Correlation between COVID-19 data accuracy and countries' development levels April 27, 2020 Here on GeoRank.org, we allow comparing countries by COVID-19 statistics. But the accuracy of the data provided by each country may vary.
We conducted a small study and built charts to show that data accuracy depends on development and freedom levels of the country.
Our goal was to find out whether there is a correlation between the number of confirmed coronavirus cases per 100,000 people in a country and GDP per capita, the Human Freedom Index, or the Corruption Perceptions Index.
If such correlation exists, that would mean that data accuracy decreases along with these indicators.
There is a strong statistically significant correlation between countries' confirmed COVID-19 cases and GDP per capita. The correlation coefficient is 0.8 (95% CI: 0.74 - 0.85), which wouldn't have existed if the data accuracy was the same in every country.
The chart includes only countries with a population of more than 300,000 people. Otherwise small countries like the Vatican would distort the values of confirmed cases per 100,000 people.
But even for the sample of all 197 countries, the correlation coefficient is 0.49 (95% CI: 0.38 - 0.59) that is still a strong statistically significant correlation.
Confirmed COVID-19 cases per 100,000 people also correlate with the Human Freedom Index (by Cato Institute ) and the Corruption Perceptions Index (by Transparency International ).
For comparison, here's how the graph of coronavirus cases per 100K by total population looks like:
The correlation coefficient is -0.04 (95% CI: -0.19 - +0.11) and the regression line is almost parallel to the abscissa axis, showing no correlation, as expected.
173 countries with a population more than 300,000 ranked by confirmed COVID-19 cases (Data on April 27, 2020):
Show Full Table Rank Country Population Confirmed GDP per capita Human Freedom Index Corruption Perceptions Index 1 United States 325.1M
985,975
$63k
8.39
71
2 Spain 46.5M
226,629
$30k
8.22
58
3 Italy 60.6M
197,675
$34k
8.01
52
4 France 66.6M
162,100
$41k
8.25
72
5 Germany 83M
157,770
$48k
8.42
80
6 United Kingdom 65.1M
152,840
$43k
8.55
80
7 Turkey 82M
110,130
$9.4k
6.96
41
8 Iran 77.4M
90,481
$5.6k
5.29
28
9 Russia 146.8M
87,147
$11k
6.49
28
10 China 1.4B
82,830
$9.8k
6.11
39
11 Brazil 208.5M
63,100
$8.9k
7.05
35
12 Canada 35.7M
46,895
$46k
8.69
81
13 Belgium 11.2M
46,687
$48k
8.28
75
14 Netherlands 17.2M
37,845
$53k
8.49
82
15 Switzerland 8.2M
29,061
$83k
8.83
85
16 India 1.3B
27,977
$2k
6.8
41
17 Peru 30.4M
27,517
$6.9k
7.46
35
18 Portugal 10.6M
23,864
$23k
8.11
64
19 Ecuador 15.7M
22,719
$6.3k
6.7
34
20 Ireland 4.8M
19,262
$79k
8.48
73
21 Sweden 10.3M
18,640
$55k
8.48
85
22 Saudi Arabia 33M
17,522
$23k
5.66
49
23 Israel 8.9M
15,466
$42k
7.41
61
24 Austria 8.8M
15,274
$51k
