Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments
Aedes albopictus is an invasive mosquito species that can maintain and transmit several arboviruses causing disease in humans. Understanding the determinants of its ecology and population dynamics to predict its abundance was the main objective of this study.Adult mosquitoes were captured weekly bet...
| Autores: | , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/43501 |
| Acceso en línea: | https://hdl.handle.net/10578/43501 |
| Access Level: | acceso abierto |
| Palabra clave: | Invasive species Meteorological modelling Mosquito Population dynamics Vector-borne disease |
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| dc.title.none.fl_str_mv |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments |
| title |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments |
| spellingShingle |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments Torina , Alessandra Invasive species Meteorological modelling Mosquito Population dynamics Vector-borne disease |
| title_short |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments |
| title_full |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments |
| title_fullStr |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments |
| title_full_unstemmed |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments |
| title_sort |
Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environments |
| dc.creator.none.fl_str_mv |
Torina , Alessandra la Russa , Francesco Blanda , Valeria Peralbo Moreno, Alfonso Casades Martí, Laia Di Paquale , Liliana Bongiorno , Carmelo Badaco , Valeria Vitale Toma , Luciano Ruiz Fons, José Francisco |
| author |
Torina , Alessandra |
| author_facet |
Torina , Alessandra la Russa , Francesco Blanda , Valeria Peralbo Moreno, Alfonso Casades Martí, Laia Di Paquale , Liliana Bongiorno , Carmelo Badaco , Valeria Vitale Toma , Luciano Ruiz Fons, José Francisco |
| author_role |
author |
| author2 |
la Russa , Francesco Blanda , Valeria Peralbo Moreno, Alfonso Casades Martí, Laia Di Paquale , Liliana Bongiorno , Carmelo Badaco , Valeria Vitale Toma , Luciano Ruiz Fons, José Francisco |
| author2_role |
author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Invasive species Meteorological modelling Mosquito Population dynamics Vector-borne disease |
| topic |
Invasive species Meteorological modelling Mosquito Population dynamics Vector-borne disease |
| description |
Aedes albopictus is an invasive mosquito species that can maintain and transmit several arboviruses causing disease in humans. Understanding the determinants of its ecology and population dynamics to predict its abundance was the main objective of this study.Adult mosquitoes were captured weekly between 2009 and 2016 with BG sentinel traps baited with BG-Lure outdoors at a collection site within the urban area of Palermo (southern Italy). In parallel, between 2012 and 2016, we monitored the uninterrupted weekly abundance of Ae. albopictus at four additional sites nearby over an area of about two hectares. Catches were collected three times per week and mosquitoes were identified morphologically.To identify the determinants of mosquito abundance, seasonal autoregressive integrated moving-average and Poisson regression models were fitted to the weekly abundance of Ae. albopictus with a series of weather predictors that potentially modulate its activity and population dynamics. The time lag of the influence of predictors was analysed to identify the intergenerational environmental determinants of Ae. albopictus population dynamics. A cross-validation of the predictive accuracy of the different models was carried out to select the best predictive model. Over 7 years we captured 12,152 Ae. albopictus in the first trap and another 58,710 in four years of trapping in four additional traps. Aedes albopictus abundance was highly seasonal, with activity between mid-March and late December, highest abundances between July and September, and peak abundances in autumn. The predictive potential of the best model was further externally validated with four years of data from the other four traps, showing a high predictive capacity and a very good fit of seasonality and abundance peaks. Relative humidity, vapour saturation deficit and wind speed were identified as the main determinants of the weekly abundance of Ae. albopictus. The results obtained will allow accurate prediction of the abundance of this invasive mosquito in coastal Mediterranean areas and the design of ad-hoc measures for efficient and environmentally sustainable control. |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023 2025 2025 |
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info:eu-repo/semantics/article |
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article |
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https://hdl.handle.net/10578/43501 |
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https://hdl.handle.net/10578/43501 |
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Inglés |
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Inglés |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf application/pdf |
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Elsevier |
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Elsevier |
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reponame:RUIdeRA. Repositorio Institucional de la UCLM instname:Universidad de Castilla-La Mancha |
