Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in United Kingdom of about 3.56% each day. That corresponds to a doubling of the numbers approx. every 20 days.
The graph above and the following table show the course of reported coronavirus infections in United Kingdom assuming that the numbers are following an exponential trend without any slowdown.
99,500

104,000
+4,660 (+4.69%)
110,000
+5,620 (+5.4%)
115,000
+5,550 (+5.05%)
121,000
+5,860 (+5.08%)
126,000
+4,680 (+3.87%)
130,000
+4,320 (+3.43%)
135,000
+4,470 (+3.43%)
139,000
+4,610 (+3.42%)
145,000
+5,390 (+3.87%)
150,000
149,000  150,000
+4,960 (+3.43%)
155,000
155,000  155,000
+5,330 (+3.56%)
160,000
160,000  161,000
+5,520 (+3.56%)
166,000
166,000  167,000
+5,710 (+3.56%)
172,000
172,000  172,000
+5,920 (+3.56%)
178,000
178,000  179,000
+6,130 (+3.56%)
185,000
184,000  185,000
+6,340 (+3.56%)
191,000
191,000  192,000
+6,570 (+3.56%)
198,000
197,000  198,000
+6,800 (+3.56%)
205,000
204,000  205,000
+7,050 (+3.56%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in United Kingdom of about 3.98% each day. That corresponds to a doubling of the numbers approx. every 18 days.
The graph above and the following table show the course of reported deaths by coronavirus in United Kingdom assuming that the numbers are following an exponential trend without any slowdown.
12,900

13,800
+865 (+6.71%)
14,600
+848 (+6.16%)
15,500
+891 (+6.1%)
16,100
+597 (+3.85%)
16,600
+455 (+2.83%)
17,400
+828 (+5%)
18,200
+773 (+4.45%)
18,800
+640 (+3.53%)
19,600
+776 (+4.13%)
20,300
20,300  20,400
+780 (+3.99%)
21,200
21,100  21,200
+810 (+3.98%)
22,000
21,900  22,100
+843 (+3.98%)
22,900
22,800  23,000
+876 (+3.98%)
23,800
23,700  23,900
+911 (+3.98%)
24,700
24,600  24,800
+947 (+3.98%)
25,700
25,600  25,800
+985 (+3.98%)
26,700
26,600  26,800
+1,020 (+3.98%)
27,800
27,700  27,900
+1,070 (+3.98%)
28,900
28,800  29,000
+1,110 (+3.98%)
In United Kingdom, approx. 0.94% of the population die each year. With a population of roughly 66,500,000 people in United Kingdom, that corresponds to about 1,710 deaths per day on the statistical average.
The graph above shows the reported daily deaths by coronavirus in contrast to the statistical number as baseline.
To estimate the mortality rate of coronavirus infections, we need to consider that a reported death already showed up in the reported cases a few days before. It is presumed that this lag is between 7 and 14 days. If we assumed that the lag was about 7 days, the mortality rate in United Kingdom would be approx. 18%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in United Kingdom in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in United Kingdom in the previous days.
The graph tries to predict the number of required intensive care units in United Kingdom. We assume the following:
The graph above and the following table show the course of reported coronavirus infections in awaiting clarification assuming that the numbers are following an exponential trend without any slowdown.
8

14
+6 (+75%)
The graph above shows the daily increase of reported coronavirus infections in awaiting clarification in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Barnet of about 29% each day. That corresponds to a doubling of the numbers approx. every 2.7 days.
The graph above and the following table show the course of reported coronavirus infections in Barnet assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
4
+1 (+33.3%)
5
+1 (+25%)
8
+3 (+60%)
8
+0 (+0%)
11
9  14
+3 (+41.4%)
15
12  18
+3 (+29%)
19
15  23
+4 (+29%)
24
20  30
+5 (+29%)
31
26  38
+7 (+29%)
40
33  49
+9 (+29%)
52
43  63
+12 (+29%)
67
55  82
+15 (+29%)
87
72  106
+20 (+29%)
112
92  136
+25 (+29%)
The graph above shows the daily increase of reported coronavirus infections in Barnet in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Barnsley of about 1.46e10% each day. That corresponds to a doubling of the numbers approx. every ,480,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Barnsley assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
2  2
+0 (+3.64e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
The graph above shows the daily increase of reported coronavirus infections in Barnsley in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Birmingham assuming that the numbers are following an exponential trend without any slowdown.
1

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
The graph above shows the daily increase of reported coronavirus infections in Birmingham in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Bolton of about 12.9% each day. That corresponds to a doubling of the numbers approx. every 5.7 days.
The graph above and the following table show the course of reported coronavirus infections in Bolton assuming that the numbers are following an exponential trend without any slowdown.
1