8.42
76
25 Mexico 130.5M
14,677
$9.7k
6.94
28
26 Singapore 5.9M
14,423
$65k
8.1
85
27 Japan 127.1M
13,441
$39k
8.31
73
28 Chile 18.1M
13,331
$16k
8.11
67
29 Pakistan 197M
13,328
$1.5k
5.44
33
30 Poland 38.5M
11,761
$15k
8.02
60
31 Romania 19.6M
11,339
$12k
8
47
32 Belarus 9.5M
11,289
$6.3k
6.16
44
33 South Korea 51.1M
10,738
$31k
8.15
57
34 United Arab Emirates 9.3M
10,349
$43k
6.56
70
35 Qatar 2.2M
10,287
$69k
6.22
62
36 Indonesia 264M
9,096
$3.9k
6.81
38
37 Ukraine 42.6M
9,009
$3.1k
6.81
32
38 Denmark 5.8M
8,698
$61k
8.73
88
39 Serbia 7M
8,042
$7.2k
7.19
39
40 Philippines 101M
7,777
$3.1k
6.92
36
41 Norway 5.3M
7,527
$82k
8.61
84
42 Czech Republic 10.6M
7,408
$23k
8.3
59
43 Australia 23.4M
6,720
$57k
8.73
77
44 Dominican Republic 10.4M
6,135
$8.1k
6.6
30
45 Bangladesh 156.6M
5,913
$1.7k
5.8
26
46 Malaysia 31.6M
5,820
$11k
6.38
47
47 Panama 3.9M
5,779
$16k
7.53
37
48 Colombia 49.1M
5,379
$6.7k
6.78
36
49 Finland 5.5M
4,695
$50k
8.7
85
50 South Africa 57.7M
4,546
$6.4k
6.78
43
51 Egypt 94.8M
4,534
$2.5k
5.82
35
52 Morocco 36M
4,115
$3.2k
6.24
43
53 Argentina 44.9M
3,892
$12k
7.1
40
54 Luxembourg 614k
3,723
$117k
8.46
81
55 Moldova 2.6M
3,408
$3.2k
7.17
33
56 Algeria 41.3M
3,382
$4.1k
5.29
35
57 Kuwait 4.7M
3,075
$34k
6.6
41
58 Thailand 65.9M
2,931
$7.3k
7.11
36
59 Kazakhstan 18M
2,791
$9.8k
6.91
31
60 Bahrain 1.3M
2,647
$24k
7.15
36
61 Hungary 10M
2,583
$16k
8.11
46
62 Greece 10.8M
2,517
$20k
7.77
45
63 Oman 3.6M
2,049
$16k
6.3
52
64 Croatia 4.1M
2,030
$15k
7.46
48
65 Uzbekistan 32.4M
1,887
$1.5k
-
23
66 Iraq 33.4M
1,820
$5.8k
4.28
18
67 Armenia 2.9M
1,808
$4.2k
7.42
35
68 Iceland 357k
1,792
$73k
8.22
76
69 Afghanistan 34.9M
1,703
$521
-
16
70 Estonia 1.3M
1,647
$23k
8.44
73
71 Azerbaijan 10M
1,645
$4.7k
6.44
25
72 Cameroon 24.1M
1,621
$1.5k
5.7
25
73 Ghana 28.3M
1,550
$2.2k
7.21
41
74 Bosnia and Herzegovina 3.5M
1,516
$6.1k
7.27
38
75 New Zealand 4.9M
1,469
$42k
8.94
87
76 Lithuania 2.8M
1,449
$19k
7.94
59
77 Slovenia 2.1M
1,402
$26k
7.88
60
78 North Macedonia 2.1M
1,386
$6.1k
7.55
37
79 Slovakia 5.4M
1,381
$19k
8.29
50
80 Cuba 11.3M
1,369
$8.8k
-
47
81 Bulgaria 7.3M
1,348
$9.3k
7.78
42
82 Nigeria 190.9M
1,273
$2k
6.1
27
83 Ivory Coast 20.3M
1,150
$1.7k
5.95
35
84 Djibouti 850k
1,023
$3.1k
-
31
85 Guinea 11.6M
996
$879
5.68
28
86 Bolivia 11.1M
950
$3.5k
6.75
29
87 Tunisia 11.6M
949
$3.4k
6.1
43
88 Latvia 2M
818
$18k
8.16
58
89 Cyprus 1.1M
817
$28k
8.39
59
90 Albania 3M
726
$5.3k
7.68
36
91 Lebanon 4.5M
707
$8.3k
6.72
28
92 Niger 17.1M
696
$414
6
34
93 Costa Rica 4.9M
695
$12k
7.81
56
94 Kyrgyzstan 6.2M
695
$1.3k
6.65
29
95 Senegal 14.1M
671
$1.5k
6.29
45
96 Honduras 8.1M
661
$2.5k
7.13
29
97 Burkina Faso 19.2M
632
$715
6.84
41
98 Uruguay 3.4M
606
$17k
7.93
70
99 Sri Lanka 21.4M
557
$4.1k
5.69
38
100 Guatemala 15.5M
500
$4.5k
7.21
27
101 Georgia 3.7M
496
$4.7k
7.48
58
102 Palestine 4.7M
495
