amplifying and accidental hosts and the interactions between them. Because of these features, outbreaks of WNV infection are highly sporadic and focal in nature, exhibiting high variability in their development and incidence across different regions. Studies are needed at local levels that compare different habitats and mosquito/vertebrate communities to determine how environmental parameters influence vector population and disease transmission dynamics and how mosquito control interventions may alter these dynamics. We used mathematical modeling to increase our understanding on how weather variables affect mosquito populations of the genus Culex in different parts of Europe. The results show that daily temperature is a good predictor of C. pipiens population size, and that a SARIMA model is better, but that there are other local environmental factors that need to be known before a universal predictive model can be developed.
Technical Abstract: Culex pipiens is the major vector of West Nile Virus in Europe, and is causing frequent outbreaks throughout the southern part of the continent. Proper empirical modelling of the population dynamics of this species can help in understanding West Nile Virus epidemiology, optimizing vector surveillance and evaluating mosquito control efforts. But modelling results may differ from place to place. In this study we look at which type of models and weather variables can be consistently used across different locations. Weekly mosquito trap collections from 8 functional units located in France, Greece, Italy and Serbia for several years were combined. Additionally rainfall, relative humidity and temperature were recorded. Correlations between lagged weather conditions and Cx. pipiens dynamics were analysed. Also seasonal autoregressive integrating moving average (SARIMA) models were fitted to describe the temporal dynamics of Cx. pipiens and to check whether the weather variables could improve these models. Correlations were strongest between mean temperatures at short time lags, followed by relative humidity, probably due to collinearity. Precipitation alone had weak correlations and inconsistent patterns across sites. SARIMA models could also make reasonable predictions, especially when longer time series of Cx. pipiens observations are available. Average temperature was a consistently good predictor across sites. When only short time series of observations are available, average temperature can be therefore used to model Cx. pipiens dynamics. When longer time series are available SARIMAs can provide better statistical descriptions of Cx. pipiens dynamics, without the need for further weather variables.