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Universidad de Castilla-La Mancha |
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RUIdeRA. Repositorio Institucional de la UCLM |
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RUIdeRA. Repositorio Institucional de la UCLM |
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1869411654802866176 |
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Modelling time-series Aedes albopictus abundance as a forecasting tool in urban environmentsTorina , Alessandrala Russa , FrancescoBlanda , ValeriaPeralbo Moreno, AlfonsoCasades Martí, LaiaDi Paquale , LilianaBongiorno , CarmeloBadaco , Valeria VitaleToma , LucianoRuiz Fons, José FranciscoInvasive speciesMeteorological modellingMosquitoPopulation dynamicsVector-borne diseaseAedes albopictus is an invasive mosquito species that can maintain and transmit several arboviruses causing disease in humans. Understanding the determinants of its ecology and population dynamics to predict its abundance was the main objective of this study.Adult mosquitoes were captured weekly between 2009 and 2016 with BG sentinel traps baited with BG-Lure outdoors at a collection site within the urban area of Palermo (southern Italy). In parallel, between 2012 and 2016, we monitored the uninterrupted weekly abundance of Ae. albopictus at four additional sites nearby over an area of about two hectares. Catches were collected three times per week and mosquitoes were identified morphologically.To identify the determinants of mosquito abundance, seasonal autoregressive integrated moving-average and Poisson regression models were fitted to the weekly abundance of Ae. albopictus with a series of weather predictors that potentially modulate its activity and population dynamics. The time lag of the influence of predictors was analysed to identify the intergenerational environmental determinants of Ae. albopictus population dynamics. A cross-validation of the predictive accuracy of the different models was carried out to select the best predictive model. Over 7 years we captured 12,152 Ae. albopictus in the first trap and another 58,710 in four years of trapping in four additional traps. Aedes albopictus abundance was highly seasonal, with activity between mid-March and late December, highest abundances between July and September, and peak abundances in autumn. The predictive potential of the best model was further externally validated with four years of data from the other four traps, showing a high predictive capacity and a very good fit of seasonality and abundance peaks. Relative humidity, vapour saturation deficit and wind speed were identified as the main determinants of the weekly abundance of Ae. albopictus. The results obtained will allow accurate prediction of the abundance of this invasive mosquito in coastal Mediterranean areas and the design of ad-hoc measures for efficient and environmentally sustainable control.Aedes albopictus is an invasive mosquito species that can maintain and transmit several arboviruses causing disease in humans. Understanding the determinants of its ecology and population dynamics to predict its abundance was the main objective of this study.Adult mosquitoes were captured weekly between 2009 and 2016 with BG sentinel traps baited with BG-Lure outdoors at a collection site within the urban area of Palermo (southern Italy). In parallel, between 2012 and 2016, we monitored the uninterrupted weekly abundance of Ae. albopictus at four additional sites nearby over an area of about two hectares. Catches were collected three times per week and mosquitoes were identified morphologically.To identify the determinants of mosquito abundance, seasonal autoregressive integrated moving-average and Poisson regression models were fitted to the weekly abundance of Ae. albopictus with a series of weather predictors that potentially modulate its activity and population dynamics. The time lag of the influence of predictors was analysed to identify the intergenerational environmental determinants of Ae. albopictus population dynamics. A cross-validation of the predictive accuracy of the different models was carried out to select the best predictive model. Over 7 years we captured 12,152 Ae. albopictus in the first trap and another 58,710 in four years of trapping in four additional traps. Aedes albopictus abundance was highly seasonal, with activity between mid-March and late December, highest abundances between July and September, and peak abundances in autumn. The predictive potential of the best model was further externally validated with four years of data from the other four traps, showing a high predictive capacity and a very good fit of seasonality and abundance peaks. Relative humidity, vapour saturation deficit and wind speed were identified as the main determinants of the weekly abundance of Ae. albopictus. The results obtained will allow accurate prediction of the abundance of this invasive mosquito in coastal Mediterranean areas and the design of ad-hoc measures for efficient and environmentally sustainable control.Elsevier202520252023info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://hdl.handle.net/10578/43501reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglésinfo:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/435012026-05-27T07:36:41Z |
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15,812455 |