Covid mortality

	A	B	C	D	E	F	G	H	I	J	K
1	Place	Deaths	Recovered	Confirmed cases	Active	Total concluded cases	% dead in concluded cases	Confidence (endpoint/ total for over 500 cases, discounted below that)	Notes	Data source is	https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
2	Anhui	6	984	990	0	990	0.61%	100.0%
3	Henan	22	1249	1273	2	1271	1.73%	99.8%
4	Jiangxi	1	932	935	2	933	0.11%	99.8%
5	Jiangsu	0	627	631	4	627	0.00%	99.4%
6	Zhejiang	1	1195	1215	19	1196	0.08%	98.4%
7	Sichuan	3	488	539	48	491	0.61%	98.2%
8	Hunan	4	995	1018	19	999	0.40%	98.1%
9	Chongqing	6	549	576	21	555	1.08%	96.4%
10	Shandong	6	726	760	28	732	0.82%	96.3%
11	Guangdong	8	1282	1356	66	1290	0.62%	95.1%
12	Heilongjiang	13	440	482	29	453	2.87%	90.6%
13	Hubei	3046	49134	67773	15593	52180	5.84%	77.0%	Epicenter
14	South Korea	61	288	7755	7406	349	17.48%	69.8%
15	Beijing	8	326	435	101	334	2.40%	66.8%
16	Diamond Princess	7	325	696	364	332	2.11%	66.4%	Cruise ship
17	Shanghai	3	320	344	21	323	0.93%	64.6%
18	Hebei	6	307	318	5	313	1.92%	62.6%
19	Fujian	1	295	296	0	296	0.34%	59.2%
20	Guangxi	2	238	252	12	240	0.83%	48.0%
21	Spain	55	183	2277	2039	238	23.11%	47.6%
22	Shaanxi	1	232	245	12	233	0.43%	46.6%
23	Iran	354	2959	9000	5687	3313	10.69%	36.8%
24	Yunnan	2	170	174	2	172	1.16%	34.4%
25	Hainan	6	159	168	3	165	3.64%	33.0%
26	Guizhou	2	133	146	11	135	1.48%	27.0%
27	Tianjin	3	131	136	2	134	2.24%	26.8%
28	Liaoning	1	111	125	13	112	0.89%	22.4%
29	Singapore	0	96	178	82	96	0.00%	19.2%
30	Japan	17	76	639	546	93	18.28%	18.6%
31	Jilin	1	91	93	1	92	1.09%	18.4%
32	Gansu	2	88	127	37	90	2.22%	18.0%
33	Xinjiang	3	73	76	0	76	3.95%	15.2%
34	Italy	827	1045	12462	10590	1872	44.18%	15.0%
35	Inner Mongolia	1	71	75	3	72	1.39%	14.4%
36	Ningxia	0	72	75	3	72	0.00%	14.4%
37	Hong Kong	3	65	126	58	68	4.41%	13.6%
38	US (all)	36	8	1281	1237	44	81.82%	8.8%
39	Bahrain	0	35	195	160	35	0.00%	7.0%
40	Thailand	1	31	32	0	32	3.13%	6.4%
41	France	19	12	2284	2253	31	61.29%	6.2%
42	Washington State	29	1	366	336	30	96.67%	6.0%
43	Germany	3	25	1908	1880	28	10.71%	5.6%
44	Egypt	1	27	60	32	28	3.57%	5.6%
45	UK	8	18	456	430	26	30.77%	5.2%
46	Malaysia	0	26	149	123	26	0.00%	5.2%
47	Iraq	7	15	71	49	22	31.82%	4.4%
48	Taiwan	1	17	48	30	18	5.56%	3.6%
49	Qinghai	0	18	18	0	18	0.00%	3.6%
50	Vietnam	0	16	38	22	16	0.00%	3.2%
51	Peru	0	11	11	0	11	0.00%	2.2%
52	Macau	0	10	10	0	10	0.00%	2.0%
53	Oman	0	9	18	9	9	0.00%	1.8%
54	Switzerland	4	4	652	644	8	50.00%	1.6%
55	Queensland, Aus	0	8	20	12	8	0.00%	1.6%
56	Victoria, Aus	0	7	21	14	7	0.00%	1.4%
57	UAE	0	7	7	0	7	0.00%	1.4%
58	New South Wales	2	4	65	59	6	33.33%	1.2%
59	Romania	0	6	47	41	6	0.00%	1.2%
60	Netherlands	5	0	503	498	5	100.00%	1.0%
61	California	3	2	177	172	5	60.00%	1.0%
62	India	1	4	62	57	5	20.00%	1.0%
63	British Columbia	1	4	39	34	5	20.00%	1.0%
64	Belgium	3	1	314	310	4	75.00%	0.8%
65	Austria	0	4	246	242	4	0.00%	0.8%
66	Israel	0	4	109	105	4	0.00%	0.8%
67	Lebanon	3	1	61	57	4	75.00%	0.8%
68	Ontario	0	4	41	37	4	0.00%	0.8%
69	Philippines	1	2	49	46	3	33.33%	0.6%
70	Russia	0	3	20	17	3	0.00%	0.6%
71	Belarus	0	3	9	6	3	0.00%	0.6%
72	Sweden	1	1	500	498	2	50.00%	0.4%
73	Kuwait	0	2	72	70	2	0.00%	0.4%
74	San Marino	2	0	62	60	2	100.00%	0.4%
75	Florida	2	0	28	26	2	100.00%	0.4%
76	Illinois	0	2	25	23	2	0.00%	0.4%
77	South Australia	0	2	9	7	2	0.00%	0.4%
78	Norway	0	1	598	597	1	0.00%	0.2%
79	Denmark	0	1	442	441	1	0.00%	0.2%
80	Massachusetts	0	1	95	94	1	0.00%	0.2%
81	Finland	0	1	59	58	1	0.00%	0.2%
82	Argentina	1	0	19	18	1	100.00%	0.2%
83	Western Australia	1	0	9	8	1	100.00%	0.2%
84	Wisconsin	0	1	6	5	1	0.00%	0.2%
85	Cambodia	0	1	3	2	1	0.00%	0.2%
86	Sri Lanka	0	1	2	1	1	0.00%	0.2%
87	Arizona	0	1	1	0	1	0.00%	0.2%
88	Mexico	0	1	1	0	1	0.00%	0.2%
89	Nepal	0	1	1	0	1	0.00%	0.2%
90	Pakistan	0	1	1	0	1	0.00%	0.2%
91	Tibet	0	1	1	0	1	0.00%	0.2%
92	Senegal	0	1	1	0	1	0.00%	0.2%
93	New Zealand	0	0	5	5	0	#DIV/0!	0.0%
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