Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in France of about 0.271% each day. That corresponds to a doubling of the numbers approx. every 260 days.
The graph above and the following table show the course of reported coronavirus infections in France assuming that the numbers are following an exponential trend without any slowdown.
135,000

147,000
+12,500 (+9.29%)
149,000
+2,040 (+1.39%)
149,000
+19 (+0.0127%)
154,000
+4,950 (+3.32%)
156,000
+2,380 (+1.55%)
159,000
+2,820 (+1.8%)
157,000
+2,170 (+1.36%)
159,000
+2,340 (+1.49%)
160,000
+492 (+0.309%)
160,000
158,000  162,000
+82 (+0.0511%)
160,000
159,000  162,000
+434 (+0.271%)
161,000
159,000  163,000
+435 (+0.271%)
161,000
159,000  163,000
+436 (+0.271%)
162,000
160,000  164,000
+437 (+0.271%)
162,000
160,000  164,000
+438 (+0.271%)
163,000
161,000  165,000
+440 (+0.271%)
163,000
161,000  165,000
+441 (+0.271%)
164,000
162,000  166,000
+442 (+0.271%)
164,000
162,000  166,000
+443 (+0.271%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in France of about 2.28% each day. That corresponds to a doubling of the numbers approx. every 31 days.
The graph above and the following table show the course of reported deaths by coronavirus in France assuming that the numbers are following an exponential trend without any slowdown.
17,200

17,900
+753 (+4.38%)
18,700
+762 (+4.25%)
19,300
+642 (+3.43%)
19,700
+399 (+2.06%)
20,300
+548 (+2.78%)
20,800
+537 (+2.65%)
21,400
+544 (+2.61%)
21,900
+516 (+2.41%)
22,300
+390 (+1.78%)
22,800
22,700  22,900
+560 (+2.51%)
23,400
23,300  23,500
+521 (+2.28%)
23,900
23,800  24,000
+533 (+2.28%)
24,400
24,300  24,500
+546 (+2.28%)
25,000
24,900  25,100
+558 (+2.28%)
25,600
25,500  25,700
+571 (+2.28%)
26,200
26,000  26,300
+584 (+2.28%)
26,700
26,600  26,900
+597 (+2.28%)
27,400
27,200  27,500
+611 (+2.28%)
28,000
27,900  28,100
+625 (+2.28%)
In France, approx. 0.93% of the population die each year. With a population of roughly 67,000,000 people in France, 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 France would be approx. 15%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in France in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in France in the previous days.
The graph tries to predict the number of required intensive care units in France. We assume the following:
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in AuvergneRhôneAlpes of about 9.75% each day. That corresponds to a doubling of the numbers approx. every 7.5 days.
The graph above and the following table show the course of reported coronavirus infections in AuvergneRhôneAlpes assuming that the numbers are following an exponential trend without any slowdown.
710

858
+148 (+20.8%)
1,010
+156 (+18.2%)
1,100
+87 (+8.58%)
1,270
+165 (+15%)
1,430
+165 (+13%)
1,730
+299 (+20.9%)
1,730
+0 (+0%)
1,860
+127 (+7.34%)
2,090
+236 (+12.7%)
2,280
2,230  2,320
+184 (+8.78%)
2,500
2,450  2,550
+222 (+9.75%)
2,740
2,690  2,800
+244 (+9.75%)
3,010
2,950  3,070
+267 (+9.75%)
3,300
3,230  3,370
+293 (+9.75%)
3,620
3,550  3,700
+322 (+9.75%)
3,980
3,900  4,060
+353 (+9.75%)
4,370
4,280  4,460
+388 (+9.75%)
4,790
4,690  4,890
+426 (+9.75%)
5,260
5,150  5,370
+467 (+9.75%)
The graph above shows the daily increase of reported coronavirus infections in AuvergneRhôneAlpes in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in BourgogneFrancheComté of about 8.3% each day. That corresponds to a doubling of the numbers approx. every 8.7 days.
The graph above and the following table show the course of reported coronavirus infections in BourgogneFrancheComté assuming that the numbers are following an exponential trend without any slowdown.
549