1
+0 (+0%)
2
+1 (+100%)
3
+1 (+50%)
3
+0 (+0%)
3
+0 (+0%)
4
3  5
+0 (+22.5%)
4
3  5
+0 (+12.9%)
5
4  6
+0 (+12.9%)
5
4  7
+0 (+12.9%)
6
5  7
+0 (+12.9%)
7
5  8
+0 (+12.9%)
8
6  10
+0 (+12.9%)
9
7  11
+0 (+12.9%)
10
8  12
+1 (+12.9%)
11
9  14
+1 (+12.9%)
The graph above shows the daily increase of reported coronavirus infections in Bolton in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Bournemouth, Christchurch and Poole of about 17.6% each day. That corresponds to a doubling of the numbers approx. every 4.3 days.
The graph above and the following table show the course of reported coronavirus infections in Bournemouth, Christchurch and Poole assuming that the numbers are following an exponential trend without any slowdown.
2

2
+0 (+0%)
3
+1 (+50%)
3
+0 (+0%)
4
3  4
+0 (+22.5%)
4
4  5
+0 (+17.6%)
5
4  6
+0 (+17.6%)
6
5  7
+0 (+17.6%)
7
6  8
+1 (+17.6%)
8
7  10
+1 (+17.6%)
10
8  12
+1 (+17.6%)
11
10  14
+2 (+17.6%)
13
11  16
+2 (+17.6%)
16
13  19
+2 (+17.6%)
The graph above shows the daily increase of reported coronavirus infections in Bournemouth, Christchurch and Poole in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Bracknell Forest of about 1.46e10% each day. That corresponds to a doubling of the numbers approx. every ,480,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Bracknell Forest assuming that the numbers are following an exponential trend without any slowdown.
0

2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
2  2
+0 (+3.64e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
The graph above shows the daily increase of reported coronavirus infections in Bracknell Forest in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Brent assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
3
+2 (+200%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Brent in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Brighton and Hove of about 4.09% each day. That corresponds to a doubling of the numbers approx. every 17 days.
The graph above and the following table show the course of reported coronavirus infections in Brighton and Hove assuming that the numbers are following an exponential trend without any slowdown.
6

7
+1 (+16.7%)
7
+0 (+0%)
8
+1 (+14.3%)
8
+0 (+0%)
8
+0 (+0%)
9
8  9
+0 (+6.9%)
9
8  10
+0 (+4.09%)
9
9  10
+0 (+4.09%)
10
9  10
+0 (+4.09%)
10
9  11
+0 (+4.09%)
10
10  11
+0 (+4.09%)
11
10  12
+0 (+4.09%)
11
11  12
+0 (+4.09%)
12
11  13
+0 (+4.09%)
12
11  13
+0 (+4.09%)
The graph above shows the daily increase of reported coronavirus infections in Brighton and Hove in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Bristol, City of of about 12.9% each day. That corresponds to a doubling of the numbers approx. every 5.7 days.
The graph above and the following table show the course of reported coronavirus infections in Bristol, City of assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
2
+1 (+100%)
2
+0 (+0%)
2
+0 (+0%)
3
+1 (+50%)
3
2  4
+0 (+1.19e10%)
3
3  4
+0 (+12.9%)
4
3  5
+0 (+12.9%)
4
3  5
+0 (+12.9%)
5
4  6
+0 (+12.9%)
6
4  7
+0 (+12.9%)
6
5  8
+0 (+12.9%)
7
6  9
+0 (+12.9%)
8
6  10
+0 (+12.9%)
9
7  11
+1 (+12.9%)
The graph above shows the daily increase of reported coronavirus infections in Bristol, City of in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Bromley assuming that the numbers are following an exponential trend without any slowdown.
1

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
2
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Bromley in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Buckinghamshire assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
2
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Buckinghamshire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Bury assuming that the numbers are following an exponential trend without any slowdown.
1

4
+3 (+300%)
3
+1 (+25%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Bury in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Camden of about 48.9% each day. That corresponds to a doubling of the numbers approx. every 1.7 days.
The graph above and the following table show the course of reported coronavirus infections in Camden assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
2
+0 (+0%)
4
+2 (+100%)
5
+1 (+25%)
7
+2 (+40%)
11
9  14
+4 (+58.1%)
16
13  21
+5 (+48.9%)
25
20  31
+8 (+48.9%)
37
29  46
+12 (+48.9%)
54
44  68
+18 (+48.9%)
81
65  101
+27 (+48.9%)
121
97  150
+40 (+48.9%)
180
144  224
+59 (+48.9%)
268
214  334
+88 (+48.9%)
398
319  497
+131 (+48.9%)
The graph above shows the daily increase of reported coronavirus infections in Camden in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Cornwall assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
The graph above shows the daily increase of reported coronavirus infections in Cornwall in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Cornwall and Isles of Scilly of about 25% each day. That corresponds to a doubling of the numbers approx. every 3.1 days.
The graph above and the following table show the course of reported coronavirus infections in Cornwall and Isles of Scilly assuming that the numbers are following an exponential trend without any slowdown.
2

