Mapping of Aedes albopictus Abundance at a Local Scale in Italy

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.

Complementarity of empirical and process-based approaches to modelling mosquito population dynamics with Aedes albopictus as an example—Application to the development of an operational mapping tool of vector populations

“…Two main approaches are used to understand and predict mosquito population dynamics: i) process-based (or mechanistic) models describing biological knowledge within a mathematical or computational framework, and ii) empirical (or statistical) models, which try to find, from the observed data, a predictive function of the response variable (mosquito populations) based on a set of predictors within a statistical or a machine learning framework. Both approaches have been successfully applied to different mosquito species and geographical contexts [5][6][7][8][9][10][11][12][13][14][15][16][17], resulting in a better understanding of their distribution [5-8, 11, 12, 16] and dynamics [9,10,13,17,18] and the assessment of different mosquito control strategies [19,20]. However, most case studies only develop one of the two approaches (either empirical [5-8, 11, 12, 14, 16] or process-based [9,10,13,15,17] depending on the availability of data and knowledge), and do not compare the capacity of the two approaches to predict mosquito population dynamics.…”

“…albopictus distribution and dynamics have been developed in recent years. Distribution maps have been derived from environmental and meteorological datasets using empirical models, at worldwide [7], regional [8], national [11,12] and local scales [6,16]. In Reunion Island, theoretical process-based population dynamics models have been used to assess control strategies [20,25], taking into account mosquito dispersal [26,27] and the impact of human behavior [28].…”

Dirofilaria immitis in wolves recolonizing northern Italy: are wolves competent hosts?

“…2 ) originated from the Alps, where temperatures are not or are rarely favorable to the completion of the D. immitis life-cycle in the potential mosquito vectors, although still compatible with the survival and hatching of mosquito eggs [ 35 – 37 ]. In mountain areas, activity of the potential vectors is also shorter than in lower altitude zones, often permitting no more than a single reproductive cycle per year [ 35 ]. In this study, the maximum altitude recorded for a heartworm-positive wolf was c .350 m above sea level, corresponding to hill zones at the limit with low mountains.…”

Seasonality and timing of peak abundance of <em>Aedes albopictus</em> in Europe: Implications to public and animal health

“…Over the last decade several population models have been created for Ae. albopictus for the USA (Erickson et al, 2010) and for Europe (Poletti et al, 2011;Caminade et al, 2012;Tran et al, 2013;Erguler et al, 2016;Baldacchino et al, 2017;Metelmann et al, 2019;Wint et al, 2020), with some having explicit references to environmental conditions (Erguler et al, 2016). All models focused on local abundance levels with the exception of Erguler et al (2016) which tried to extrapolate the method developed to Europe, but the output represents an index of mosquito habitat suitability instead of abundance.…”

“…Local scale field studies (Medlock et al, 2006;Roiz et al, 2010) provided important insights on the impact of climatic variables and supported the development of local-scale mathematical models (Baldacchino et al, 2017). However, a broader-scale analysis of Ae.…”