Volume 3, Issue 1 (1-2021)                   sjmshm 2021, 3(1): 1-7 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Haghbayan M, Khatami S S, Nasrollahi Heravi F. The Estimation of Newly Infected Cases of Covid-19 with Consideration of Governmental Action and Behavior of People in Iran. sjmshm. 2021; 3 (1) :1-7
URL: http://sjmshm.srpub.org/article-3-81-en.html
Master Student of Industrial Engineering , Amir Kabir University, Tehran, Iran.
Abstract:   (315 Views)
The Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused 414179 infected cases and 18440 deaths up to March 25, 2020. The aim of this study was to estimate the new cases of COVID-19 in future days in Iran based on multiple factors such as governmental actions and people's behavior. We constructed the model based on governmental actions, people's behavior and lag time for governmental action. We estimated the governmental actions ratio and people’s behavior with minimum sum square error with OptQuest arena software. By estimation the new cases under three scenarios for governmental actions, we predicted the new cases and cumulative death for different genders for all scenarios. Based on the first scenario, the maximum number of newly infected cases was 3117. Total cumulative death for 110th day for males and females respectively was 3157 and 2285. According to the second scenario, the maximum number of newly infected cases was 3117. Total cumulative death for 151st day for males and females respectively was 3504 and 2536. By selecting the third scenario, there were two peak points. In the first peak point, the maximum number of newly infected cases was 3117. In the second peak, the maximum number of newly infected cases was 3190. Based on the result of this study, it seems that the best option for the government is to keep social distance and close economic activity, so the number of new cases will be decreased.
Full-Text [PDF 550 kb]   (134 Downloads)    
Type of Study: Research | Subject: Public Health and Health Policy
Received: 2020/10/25 | Accepted: 2020/11/30 | Published: 2021/01/30

References
1. Verity R. et al. Estimates of the severity of coronavirus disease 2019: A model-based analysis. Lancet Infect Dis. 2020.
2. Xu X. et al. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2. Eur J Nucl Med Mol Imag. 2020; 47(5): 1275-1280. [DOI:10.1007/s00259-020-04735-9] [PMID] [PMCID]
3. Guan WJ. et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. Feb 28 2020.
4. Zhou F. et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet, 2020; 395(10229): 1054-1062. [DOI:10.1016/S0140-6736(20)30566-3]
5. Mehta P, McAuley DF, Brown M, Sanchez E, Tattersall RS, Manson JJ. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet, 2020; 395(10229): 1033-1034. [DOI:10.1016/S0140-6736(20)30628-0]
6. Murphy A, Abdi Z, Harirchi I, McKee M, Ahmadnezhad E. Economic sanctions and Iran's capacity to respond to COVID-19. Lancet Publ Health, 2020. [DOI:10.1016/S2468-2667(20)30083-9]
7. Lin Q. et al. A conceptual model for the coronavirus disease 2019 (COVID-19) outbreak in Wuhan, China with individual reaction and governmental action. Int J Infect Dis. 2020; 93: 211-216. [DOI:10.1016/j.ijid.2020.02.058] [PMID] [PMCID]
8. Worldometer. Iran Coronavirus Update with Statistics and Graphs. 2020; https://www.worldometers.info/coronavirus/country/iran/
9. Epidemiology IJO. Iranian Epidemiology Journalist in Coronavirus Epidemic. Iran J Epidemiol. 2020.
10. He D, Dushoff J, Day T, Ma J, Earn DJ. Inferring the causes of the three waves of the 1918 influenza pandemic in England and Wales. Proc Biol Sci. 2013; 280(1766): 20131345. [DOI:10.1098/rspb.2013.1345] [PMID] [PMCID]
11. Kucharski AJ. et al. Early dynamics of transmission and control of COVID-19: A mathematical modelling study. Lancet Infect Dis. 2020. [DOI:10.1101/2020.01.31.20019901]
12. Moorthy V, Henao Restrepo AM, Preziosi MP, Swaminathan S. Data sharing for novel coronavirus (COVID-19). Bull World Health Organ. 2020; 98(3): 150. [DOI:10.2471/BLT.20.251561] [PMID] [PMCID]

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.