Mapping of Aedes albopictus Abundance at a Local Scale in Italy

Frédéric Baldacchino,Giovanni Marini,Roberto Zorer,Matteo Marcantonio,Mattia Manica,Gioia Capelli,Fabrizio Montarsi,Annapaola Rizzoli,Roberto Rosà,Daniele Arnoldi,Luca Delucchi

doi:10.3390/rs9070749

Abstract

Given the growing risk of arbovirus outbreaks in Europe, there is a clear need to better describe the distribution of invasive mosquito species such as Aedes albopictus. Current challenges consist in simulating Ae. albopictus abundance, rather than its presence, and mapping its simulated abundance at a local scale to better assess the transmission risk of mosquito-borne pathogens and optimize mosquito control strategy. During 2014–2015, we sampled adult mosquitoes using 72 BG-Sentinel traps per year in the provinces of Belluno and Trento, Italy. We found that the sum of Ae. albopictus females collected during eight trap nights from June to September was positively related to the mean temperature of the warmest quarter and the percentage of artificial areas in a 250 m buffer around the sampling locations. Maps of Ae. albopictus abundance simulated from the most parsimonious model in the study area showed the largest populations in highly artificial areas with the highest summer temperatures, but with a high uncertainty due to the variability of the trapping collections. Vector abundance maps at a local scale should be promoted to support stakeholders and policy-makers in optimizing vector surveillance and control.

Highlights

The increasing spread of invasive mosquito species (IMS) and theemergence of mosquito-borne pathogens, such as the dengue, chikungunya, and Zika viruses, are a major threat to public health worldwide [1,2]
We aimed to model the abundance of Ae. albopictus females collected from adult traps, including both meteorological and LULC variables, and produce a map of the simulated abundance of this species in a specific area of north-eastern Italy
We investigated the association between Ae. albopictus female abundance and a range of meteorological and LULC variables based on the collection carried out during 2014–2015 using R version 3.2.2 [42]

Summary

Introduction

The increasing spread of invasive mosquito species (IMS) and the (re-)emergence of mosquito-borne pathogens, such as the dengue, chikungunya, and Zika viruses, are a major threat to public health worldwide [1,2]. In Europe, Ae. albopictus has colonized almost all of the Mediterranean countries, and has been involved in the local transmission of the dengue and chikungunya viruses in Italy, France, and Croatia [5]. Given the growing risk of arbovirus outbreaks in Europe, it is crucial to better describe the distribution of IMS such as Ae. albopictus based on species distribution models and mapping. Remote Sensing (RS) and Geographic Information Systems (GIS) are helpful tools for predicting and mapping species distribution [8,9]

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Discussion

Conclusion