4
+2 (+100%)
4
+0 (+0%)
5
+1 (+25%)
7
5  8
+2 (+31.3%)
8
7  10
+2 (+25%)
10
8  13
+2 (+25%)
13
10  16
+3 (+25%)
16
13  20
+3 (+25%)
20
16  24
+4 (+25%)
25
20  31
+5 (+25%)
31
26  38
+6 (+25%)
39
32  48
+8 (+25%)
49
40  60
+10 (+25%)
The graph above shows the daily increase of reported coronavirus infections in Cornwall and Isles of Scilly in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Coventry of about 4.14% each day. That corresponds to a doubling of the numbers approx. every 17 days.
The graph above and the following table show the course of reported coronavirus infections in Coventry assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
3
+2 (+200%)
2
+1 (+33.3%)
3
+1 (+50%)
3
+0 (+0%)
3
2  4
+0 (+3.95e11%)
3
2  4
+0 (+4.14%)
3
2  5
+0 (+4.14%)
3
2  5
+0 (+4.14%)
4
3  5
+0 (+4.14%)
4
3  5
+0 (+4.14%)
4
3  5
+0 (+4.14%)
4
3  6
+0 (+4.14%)
4
3  6
+0 (+4.14%)
4
3  6
+0 (+4.14%)
The graph above shows the daily increase of reported coronavirus infections in Coventry in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Cumbria of about 14.4% each day. That corresponds to a doubling of the numbers approx. every 5.2 days.
The graph above and the following table show the course of reported coronavirus infections in Cumbria assuming that the numbers are following an exponential trend without any slowdown.
0

4
+0 (+0%)
5
+1 (+25%)
5
+0 (+0%)
7
+2 (+40%)
7
+0 (+0%)
8
7  10
+1 (+18.3%)
9
8  11
+1 (+14.4%)
11
9  13
+1 (+14.4%)
12
11  14
+2 (+14.4%)
14
12  16
+2 (+14.4%)
16
14  19
+2 (+14.4%)
19
16  22
+2 (+14.4%)
21
18  25
+3 (+14.4%)
24
21  28
+3 (+14.4%)
28
24  32
+4 (+14.4%)
The graph above shows the daily increase of reported coronavirus infections in Cumbria in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Derbyshire of about 2.91e10% each day. That corresponds to a doubling of the numbers approx. every ,240,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Derbyshire assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
4
+1 (+33.3%)
4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
4
4  4
+0 (+7.28e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
The graph above shows the daily increase of reported coronavirus infections in Derbyshire in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Devon of about 3.25% each day. That corresponds to a doubling of the numbers approx. every 22 days.
The graph above and the following table show the course of reported coronavirus infections in Devon assuming that the numbers are following an exponential trend without any slowdown.
7

10
+3 (+42.9%)
12
+2 (+20%)
12
+0 (+0%)
13
+1 (+8.33%)
13
+0 (+0%)
14
13  14
+0 (+4.08%)
14
13  14
+0 (+3.25%)
14
14  15
+0 (+3.25%)
15
14  15
+0 (+3.25%)
15
15  16
+0 (+3.25%)
16
15  16
+0 (+3.25%)
16
16  17
+0 (+3.25%)
17
16  18
+0 (+3.25%)
17
17  18
+0 (+3.25%)
18
17  19
+0 (+3.25%)
The graph above shows the daily increase of reported coronavirus infections in Devon in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Ealing assuming that the numbers are following an exponential trend without any slowdown.
1

5
+4 (+400%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Ealing in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Essex of about 5.62% each day. That corresponds to a doubling of the numbers approx. every 13 days.
The graph above and the following table show the course of reported coronavirus infections in Essex assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
5
+2 (+66.7%)
5
+0 (+0%)
5
+0 (+0%)
6
+1 (+20%)
6
5  7
+0 (+1.02e10%)
6
6  7
+0 (+5.62%)
7
6  7
+0 (+5.62%)
7
6  8
+0 (+5.62%)
7
7  8
+0 (+5.62%)
8
7  9
+0 (+5.62%)
8
8  9
+0 (+5.62%)
9
8  10
+0 (+5.62%)
9
8  10
+0 (+5.62%)
10
9  11
+0 (+5.62%)
The graph above shows the daily increase of reported coronavirus infections in Essex in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Gloucestershire of about 9.01% each day. That corresponds to a doubling of the numbers approx. every 8 days.
The graph above and the following table show the course of reported coronavirus infections in Gloucestershire assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
4
+1 (+33.3%)
4
3  5
+0 (+1.25e10%)
4
4  5
+0 (+9.01%)
5
4  6
+0 (+9.01%)
5
4  6
+0 (+9.01%)
6
5  7
+0 (+9.01%)
6
5  7
+0 (+9.01%)
7
6  8
+0 (+9.01%)
7
6  9
+0 (+9.01%)
8
7  9
+0 (+9.01%)
9
7  10
+0 (+9.01%)
The graph above shows the daily increase of reported coronavirus infections in Gloucestershire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Hackney assuming that the numbers are following an exponential trend without any slowdown.
0