$3.2k
-
-
103 DR Congo 86.8M
459
$562
5.27
20
104 Malta 423k
448
$30k
8.42
54
105 Jordan 10.4M
447
$4.2k
6.59
49
106 Somalia 11M
436
$315
-
10
107 Taiwan 23.6M
429
$25k
7.79
63
108 Mali 18.5M
389
$900
6.07
32
109 Kenya 48.5M
363
$1.7k
6.61
27
110 Jamaica 2.9M
350
$5.4k
7.16
44
111 Mauritius 1.3M
332
$11k
8.18
51
112 Venezuela 28.5M
325
$16k
5.27
18
113 El Salvador 6.3M
323
$4.1k
7.4
35
114 Montenegro 622k
321
$8.8k
7.67
45
115 Tanzania 57.3M
299
$1.1k
6.37
36
116 Vietnam 94.7M
270
$2.6k
6.31
33
117 Equatorial Guinea 1.2M
258
$10k
-
16
118 Sudan 40.5M
237
$977
4.44
16
119 Paraguay 6.8M
228
$5.8k
7.02
29
120 Maldives 345k
214
$10k
-
31
121 Congo 5.3M
200
$2.1k
5.55
19
122 Rwanda 12.2M
191
$773
7
56
123 Gabon 1.7M
176
$8k
5.79
31
124 Myanmar 53.3M
146
$1.3k
4.81
29
125 Brunei 418k
138
$32k
6.66
63
126 Ethiopia 105M
124
$772
5.33
34
127 Liberia 4.7M
124
$677
6.6
32
128 Madagascar 22.9M
124
$528
6.69
25
129 Cambodia 15.1M
122
$1.5k
7.22
20
130 Trinidad and Tobago 1.3M
116
$17k
6.81
41
131 Cape Verde 546k
106
$3.6k
7.4
57
132 Togo 6.3M
98
$679
5.67
30
133 Sierra Leone 7.6M
93
$534
6.24
30
134 Zambia 17.1M
88
$1.5k
6.67
35
135 Bahamas 377k
80
$32k
7.97
65
136 Uganda 42.9M
79
$643
6.4
26
137 Mozambique 25.8M
76
$499
6.14
23
138 Guyana 800k
74
$5k
6.68
37
139 Haiti 10.3M
74
$868
7.04
20
140 Benin 10M
64
$902
6.85
40
141 Libya 5.7M
61
$7.2k
4.98
17
142 Eswatini 1.4M
59
$4.1k
6.11
38
143 Guinea-Bissau 1.5M
53
$778
5.97
16
144 Nepal 29.4M
52
$1k
6.83
31
145 Chad 11M
46
$728
5.23
19
146 Syria 19.8M
43
$2k
5.34
13
147 Eritrea 3.5M
39
$811
-
24
148 Mongolia 3.1M
38
$4.1k
7.17
37
149 Malawi 18.6M
34
$389
6.68
32
150 Zimbabwe 14.1M
31
$2.1k
4.96
22
151 Angola 29.8M
26
$3.4k
5.02
19
152 East Timor 1.2M
24
$2k
6.41
35
153 Botswana 2M
22
$8.3k
6.81
61
154 Laos 6.8M
19
$2.5k
6.2
29
155 Central African Republic 5M
19
$476
5.58
26
156 Belize 375k
18
$4.9k
7.37
-
157 Fiji 881k
18
$6.3k
7.46
-
158 Namibia 2.3M
16
$5.9k
6.97
53
159 Nicaragua 6.2M
13
$2k
7.22
25
160 Burundi 10.9M
11
$272
5.7
17
161 Suriname 539k
10
$6.2k
7.19
43
162 Gambia 1.9M
10
$716
6.52
37
163 Papua New Guinea 7.3M
8
$2.7k
6.99
28
164 Bhutan 754k
7
$3.2k
6.85
68
165 Mauritania 3.5M
7
$1.2k
5.52
27
166 South Sudan 12.6M
6
$1.1k
-
13
167 Yemen 26.2M
1
$944
5.4
14
168 North Korea 24.9M
0
$1.7k
-
14
169 Solomon Islands 561k
0
$2.1k
-
44
170 Tajikistan 8.9M
0
$827
6.64
25
171 Turkmenistan 5.1M
0
$7k
-
20
172 Comoros 735k
0
$1.4k
-
27
173 Lesotho 2.2M
0
$1.3k
6.16
41
Okay, but what does it all mean?
It shows that the number of confirmed coronavirus cases in each country is literally what the country has managed to detect .
But little it says about the actual numbers , especially in developing countries, as testing policies and capabilities vary greatly.
So while comparing, keep in mind that data accuracy depends on a country's level of development.
