ارائه چارچوبی مکانی برای مدیریت، بررسی همبستگی مکانی و کنترل بیماری‌های واگیردار (مطالعه موردی شهرستان همدان)

امروزه مهم‌ترین اهداف هر سازمان بهداشتی، سالم‌سازی محیط‌زیست، کنترل بیماری‌ها، آموزش بهداشت، پیش‌گیری، اقدامات پزشکی و پرستاری جهت تشخیص سریع، کنترل و مدیریت بیماری‌ها می‌باشد. در جوامع امروزی سطح زندگی مردم ارتباط مستقیم با مراقبت‌های بهداشتی در آن‌ها دارد، رشد و توسعه امور بهداشتی باعث بالا رفتن سطح زندگی مردم ازنظر فرهنگ و سلامت خواهد شد. در بررسی بیماری‌ها مطالعه مکانی منطقه از اهمیت خاصی برخوردار است، چراکه وقوع بسیاری از بیماری‌ها به شرایط جغرافیایی منطقه وابسته است. بسیاری از عوامل بیماری‌زا اپیدمیک هستند و به منطقه یا ناحیه خاصی تعلق ندارند، درحالی‌که برخی از آن‌ها در مناطق خاصی رخ می‌دهند. به‌منظور بررسی جنبه‌های مختلف یک بیماری و بررسی ارتباط آن با عوامل محیطی، اقتصادی و اجتماعی و اکولوژیکی، gis ابزارهای مناسبی را در اختیار قرار می‌دهد. با استفاده از gis می‌توان توزیع بیماری را در مقیاس‌های مختلف مشاهده کرد از تحلیل‌های زمین‌آماری برای کشف رابطه عوامل مختلف با بیماری استفاده کرد، با تحلیل‌های مکانی-زمانی، بیماری را پیش‌بینی نمود و برای مقابله با آن طرح‌های ایمن‌سازی مطرح نمود و با تحلیل‌هایی چون دسترسی، توزیع منابع را بررسی نمود. هدف تحقیق حاضر ارائه مدلی جهت بررسی الگوی توزیع بیماری‌های اوریون، سیاه‌سرفه، سرخجه، آبله‌مرغان و هاری در سطح شهر همدان و در سال‌های 1394 تا 1398 می‌باشد. در این خصوص ابتدا آزمون های آماری کلاسیک در ارتباط با داده های بیماری‌های موردبررسی اجرا شد. سپس آمار توصیفی مربوط به بیماران موردبررسی قرار گرفت. متغیرهای مربوط به اطلاعات جمعیت شناختی، شامل جنسیت و سن بیماران می‌باشد. پس از انجام آزمون‌های آماری کلاسیک، آماره‌های مکانی تحقیق همچون، بررسی خوشه بندی مبتلایان به بیماری های موردتحقیق، خودهمبستگی مکانی و توزیع براساس فاصله از کاربری های شهری بررسی گردید. پس‌ازآن با استفاده از داده های موجود، براساس روش مدل‌سازی میانگین متحرک، مدل توزیع بیماری در سطح شهر همدان تولید و یافته های مدل با استفاده از داده‌های توزیع بیماری مربوط به سال 1398 ارزیابی و صحت سنجی گردید. ﮔﺮدﯾﺪ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن داد ﮐﻪ ﻣﺪل ﻃﺮاﺣﯽ ﺷﺪه ﺟﻬﺖ ﺷﻨﺎﺳﺎﯾﯽ ﺗﻮزﯾﻊ ﺑﯿﻤﺎریﻫﺎ در ﺷﻬﺮﺳﺘﺎن ﻫﻤﺪان در ﺳﻄﺢ اﻃﻤﯿﻨﺎن 90% راﺑﻄﻪ ﻣﻌﻨﺎداری دارد و ﻣﺪل ﺑﻪ ﺧﻮﺑﯽ ﺑﺮازش ﺷﺪه اﺳﺖ.

