Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern Italy

Abstract Background In Italy, malaria was endemic until the 1970s, when it was declared eradicated by WHO. Nowadays, with the persistence of competent mosquito populations, the effect of climate change, and increased possibility of importing malaria parasites from endemic counties due to growing mig...

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Main Authors: Gianni Gilioli, Francesco Defilippo, Anna Simonetto, Alessandro Heinzl, Manlio Migliorati, Mattia Calzolari, Sabrina Canziani, Davide Lelli, Antonio Lavazza
Format: Article
Language:English
Published: BMC 2024-03-01
Series:Parasites & Vectors
Subjects:
Online Access:https://doi.org/10.1186/s13071-024-06208-6
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author Gianni Gilioli
Francesco Defilippo
Anna Simonetto
Alessandro Heinzl
Manlio Migliorati
Mattia Calzolari
Sabrina Canziani
Davide Lelli
Antonio Lavazza
author_facet Gianni Gilioli
Francesco Defilippo
Anna Simonetto
Alessandro Heinzl
Manlio Migliorati
Mattia Calzolari
Sabrina Canziani
Davide Lelli
Antonio Lavazza
author_sort Gianni Gilioli
collection DOAJ
description Abstract Background In Italy, malaria was endemic until the 1970s, when it was declared eradicated by WHO. Nowadays, with the persistence of competent mosquito populations, the effect of climate change, and increased possibility of importing malaria parasites from endemic counties due to growing migration, a malaria resurgence in Italy has become more likely. Hence, enhancing the understanding of the current distribution of the Anopheles maculipennis complex and the factors that influence the presence of this malaria vector is crucial, especially in Northern Italy, characterised by a high density of both human population and livestock. Methods To assess the presence and abundance of malaria vectors, a 4-year field survey in the plain areas of Lombardy and Emilia-Romagna region in Italy was conducted. Every sampling point was characterised in space by the land use in a 500-m radius and in time considering meteorological data collected in the short and long time periods before sampling. We combined the results of a linear regression model with a random forest analysis to understand the relative importance of the investigated niche dimensions in determining Anopheles mosquito presence and abundance. Results The estimated normalised variable importance indicates that rice fields were the most important land use class explaining the presence of Anopheles, followed by transitional woodlands and shrubland. Farm buildings were the third variable in terms of importance, likely because of the presence of animal shelters, followed by urbanised land. The two most important meteorological variables influencing the abundance of Anopheles in our study area were mean temperature in the 24 h before the sampling date and the sum of degree-days with temperature between 18 °C and 30 °C in the 14 days before the sampling date. Conclusions The results obtained in this study could be helpful in predicting the risk of autochthonous malaria transmission, based on local information on land cover classes that might facilitate the presence of malaria vectors and presence of short- and medium-term meteorological conditions favourable to mosquito development and activity. The results can support the design of vector control measures through environmental management. Graphical Abstract
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spelling doaj.art-fb1704377f05441482ff5416083d03da2024-03-10T12:07:08ZengBMCParasites & Vectors1756-33052024-03-0117111010.1186/s13071-024-06208-6Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern ItalyGianni Gilioli0Francesco Defilippo1Anna Simonetto2Alessandro Heinzl3Manlio Migliorati4Mattia Calzolari5Sabrina Canziani6Davide Lelli7Antonio Lavazza8Department of Civil Engineering Architecture Land and Environment and Mathematics, University of BresciaInstitute Zooprofilattico Sperimentale Della Lombardia E Dell’Emilia RomagnaDepartment of Civil Engineering Architecture Land and Environment and Mathematics, University of BresciaDepartment of Civil Engineering Architecture Land and Environment and Mathematics, University of BresciaDepartment of Civil Engineering Architecture Land and Environment and Mathematics, University of BresciaInstitute Zooprofilattico Sperimentale Della Lombardia E Dell’Emilia RomagnaInstitute Zooprofilattico Sperimentale Della Lombardia E Dell’Emilia RomagnaInstitute Zooprofilattico Sperimentale Della Lombardia E Dell’Emilia RomagnaInstitute Zooprofilattico Sperimentale Della Lombardia E Dell’Emilia RomagnaAbstract Background In Italy, malaria was endemic until the 1970s, when it was declared eradicated by WHO. Nowadays, with the persistence of competent mosquito populations, the effect of climate change, and increased possibility of importing malaria parasites from endemic counties due to growing migration, a malaria resurgence in Italy has become more likely. Hence, enhancing the understanding of the current distribution of the Anopheles maculipennis complex and the factors that influence the presence of this malaria vector is crucial, especially in Northern Italy, characterised by a high density of both human population and livestock. Methods To assess the presence and abundance of malaria vectors, a 4-year field survey in the plain areas of Lombardy and Emilia-Romagna region in Italy was conducted. Every sampling point was characterised in space by the land use in a 500-m radius and in time considering meteorological data collected in the short and long time periods before sampling. We combined the results of a linear regression model with a random forest analysis to understand the relative importance of the investigated niche dimensions in determining Anopheles mosquito presence and abundance. Results The estimated normalised variable importance indicates that rice fields were the most important land use class explaining the presence of Anopheles, followed by transitional woodlands and shrubland. Farm buildings were the third variable in terms of importance, likely because of the presence of animal shelters, followed by urbanised land. The two most important meteorological variables influencing the abundance of Anopheles in our study area were mean temperature in the 24 h before the sampling date and the sum of degree-days with temperature between 18 °C and 30 °C in the 14 days before the sampling date. Conclusions The results obtained in this study could be helpful in predicting the risk of autochthonous malaria transmission, based on local information on land cover classes that might facilitate the presence of malaria vectors and presence of short- and medium-term meteorological conditions favourable to mosquito development and activity. The results can support the design of vector control measures through environmental management. Graphical Abstracthttps://doi.org/10.1186/s13071-024-06208-6MalariaAnophelesLand useMeteorological variables
spellingShingle Gianni Gilioli
Francesco Defilippo
Anna Simonetto
Alessandro Heinzl
Manlio Migliorati
Mattia Calzolari
Sabrina Canziani
Davide Lelli
Antonio Lavazza
Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern Italy
Parasites & Vectors
Malaria
Anopheles
Land use
Meteorological variables
title Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern Italy
title_full Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern Italy
title_fullStr Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern Italy
title_full_unstemmed Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern Italy
title_short Characterization of environmental drivers influencing the abundance of Anopheles maculipennis complex in Northern Italy
title_sort characterization of environmental drivers influencing the abundance of anopheles maculipennis complex in northern italy
topic Malaria
Anopheles
Land use
Meteorological variables
url https://doi.org/10.1186/s13071-024-06208-6
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