2
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Hackney in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Hackney and City of London of about 18.9% each day. That corresponds to a doubling of the numbers approx. every 4 days.
The graph above and the following table show the course of reported coronavirus infections in Hackney and City of London assuming that the numbers are following an exponential trend without any slowdown.
2

2
+0 (+0%)
3
+1 (+50%)
4
+1 (+33.3%)
4
3  6
+0 (+6%)
5
4  7
+0 (+18.9%)
6
5  8
+0 (+18.9%)
7
5  9
+1 (+18.9%)
8
6  11
+1 (+18.9%)
10
8  13
+2 (+18.9%)
12
9  16
+2 (+18.9%)
14
11  19
+2 (+18.9%)
17
13  23
+3 (+18.9%)
20
15  27
+3 (+18.9%)
The graph above shows the daily increase of reported coronavirus infections in Hackney and City of London in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Hammersmith and Fulham of about 12.9% each day. That corresponds to a doubling of the numbers approx. every 5.7 days.
The graph above and the following table show the course of reported coronavirus infections in Hammersmith and Fulham assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
2
+1 (+100%)
2
+0 (+0%)
2
+0 (+0%)
3
+1 (+50%)
3
2  4
+0 (+1.19e10%)
3
3  4
+0 (+12.9%)
4
3  5
+0 (+12.9%)
4
3  5
+0 (+12.9%)
5
4  6
+0 (+12.9%)
6
4  7
+0 (+12.9%)
6
5  8
+0 (+12.9%)
7
6  9
+0 (+12.9%)
8
6  10
+0 (+12.9%)
9
7  11
+1 (+12.9%)
The graph above shows the daily increase of reported coronavirus infections in Hammersmith and Fulham in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Hampshire of about 18.3% each day. That corresponds to a doubling of the numbers approx. every 4.1 days.
The graph above and the following table show the course of reported coronavirus infections in Hampshire assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
8
+6 (+300%)
8
+0 (+0%)
10
+2 (+25%)
13
+3 (+30%)
15
13  17
+2 (+11.8%)
17
15  20
+3 (+18.3%)
20
18  23
+3 (+18.3%)
24
21  28
+4 (+18.3%)
28
25  33
+4 (+18.3%)
34
29  39
+5 (+18.3%)
40
35  46
+6 (+18.3%)
47
41  54
+7 (+18.3%)
56
49  64
+9 (+18.3%)
66
57  76
+10 (+18.3%)
The graph above shows the daily increase of reported coronavirus infections in Hampshire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Havering assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
0
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Havering in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Hertfordshire of about 12.6% each day. That corresponds to a doubling of the numbers approx. every 5.9 days.
The graph above and the following table show the course of reported coronavirus infections in Hertfordshire assuming that the numbers are following an exponential trend without any slowdown.
5

8
+3 (+60%)
13
+5 (+62.5%)
13
+0 (+0%)
16
+3 (+23.1%)
18
+2 (+12.5%)
20
18  22
+2 (+10.9%)
22
21  25
+3 (+12.6%)
25
23  28
+3 (+12.6%)
28
26  31
+3 (+12.6%)
32
29  35
+4 (+12.6%)
36
33  39
+4 (+12.6%)
41
37  44
+5 (+12.6%)
46
42  50
+5 (+12.6%)
51
47  56
+6 (+12.6%)
58
53  63
+6 (+12.6%)
The graph above shows the daily increase of reported coronavirus infections in Hertfordshire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Hillingdon assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
3
+2 (+200%)
The graph above shows the daily increase of reported coronavirus infections in Hillingdon in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Hounslow of about 22.7% each day. That corresponds to a doubling of the numbers approx. every 3.4 days.
The graph above and the following table show the course of reported coronavirus infections in Hounslow assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
3
+0 (+0%)
5
+2 (+66.7%)
5
+0 (+0%)
6
5  8
+1 (+29.1%)
8
6  10
+1 (+22.7%)
10
8  12
+2 (+22.7%)
12
9  15
+2 (+22.7%)
15
12  18
+3 (+22.7%)
18
14  23
+3 (+22.7%)
22
18  28
+4 (+22.7%)
27
21  34
+5 (+22.7%)
33
26  42
+6 (+22.7%)
41
32  51
+8 (+22.7%)
The graph above shows the daily increase of reported coronavirus infections in Hounslow in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Kensington and Chelsea of about 26.8% each day. That corresponds to a doubling of the numbers approx. every 2.9 days.
The graph above and the following table show the course of reported coronavirus infections in Kensington and Chelsea assuming that the numbers are following an exponential trend without any slowdown.
1

