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Spatial patterns and prevalence of Hepatitis C virus in Punjab during 2010-2017

机译:2010-2017年旁遮普邦丙型肝炎病毒的空间分布和流行情况

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The upsurge of contemporary urbanization has created potential risks for the emergence of infectious diseases like HCV affecting millions of people around the globe. The present research studied the spatial patterns of HCV and its prevalence in the Punjab province for the years 2010, 2013 and 2017. Secondary data sources were used, and district-wise figures of HCV patients were obtained from Directorate of General Health Services Punjab, Health Department Lahore (DGHSP). The data for population was attained from Punjab Bureau of Statistics, Lahore. The collected data were processed and analysed in Microsoft Excel 365 and SPSS 22 for calculating HCV prevalence rate. The spread and major clusters of HCV were shown through maps using ArcGIS 10.5. The results show that HCV has gradually increased in number and expanded in spatial spread within the study area since 2010 and the concentration of disease is found in the north eastern, eastern and central districts of Punjab. Most affected districts are Multan, Lahore, Faisalabad, Toba Tek Singh, Bahawalpur, Sahiwal and Gujranwala. Highest prevalence rate of HCV is found in Multan district with 3.39% hence, all other districts have HCV prevalence rate less than 1%. The study suggests future studies to identify the possible environmental risk factors responsible for the spread of disease in the highly affected districts of Punjab and examine the disease pattern through popular mapping techniques like using hot spot analysis and interpolation method.
机译:当代城市化的高潮为诸如HCV之类的传染病的出现带来了潜在的风险,影响了全球数百万人。本研究研究了2010年,2013年和2017年旁遮普省HCV的空间格局及其流行情况。使用了二级数据来源,并从卫生部旁遮普邦总卫生服务局获得了HCV患者的地区数字。拉合尔部门(DGHSP)。人口数据是从拉合尔旁遮普统计局获得的。收集的数据在Microsoft Excel 365和SPSS 22中进行处理和分析,以计算HCV患病率。 HCV的扩散群和主要群通过使用ArcGIS 10.5的地图显示。结果表明,自2010年以来,HCV的数量在研究区域内逐渐增加,在空间上扩展,并且在旁遮普邦的东北,东部和中部地区发现了疾病的集中地。受影响最严重的地区是木尔坦,拉合尔,费萨拉巴德,托巴·泰·辛格,巴哈瓦尔布尔,萨希瓦尔和古吉兰瓦拉。在木尔坦地区,HCV的患病率最高,为3.39%,因此所有其他地区的HCV患病率均低于1%。这项研究建议未来的研究,以确定可能造成疾病流行的旁遮普邦受灾地区的环境危险因素,并通过流行的制图技术(例如使用热点分析和内插法)来检查疾病模式。

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