Panahi Mohammad Hossein, Parsaeian Mahboubeh, Mansournia Mohammad Ali, Khoshabi Mostafa, Gouya Mohammad Mehdi, Hemati Payman, Fotouhi Akbar
Epidemiology and Biostatistics Department, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Department of Geo-Spatial Information System (GIS), Center of Excellence in GIS, K.N. Toosi University of Technology, Tehran, Iran.
Med J Islam Repub Iran. 2020 Jun 22;34:65. doi: 10.34171/mjiri.34.65. eCollection 2020.
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. 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. 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. 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.
研究该疾病的空间特征有助于决策者和研究人员更好地了解疾病模式，对实施疾病控制计划也非常重要。鉴于伊朗地域辽阔，以及该国多样的地理和气候条件，使用地理信息系统（GIS）是研究流感的一种合适方法。在本研究中，我们通过应用时空分析，利用地理信息系统（GIS），清晰呈现了2011年至2016年期间伊朗各省流感样疾病（ILI）的分布情况。估算了按地点和年份划分的疾病发病率，然后区分出热点和冷点。本研究使用了2011年8月至2016年8月伊朗流感监测系统记录的ILI发病率数据。采用了分级统计图法以及各种等距和自然间断点分类法。然后使用局部Getis-Ord Gi方法来识别热点以及因某些原因疾病分布在空间上显著聚集的区域。使用ArcGIS 10.2软件进行统计分析。本研究表明，ILI发病率最高的时期是2014年8月至2015年8月，发病率为每10万人180.26（95%CI：177.65至182.9）。结果显示，ILI发病率5年平均值最高的省份是赞詹、马克azi、洛雷斯坦、伊拉姆、北呼罗珊和南呼罗珊省。此外，局部Getis-Ord Gi方法的结果表明，ILI在2011年至2013年期间在伊朗东部边境形成了一个热点，随后在2014年至2016年期间在该国西部地区形成了热点。鉴于流感的重要性及其对社会造成的巨大经济负担，识别热点地区有助于更好地管理该疾病。本研究表明该疾病的分布在该国西部地区形成了一个热点。
