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Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases

BACKGROUND: The Epidemic Intelligence from Open Sources (EIOS) system, jointly developed by the World Health Organisation (WHO), the Joint Research Centre (JRC) of the European Commission and various partners, is a web-based platform that facilitate the monitoring of information on public health thr...

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Autores principales: Fanelli, Angela, Schnitzler, Johannes Christof, De Nardi, Marco, Donachie, Alastair, Capua, Ilaria, Lanave, Gianvito, Buonavoglia, Domenico, Caceres-Soto, Paula, Tizzani, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Centre for Disease Prevention and Control (ECDC) 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283452/
https://www.ncbi.nlm.nih.gov/pubmed/37078883
http://dx.doi.org/10.2807/1560-7917.ES.2023.28.16.2200542
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author Fanelli, Angela
Schnitzler, Johannes Christof
De Nardi, Marco
Donachie, Alastair
Capua, Ilaria
Lanave, Gianvito
Buonavoglia, Domenico
Caceres-Soto, Paula
Tizzani, Paolo
author_facet Fanelli, Angela
Schnitzler, Johannes Christof
De Nardi, Marco
Donachie, Alastair
Capua, Ilaria
Lanave, Gianvito
Buonavoglia, Domenico
Caceres-Soto, Paula
Tizzani, Paolo
author_sort Fanelli, Angela
collection PubMed
description BACKGROUND: The Epidemic Intelligence from Open Sources (EIOS) system, jointly developed by the World Health Organisation (WHO), the Joint Research Centre (JRC) of the European Commission and various partners, is a web-based platform that facilitate the monitoring of information on public health threats in near real-time from thousands of online sources. AIMS: To assess the capacity of the EIOS system to strengthen data collection for neglected diseases of public health importance, and to evaluate the use of EIOS data for improving the understanding of the geographic extents of diseases and their level of risk. METHODS: A Bayesian additive regression trees (BART) model was implemented to map the risk of Crimean-Congo haemorrhagic fever (CCHF) occurrence in 52 countries and territories within the European Region between January 2012 and March 2022 using data on CCHF occurrence retrieved from the EIOS system. RESULTS: The model found a positive association between all temperature-related variables and the probability of CCHF occurrence, with an increased risk in warmer and drier areas. The highest risk of CCHF was found in the Mediterranean basin and in areas bordering the Black Sea. There was a general decreasing risk trend from south to north across the entire European Region. CONCLUSION: The study highlights that the information gathered by public health intelligence can be used to build a disease risk map. Internet-based sources could aid in the assessment of new or changing risks and planning effective actions in target areas.
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spelling pubmed-102834522023-06-22 Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases Fanelli, Angela Schnitzler, Johannes Christof De Nardi, Marco Donachie, Alastair Capua, Ilaria Lanave, Gianvito Buonavoglia, Domenico Caceres-Soto, Paula Tizzani, Paolo Euro Surveill Research BACKGROUND: The Epidemic Intelligence from Open Sources (EIOS) system, jointly developed by the World Health Organisation (WHO), the Joint Research Centre (JRC) of the European Commission and various partners, is a web-based platform that facilitate the monitoring of information on public health threats in near real-time from thousands of online sources. AIMS: To assess the capacity of the EIOS system to strengthen data collection for neglected diseases of public health importance, and to evaluate the use of EIOS data for improving the understanding of the geographic extents of diseases and their level of risk. METHODS: A Bayesian additive regression trees (BART) model was implemented to map the risk of Crimean-Congo haemorrhagic fever (CCHF) occurrence in 52 countries and territories within the European Region between January 2012 and March 2022 using data on CCHF occurrence retrieved from the EIOS system. RESULTS: The model found a positive association between all temperature-related variables and the probability of CCHF occurrence, with an increased risk in warmer and drier areas. The highest risk of CCHF was found in the Mediterranean basin and in areas bordering the Black Sea. There was a general decreasing risk trend from south to north across the entire European Region. CONCLUSION: The study highlights that the information gathered by public health intelligence can be used to build a disease risk map. Internet-based sources could aid in the assessment of new or changing risks and planning effective actions in target areas. European Centre for Disease Prevention and Control (ECDC) 2023-04-20 /pmc/articles/PMC10283452/ /pubmed/37078883 http://dx.doi.org/10.2807/1560-7917.ES.2023.28.16.2200542 Text en This article is copyright of the authors or their affiliated institutions, 2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made.
spellingShingle Research
Fanelli, Angela
Schnitzler, Johannes Christof
De Nardi, Marco
Donachie, Alastair
Capua, Ilaria
Lanave, Gianvito
Buonavoglia, Domenico
Caceres-Soto, Paula
Tizzani, Paolo
Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases
title Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases
title_full Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases
title_fullStr Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases
title_full_unstemmed Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases
title_short Epidemic intelligence data of Crimean-Congo haemorrhagic fever, European Region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases
title_sort epidemic intelligence data of crimean-congo haemorrhagic fever, european region, 2012 to 2022: a new opportunity for risk mapping of neglected diseases
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283452/
https://www.ncbi.nlm.nih.gov/pubmed/37078883
http://dx.doi.org/10.2807/1560-7917.ES.2023.28.16.2200542
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