Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach

Abstract Background Mechanistic models play an important role in many biological disciplines, and they can effectively contribute to evaluate the spatial-temporal evolution of mosquito populations, in the light of the increasing knowledge of the crucial driving role on vector dynamics played by mete...

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Published in:Malaria Journal
Main Authors: Gilioli Gianni, Mariani Luigi
Format: Article in Journal/Newspaper
Language:English
Published: BMC 2011
Subjects:
Online Access:https://doi.org/10.1186/1475-2875-10-294
https://doaj.org/article/5548c2285f9a4dd48082f8100a674a33
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spelling ftdoajarticles:oai:doaj.org/article:5548c2285f9a4dd48082f8100a674a33 2023-05-15T15:16:42+02:00 Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach Gilioli Gianni Mariani Luigi 2011-10-01T00:00:00Z https://doi.org/10.1186/1475-2875-10-294 https://doaj.org/article/5548c2285f9a4dd48082f8100a674a33 EN eng BMC http://www.malariajournal.com/content/10/1/294 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-10-294 1475-2875 https://doaj.org/article/5548c2285f9a4dd48082f8100a674a33 Malaria Journal, Vol 10, Iss 1, p 294 (2011) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2011 ftdoajarticles https://doi.org/10.1186/1475-2875-10-294 2022-12-31T08:34:29Z Abstract Background Mechanistic models play an important role in many biological disciplines, and they can effectively contribute to evaluate the spatial-temporal evolution of mosquito populations, in the light of the increasing knowledge of the crucial driving role on vector dynamics played by meteo-climatic features as well as other physical-biological characteristics of the landscape. Methods In malaria eco-epidemiology landscape components (atmosphere, water bodies, land use) interact with the epidemiological system (interacting populations of vector, human, and parasite). In the background of the eco-epidemiological approach, a mosquito population model is here proposed to evaluate the sensitivity of An. gambiae s.s. population to some peculiar thermal-pluviometric scenarios. The scenarios are obtained perturbing meteorological time series data referred to four Kenyan sites (Nairobi, Nyabondo, Kibwesi, and Malindi) representing four different eco-epidemiological settings. Results Simulations highlight a strong dependence of mosquito population abundance on temperature variation with well-defined site-specific patterns. The upper extreme of thermal perturbation interval (+ 3°C) gives rise to an increase in adult population abundance at Nairobi (+111%) and Nyabondo (+61%), and a decrease at Kibwezi (-2%) and Malindi (-36%). At the lower extreme perturbation (-3°C) is observed a reduction in both immature and adult mosquito population in three sites (Nairobi -74%, Nyabondo -66%, Kibwezi -39%), and an increase in Malindi (+11%). A coherent non-linear pattern of population variation emerges. The maximum rate of variation is +30% population abundance for +1°C of temperature change, but also almost null and negative values are obtained. Mosquitoes are less sensitive to rainfall and both adults and immature populations display a positive quasi-linear response pattern to rainfall variation. Conclusions The non-linear temperature-dependent response is in agreement with the non-linear patterns of temperature-response ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 10 1
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
spellingShingle Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
Gilioli Gianni
Mariani Luigi
Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach
topic_facet Arctic medicine. Tropical medicine
RC955-962
Infectious and parasitic diseases
RC109-216
description Abstract Background Mechanistic models play an important role in many biological disciplines, and they can effectively contribute to evaluate the spatial-temporal evolution of mosquito populations, in the light of the increasing knowledge of the crucial driving role on vector dynamics played by meteo-climatic features as well as other physical-biological characteristics of the landscape. Methods In malaria eco-epidemiology landscape components (atmosphere, water bodies, land use) interact with the epidemiological system (interacting populations of vector, human, and parasite). In the background of the eco-epidemiological approach, a mosquito population model is here proposed to evaluate the sensitivity of An. gambiae s.s. population to some peculiar thermal-pluviometric scenarios. The scenarios are obtained perturbing meteorological time series data referred to four Kenyan sites (Nairobi, Nyabondo, Kibwesi, and Malindi) representing four different eco-epidemiological settings. Results Simulations highlight a strong dependence of mosquito population abundance on temperature variation with well-defined site-specific patterns. The upper extreme of thermal perturbation interval (+ 3°C) gives rise to an increase in adult population abundance at Nairobi (+111%) and Nyabondo (+61%), and a decrease at Kibwezi (-2%) and Malindi (-36%). At the lower extreme perturbation (-3°C) is observed a reduction in both immature and adult mosquito population in three sites (Nairobi -74%, Nyabondo -66%, Kibwezi -39%), and an increase in Malindi (+11%). A coherent non-linear pattern of population variation emerges. The maximum rate of variation is +30% population abundance for +1°C of temperature change, but also almost null and negative values are obtained. Mosquitoes are less sensitive to rainfall and both adults and immature populations display a positive quasi-linear response pattern to rainfall variation. Conclusions The non-linear temperature-dependent response is in agreement with the non-linear patterns of temperature-response ...
format Article in Journal/Newspaper
author Gilioli Gianni
Mariani Luigi
author_facet Gilioli Gianni
Mariani Luigi
author_sort Gilioli Gianni
title Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach
title_short Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach
title_full Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach
title_fullStr Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach
title_full_unstemmed Sensitivity of Anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach
title_sort sensitivity of anopheles gambiae population dynamics to meteo-hydrological variability: a mechanistic approach
publisher BMC
publishDate 2011
url https://doi.org/10.1186/1475-2875-10-294
https://doaj.org/article/5548c2285f9a4dd48082f8100a674a33
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source Malaria Journal, Vol 10, Iss 1, p 294 (2011)
op_relation http://www.malariajournal.com/content/10/1/294
https://doaj.org/toc/1475-2875
doi:10.1186/1475-2875-10-294
1475-2875
https://doaj.org/article/5548c2285f9a4dd48082f8100a674a33
op_doi https://doi.org/10.1186/1475-2875-10-294
container_title Malaria Journal
container_volume 10
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