providing a framework for management, spatial correlation and control of infectious diseases (case study of hamadan city)

 one of the main public needs of people in all societies is public health. identifying pathogenic agents and how they are transmitted and distributed in the environment is one of the management methods in providing the health needs of communities [1]. studying the distribution of diseases is important for two reasons. first, these studies can be a way to find the causes of diseases, and second, the geographical distribution of diseases can be an indicator of how people and human groups interact with the environment [6]. therefore, it is necessary to design a system for data management in order to control and care for infectious diseases. the spatial information system with the possibility of using satellite information is a new and cost-effective method in line with this need, which in the long run will compensate the initial investment by reducing the costs of data collection and disease control, and in addition, the way to use these facilities in information management systems. and provides care for other diseases. because health and illness always have a spatial dimension [8]. identifying and displaying spatial patterns plays an important role in establishing health policies. for many, spatial data analysis is the same as map production. the use of disease distribution maps for epidemiological purposes has a long history. the first step in the design of spatial information systems in hamadan city is to examine the human location and the potential and actual information sources of the infectious disease care system. the main purpose of using the spatial information system is to strengthen and support the care and management system of infectious diseases and create the ability to analyze the spatial information and then make timely decisions [9]. the studied areathis research was implemented in hamadan city. demographic information was prepared from the demographic information related to the census of 2015 in hamedan city, and to obtain information on infectious diseases, it was extracted from the classified information set of patients in bo ali sina university of medical sciences, hamedan city. specific results of this research are presented in several sections.materials and methods the information needed in this research is collected by using library studies, checking similar domestic and foreign research records, collecting descriptive information by questioning and studying the documents available in libraries, as well as field research. in this research, in order to develop the methodology and processes for investigating the distribution of diseases, as well as the effect of interactive gis systems on the control and management of diseases, two series of analysis and evaluation are carried out. descriptive test and inferential test; therefore, in order to implement the stage of identifying the distribution of diseases during a 5-year period in hamedan city, first all the necessary data of the health centers and boali university of medical sciences of hamedan are prepared and collected, after verifying the information based on statistical methods and performing the smirnov test. kolmogorov, data distribution is examined. after that, the distribution of the obtained data is checked with the t-statistics test. finally, after performing the descriptive test, this information is categorized and then analyzed based on the characteristics of the diseases and their time period, the results of these analyzes are shown in the form of tables and evaluation charts. in the spatial statistics test, in order to evaluate spatial systems on the control and management of diseases in a 5-year period, first, spatial information based on the location of the residence of each case, longitude and latitude related to the residence of each patient for the spatial analysis of the disease was obtained and in a database stored and then classified based on the main diseases. in this regard, after checking the accuracy of the entered data, secondary analysis is defined based on the main charts and tables. by examining the location of sick people in the geographic information system (gis) and entering the information and characteristics of patients in this system, important information such as the distribution of the disease, examination of the produced clusters, geographical effects on the disease, the speed of spread and transmission of the disease can be obtained. for spatial analysis, moran’s spatial autocorrelation method and pearson’s statistical test are used to estimate the correlation of diseases with spatial characteristics in the gis environment. it is also possible to implement a suitable system process framework in order to model the distribution of different diseases outside of the current research based on the mechanism of the spatial information system and satellite images in the control and management of diseases in any region. this framework includes types of diseases and time-spatial distribution patterns that cause and effect relationships between entities will be presented in the form of a block diagram.implementation the purpose of this study is to prepare a map of the spatial and temporal clusters of infectious diseases, to investigate the factors affecting the disease and their impact, and finally to find a method to model the prevalence of the disease, this model can help disease management and control programs. all information and documents related to the causes of the disease were extracted by study and evaluation. in this regard, it is necessary to perform processing related to the model on descriptive items with the same spatial unit; therefore, the required spatial unit was considered for all factors. in order to model the diseases using the moving average model, first the zoning map of hamedan city was prepared using the number of infected patients in each region. then, using the moving average model and using the raster calculator computing space in arcgis software, the final disease distribution model was produced.