6
+5 (+500%)
8
+2 (+33.3%)
8
+0 (+0%)
13
+5 (+62.5%)
15
+2 (+15.4%)
19
16  23
+4 (+27.5%)
24
20  30
+5 (+26.8%)
31
25  37
+6 (+26.8%)
39
32  47
+8 (+26.8%)
49
40  60
+10 (+26.8%)
63
51  76
+13 (+26.8%)
79
65  97
+17 (+26.8%)
101
82  123
+21 (+26.8%)
127
105  155
+27 (+26.8%)
162
132  197
+34 (+26.8%)
The graph above shows the daily increase of reported coronavirus infections in Kensington and Chelsea in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Kent of about 9.34% each day. That corresponds to a doubling of the numbers approx. every 7.8 days.
The graph above and the following table show the course of reported coronavirus infections in Kent assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
4
+2 (+100%)
4
+0 (+0%)
5
+1 (+25%)
5
+0 (+0%)
6
5  6
+0 (+11.8%)
6
6  7
+0 (+9.34%)
7
6  7
+0 (+9.34%)
7
7  8
+0 (+9.34%)
8
7  9
+0 (+9.34%)
9
8  10
+0 (+9.34%)
10
9  11
+0 (+9.34%)
10
9  12
+0 (+9.34%)
11
10  13
+0 (+9.34%)
12
11  14
+1 (+9.34%)
The graph above shows the daily increase of reported coronavirus infections in Kent in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Lambeth of about 20% each day. That corresponds to a doubling of the numbers approx. every 3.8 days.
The graph above and the following table show the course of reported coronavirus infections in Lambeth assuming that the numbers are following an exponential trend without any slowdown.
0

2
+0 (+0%)
3
+1 (+50%)
3
+0 (+0%)
4
+1 (+33.3%)
5
+1 (+25%)
6
5  7
+0 (+15.5%)
7
6  8
+1 (+20%)
8
7  10
+1 (+20%)
10
9  11
+2 (+20%)
12
10  14
+2 (+20%)
14
13  16
+2 (+20%)
17
15  20
+3 (+20%)
21
18  24
+3 (+20%)
25
22  28
+4 (+20%)
30
26  34
+5 (+20%)
The graph above shows the daily increase of reported coronavirus infections in Lambeth in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Lancashire of about 6.92% each day. That corresponds to a doubling of the numbers approx. every 10 days.
The graph above and the following table show the course of reported coronavirus infections in Lancashire assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
4
+2 (+100%)
4
+0 (+0%)
4
+0 (+0%)
5
+1 (+25%)
5
4  6
+0 (+7.12e10%)
5
5  6
+0 (+6.92%)
6
5  6
+0 (+6.92%)
6
5  7
+0 (+6.92%)
7
6  7
+0 (+6.92%)
7
6  8
+0 (+6.92%)
7
7  8
+0 (+6.92%)
8
7  9
+0 (+6.92%)
9
8  10
+0 (+6.92%)
9
8  10
+0 (+6.92%)
The graph above shows the daily increase of reported coronavirus infections in Lancashire in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Leeds of about 16.6% each day. That corresponds to a doubling of the numbers approx. every 4.5 days.
The graph above and the following table show the course of reported coronavirus infections in Leeds assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
5
+2 (+66.7%)
5
+0 (+0%)
5
+0 (+0%)
6
5  9
+1 (+29.1%)
8
6  10
+1 (+16.6%)
9
7  12
+1 (+16.6%)
10
8  14
+1 (+16.6%)
12
9  16
+2 (+16.6%)
14
10  18
+2 (+16.6%)
16
12  21
+2 (+16.6%)
19
14  25
+3 (+16.6%)
22
17  29
+3 (+16.6%)
26
19  34
+4 (+16.6%)
The graph above shows the daily increase of reported coronavirus infections in Leeds in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Leicestershire assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
2
+0 (+0%)
2
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Leicestershire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Lewisham assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
3
+1 (+50%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Lewisham in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Liverpool of about 12.9% each day. That corresponds to a doubling of the numbers approx. every 5.7 days.
The graph above and the following table show the course of reported coronavirus infections in Liverpool assuming that the numbers are following an exponential trend without any slowdown.
0