593
+44 (+8.01%)
696
+103 (+17.4%)
770
+74 (+10.6%)
903
+133 (+17.3%)
1,180
+275 (+30.5%)
1,350
+169 (+14.3%)
1,350
+0 (+0%)
1,510
+163 (+12.1%)
1,570
+59 (+3.91%)
1,720
1,670  1,780
+154 (+9.8%)
1,870
1,810  1,930
+143 (+8.3%)
2,020
1,960  2,090
+155 (+8.3%)
2,190
2,120  2,260
+168 (+8.3%)
2,370
2,290  2,450
+182 (+8.3%)
2,570
2,480  2,650
+197 (+8.3%)
2,780
2,690  2,870
+213 (+8.3%)
3,010
2,910  3,110
+231 (+8.3%)
3,260
3,160  3,370
+250 (+8.3%)
3,530
3,420  3,650
+271 (+8.3%)
The graph above shows the daily increase of reported coronavirus infections in BourgogneFrancheComté in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Bretagne of about 10.6% each day. That corresponds to a doubling of the numbers approx. every 6.9 days.
The graph above and the following table show the course of reported coronavirus infections in Bretagne assuming that the numbers are following an exponential trend without any slowdown.
247

273
+26 (+10.5%)
297
+24 (+8.79%)
346
+49 (+16.5%)
359
+13 (+3.76%)
397
+38 (+10.6%)
490
+93 (+23.4%)
490
+0 (+0%)
526
+36 (+7.35%)
603
+77 (+14.6%)
659
641  678
+56 (+9.29%)
729
709  750
+70 (+10.6%)
806
784  829
+77 (+10.6%)
892
867  917
+85 (+10.6%)
986
959  1,010
+95 (+10.6%)
1,090
1,060  1,120
+105 (+10.6%)
1,210
1,170  1,240
+116 (+10.6%)
1,330
1,300  1,370
+128 (+10.6%)
1,480
1,430  1,520
+141 (+10.6%)
1,630
1,590  1,680
+156 (+10.6%)
The graph above shows the daily increase of reported coronavirus infections in Bretagne in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in CentreVal de Loire of about 24.7% 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 CentreVal de Loire assuming that the numbers are following an exponential trend without any slowdown.
103

128
+25 (+24.3%)
157
+29 (+22.7%)
219
+62 (+39.5%)
254
+35 (+16%)
291
+37 (+14.6%)
361
+70 (+24.1%)
361
+0 (+0%)
450
+89 (+24.7%)
561
+111 (+24.7%)
699
699  699
+138 (+24.7%)
872
872  872
+172 (+24.7%)
1,090
1,090  1,090
+215 (+24.7%)
1,350
1,350  1,350
+268 (+24.7%)
1,690
1,690  1,690
+334 (+24.7%)
2,110
2,110  2,110
+416 (+24.7%)
2,620
2,620  2,620
+519 (+24.7%)
3,270
3,270  3,270
+647 (+24.7%)
4,080
4,080  4,080
+807 (+24.7%)
5,080
5,080  5,080
+1,010 (+24.7%)
The graph above shows the daily increase of reported coronavirus infections in CentreVal de Loire in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Corse of about 8.07% each day. That corresponds to a doubling of the numbers approx. every 8.9 days.
The graph above and the following table show the course of reported coronavirus infections in Corse assuming that the numbers are following an exponential trend without any slowdown.
145

152
+7 (+4.83%)
162
+10 (+6.58%)
168
+6 (+3.7%)
173
+5 (+2.98%)
183
+10 (+5.78%)
194
+11 (+6.01%)
194
+0 (+0%)
217
+23 (+11.9%)
225
+8 (+3.69%)
247
239  255
+22 (+9.57%)
266
258  275
+20 (+8.07%)
288
279  297
+21 (+8.07%)
311
301  321
+23 (+8.07%)
336
326  347
+25 (+8.07%)
363
352  375
+27 (+8.07%)
393
380  406
+29 (+8.07%)
424
411  438
+32 (+8.07%)
459
444  474
+34 (+8.07%)
496
480  512
+37 (+8.07%)
The graph above shows the daily increase of reported coronavirus infections in Corse in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Grand Est of about 13.7% each day. That corresponds to a doubling of the numbers approx. every 5.4 days.
The graph above and the following table show the course of reported coronavirus infections in Grand Est assuming that the numbers are following an exponential trend without any slowdown.
1,820

2,160
+343 (+18.8%)
2,640
+480 (+22.2%)
3,010
+363 (+13.7%)
3,090
+83 (+2.76%)
3,400
+306 (+9.91%)
4,260
+861 (+25.4%)
4,260
+0 (+0%)
4,920
+666 (+15.6%)
5,480
+557 (+11.3%)
6,270
6,170  6,370
+792 (+14.5%)
7,130
7,010  7,240
+857 (+13.7%)
8,100
7,970  8,230
+974 (+13.7%)
9,210
9,060  9,360
+1,110 (+13.7%)
10,500
10,300  10,600
+1,260 (+13.7%)
11,900
11,700  12,100
+1,430 (+13.7%)
13,500
13,300  13,700
+1,620 (+13.7%)
15,400
15,100  15,600
+1,850 (+13.7%)
17,500
17,200  17,800
+2,100 (+13.7%)
19,800
19,500  20,200
+2,390 (+13.7%)
The graph above shows the daily increase of reported coronavirus infections in Grand Est in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Guadeloupe of about 11.3% each day. That corresponds to a doubling of the numbers approx. every 6.5 days.
The graph above and the following table show the course of reported coronavirus infections in Guadeloupe assuming that the numbers are following an exponential trend without any slowdown.
27

