System dynamics simulation on spread of COVID-19 by traffic and transportation

ZHONG Peng-yun; YIN Hui

doi:10.19818/j.cnki.1671-1637.2020.03.009

Volume 20 Issue 3

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ZHONG Peng-yun, YIN Hui. System dynamics simulation on spread of COVID-19 by traffic and transportation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(3): 100-109. doi: 10.19818/j.cnki.1671-1637.2020.03.009

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ZHONG Peng-yun, YIN Hui. System dynamics simulation on spread of COVID-19 by traffic and transportation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(3): 100-109. doi: 10.19818/j.cnki.1671-1637.2020.03.009

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System dynamics simulation on spread of COVID-19 by traffic and transportation

doi: 10.19818/j.cnki.1671-1637.2020.03.009

ZHONG Peng-yun^1
,,
YIN Hui²

1.
Safety Research Center of Traffic and Transportation, Yunnan Science Research Institute of Communication Co., Ltd., Kunming 650011, Yunnan, China
2.
Kunming Engineering Corporation Limited, Power China, Kunming 650051, Yunnan, China

Funds:

National Natural Science Foundation of China 41501174

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Author Bio:
CHONG Peng-yun(1988-), male, senior engineer, PhD, chongzi512@foxmail.com
Received Date: 2020-04-08
Publish Date: 2020-06-25

Abstract

Abstract

To research the influence of traffic and transportation on the spread of corona virus disease 2019(COVID-19), the model of COVID-19 spreaded by traffic and transportation was established based on the system dynamics. Based on the hypothesis of model, the population was divided into the susceptible individual, explored individual, infected individual and removed individual. According to the spreading characteristics of COVID-19, the modified susceptible-explored-infected-removed(SEIR) and susceptible-explored-infected(SEI) spreading dynamics equations of COVID-19 of epidemic area, port, station, car, ship and related area were established under the influence of traffic and transportation. Based on the analysis of spread process of COVID-19 by traffic and transportation, a causal loop of the system dynamics model of traffic and transportation spreading the COVID-19 was drawn, and a causality feedback loop was analyzed. The model of COVID-19 spreaded by traffic and transportation was established based on the system dynamics, and the dimensional consistency, mechanical error, model validity, and extreme condition of the model were tested. Taking the City A as the research example, the influence of traffic and transportation on the spread of COVID-19 was researched by establishing three simulation scenarios. Simulation result shows that the number of individuals infected with the COVID-19 in City A reaches a peak on the 32 nd day after the outbreak, and 77 726 people were infected, and that of the area outside the City A reaches the peak on the 30 th day after the outbreak, and 28 084 people were infected. The traffic and transportation have positive feedback effects on the spread of COVID-19. The peak volumes of infected and removed individuals of COVID-19 under the influence of traffic and transportation are 18.62 and 10.99 times of those without the participation of traffic and transportation, respectively. Therefore, the traffic control measures have a positive effect on controlling the development and preventing the spread of COVID-19. The increase of public transport proportion will accelerate the spread of COVID-19. Therefore, reducing people's travel demands and the proportion of public transport, and increasing the virus elimination work of public transportation car, ship, port and station can effectively slow down the spread of COVID-19.
- traffic system,
- spread of COVID-19,
- system dynamics,
- modeling and simulation,
- causal loop,
- stock and flow

