Extracting hidden rules from Brucellosis patients data in Razavi Khorasan province using association rule mining technique

Brucellosis is a transmissible disease between humans and animals through infected animals and their products. The disease exists in most parts of the world especially in developing countries. Because of the serious impact of the disease in public health and socio-economical status, controlling the disease is very important in developing countries. The purpose of this article is to identify hidden patterns and relations between brucellosis patients which can be beneficial for physicians in diagnosis process. This study is a retrospective study of data collected from brucellosis patients of Razavi Khorasan province recorded at the health center, have been used. Due to differences in format and number of features collected during different years, before processing operations carried out in several stages to the same data. Fields associated with different methods and with expert opinion was converted into discrete fields and fields lost was estimated using the EM algorithm. APPIORI algorithm analysis was performed using the hidden relationships between data found that significant relationships were infected with expert opinion. Among the 163 relationship with over 7.0 Confidence rate which Weka software was discovered, by the application in consultation with an infectious disease expert, 10 clinically significant relationships were reported. Diagnosing brucellosis is really difficult to physicians because of its vague nature and symptoms. Because many unknown relationships between risk factors and demographic characteristics of the patients, the use of data mining concepts, especially in the medical data is beneficial because usually high volume assumptions are available. Further studies can test the validity of these rules like Randomize Control Trial studies

Epidemiological and clinical characteristics of human brucellosis in Razavi Khorasan proivince and important risk factors in the years 2008 to 2013

Background & Purpose: Brucellosis is a transmissible disease between humans and animals that is transmitted through infected animals and their products. Razavi Khorasan which is classified as a high incidence province, considered as one of the notable areas for controlling the disease. Materials &Methods: Data on 5743 cases in Razavi Khorasan (Mashhad Medical University Coverage) over 5 years were analyzed. A GIS map is designed to show and compare incidence rate among different regions using ArcGIS software and different correlations between patients specifications are analyzed. Results: The mean incidence of disease in the province is 26 per hundred thousand people which is highly correlated to animal population of every area. In the first 3 years of study the disease incidence was ascending and in last 2 years it was descending and in May till August the prevalence was more than other months.85% of patients were rural and 15% were urban. 56.9% were male and 43.1% female. Household and farmer-rancher were the most common jobs. Average age of patients was 33.4 ±18.1 year. 77.2% had consumption of unpasteurized dairy products which milk (91.4%) and cheese (21.4%) had the highest consumption. The most common symptoms were fever (79%) and anorexia (47.5%). A significant relationship between location and both livestock vaccination history and also family history, was found. Conclusion: because of higher incidence rate of the disease in Daregaz, Takhtjolge and Rashtkhar, and young people aged 10 to 30 years and villagers, It’s need to control the disease in these groups

An age-integrated approach to improve measurement of potential spatial accessibility to emergency medical services for urban areas

Objective: This study aimed to develop an age‐included approach to measure the potential accessibility to Emergency medical services (EMS) across urban and suburban areas of Mashhad city in Iran. Methods: We used an improved version of two‐step floating catchment area (2SFCA) and enhanced 2SFCA (E2SFCA) methods to measure the potential accessibility to EMS services with inclusion of age factor. This enabled us to better model accessibility of the older population to the EMS. We used 22 800 records of EMS enquiries from July to September 2018 to evaluate and assess the potential improvement in access to the EMS with incorporating age in the model. Results: Suburb areas had less potential accessibility compared with central urban due to the high density of EMS stations in the city center areas. Our model showed slight improvement in potential accessibility measurement as a result of the proposed age‐integrated method. Conclusion: An age‐integrated index of accessibility method takes into account the age distribution of the population in service area is highly associated with actual measures of accessibility to EMS services. Identifying areas with poor access to EMS will help policymakers to design better policy planning to allocate resources and improve provision of EMS services.This project is funded by Mashhad University of Medical Sciences (grant number 970861

Comparing potential spatial access with self-reported travel times and cost analysis to haemodialysis facilities in north-eastern Iran