33
+6 (+22.2%)
45
+12 (+36.4%)
51
+6 (+13.3%)
56
+5 (+9.8%)
58
+2 (+3.57%)
62
+4 (+6.9%)
62
+0 (+0%)
73
+11 (+17.7%)
76
+3 (+4.11%)
87
82  91
+11 (+13.9%)
96
91  102
+10 (+11.3%)
107
102  113
+11 (+11.3%)
119
113  126
+12 (+11.3%)
133
126  140
+14 (+11.3%)
148
140  156
+15 (+11.3%)
165
156  174
+17 (+11.3%)
184
174  193
+19 (+11.3%)
204
194  215
+21 (+11.3%)
227
216  240
+23 (+11.3%)
The graph above shows the daily increase of reported coronavirus infections in Guadeloupe in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Guyane of about 18% each day. That corresponds to a doubling of the numbers approx. every 4.2 days.
The graph above and the following table show the course of reported coronavirus infections in Guyane assuming that the numbers are following an exponential trend without any slowdown.
11

11
+0 (+0%)
15
+4 (+36.4%)
15
+0 (+0%)
18
+3 (+20%)
19
+1 (+5.56%)
20
+1 (+5.26%)
20
+0 (+0%)
23
+3 (+15%)
28
+5 (+21.7%)
33
32  34
+5 (+16.8%)
39
38  40
+6 (+18%)
46
44  47
+7 (+18%)
54
52  55
+8 (+18%)
63
62  65
+10 (+18%)
75
73  77
+11 (+18%)
88
86  91
+13 (+18%)
104
102  107
+16 (+18%)
123
120  126
+19 (+18%)
145
142  149
+22 (+18%)
The graph above shows the daily increase of reported coronavirus infections in Guyane in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in HautsdeFrance of about 17.8% each day. That corresponds to a doubling of the numbers approx. every 4.2 days.
The graph above and the following table show the course of reported coronavirus infections in HautsdeFrance assuming that the numbers are following an exponential trend without any slowdown.
612

665
+53 (+8.66%)
700
+35 (+5.26%)
759
+59 (+8.43%)
791
+32 (+4.22%)
936
+145 (+18.3%)
1,270
+333 (+35.6%)
1,270
+0 (+0%)
1,530
+263 (+20.7%)
1,750
+221 (+14.4%)
2,090
2,040  2,130
+333 (+19%)
2,460
2,400  2,510
+372 (+17.8%)
2,900
2,830  2,960
+438 (+17.8%)
3,410
3,330  3,490
+516 (+17.8%)
4,020
3,930  4,110
+608 (+17.8%)
4,740
4,630  4,840
+716 (+17.8%)
5,580
5,450  5,710
+844 (+17.8%)
6,570
6,420  6,720
+994 (+17.8%)
7,740
7,570  7,920
+1,170 (+17.8%)
9,120
8,920  9,340
+1,380 (+17.8%)
The graph above shows the daily increase of reported coronavirus infections in HautsdeFrance in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in IledeFrance of about 10.9% each day. That corresponds to a doubling of the numbers approx. every 6.7 days.
The graph above and the following table show the course of reported coronavirus infections in IledeFrance assuming that the numbers are following an exponential trend without any slowdown.
2,180

2,690
+516 (+23.7%)
3,380
+691 (+25.7%)
3,820
+434 (+12.8%)
4,700
+877 (+23%)
5,280
+588 (+12.5%)
6,210
+928 (+17.6%)
6,210
+0 (+0%)
6,800
+587 (+9.45%)
7,660
+862 (+12.7%)
8,450
8,350  8,560
+791 (+10.3%)
9,370
9,260  9,490
+922 (+10.9%)
10,400
10,300  10,500
+1,020 (+10.9%)
11,500
11,400  11,700
+1,130 (+10.9%)
12,800
12,600  12,900
+1,260 (+10.9%)
14,200
14,000  14,400
+1,390 (+10.9%)
15,700
15,500  15,900
+1,550 (+10.9%)
17,400
17,200  17,700
+1,720 (+10.9%)
19,300
19,100  19,600
+1,900 (+10.9%)
21,500
21,200  21,700
+2,110 (+10.9%)
The graph above shows the daily increase of reported coronavirus infections in IledeFrance in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in La Réunion of about 15.2% each day. That corresponds to a doubling of the numbers approx. every 4.9 days.
The graph above and the following table show the course of reported coronavirus infections in La Réunion assuming that the numbers are following an exponential trend without any slowdown.
12

