Mechanistic model for predicting the seasonal abundance of Culicoides biting midges and the impacts of insecticide control

Steven M White,Christopher R Shortall,Christopher J Sanders,Bethan V Purse

doi:10.1186/s13071-017-2097-5

Steven M White, Christopher R Shortall + Show 2 more

Open Access

https://doi.org/10.1186/s13071-017-2097-5

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Abstract

BackgroundUnderstanding seasonal patterns of abundance of insect vectors is important for optimisation of control strategies of vector-borne diseases. Environmental drivers such as temperature, humidity and photoperiod influence vector abundance, but it is not generally known how these drivers combine to affect seasonal population dynamics.MethodsIn this paper, we derive and analyse a novel mechanistic stage-structured simulation model for Culicoides biting midges-the principle vectors of bluetongue and Schmallenberg viruses which cause mortality and morbidity in livestock and impact trade. We model variable life-history traits as functional forms that are dependent on environmental drivers, including air temperature, soil temperature and photoperiod. The model is fitted to Obsoletus group adult suction-trap data sampled daily at five locations throughout the UK for 2008.ResultsThe model predicts population dynamics that closely resemble UK field observations, including the characteristic biannual peaks of adult abundance. Using the model, we then investigate the effects of insecticide control, showing that control strategies focussing on the autumn peak of adult midge abundance have the highest impact in terms of population reduction in the autumn and averaged over the year. Conversely, control during the spring peak of adult abundance leads to adverse increases in adult abundance in the autumn peak.ConclusionsThe mechanisms of the biannual peaks of adult abundance, which are important features of midge seasonality in northern Europe and are key determinants of the risk of establishment and spread of midge-borne diseases, have been hypothesised over for many years. Our model suggests that the peaks correspond to two generations per year (bivoltine) are largely determined by pre-adult development. Furthermore, control strategies should focus on reducing the autumn peak since the immature stages are released from density-dependence regulation. We conclude that more extensive modelling of Culicoides biting midge populations in different geographical contexts will help to optimise control strategies and predictions of disease outbreaks.

Highlights

Understanding seasonal patterns of abundance of insect vectors is important for optimisation of control strategies of vector-borne diseases
Vector-borne diseases account for a large proportion, approximately 30%, of the World’s emerging infectious diseases, and the rate of emergence is on the increase [1]
For other midge-borne pathogens, disease impacts may depend on whether infection by adult vectors occurs during a critical window in the seasonal reproductive cycle of host animals (Schmallenberg virus infection must occur in a particular period of pregnancy in host ruminants to result in abortions or congenital malformations [10, 11])

Summary

Introduction

Understanding seasonal patterns of abundance of insect vectors is important for optimisation of control strategies of vector-borne diseases. Understanding seasonal dynamics of Culicoides is critical to understanding and predicting persistence and spread of these emerging, high impact livestock diseases, in temperate zones, and to optimising mitigation strategies. This understanding is critical for Europe which has suffered tens of thousands of outbreaks due to multiple incursions and rapid spread of bluetongue virus strains [15, 16] and the emergence and spread of a novel Orthabunyavirus, Schmallenberg virus [17]

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