http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Behzad Kiani (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
Spatial epidemiology of COVID-19 infection through the first outbreak in the city of Mashhad, Iran
Hasan Mansouritorghabeh,Ahmad Bagherimoghaddam,Saeid Eslami,Amene Raouf‑Rahmati,Davidson H. Hamer,Behzad Kiani,Shahab MohammadEbrahimi 대한공간정보학회 2022 Spatial Information Research Vol.30 No.5
The COVID-19 epidemic is currently the most important public health challenge worldwide. The current study aimed to survey the spatial epidemiology of the COVID-19 outbreak in Mashhad, Iran, across the first outbreak. The data was including the hospitalized lab-confirmed COVID-19 cases from Feb 4 until Apr 13, 2020. For comparison between the groups, classical statistics analyses were used. A logistic regression model was built to detect the factors affecting mortality. After calculating the empirical Bayesian rate (EBR), the Local Moran’s I statistic was applied to quantify the spatial autocorrelation of disease. The total cumulative incidence and case fatality rates were respectively 4.6 per 10,000 (95% CI: 4.3–4.8) and 23.1% (95% CI: 23.2–25.4). Of 1535 cases, 62% were males and were more likely to die than females (adjusted Odds Ratio (aOR): 1.58, 95% CI: 1.23–2.04). The odds of death for patients over 60 years was more than three times (aOR: 3.66, 95% CI: 2.79–4.81). Although the distribution of COVID-19 patients was nearly random in Mashhad, the downtown area had the most significant high-high clusters throughout most of the biweekly periods. The most likely factors influencing the development of hotspots around the downtown include the congested population (due to the holy shrine), low socioeconomic and deprived neighborhoods, poor access to health facilities, indoor crowding, and further use of public transportation. Constantly raising public awareness, emphasizing social distancing, and increasing the whole community immunization, particularly in the highpriority areas detected by spatial analysis, can lead people to a brighter picture of their lives.
-
Spatio-temporal analysis of fire incidences in urban context: the case study of Mashhad, Iran
Mohammad Mahdi Barati Jozan,Alireza Mohammadi,Aynaz Lotfata,Hamed Tabesh,Behzad Kiani 대한공간정보학회 2024 Spatial Information Research Vol.32 No.1
The study aims to identify fire patterns in Mashhad, the second-most populous city in Iran, between 2015 and 2019. Spatial scan statistics were utilized to determine the spatiotemporal patterns of 29,889 fire events in the research area. There were four primary types of fires: (1) structural fires (39%), (2) vehicle fires (11%), (3) green and open space fires (19%), and (4) others (31%). The interval from 12:00 to 23:00 h was identified as the high-risk period for all fire incidents. Fires were common in the nearby city core. Additionally, three significant hourly spatial-temporal clusters of firefighting operations were identified: the western part of the city between 12:00 and 23:00, the city center between 11:00 and 22:00, and the southeastern part between 11:00 and 22:00. Population density, illiteracy ratio, unemployment ratio, youth ratio, lowincome population, and the number of old buildings might be socio-economic criteria that contribute to the spatiotemporal pattern of urban fires. Urban planners might prioritize high-risk neighborhoods when allocating resources for fire safety. Future research could specifically investigate high-risk regions to identify relevant characteristics in these areas.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