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References

[1]	SHE Jia-tong, LIU Wen-jun. Epidemiological characteristics, prevention and control measures of children's coronavirus disease[J]. Journal of Tropical Medicine, 2020, 20(2): 153-155, 172. (in Chinese). doi: 10.3969/j.issn.1672-3619.2020.02.003
[2]	HUANG Chao-lin, WANG Ye-ming, LI Xing-wang, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China[J]. The Lancet, 2020, 395(10223): 497-506. doi: 10.1016/S0140-6736(20)30183-5
[3]	ZHAO Dan, YU Jing-jing, LIU Ping-xian, et al. Characteristics of dental emergencies during COVID-19 outbreak in Wuhan[J]. Journal of Oral Science Research, 2020, 36(2): 98-103. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-KQYZ202002002.htm
[4]	OLSEN S J, CHANG H L, CHEUNG T Y, et al. Transmission of the severe acute respiratory syndrome on aircraft[J]. New England Journal of Medicine, 2003, 349(25): 2416-2422. doi: 10.1056/NEJMoa031349
[5]	YANG Hua, LI Xiao-wen, SHI Hong, et al. "Fly dots" spreading model of SARS along transportation[J]. Journal of Remote Sensing, 2003, 7(4): 251-255. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-YGXB200304002.htm
[6]	ZHANG Dian-ye, GUO Han-ying. Effect of traffic and transportation preventing and controlling sever acute respiratory syndrome epidemic situation[J]. Journal of Transportation Engineering and Information, 2003, 1(1): 31-36. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-JTGC200301004.htm
[7]	GUO Han-ying, ZHANG Dian-ye, SHI Hong-guo. Spreading theory and model study of broke-out diseases in traffic and transportation[J]. Railway Transport and Economy, 2004, 26(2): 65-67. (in Chinese). doi: 10.3969/j.issn.1003-1421.2004.02.028
[8]	SUN Gen-nian, MA Li-jun. Post-evaluation of impact of SARS in 2003 on railway passenger traffic volumes[J]. Journal of the China Railway Society, 2006, 28(6): 28-34. (in Chinese). doi: 10.3321/j.issn:1001-8360.2006.06.005
[9]	FANG L Q, DE VLAS S J, LIANG S, et al. Environmental factors contributing to the spread of H5N1 avian influenza in mainland China[J]. Plos One, 2008, 3(5): e2268. doi: 10.1371/journal.pone.0002268
[10]	CAO Chun-xiang, XU Min, CHANG Chao-yi, et al. Risk analysis for the highly pathogenic avian influenza in mainland China using meta-modeling[J]. Chinese Science Bulletin, 2010, 55(33): 3205-3213. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-KXTB201033007.htm
[11]	KHAN K, ARINO J, HU W, et al. Spread of a novel influenza a (H1N1) virus via global airline transportation[J]. New England Journal of Medicine, 2009, 361(2): 212-214. doi: 10.1056/NEJMc0904559
[12]	CHANG Chao-yi, CAO Chun-xiang, WANG Qiao, et al. The novel H1N1 influenza a global airline transmission and early warning without travel containments[J]. Chinese Science Bulletin, 2010, 55(12): 1128-1133. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-KXTB201012009.htm
[13]	HUANG Cheng-cheng, PANG Ke, GAO Hong-li. Clinical characteristics of coronavirus disease 2019 in a Chongqing hospital: analysis of 89 cases[J]. Journal of Third Military Medical University, 2020, 42(9): 883-886. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-DSDX202009006.htm
[14]	XIANG Tian-xin, LIU Jia-ming, XU Fei, et al. Analysis of clinical characteristics of 49 patients with coronavirus disease 2019 in Jiangxi[J]. Chinese Journal of Respiratory and Critical Care Medicine, 2020, 19(2): 154-160. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZGHW202002022.htm
[15]	YU Si-miao, WANG Zhong-xia, QIN En-qiang, et al. Clinical characteristics of 25 suspected novel coronavirus pneumonia patients[J]. Chinese Journal of Integrated Traditional and Western Medicine, 2020, 40(3): 369-370. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZZXJ202003031.htm
[16]	XIA Wen-guang, AN Chang-qing, ZHENG Chan-juan, et al. Clinical observation on 34 patients with novel coronavirus pneumonia (COVID-19) treated with integrated traditional Chinese and Western medicine[J]. Journal of Traditional Chinese Medicine, 2020, 61(5): 375-382. (in Chinese). doi: 10.3969/j.issn.0411-8421.2020.05.045
