CovidStanfordV1, Main, Exploration, bibRecord, 000819

AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission.

Identifieur interne : 000819 ( Main/Exploration ); précédent : 000818; suivant : 000820

AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission.

Auteurs : Á G. Mu Oz [États-Unis] ; X. Chourio [États-Unis] ; Ana Rivière-Cinnamond [États-Unis] ; M A Diuk-Wasser [États-Unis] ; P A Kache [États-Unis] ; E A Mordecai [États-Unis] ; L. Harrington [États-Unis] ; M C Thomson [États-Unis, Royaume-Uni]

Source :

Scientific reports [ 2045-2322 ] ; 2020.

RBID : pubmed:32724218

Descripteurs français

KwdFr :
- Aedes (virologie), Animaux (MeSH), Bases de données factuelles (MeSH), Betacoronavirus (isolement et purification), Climat (MeSH), Humains (MeSH), Infections à coronavirus (anatomopathologie), Infections à coronavirus (transmission), Infections à coronavirus (virologie), Pandémies (MeSH), Pneumopathie virale (anatomopathologie), Pneumopathie virale (transmission), Pneumopathie virale (virologie), Prise de décision (MeSH), Surveillance épidémiologique (médecine vétérinaire), Vecteurs moustiques (virologie).
MESH :
- anatomopathologie : Infections à coronavirus, Pneumopathie virale.
- isolement et purification : Betacoronavirus.
- médecine vétérinaire : Surveillance épidémiologique.
- virologie : Aedes, Infections à coronavirus, Pneumopathie virale, Vecteurs moustiques.
- transmission : Animaux, Bases de données factuelles, Climat, Humains, Infections à coronavirus, Pandémies, Pneumopathie virale, Prise de décision.

English descriptors

KwdEn :
- Aedes (virology), Animals (MeSH), Betacoronavirus (isolation & purification), COVID-19 (MeSH), Climate (MeSH), Coronavirus Infections (pathology), Coronavirus Infections (transmission), Coronavirus Infections (virology), Databases, Factual (MeSH), Decision Making (MeSH), Epidemiological Monitoring (veterinary), Humans (MeSH), Mosquito Vectors (virology), Pandemics (MeSH), Pneumonia, Viral (pathology), Pneumonia, Viral (transmission), Pneumonia, Viral (virology), SARS-CoV-2 (MeSH), Vector Borne Diseases (epidemiology), Vector Borne Diseases (pathology), Vector Borne Diseases (virology).
MESH :
- epidemiology : Vector Borne Diseases.
- isolation & purification : Betacoronavirus.
- pathology : Coronavirus Infections, Pneumonia, Viral, Vector Borne Diseases.
- transmission : Coronavirus Infections, Pneumonia, Viral.
- veterinary : Epidemiological Monitoring.
- virology : Aedes, Coronavirus Infections, Mosquito Vectors, Pneumonia, Viral, Vector Borne Diseases.
- Animals, COVID-19, Climate, Databases, Factual, Decision Making, Humans, Pandemics, SARS-CoV-2.

Abstract

Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. In the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for [Formula: see text]-borne diseases' environmental suitability (AeDES) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies .

DOI: 10.1038/s41598-020-69625-4
PubMed: 32724218
PubMed Central: PMC7387552

Affiliations:

Links toward previous steps (curation, corpus...)

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Le document en format XML

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<front><div type="abstract" xml:lang="en">Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. In the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for [Formula: see text]-borne diseases' environmental suitability (AeDES) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies .</div>
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<Abstract><AbstractText>Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. In the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for [Formula: see text]-borne diseases' environmental suitability (AeDES) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies .</AbstractText>
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AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission.

AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission.

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