Coronavirus COVID-19. Current state and last updates.

Coronavirus COVID-19. Current state and last updates.

15-Apr-2024                World              Russia    Europe    Asia    North America    South America    Africa    Oceania          
CountryActive cases1 Week2 Week4 WeekPopulation
Total/1m popStart fromSpeedNew casesRecoveredDiedTotalStart fromSpeedNew casesRecoveredDiedTotalStart fromSpeedNew casesRecoveredDiedTotal
1Sao Tome and Principe 1358.56617.9%13607218.3%19801100.0%26130130.222
2Burkina Faso 1185.541180.0%00001130.3%50051130.2%500521.298
3Botswana 788330.547880.0%00007850.0%30035921.0%196001962.384
4Egypt 49,228474.8649,2280.0%000049,2280.0%000049,2280.0%0000103.668
5South Africa 61,3621,025.6661,3620.0%000061,3620.0%000061,3620.0%000059.827
6Algeria 82,0681,848.4682,0680.0%000082,0680.0%000082,0680.0%000044.398
7Morocco 00.0000.0%000000.0%000000.0%48024637.214
8Tunisia 00.0000.0%000000.0%000000.0%000011.904
9Senegal 583.40580.0%0000580.0%0000580.0%000017.048
10Réunion 00.0000.0%000000.0%000000.0%00000.900
11DRC 13,381146.3513,3810.0%000013,3810.0%000013,3810.0%000091.431
12Cameroon 1254.631250.0%00001250.0%00001250.0%000027.001
13Nigeria 4,08019.464,0800.0%00004,0800.0%00004,0800.0%0000209.659
14Ghana 20.0620.0%000020.0%000020.0%000031.521
15Rwanda 110.84110.0%0000110.0%0000110.0%000013.173
16Ivory Coast 521.94520.0%0000520.0%0000520.0%000026.828
17Ethiopia 5,41246.295,4120.0%00005,4120.0%00005,3720.0%400040116.925
18Kenya 1,13220.741,1320.0%00001,1320.0%00001,1320.0%000054.588
19Mauritius 696546.746960.0%00006960.0%00006960.0%00001.273
20Seychelles 00.0000.0%000000.0%000000.0%00000.099
21Tanzania 00.0000.0%000000.0%000000.0%000060.904
22Equatorial Guinea 13996.861390.0%00001390.0%00001390.0%00001.435
23Congo 983175.169830.0%00009830.0%00009830.0%00005.612
24Gabon 7030.95700.0%0000700.0%0000700.0%00002.262
25Mayotte 00.0000.0%000000.0%000000.0%00000.277
26Namibia 1,184460.161,1840.0%00001,1840.0%00001,0780.3%109031062.573
27Sudan 00.0000.0%000000.0%000000.0%000044.555
28Benin 262.11260.0%0000260.0%0000260.0%000012.342
29Liberia 122.33120.0%0000120.0%0000120.0%00005.140
30Mauritania 38080.273800.0%00003800.0%00003710.1%90094.734
31Zambia 3,919209.153,9190.0%00003,9190.0%00003,9190.0%000018.738
32CAR 12725.981270.0%00001270.0%00001270.0%00004.888
33Chad 2,633157.192,6330.0%00002,6330.0%00002,6330.0%000016.750
34Djibouti 7474.15740.0%0000740.0%0000740.0%00000.998
35Gambia 6526.39650.0%0000650.0%0000650.0%00002.463
36Guinea 34725.943470.0%00003470.0%00003470.0%000013.378
37Niger 72929.397290.0%00007290.0%00007290.0%000024.807
38Somalia 12,791789.6712,7910.0%000012,7910.0%000012,7910.0%000016.198
39Eswatini 648554.796480.0%00006480.0%00006480.0%00001.168
40Togo 10.1210.0%000010.0%000023.3%340-18.412
41Mozambique 2,67684.002,6760.0%00002,6760.0%00002,6760.0%000031.858
42Cabo Verde 305544.643050.0%00003050.0%00003050.0%00000.560
43Madagascar 1987.031980.0%00001980.0%00001980.0%000028.181
44Zimbabwe 1,731115.301,7310.0%00001,7310.0%00001,7030.1%31032815.013
45Angola 1,97158.721,9710.0%00001,9710.0%00001,9670.0%400433.568
46Eritrea 00.0000.0%000000.0%000000.0%00003.580
47Uganda 68,0861,456.9568,0860.0%000068,0860.0%000067,9200.0%1660016646.732
48Guinea-Bissau 508254.005080.0%00005080.0%00005080.0%00002.000
49Mali 894.31890.0%0000890.0%0000890.0%000020.652
50Libya 20.2920.0%000020.0%000020.0%00006.936
51Sierra Leone 00.0000.0%000000.0%000000.0%00008.089
52Burundi 1,11491.811,1140.0%00001,1140.0%00001,1140.0%000012.134
53Western Sahara 00.0000.0%000000.0%000000.0%00000.607
54Malawi 00.0000.0%000000.0%000000.0%000019.470
55South Sudan 55749.365570.0%00005570.0%00005570.0%000011.285
56Comoros 910.2090.0%000090.0%000090.0%00000.882
57Lesotho 9,4354,380.229,4350.0%00009,4350.0%00009,4350.0%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/