[17]	LI Min, WANG Jin. Research status of ambroxol in the treatment of coronavirus disease 2019[J]. The Chinese Journal of Clinical Pharmacology, 2020, 36(9): 1157-1159, 1168. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-GLYZ202009030.htm
[18]	ZHENG Kai-lian, ZHANG You, WANG Qiong-ya, et al. Severe coronavirus disease 2019 successfully treated with glucocorticoid and high-dose intravenous immunoglobulin: a case report and analysis of clinical experience[J]. Academic Journal of Second Military Medical University, 2020, 41(2): 181-185. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-DEJD202002010.htm
[19]	SUN Kai-bin, ZHANG Xin-yu, LIU Jing, et al. Network pharmacological analysis and mechanism prediction of Xiaochaihu decoction in treatment of COVID-19 with syndrome of pathogenic heat lingering in lung and obstructive cardinalate[J]. Chinese Traditional and Herbal Drugs, 2020, 51(7): 1750-1760. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZCYO202007009.htm
[20]	NI Zhong, LUO Feng-ming, WANG Ji-mei, et al. Recommendations for nebulized inhalation therapy for COVID-19 patients[J]. Chinese Journal of Respiratory and Critical Care Medicine, 2020, 19(2): 120-124. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZGHW202002009.htm
[21]	WANG Yu-guang, QI Wen-sheng, MA Jia-ju, et al. Clinical features and syndrome differentiation of novel coronavirus pneumonia in traditional Chinese medicine[J]. Journal of Traditional Chinese Medicine, 2020, 61(4): 281-285. (in Chinese). doi: 10.3969/j.issn.0411-8421.2020.04.025
[22]	YAO Wen-qing, SUN Bai-hong, TIAN Yuan-meng, et al. Epidemiological characteristics of 125 confirmed novel coronavirus disease in Liaoning Province[J]. Chinese Journal of Public Health, 2020, 36(4): 481-485. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZGGW202004005.htm
[23]	WANG Xiao-jun, GAO Jing, WANG Xiao-bo, et al. Clinical and epidemiological characteristics of patients with COVID-19 in Gansu Province[J]. Chinese Journal of Infection Control, 2020, 19(3): 223-226. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-GRKZ202003004.htm
[24]	LIANG Ji-ren, WEI Song-hua, QIAN Xiu-fang, et al. Epidemiological and clinical characteristics of 14 cases of COVID-19[J]. Chinese Journal of Infection Control, 2020, 19(3): 245-249. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-GRKZ202003008.htm
[25]	ZHUANG Ying-jie, CHEN Zhu, LI Jin, et al. Clinical and epidemiological characteristics of 26 patients diagnosed with COVID-19[J]. Chinese Journal of Nosocomiology, 2020, 30(6): 826-829. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZHYY202006008.htm
[26]	ZHANG Yuan-hui, TANG Long, JIANG Qian, et al. Psychological distress among nurses who are from other provinces and engaged in assisting to combat the recent outbreak of COVID-19 in Wuhan[J]. Journal of Nursing Science, 2020, 35(5): 5-8. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-HLXZ202005004.htm
[27]	SHI Dan-yi, FAN Bao-chao, CHANG Xin-jian, et al. Genetic analysis on the homology between severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) and common domestic animal coronaviruses[J]. Jiangsu Journal of Agricultural Sciences, 2020, 36(1): 251-253. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-JSNB202001036.htm
[28]	KUANG Hui-hui, YU Mei, YU Shuai, et al. Detection of nucleic acid of 2019-nCoV in medical laboratory and its practice[J]. Chinese Journal of Nosocomiology, 2020, 30(6): 830-833. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZHYY202006009.htm
[29]	YE Ying, FAN Wei, WANG Hai-feng, et al. Clustering of 2019 novel coronavirus disease epidemic in Henan Province[J]. Chinese Journal of Public Health, 2020, 36(4): 465-468. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZGGW202004001.htm
[30]	CHEN Fang, WU Jia-bing, JIANG Jing-jing, et al. Epidemiological characteristics of clusters of COVID-19 in Anhui Province[J]. Chinese Journal of Public Health, 2020, 36(4): 469-472. (in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-ZGGW202004002.htm

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System dynamics simulation on spread of COVID-19 by traffic and transportation

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