3
+0 (+0%)
4
+1 (+33.3%)
5
+1 (+25%)
5
+0 (+0%)
6
+1 (+20%)
7
6  7
+0 (+11.8%)
8
7  8
+0 (+12.9%)
9
8  9
+0 (+12.9%)
10
9  11
+1 (+12.9%)
11
10  12
+1 (+12.9%)
12
11  14
+1 (+12.9%)
14
13  15
+2 (+12.9%)
16
14  17
+2 (+12.9%)
18
16  19
+2 (+12.9%)
20
18  22
+2 (+12.9%)
The graph above shows the daily increase of reported coronavirus infections in Liverpool in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Luton of about 1.46e10% each day. That corresponds to a doubling of the numbers approx. every ,480,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Luton assuming that the numbers are following an exponential trend without any slowdown.
0

2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
2  2
+0 (+3.64e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
The graph above shows the daily increase of reported coronavirus infections in Luton in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Manchester assuming that the numbers are following an exponential trend without any slowdown.
1

5
+4 (+400%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
5
5  5
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Manchester in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Medway of about 1.46e10% each day. That corresponds to a doubling of the numbers approx. every ,480,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Medway assuming that the numbers are following an exponential trend without any slowdown.
0

2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
2  2
+0 (+3.64e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
The graph above shows the daily increase of reported coronavirus infections in Medway in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Milton Keynes assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
2
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Milton Keynes in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Newcastle upon Tyne of about 23.1% each day. That corresponds to a doubling of the numbers approx. every 3.3 days.
The graph above and the following table show the course of reported coronavirus infections in Newcastle upon Tyne assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
4
+1 (+33.3%)
4
+0 (+0%)
6
+2 (+50%)
7
6  8
+0 (+15.5%)
9
7  10
+2 (+23.1%)
11
9  12
+2 (+23.1%)
13
11  15
+2 (+23.1%)
16
13  19
+3 (+23.1%)
20
17  23
+4 (+23.1%)
24
20  28
+5 (+23.1%)
30
25  35
+6 (+23.1%)
37
31  43
+7 (+23.1%)
45
38  53
+8 (+23.1%)
The graph above shows the daily increase of reported coronavirus infections in Newcastle upon Tyne in the previous days.
The graph above and the following table show the course of reported coronavirus infections in North Tyneside assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
The graph above shows the daily increase of reported coronavirus infections in North Tyneside in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Northamptonshire of about 9.34% each day. That corresponds to a doubling of the numbers approx. every 7.8 days.
The graph above and the following table show the course of reported coronavirus infections in Northamptonshire assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
4
+2 (+100%)
4
+0 (+0%)
5
+1 (+25%)
5
+0 (+0%)
6
5  6
+0 (+11.8%)
6
6  7
+0 (+9.34%)
7
6  7
+0 (+9.34%)
7
7  8
+0 (+9.34%)
8
7  9
+0 (+9.34%)
9
8  10
+0 (+9.34%)
10
9  11
+0 (+9.34%)
10
9  12
+0 (+9.34%)
11
10  13
+0 (+9.34%)
12
11  14
+1 (+9.34%)
The graph above shows the daily increase of reported coronavirus infections in Northamptonshire in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Nottingham of about 12.9% each day. That corresponds to a doubling of the numbers approx. every 5.7 days.
The graph above and the following table show the course of reported coronavirus infections in Nottingham assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
3
+1 (+50%)
3
2  4
+0 (+1.19e10%)
3
3  4
+0 (+12.9%)
4
3  5
+0 (+12.9%)
4
3  5
+0 (+12.9%)
5
4  6
+0 (+12.9%)
6
4  7
+0 (+12.9%)
6
5  8
+0 (+12.9%)
7
6  9
+0 (+12.9%)
8
6  10
+0 (+12.9%)
9
7  11
+1 (+12.9%)
The graph above shows the daily increase of reported coronavirus infections in Nottingham in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Nottinghamshire of about 23.1% each day. That corresponds to a doubling of the numbers approx. every 3.3 days.
The graph above and the following table show the course of reported coronavirus infections in Nottinghamshire assuming that the numbers are following an exponential trend without any slowdown.
0

