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
1Seychelles 5265,313.135260.0%000021247.2%783469031421224.7%78346903140.099
2Ivory Coast 531.9844113.6%5041093242.2%99762215319.3%1291263026.828
3Mauritania 367.603026.7%82061825.0%2671181418.5%3291224.734
4Ghana 45814.5333485.3%285161012433416.7%285161012414825.4%572262031031.521
5Mozambique 1263.961260.0%000011615.9%93821101168.8%938211031.858
6Morocco 1293.4711813.6%16501110811.3%58370211576.6%891170-2837.214
7Senegal 1136.631130.0%00001148.3%43440-11127.5%74730117.048
8Zambia 1085.7613912.9%18490-311238.3%46610-151837.0%1101850-7518.738
9Kenya 681.25875.7%5240-191007.8%35643-321015.9%50803-3354.588
10Eritrea 20.5620.0%000037.5%120-173.7%270-53.580
11Togo 18421.871993.5%7220-152426.8%731301-582526.3%1352021-688.412
12Zimbabwe 50133.375010.0%00005244.0%891093-235003.8%1471433115.013
13South Africa 7,627127.487,6270.0%00006,6683.5%9750169595,7294.2%1,9140161,89859.827
14Libya 476.78470.0%0000483.0%670-13012.9%40230176.936
15Cabo Verde 70125.00740.0%040-4692.1%6501613.2%156090.560
16Rwanda 806.07791.3%1001751.6%5005701.9%10001013.173
17Mali 25412.302761.1%3250-223591.3%191231-1054121.3%401971-15820.652
18Malawi 47324.294730.0%00004651.2%2313284650.7%23132819.470
19Nigeria 3,88218.523,8461.3%49130363,8340.7%115670483,8920.9%2452550-10209.659
20Mauritius 610479.186100.0%00006510.6%17571-416510.4%17571-411.273
21Equatorial Guinea 13996.861390.0%00001370.4%20021370.3%31021.435
22Réunion 52,87158,745.5652,8710.0%000052,2510.3%6230362052,2510.2%623036200.900
23DRC 7,93086.737,9300.0%00007,9060.1%41161247,9060.1%411612491.431
24Ethiopia 14,085120.4614,0850.1%880014,0530.1%532103214,0540.1%8251031116.925
25Chad 2,516150.212,5160.0%00002,5140.0%20022,5060.1%10001016.750
26Algeria 81,4841,835.3181,4850.0%340-181,4780.0%22160681,4740.0%392901044.398
27Egypt 48,850471.2248,8500.0%000048,8500.0%000048,8500.0%0000103.668
28Tunisia 00.0000.0%000000.0%000000.0%3410333811.904
29Burkina Faso 1014.741010.0%00001010.0%000010928.0%5035110-821.298
30Cameroon 1,10140.781,1010.0%00001,1010.0%00001,1010.0%000027.001
31Tanzania 00.0000.0%000000.0%99009900.0%99009960.904
32Congo 44579.294450.0%00004450.0%00004450.0%00005.612
33Gabon 9341.11930.0%0000930.0%0000930.0%00002.262
34Mayotte 00.0000.0%000000.0%18001800.0%1800180.277
35Namibia 375145.743750.0%00003750.0%00003750.0%00002.573
36Sudan 1,03423.211,0340.0%00001,0450.0%0110-111,0740.0%0400-4044.555
37Benin 15312.401530.0%00001530.0%00001530.0%000012.342
38Liberia 316.03310.0%0000310.0%0000310.0%00005.140
39CAR 28057.282800.0%00002800.0%00002710.5%90094.888
40Djibouti 7474.15740.0%0000740.0%0000740.0%00000.998
41Gambia 10843.851080.0%00001080.0%00001080.0%00002.463
42Guinea 32324.143230.0%00003230.0%00003230.0%000013.378
43Niger 72929.397290.0%00007290.0%00007290.0%000024.807
44Somalia 12,680782.8112,6800.0%000012,6800.0%000012,6730.0%700716.198
45Eswatini 1311.13130.0%0000130.0%0000714.4%115061.168
46Madagascar 240.85240.0%0000240.0%0000208.8%16120428.181
47Angola 591.76590.0%0000590.0%0000590.0%000033.568
48Uganda 65,3371,398.1265,3370.0%000065,3370.0%000065,3370.0%000046.732
49Guinea-Bissau 320160.003200.0%00003200.0%00003200.0%00002.000
50Botswana 564236.585640.0%00005640.0%00003855.7%181021792.384
51Sierra Leone 00.0000.0%000000.0%000000.0%00008.089
52Burundi 53243.845320.0%00005320.0%00005312.6%1031020112.134
53Sao Tome and Principe 2194.59210.0%0000210.0%00001513.3%2115060.222
54Western Sahara 00.0000.0%000000.0%000000.0%00000.607
55South Sudan 35031.013500.0%00003500.0%00003500.0%000011.285
56Comoros 55.6750.0%000050.0%000050.0%00000.882
57Lesotho 7,8043,623.037,8040.0%00007,8040.0%00007,8040.0%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/