Analysis on early spatiotemporal transmission characteristics of COVID-19

Cong Wang; Jie Yan; Xu Wang; Min Li

doi:10.7498/aps.69.20200285

Journals >Acta Physica Sinica >Volume 69 >Issue 8 >Page 080701-1 > Article

Acta Physica Sinica
Vol. 69, Issue 8, 080701-1 (2020)

Analysis on early spatiotemporal transmission characteristics of COVID-19

Cong Wang^1、2, Jie Yan^2、3、*, Xu Wang⁴, and Min Li⁵

Author Affiliations

¹Department of Computer Science & Technology, Sichuan Police College, Luzhou 646000, China

²Institute of Sichuan Police Science, Sichuan Police College, Chengdu 610200, China

³Department of Road Traffic Management, Sichuan Police College, Luzhou 646000, China

⁴School of Movie and Media, Sichuan Normal University, Chengdu 610068, China

⁵School of Computer Science, Sichuan Normal University, Chengdu 610068, China

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DOI: 10.7498/aps.69.20200285 Cite this Article

Cong Wang, Jie Yan, Xu Wang, Min Li. Analysis on early spatiotemporal transmission characteristics of COVID-19[J]. Acta Physica Sinica, 2020, 69(8): 080701-1 Copy Citation Text

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Comparing the actual cumulative number of cases and its estimations according to different: (a) Year 2019; (b) year 2020.

Fig. 1. Comparing the actual cumulative number of cases and its estimations according to different

: (a) Year 2019; (b) year 2020.

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Comparing the migration index of Wuhan before the spring festival with the same period of 2019: (a) Inner migration index; (b) outer migration index.

Fig. 2. Comparing the migration index of Wuhan before the spring festival with the same period of 2019: (a) Inner migration index; (b) outer migration index.

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Fig. 3. The estimation errors of the first arrival times for each provinces.

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日期	人数	日期	人数	日期	人数	日期	人数	日期	人数
12/09	1	12/17	12	12/21	29	12/25	47	12/29	78
12/11	2	12/18	14	12/22	37	12/26	49	12/30	90
12/12	5	12/19	16	12/23	40	12/27	59	12/31	102
12/15	8	12/20	25	12/24	45	12/28	68

Table 1.

The cumulative number of confirmed cases in 2019.

2019年累积发病人数

截至时点	估计发病人数		实际发病人数	上报CCDC人数
截至时点	软件抓取法	蒙特卡罗法	实际发病人数	上报CCDC人数
2019/12/31	102	49	102	0
2020/01/10	738	459	738—781	41
2020/01/20	6162	5800	6143—6187	291
2020/01/31	32661	29654	32633—32677	11821
2020/02/11	44692	69163	44672	44730

Table 2.

The cumulative number of confirmed cases in each time slots in 2020.

2020年各时间段累积发病人数

截止日期	$\beta $	置信区间	R²	截止日期	$\beta $	置信区间	R²
2019/12/31	0.2213	[0.2152, 0.2274]	0.868	2020/01/11	0.2066	[0.2056, 0.2274]	0.990
2020/01/01	0.2171	[0.2116, 0.2225]	0.878	2020/01/12	0.2063	[0.2056, 0.2071]	0.993
2020/01/02	0.2168	[0.2127, 0.2209]	0.923	20200/1/13	0.2060	[0.2054, 0.2067]	0.995
2020/01/03	0.2159	[0.2127, 0.2191]	0.949	2020/01/14	0.2059	[0.2054, 0.2064]	0.997
2020/01/04	0.2155	[0.2130, 0.2179]	0.967	2020/01/15	0.2056	[0.2052, 0.2060]	0.998
2020/01/05	0.2138	[0.2118, 0.2159]	0.973	2020/10/16	0.2058	[0.2054, 0.2061]	0.998
2020/01/06	0.2127	[0.2109, 0.2144]	0.980	2020/01/17	0.2060	[0.2057, 0.2063]	0.999
2020/01/07	0.2109	[0.2093, 0.2126]	0.980	2020/01/18	0.2064	[0.2061, 0.2066]	0.999
2020/01/08	0.2091	[0.2075, 0.2107]	0.979	2020/01/19	0.2065	[0.2063, 0.2067]	0.999
2020/01/09	0.2080	[0.2067, 0.2094]	0.984	2020/01/20	0.2066	[0.2064, 0.2068]	0.999
2020/01/10	0.2067	[0.2054, 0.2080]	0.985	2020/01/21	0.2070	[0.2068, 0.2073]	0.999

