Modeling and forecasting the spread tendency of the COVID-19 in China

Advances in Continuous and Discrete Models

Theory and Modern Applications

Table 2 The forecasting infected and removed from February 16 to March 3

Day	Infected	Forecasting Infected	Removed	Forecasting Removed	Death	Forecasting Death	Cured	Forecasting Cured
38	57,934	58,217	12,614	12,684	1770	1796	10,844	10,907
39	58,016	58,338	14,420	14,431	1868	1912	12,552	12,537
40	57,805	58,274	16,380	16,181	2004	2029	14,376	14,171
41	56,303	56,552	18,273	18,512	2118	2146	16,155	16,385
42	54,965	54,875	20,500	20,774	2236	2259	18,264	18,534
43	53,284	53,242	23,004	22,969	2345	2369	20,659	20,619
44	51,606	51,654	25,330	25,099	2442	2475	22,888	22,643
45	49,824	50,107	27,326	27,165	2592	2578	24,734	24,606
46	47,672	48,603	29,986	29,169	2663	2679	27,323	26,510
47	45,604	45,682	32,460	32,572	2715	2727	29,745	29,863
48	43,258	42,945	35,239	35,769	2744	2773	32,495	33,015
49	39,919	40,383	38,905	38,775	2788	2816	36,117	35,978
50	37,414	37,982	41,837	41,602	2835	2856	39,002	38,765
51	35,329	35,732	44,495	44,261	2870	2894	41,625	41,386
52	32,652	32,891	47,374	47,298	2912	2930	44,462	44,387
53	30,004	30,288	50,147	50,094	2943	2962	47,204	47,150
54	27,433	27,902	52,837	52,668	2981	2993	49,856	49,694