The Geographical Distribution of Probable COVID-19 Patients Transferred by Tehran Emergency Medical Services; a Cross Sectional Study
学术急诊医学档案,
卷 9 编号 1 (2021),
1 十月 2021
,
第 e25 页
https://doi.org/10.22037/aaem.v9i1.1177
摘要
Introduction: Mapping of COVID-19 infection in the city can help us know more about how the disease is distributed and spread. This study was conducted to investigate the geographical distribution of probable COVID-19 patients who were transferred to destination hospitals by emergency medical services (EMS) in the first wave of the epidemic, in Tehran, Iran.
Methods: This cross-sectional study was performed based on recorded missions during the first 3-month period of the pandemic in Tehran, Iran. All probable cases of COVID-19 who were transferred to the hospitals following contact with Tehran EMS during the study period were enrolled. Arc-GIS software was utilized to draw the distribution map of the contact places of the cases.
Results: In this study, the data of 4018 patients were analyzed (60.9% male). The mean age of the patients was 54.1 ± 20.7 years; and the mean age of the patients had increased with time during the studied 3 months (p = 0.003). The average incidence rate of this disease in Tehran during the study period was 4.6 per 10,000 population. Generally, the lowest and highest raw frequencies of Tehran COVID-19 contamination were seen in municipal districts 21 and 4, respectively. The raw frequency of cases during the 3-month study period also showed that the highest number of cases in Tehran occurred in municipal districts 5 and 4, respectively.
Conclusion: In the present study, using geographic information systems (GIS), geographical distribution map of COVID-19 in Tehran, Iran, during the first 3 months of the pandemic was drawn.
- Emergency Medical Services
- Geographic Information Systems
- COVID-19
- Tehran
- Iran
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参考
Vahidi E, Jalili M. Why COVID-19? Advanced Journal of Emergency Medicine. 2020;4(2s):e36.
Rezaei M, Nouri AA, Park GS, Kim DH. Application of Geographic Information System in Monitoring and Detecting the COVID-19 Outbreak. Iranian Journal of Public Health. 2020;49:114-6.
Sarwar S, Waheed R, Sarwar S, Khan A. COVID-19 challenges to Pakistan: Is GIS analysis useful to draw solutions? The Science of the total environment. 2020;730:139089.
Kolivand P-H, Faraji Sabokbar H, Saberian P, Bahmanabadi M, Hasani-Sharamin P, Baratloo A. Spatial Analysis of Geographic Distribution and Accessibility of Suspected Acute Stroke Patients Transferred to Acute Stroke Centers by Emergency Medical Services in Tehran, Iran: A Cross-Sectional Study. Iranian Red Crescent Medical Journal. 2020;22(7):e101502.
Kamel Boulos MN, Geraghty EM. Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbreaks and epidemics. International journal of health geographics. 2020;19(1):8.
Haining RP, Haining R. Spatial data analysis: theory and practice: Cambridge university press; 2003.
WHO. Public health surveillance for COVID-19: interim guidance 2020 [Available from: https://www.who.int/publications/i/item/who-2019-nCoV-surveillanceguidance-2020.7.
Ramírez-Aldana R, Gomez-Verjan JC, Bello-Chavolla OY. Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level. PLoS neglected tropical diseases. 2020;14(11):e0008875.
Hazbavi Z, Mostfazadeh R, Alaei N, Azizi E. Spatial and temporal analysis of the COVID-19 incidence pattern in Iran. Environmental Science and Pollution Research. 2020:1-11.
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