Table 3. Possible values of the infection rate.

截至时点	$\beta $
截至时点	0.2213	0.2159	0.2080	0.2066
2019/12/31	130	116	97	95
2020/01/10	1190	1001	777	753
2020/01/20	10870	8666	6220	5964

Table 4.

Cumulative confirmed cases in key time nodes.

重要时间节点的累积发病人数

日期	迁徙指数	人数/万	日期	迁徙指数	人数/万	日期	迁徙指数	人数/万
2020/01/10	6.6232	27	2020/01/22	11.8403	29.96	2019/01/29	7.0282	27.2
2020/01/11	7.5612	29.8	2019/01/21	4.5718	21.6	2019/01/30	7.1072	27.7
2020/01/12	6.2165	27	2019/01/22	4.6892	21.4	2019/01/31	7.4800	28.1
2020/01/13	5.7620	24.8	2019/01/23	4.8062	23	2019/02/01	8.7140	29.8
2020/01/15	5.9087	26.5	2019/01/24	4.8605	21.7	2019/02/02	9.6043	31.5
2020/01/16	6.0028	27.7	2019/01/26	7.0436	27	2019/02/03	9.2247	29.1
2020/01/19	7.4060	30	2019/01/28	6.7706	26.8

Table 5.

The Baidu inner migration index and the number of the travelers sent from Wuhan`s major railway stations.

武汉市三大火车站发送旅客人数与迁出指数

省份	$\beta $			实际日期	省份	$\beta $			实际日期
省份	0.2213	0.2159	0.2070	实际日期	省份	0.2213	0.2159	0.2070	实际日期
安徽	01/06	01/06	01/07	01/07	辽宁	01/11	01/12	01/13	01/09
北京	01/07	01/07	01/08	01/08*	内蒙古	01/13	01/14	01/16	01/16
福建	01/09	01/09	01/10	01/06	宁夏	01/17	01/18	01/20	01/17
甘肃	01/10	01/11	01/12	01/04	青海	01/19	01/21	01/23	01/21
广东	01/05	01/05	01/06	01/04	山东	01/08	01/08	01/09	01/08
广西	01/08	01/09	01/09	01/13	山西	01/09	01/10	01/10	01/14
贵州	01/08	01/08	01/09	01/06	陕西	01/09	01/09	01/10	01/12
海南	01/10	01/11	01/12	01/13	上海	01/08	01/08	01/09	01/10
河北	01/08	01/09	01/09	01/13	四川	01/08	01/08	01/09	01/07
河南	01/04	01/04	01/05	01/03	天津	01/14	01/15	01/16	01/11
黑龙江	01/12	01/13	01/14	01/12	西藏	> 01/23	> 01/23	> 01/23	01/30
湖南	01/05	01/05	01/06	01/05	新疆	01/12	01/12	01/14	01/17
吉林	01/15	01/15	01/17	01/14	云南	01/09	01/11	01/10	01/07
江苏	01/06	01/07	01/07	01/10	浙江	01/07	01/07	01/08	01/04
江西	01/06	01/07	01/07	01/07	重庆	01/08	01/08	01/09	01/06

Table 6.

The arrival times of each provinces.

省级区域的首例到达时间

Cong Wang, Jie Yan, Xu Wang, Min Li. Analysis on early spatiotemporal transmission characteristics of COVID-19[J]. Acta Physica Sinica, 2020, 69(8): 080701-1

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