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A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016

Background: Investigating the spatial aspects of the disease can help decision-makers and researchers better understand the pattern of the disease, and is also very important in the implementation of the disease control programs. Given the vast area of Iran, as well as the diverse geographical and c...

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Autores principales: Panahi, Mohammad Hossein, Parsaeian, Mahboubeh, Mansournia, Mohammad Ali, Khoshabi, Mostafa, Gouya, Mohammad Mehdi, Hemati, Payman, Fotouhi, Akbar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Iran University of Medical Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500421/
https://www.ncbi.nlm.nih.gov/pubmed/32974231
http://dx.doi.org/10.34171/mjiri.34.65
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author Panahi, Mohammad Hossein
Parsaeian, Mahboubeh
Mansournia, Mohammad Ali
Khoshabi, Mostafa
Gouya, Mohammad Mehdi
Hemati, Payman
Fotouhi, Akbar
author_facet Panahi, Mohammad Hossein
Parsaeian, Mahboubeh
Mansournia, Mohammad Ali
Khoshabi, Mostafa
Gouya, Mohammad Mehdi
Hemati, Payman
Fotouhi, Akbar
author_sort Panahi, Mohammad Hossein
collection PubMed
description Background: Investigating the spatial aspects of the disease can help decision-makers and researchers better understand the pattern of the disease, and is also very important in the implementation of the disease control programs. Given the vast area of Iran, as well as the diverse geographical and climate conditions of the country, using the geographical information system (GIS) is a suitable method for the study of influenza. In this study, we provide a clear picture of the distribution of the influenza-like illness (ILI) in Iranian provinces through the years from 2011 to 2016 by applying a spatio-temporal analysis, using geographic information system (GIS). Disease rates by location and year are estimated, and then hot spots and cold spots are distinguished. Methods: This study was conducted using the ILI incidence rate data recorded in the Iranian Influenza Surveillance System from August 2011 to August 2016. The Choropleth map method and the various equal interval and natural break classifications were used. The local Getis-Ord Gi* method was then used to identify the hot spots and regions where, for some reason, the distribution of the disease had significantly clustered spatially. Statistical analyses were done using the ArcGIS 10.2 software. Results: This study indicates that the highest ILI rate belongs to the period from August 2014 to August 2015 with a rate of 180.26 (95%CI: 177.65 to 182.9) per 100,000 people. The results show that the highest 5-year mean of ILI rate belongs to Zanjan, Markazi, Lorestan, Ilam, North Khorasan, and South Khorasan provinces. Also, results from the local Getis-Ord Gi* method show that ILI has formed a hot spot between the years 2011 and 2013 on the eastern borders of Iran and afterward during the years 2014 to 2016 in the western regions of the country. Conclusion: Given the importance of influenza and its huge economic burden on the society, identifying the hot spot regions can help better manage the disease. This study indicates the distribution of the disease has formed a hot spot in the western regions of the country.
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spelling pubmed-75004212020-09-23 A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016 Panahi, Mohammad Hossein Parsaeian, Mahboubeh Mansournia, Mohammad Ali Khoshabi, Mostafa Gouya, Mohammad Mehdi Hemati, Payman Fotouhi, Akbar Med J Islam Repub Iran Original Article Background: Investigating the spatial aspects of the disease can help decision-makers and researchers better understand the pattern of the disease, and is also very important in the implementation of the disease control programs. Given the vast area of Iran, as well as the diverse geographical and climate conditions of the country, using the geographical information system (GIS) is a suitable method for the study of influenza. In this study, we provide a clear picture of the distribution of the influenza-like illness (ILI) in Iranian provinces through the years from 2011 to 2016 by applying a spatio-temporal analysis, using geographic information system (GIS). Disease rates by location and year are estimated, and then hot spots and cold spots are distinguished. Methods: This study was conducted using the ILI incidence rate data recorded in the Iranian Influenza Surveillance System from August 2011 to August 2016. The Choropleth map method and the various equal interval and natural break classifications were used. The local Getis-Ord Gi* method was then used to identify the hot spots and regions where, for some reason, the distribution of the disease had significantly clustered spatially. Statistical analyses were done using the ArcGIS 10.2 software. Results: This study indicates that the highest ILI rate belongs to the period from August 2014 to August 2015 with a rate of 180.26 (95%CI: 177.65 to 182.9) per 100,000 people. The results show that the highest 5-year mean of ILI rate belongs to Zanjan, Markazi, Lorestan, Ilam, North Khorasan, and South Khorasan provinces. Also, results from the local Getis-Ord Gi* method show that ILI has formed a hot spot between the years 2011 and 2013 on the eastern borders of Iran and afterward during the years 2014 to 2016 in the western regions of the country. Conclusion: Given the importance of influenza and its huge economic burden on the society, identifying the hot spot regions can help better manage the disease. This study indicates the distribution of the disease has formed a hot spot in the western regions of the country. Iran University of Medical Sciences 2020-06-22 /pmc/articles/PMC7500421/ /pubmed/32974231 http://dx.doi.org/10.34171/mjiri.34.65 Text en © 2020 Iran University of Medical Sciences http://creativecommons.org/licenses/by-nc-sa/1.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial-ShareAlike 1.0 License (CC BY-NC-SA 1.0), which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly.
spellingShingle Original Article
Panahi, Mohammad Hossein
Parsaeian, Mahboubeh
Mansournia, Mohammad Ali
Khoshabi, Mostafa
Gouya, Mohammad Mehdi
Hemati, Payman
Fotouhi, Akbar
A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016
title A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016
title_full A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016
title_fullStr A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016
title_full_unstemmed A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016
title_short A spatio-temporal analysis of influenza-like illness in Iran from 2011 to 2016
title_sort spatio-temporal analysis of influenza-like illness in iran from 2011 to 2016
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500421/
https://www.ncbi.nlm.nih.gov/pubmed/32974231
http://dx.doi.org/10.34171/mjiri.34.65
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