3
+0 (+0%)
3
+0 (+0%)
5
+2 (+66.7%)
5
+0 (+0%)
6
+1 (+20%)
8
6  10
+2 (+29.1%)
10
8  12
+2 (+23.1%)
12
9  15
+2 (+23.1%)
14
12  18
+3 (+23.1%)
18
14  22
+3 (+23.1%)
22
17  27
+4 (+23.1%)
27
22  34
+5 (+23.1%)
33
26  42
+6 (+23.1%)
41
33  51
+8 (+23.1%)
50
40  63
+9 (+23.1%)
The graph above shows the daily increase of reported coronavirus infections in Nottinghamshire in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Oldham of about 23.1% each day. That corresponds to a doubling of the numbers approx. every 3.3 days.
The graph above and the following table show the course of reported coronavirus infections in Oldham assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
2
+0 (+0%)
4
+2 (+100%)
4
+0 (+0%)
4
+0 (+0%)
6
4  8
+2 (+41.4%)
7
5  10
+1 (+23.1%)
9
6  13
+2 (+23.1%)
11
7  15
+2 (+23.1%)
13
9  19
+2 (+23.1%)
16
11  23
+3 (+23.1%)
20
13  29
+4 (+23.1%)
24
17  35
+5 (+23.1%)
30
20  44
+6 (+23.1%)
37
25  54
+7 (+23.1%)
The graph above shows the daily increase of reported coronavirus infections in Oldham in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Oxfordshire of about 23.4% each day. That corresponds to a doubling of the numbers approx. every 3.3 days.
The graph above and the following table show the course of reported coronavirus infections in Oxfordshire assuming that the numbers are following an exponential trend without any slowdown.
1

4
+3 (+300%)
5
+1 (+25%)
5
+0 (+0%)
7
+2 (+40%)
9
+2 (+28.6%)
11
9  12
+2 (+18.3%)
13
11  15
+2 (+23.4%)
16
14  19
+3 (+23.4%)
20
17  23
+4 (+23.4%)
25
21  29
+5 (+23.4%)
30
26  36
+6 (+23.4%)
38
32  44
+7 (+23.4%)
46
40  54
+9 (+23.4%)
57
49  67
+11 (+23.4%)
70
60  82
+13 (+23.4%)
The graph above shows the daily increase of reported coronavirus infections in Oxfordshire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Shropshire assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
The graph above shows the daily increase of reported coronavirus infections in Shropshire in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Southwark of about 45.7% each day. That corresponds to a doubling of the numbers approx. every 1.8 days.
The graph above and the following table show the course of reported coronavirus infections in Southwark assuming that the numbers are following an exponential trend without any slowdown.
1

1
+0 (+0%)
3
+2 (+200%)
5
+2 (+66.7%)
8
+3 (+60%)
9
+1 (+12.5%)
15
12  18
+6 (+63.3%)
21
17  26
+7 (+45.7%)
31
25  38
+10 (+45.7%)
45
37  56
+14 (+45.7%)
66
54  82
+21 (+45.7%)
97
78  119
+30 (+45.7%)
141
114  173
+44 (+45.7%)
205
167  253
+64 (+45.7%)
299
243  368
+94 (+45.7%)
436
354  537
+137 (+45.7%)
The graph above shows the daily increase of reported coronavirus infections in Southwark in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Staffordshire of about 2.91e10% each day. That corresponds to a doubling of the numbers approx. every ,240,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Staffordshire assuming that the numbers are following an exponential trend without any slowdown.
1

4
+3 (+300%)
4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
4
4  4
+0 (+7.28e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
The graph above shows the daily increase of reported coronavirus infections in Staffordshire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in StocktononTees assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
2
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in StocktononTees in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Surrey of about 23.1% each day. That corresponds to a doubling of the numbers approx. every 3.3 days.
The graph above and the following table show the course of reported coronavirus infections in Surrey assuming that the numbers are following an exponential trend without any slowdown.
1

4
+3 (+300%)
5
+1 (+25%)
6
+1 (+20%)
6
+0 (+0%)
10
+4 (+66.7%)
11
9  14
+0 (+9.54%)
13
11  17
+3 (+23.1%)
17
13  21
+3 (+23.1%)
20
16  26
+4 (+23.1%)
25
20  32
+5 (+23.1%)
31
25  39
+6 (+23.1%)
38
30  48
+7 (+23.1%)
47
37  59
+9 (+23.1%)
58
46  72
+11 (+23.1%)
71
57  89
+13 (+23.1%)
The graph above shows the daily increase of reported coronavirus infections in Surrey in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Sutton assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
0
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
4
+2 (+100%)
The graph above shows the daily increase of reported coronavirus infections in Sutton in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Swindon of about 1.46e10% each day. That corresponds to a doubling of the numbers approx. every ,480,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Swindon assuming that the numbers are following an exponential trend without any slowdown.
0

1
+0 (+0%)
2
+1 (+100%)
2
+0 (+0%)
2
+0 (+0%)
2
+0 (+0%)
2
2  2
+0 (+3.64e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
2
2  2
+0 (+1.46e10%)
The graph above shows the daily increase of reported coronavirus infections in Swindon in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Torbay of about 4.73% each day. That corresponds to a doubling of the numbers approx. every 15 days.
The graph above and the following table show the course of reported coronavirus infections in Torbay assuming that the numbers are following an exponential trend without any slowdown.
1