End-stage renal disease patients regularly need haemodialysis three times a week. Their poor access to haemodialysis facilities is significantly associated with a high mortality rate. The present cross-sectional study aimed to measure the potential spatial access to dialysis services at a small area level (census tract level) in North Khorasan Province, Iran. The patients were interviewed to obtain their travel information. The two-step floating catchment area (2SFCA) method was used to measure the spatial accessibility of patients to the dialysis centres. The capacity of the dialysis centre was defined as the number of active dialysis facilities in each centre and the haemodialysis patients in each area were considered as the users of dialysis services. The travel cost from each patient's residence to the haemodialysis facilities was visualized by the Kriging interpolation algorithm in the study area. Spatial accessibility to the dialysis centre was poor in the northern part of the study area. Fortunately, there were not many haemodialysis patients in that area. Patients' travel costs were high in the northern areas compared to the rest of study area. We observed a statistically significant reverse correlation between the self-reported travel time and computed spatial accessibility (-0.570, P value <0.01, two-tailed spearman test). This study supports the notion that the 2SFCA method could be associated with revealed access time to dialysis facilities, especially in low traffic and in flat areas such as northern Khorasan. The mapping of patients' distribution and interpolated travel cost to the haemodialysis facilities could help policymakers to allocate health resources to the areas where the need is greater.n. 931059 from Mashhad University of Medical Sciences, Iran

Comparing potential spatial access with self-reported travel times and cost analysis to haemodialysis facilities in North-eastern Iran

End-stage renal disease patients regularly need haemodialysis three times a week. Their poor access to haemodialysis facilities is significantly associated with a high mortality rate. The present cross-sectional study aimed to measure the potential spatial access to dialysis services at a small area level (census tract level) in North Khorasan Province, Iran. The patients were interviewed to obtain their travel information. The two-step floating catchment area (2SFCA) method was used to measure the spatial accessibility of patients to the dialysis centres. The capacity of the dialysis centre was defined as the number of active dialysis facilities in each centre and the haemodialysis patients in each area were considered as the users of dialysis services. The travel cost from each patient’s residence to the haemodialysis facilities was visualized by the Kriging interpolation algorithm in the study area. Spatial accessibility to the dialysis centre was poor in the northern part of the study area. Fortunately, there were not many haemodialysis patients in that area. Patients’ travel costs were high in the northern areas compared to the rest of study area. We observed a statistically significant reverse correlation between the self-reported travel time and computed spatial accessibility (-0.570, P value <0.01, two-tailed spearman test). This study supports the notion that the 2SFCA method could be associated with revealed access time to dialysis facilities, especially in low traffic and in flat areas such as northern Khorasan. The mapping of patients’ distribution and interpolated travel cost to the haemodialysis facilities could help policymakers to allocate health resources to the areas where the need is greater

Paediatric, pedestrian road traffic injuries in the city of Mashhad in north-eastern Iran 2015-2019: a data note

Objectives:The leading factors of paediatric, pedestrian road traffic injuries (PPRTIs) are associated with the char-acteristics of immediate environment. Spatial analysis of data related to PPRTIs could provide useful knowledge for public health specialists to prevent and decrease the number of accidents. Therefore, we aim to release the datasets which have been used to conduct a multiple-scale spatial analysis of PPRTIs in the city of Mashhad, Iran, between 2015-2019.Data description:The data include four datasets. The base PPRTIs dataset includes motor vehicle accidents and their attributes in the city of Mashhad between March 2015 and March 2019. The attribute data includes the month, day of the week, hour of the day, place (longitude and latitude) of each accident, age range of the child and gender. Further-more, three spatial datasets about the city of Mashhad are introduced; (1) the digital boundaries of Neighbourhood, (2) road network dataset (street lines) and (3) urban suburbs of Mashhad.Keywords:Paediatric Accident, Pedestrian Accident, Road Traffic Injuries, Iran, Mashhad, Spatial data, Non-spatial data, Geographic Information SystemsThis study was financially supported by Mashhad University of Medical Sciences (Fund Number: 970733)

Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data

This study integrates geographical information systems (GIS) with a mathematical optimization technique to enhance emergency medical services (EMS) coverage in a county in the northeast of Iran. EMS demand locations were determined through one-year EMS call data analysis. We formulated a maximal covering location problem (MCLP) as a mixed-integer linear programming model with a capacity threshold for vehicles using the CPLEX optimizer, an optimization software package from IBM. To ensure applicability to the EMS setting, we incorporated a constraint that maintains an acceptable level of service for all EMS calls. Specifically, we implemented two scenarios: a relocation model for existing ambulances and an allocation model for new ambulances, both using a list of candidate locations. The relocation model increased the proportion of calls within the 5-minute coverage standard from 69% to 75%. With the allocation model, we found that the coverage proportion could rise to 84% of total calls by adding ten vehicles and eight new stations. The incorporation of GIS techniques into optimization modelling holds promise for the efficient management of scarce healthcare resources, particularly in situations where time is of the essence

Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice

Background: Response time to cardiovascular emergency medical requests is an important indicator in reducing cardiovascular disease (CVD) -related mortality. This study aimed to visualize the spatial-time distribution of response time, scene time, and call-to-hospital time of these emergency requests. We also identified patterns of clusters of CVD-related calls. Methods: This cross-sectional study was conducted in Mashhad, north-eastern Iran, between August 2017 and December 2019. The response time to every CVD-related emergency medical request call was computed using spatial and classical statistical analyses. The Anselin Local Moran's I was performed to identify potential clusters in the patterns of CVD-related calls, response time, call-to-hospital arrival time, and scene-to-hospital arrival time at small area level (neighborhood level) in Mashhad, Iran. Results: There were 84,239 CVD-related emergency request calls, 61.64% of which resulted in the transport of patients to clinical centers by EMS, while 2.62% of callers (a total of 2218 persons) died before EMS arrival. The number of CVD-related emergency calls increased by almost 7% between 2017 and 2018, and by 19% between 2017 and 2019. The peak time for calls was between 9 p.m. and 1 a.m., and the lowest number of calls were recorded between 3 a.m. and 9 a.m. Saturday was the busiest day of the week in terms of call volume. There were statistically significant clusters in the pattern of CVD-related calls in the south-eastern region of Mashhad. Further, we found a large spatial variation in scene-to-hospital arrival time and call-to-hospital arrival time in the area under study. Conclusion: The use of geographical information systems and spatial analyses in modelling and quantifying EMS response time provides a new vein of knowledge for decision makers in emergency services management. Spatial as well as temporal clustering of EMS calls were present in the study area. The reasons for clustering of unfavorable time indices for EMS response requires further exploration. This approach enables policymakers to design tailored interventions to improve response time and reduce CVD-related mortality.This study was financially sponsored by Mashhad University of Medical Sciences (Project grant: 980861)

Mortality due to noninfectious lower respiratory diseases: A spatiotemporal, cross‐sectional study

Abstract Background and Aims Geography plays an important role in the incidence of respiratory diseases. The aim of this study was to investigate the epidemiology and geographical distribution of death due to noninfectious lower respiratory diseases (NILRDs). Methods Data related to all death due to NILRD in Kerman Province between 2012 and 2018 were extracted from the National Mortality Registry. The underlying causes of death were extracted from the registry based on the assigned codes from ICD‐10 (International Classification of Diseases 10th Revision) classification. The existence of spatial clusters and outliers was evaluated using local indicators of spatial association statistics. Results The frequency of death due to NILRD was 8005 persons during the 7 years of the study. The main cause of death was chronic lower respiratory disease (54.2%). Other causes of death were, respectively, lung diseases due to external agents (1.09%), other respiratory diseases mainly affecting the interstitium (1.16%), other diseases of pleura (0.57%), and other diseases of the respiratory system (42.13%). The age‐ and sex‐adjusted mortality rates due to NILRD in the north and center of the province increased significantly from 2012 to 2018. Also, the results of cluster analysis identified northern regions as the clustered areas of NILRD. Conclusions Our findings showed a significant increase in mortality due to NILRD in Kerman Province during the 7 years of the study. To reduce this type of death, health policymakers should have environmental health plans and basic solutions, such as a warning system to reduce the commuting on highly air‐polluted days and to control pollutants, especially in the industrial areas of the north of this province