Coronavirus COVID-19. Current state and last updates.

Coronavirus COVID-19. Current state and last updates.

31-Dec-2021                World              Russia    Europe    Asia    North America    South America    Africa    Oceania          
CountryActive cases1 Day4 Days1 WeekPopulation
Total/1m popStart fromSpeedNew casesRecoveredDiedTotalStart fromSpeedNew casesRecoveredDiedTotalStart fromSpeedNew casesRecoveredDiedTotal
1Réunion 57,83064,255.5657,8300.0%000056,6140.5%1,217011,21656,6140.3%1,217011,2160.900
2Algeria 81,6481,839.0081,6490.0%560-181,6450.0%17140381,6300.0%462801844.398
3Uganda 65,6721,405.2965,6720.0%000065,6720.0%000065,6020.0%70007046.732
4Lesotho 7,8043,623.037,8040.0%00007,8040.0%00007,8040.0%00002.154
5Egypt 48,850471.2248,8500.0%000048,8500.0%000048,8500.0%0000103.668
6South Africa 27,942467.0527,7990.5%1430014326,9560.9%1,02203698625,7781.2%2,2000362,16459.827
7Somalia 12,743786.7012,7430.0%000012,7110.1%32003212,7110.0%32003216.198
8Ethiopia 14,672125.4814,6690.2%34310314,5630.3%18273010914,6040.3%263195068116.925
9DRC 9,13999.969,1390.0%00009,1390.0%00008,7950.6%36720334491.431
10Seychelles 2912,939.392910.0%00002910.0%000058311.8%6889800-2920.099
11Mauritius 744584.457440.0%00007324.3%1331183127322.4%1331183121.273
12Cameroon 3,412126.373,4120.0%00003,4120.0%00003,4120.0%000027.001
13Chad 2,578153.912,5780.0%00002,5780.0%00002,5730.0%500516.750
14Congo 983175.169830.0%00009830.0%00009830.0%00005.612
15CAR 583119.275830.0%00005830.0%00005830.0%00004.888
16Nigeria 3,48816.643,4880.0%00003,4880.0%00003,4880.0%0000209.659
17Cabo Verde 175312.501750.0%00001655.7%41310101856.8%1091190-100.560
18Morocco 1,14130.661,2763.8%491840-1351,2838.9%5226631-1421,2388.5%9491,0451-9737.214
19Niger 72929.397290.0%00007290.0%00007290.0%000024.807
20Guinea 47135.214710.0%00004710.0%00004710.0%000013.378
21Equatorial Guinea 12184.321210.0%00001210.0%00001200.1%10011.435
22Zimbabwe 38325.513830.0%00003830.0%00003830.0%000015.013
23Sudan 63114.166310.0%00006310.0%00007230.0%0920-9244.555
24Madagascar 47316.7839757.7%22915217639712.1%22915217626414.9%434223220928.181
25Malawi 39220.133920.0%00003920.0%00003800.5%13101219.470
26Eswatini 9480.4893148.4%138137019325.5%138137019313.9%138137011.168
27Kenya 60511.086515.8%38840-4660610.2%2882890-17067.0%4285290-10154.588
28Djibouti 7474.15740.0%0000740.0%0000740.0%00000.998
29Angola 38511.473850.0%00003850.0%00002019.8%1850118433.568
30Botswana 9640.27960.0%0000960.0%00005995.8%2897920-5032.384
31Gabon 8537.58850.0%0000850.0%00001750.1%1910-902.262
32Burundi 18315.081830.0%00001830.0%00001830.0%000012.134
33Rwanda 18313.891830.0%00006430.0%119001196416.2%1190011913.173
34South Sudan 978.60970.0%0000970.0%0000950.3%200211.285
35Namibia 4015.55400.0%0000400.0%0000400.0%00002.573
36Burkina Faso 1014.741010.0%00001010.0%00001010.0%000021.298
37Guinea-Bissau 3015.00300.0%0000300.0%0000300.0%00002.000
38Benin 715.75710.0%0000710.0%00001327.4%58005812.342
39Comoros 1820.41180.0%0000180.0%0000299.0%24350-110.882
40Mali 773.73770.0%0000770.0%0000770.4%220020.652
41Libya 436.20430.0%0000430.0%0000431.9%66006.936
42Gambia 2510.15250.0%0000250.0%0000250.0%00002.463
43Mozambique 882.76880.0%0000880.0%0000567.0%34023231.858
44Zambia 371.97370.0%0000370.0%00002111.9%25901618.738
45Senegal 331.94330.0%0000330.0%0000335.2%14140017.048
46Liberia 132.53130.0%0000130.0%0000156.3%8100-25.140
47Togo 70.8370.0%0000515.8%420286.0%450-18.412
48Ghana 90.291631.3%5120-72113.6%14260-12217.6%14260-1231.521
49Mauritania 30.6330.0%000037.5%110064.2%250-34.734
50Ivory Coast 70.26714.3%1100106.8%360-3133.0%390-626.828
51Western Sahara 00.0000.0%000000.0%000000.0%00000.607
52Eritrea 00.0000.0%000000.0%000000.0%00003.580
53Mayotte 00.0000.0%000000.0%30003000.0%594005940.277
54Tunisia 00.0000.0%000000.0%000000.0%81008111.904
55Sierra Leone 00.0000.0%000000.0%000000.0%10018.089
56Tanzania 00.0000.0%000000.0%000000.0%1850018560.904
57Sao Tome and Principe 00.0000.0%000000.0%000030.0%030-30.222
*** He recovered + died more became ill     Average daily infection rate of more than > 10%.    
* This is the current state. There are no data about 80,000 people falling ill in China in February.
** Speed ​​is the ratio of new illnesses (per week) to the number of days and to the number of sick (a week ago), which supposedly infected them.
The data source https://www.worldometers.info/coronavirus/