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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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 |
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English |
topic |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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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 |
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10 |
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1 |
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1766346991706570752 |