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
1Egypt 49,228474.8649,2280.0%000049,2280.0%000049,2280.0%0000103.668
2South Africa 61,3621,025.6661,3620.0%000061,3620.0%000061,3620.0%000059.827
3Algeria 81,9101,844.9081,9100.0%000081,9100.0%000081,9100.0%000044.398
4Morocco 3,728100.183,7280.0%00003,7280.0%00003,7280.0%000037.214
5Tunisia 00.0000.0%000000.0%000000.0%000011.904
6Senegal 191.11190.0%0000190.0%0000190.0%000017.048
7Burkina Faso 643.01640.0%0000640.0%0000640.0%000021.298
8Réunion 67,09574,550.0067,0950.0%000067,0950.0%000067,0950.0%00000.900
9DRC 11,740128.4011,7400.0%000011,7400.0%000011,7400.0%000091.431
10Cameroon 30911.443090.0%00003090.0%00003090.0%000027.001
11Nigeria 3,56717.013,5670.0%00003,5670.0%00003,5670.0%0000209.659
12Ghana 230.73230.0%0000230.0%0000230.0%000031.521
13Rwanda 796.00790.0%0000790.0%0000790.0%000013.173
14Ivory Coast 60.2260.0%000060.0%000060.0%000026.828
15Ethiopia 5,28745.225,2870.0%00005,2870.0%00005,2870.0%0000116.925
16Kenya 95717.539570.0%00009570.0%00009570.0%000054.588
17Mauritius 681534.966810.0%00006810.0%00006820.4%17180-11.273
18Seychelles 15151.52150.0%0000150.0%0000150.0%00000.099
19Tanzania 00.0000.0%000000.0%000000.0%000060.904
20Equatorial Guinea 13996.861390.0%00001390.0%00001390.0%00001.435
21Congo 983175.169830.0%00009830.0%00009830.0%00005.612
22Gabon 114.86110.0%0000110.0%0000110.0%00002.262
23Mayotte 00.0000.0%000000.0%000000.0%00000.277
24Namibia 801311.318010.0%00008010.0%00008010.0%00002.573
25Sudan 00.0000.0%000000.0%000000.0%000044.555
26Benin 40.3240.0%000040.0%000040.0%000012.342
27Liberia 122.33120.0%0000120.0%0000120.0%00005.140
28Mauritania 24752.182470.0%00002470.0%00002470.0%00004.734
29Zambia 3,902208.243,9020.0%00003,9020.0%00003,9020.0%000018.738
30CAR 5511.25550.0%0000550.0%0000550.0%00004.888
31Chad 2,633157.192,6330.0%00002,6330.0%00002,6330.0%000016.750
32Djibouti 7474.15740.0%0000740.0%0000740.0%00000.998
33Gambia 6526.39650.0%0000650.0%0000650.0%00002.463
34Guinea 33825.273380.0%00003380.0%00003380.0%000013.378
35Niger 72929.397290.0%00007290.0%00007290.0%000024.807
36Somalia 12,791789.6712,7910.0%000012,7910.0%000012,7910.0%000016.198
37Eswatini 339290.243390.0%00003390.0%00003390.0%00001.168
38Togo 70.8370.0%000070.0%000070.0%00008.412
39Mozambique 2,36974.362,3690.0%00002,3690.0%00002,3690.0%000031.858
40Cabo Verde 68121.43680.0%0000680.0%0000680.0%00000.560
41Madagascar 431.53430.0%0000430.0%0000324.3%11001128.181
42Zimbabwe 1,13675.671,1360.0%00001,1360.0%00001,1360.0%000015.013
43Angola 310.92310.0%0000310.0%0000310.0%000033.568
44Eritrea 00.0000.0%000000.0%000000.0%00003.580
45Uganda 67,7661,450.1067,7660.0%000067,7660.0%000067,7660.0%000046.732
46Guinea-Bissau 508254.005080.0%00005080.0%00005080.0%00002.000
47Mali 773.73770.0%0000770.0%0000770.0%000020.652
48Libya 00.0000.0%0000118.9%120-1110.4%120-16.936
49Botswana 406170.304060.0%00004060.0%00004010.2%50052.384
50Sierra Leone 00.0000.0%000000.0%000000.0%00008.089
51Burundi 63452.256340.0%00006340.0%00006340.0%000012.134
52Sao Tome and Principe 00.0000.0%000010.0%010-110.0%010-10.222
53Western Sahara 00.0000.0%000000.0%000000.0%00000.607
54Malawi 57129.335710.0%00005710.0%00005710.0%000019.470
55South Sudan 11510.191150.0%00001150.0%00001150.0%000011.285
56Comoros 910.2090.0%000090.0%000090.0%00000.882
57Lesotho 8,0873,754.418,0870.0%00008,0870.0%00008,0870.0%00002.154
*** 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/