4
+3 (+300%)
6
+2 (+50%)
7
+1 (+16.7%)
7
+0 (+0%)
7
+0 (+0%)
8
7  8
+0 (+8.01%)
8
7  9
+0 (+4.73%)
8
8  9
+0 (+4.73%)
9
8  9
+0 (+4.73%)
9
8  10
+0 (+4.73%)
10
9  10
+0 (+4.73%)
10
9  11
+0 (+4.73%)
10
10  11
+0 (+4.73%)
11
10  12
+0 (+4.73%)
11
11  12
+0 (+4.73%)
The graph above shows the daily increase of reported coronavirus infections in Torbay in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Tower Hamlets assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
4
+3 (+300%)
4
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Tower Hamlets in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Trafford of about 2.91e10% each day. That corresponds to a doubling of the numbers approx. every ,240,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Trafford assuming that the numbers are following an exponential trend without any slowdown.
1

4
+3 (+300%)
4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
4
4  4
+0 (+7.28e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
4
4  4
+0 (+2.91e10%)
The graph above shows the daily increase of reported coronavirus infections in Trafford in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Wandsworth assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
3
+1 (+50%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Wandsworth in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Warwickshire of about 9.01% each day. That corresponds to a doubling of the numbers approx. every 8 days.
The graph above and the following table show the course of reported coronavirus infections in Warwickshire assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
3
+0 (+0%)
4
+1 (+33.3%)
4
+0 (+0%)
4
+0 (+0%)
5
4  5
+0 (+15.5%)
5
4  6
+0 (+9.01%)
5
5  6
+0 (+9.01%)
6
5  7
+0 (+9.01%)
7
6  8
+0 (+9.01%)
7
6  8
+0 (+9.01%)
8
7  9
+0 (+9.01%)
8
7  10
+0 (+9.01%)
9
8  11
+0 (+9.01%)
10
9  12
+0 (+9.01%)
The graph above shows the daily increase of reported coronavirus infections in Warwickshire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in West Sussex assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in West Sussex in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Westminster of about 29.6% each day. That corresponds to a doubling of the numbers approx. every 2.7 days.
The graph above and the following table show the course of reported coronavirus infections in Westminster assuming that the numbers are following an exponential trend without any slowdown.
0

2
+0 (+0%)
3
+1 (+50%)
3
+0 (+0%)
5
+2 (+66.7%)
6
+1 (+20%)
8
6  10
+2 (+29.1%)
10
8  12
+2 (+29.6%)
13
11  16
+3 (+29.6%)
17
14  21
+4 (+29.6%)
22
18  27
+5 (+29.6%)
28
23  35
+6 (+29.6%)
37
30  45
+8 (+29.6%)
47
39  58
+11 (+29.6%)
62
50  76
+14 (+29.6%)
80
65  98
+18 (+29.6%)
The graph above shows the daily increase of reported coronavirus infections in Westminster in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Wigan assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Wigan in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Wiltshire of about 12.2% each day. That corresponds to a doubling of the numbers approx. every 6 days.
The graph above and the following table show the course of reported coronavirus infections in Wiltshire assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
3
+0 (+0%)
4
+1 (+33.3%)
4
+0 (+0%)
5
4  5
+0 (+15.5%)
5
5  6
+0 (+12.2%)
6
5  7
+0 (+12.2%)
7
6  7
+0 (+12.2%)
7
6  8
+0 (+12.2%)
8
7  9
+0 (+12.2%)
9
8  10
+1 (+12.2%)
10
9  12
+1 (+12.2%)
12
10  13
+1 (+12.2%)
13
11  15
+1 (+12.2%)
The graph above shows the daily increase of reported coronavirus infections in Wiltshire in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Wirral assuming that the numbers are following an exponential trend without any slowdown.
1

1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
1
+0 (+0%)
2
+1 (+100%)
The graph above shows the daily increase of reported coronavirus infections in Wirral in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Wokingham assuming that the numbers are following an exponential trend without any slowdown.
1

2
+1 (+100%)
3
+1 (+50%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in Wokingham in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Wolverhampton assuming that the numbers are following an exponential trend without any slowdown.
0

0
+0 (+0%)
0
+0 (+0%)
2
+0 (+0%)
3
+1 (+50%)
4
+1 (+33.3%)
The graph above shows the daily increase of reported coronavirus infections in Wolverhampton in the previous days.
The graph above and the following table show the course of reported coronavirus infections in York assuming that the numbers are following an exponential trend without any slowdown.
1

3
+2 (+200%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
3  3
+0 (+1.11e14%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
3
3  3
+0 (+0%)
The graph above shows the daily increase of reported coronavirus infections in York in the previous days.
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