14
+2 (+16.7%)
19
+5 (+35.7%)
38
+19 (+100%)
47
+9 (+23.7%)
64
+17 (+36.2%)
71
+7 (+10.9%)
71
+0 (+0%)
83
+12 (+16.9%)
94
+11 (+13.3%)
109
107  110
+15 (+15.9%)
126
124  127
+17 (+15.2%)
145
143  147
+19 (+15.2%)
167
164  169
+22 (+15.2%)
192
189  195
+25 (+15.2%)
221
218  224
+29 (+15.2%)
255
252  258
+34 (+15.2%)
294
290  298
+39 (+15.2%)
339
334  343
+45 (+15.2%)
390
385  395
+52 (+15.2%)
The graph above shows the daily increase of reported coronavirus infections in La Réunion in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Martinique of about 11.2% each day. That corresponds to a doubling of the numbers approx. every 6.5 days.
The graph above and the following table show the course of reported coronavirus infections in Martinique assuming that the numbers are following an exponential trend without any slowdown.
19

23
+4 (+21.1%)
32
+9 (+39.1%)
32
+0 (+0%)
37
+5 (+15.6%)
44
+7 (+18.9%)
53
+9 (+20.5%)
53
+0 (+0%)
57
+4 (+7.55%)
66
+9 (+15.8%)
72
70  75
+6 (+9.74%)
81
78  83
+8 (+11.2%)
90
87  92
+9 (+11.2%)
100
97  103
+10 (+11.2%)
111
107  114
+11 (+11.2%)
123
119  127
+12 (+11.2%)
137
133  141
+14 (+11.2%)
152
148  157
+15 (+11.2%)
170
164  175
+17 (+11.2%)
189
183  195
+19 (+11.2%)
The graph above shows the daily increase of reported coronavirus infections in Martinique in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Mayotte of about 21.1% each day. That corresponds to a doubling of the numbers approx. every 3.6 days.
The graph above and the following table show the course of reported coronavirus infections in Mayotte assuming that the numbers are following an exponential trend without any slowdown.
3

3
+0 (+0%)
6
+3 (+100%)
7
+1 (+16.7%)
11
+4 (+57.1%)
14
+3 (+27.3%)
24
+10 (+71.4%)
24
+0 (+0%)
30
+6 (+25%)
35
+5 (+16.7%)
43
42  44
+8 (+22.7%)
52
51  54
+9 (+21.1%)
63
61  65
+11 (+21.1%)
76
74  79
+13 (+21.1%)
92
90  95
+16 (+21.1%)
112
109  115
+20 (+21.1%)
136
132  140
+24 (+21.1%)
164
160  169
+29 (+21.1%)
199
193  205
+35 (+21.1%)
241
234  248
+42 (+21.1%)
The graph above shows the daily increase of reported coronavirus infections in Mayotte in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Metropolis of about 12.7% each day. That corresponds to a doubling of the numbers approx. every 5.8 days.
The graph above and the following table show the course of reported coronavirus infections in Metropolis assuming that the numbers are following an exponential trend without any slowdown.
7,650

9,040
+1,390 (+18.2%)
10,900
+1,830 (+20.2%)
12,500
+1,590 (+14.6%)
14,300
+1,820 (+14.6%)
16,500
+2,200 (+15.4%)
19,600
+3,130 (+19%)
19,600
+0 (+0%)
22,000
+2,410 (+12.3%)
24,900
+2,900 (+13.1%)
28,000
27,900  28,100
+3,120 (+12.5%)
31,600
31,500  31,700
+3,550 (+12.7%)
35,600
35,500  35,700
+4,000 (+12.7%)
40,100
40,000  40,200
+4,510 (+12.7%)
45,200
45,000  45,300
+5,080 (+12.7%)
50,900
50,800  51,100
+5,730 (+12.7%)
57,400
57,200  57,600
+6,450 (+12.7%)
64,700
64,400  64,900
+7,270 (+12.7%)
72,800
72,600  73,100
+8,200 (+12.7%)
82,100
81,800  82,300
+9,230 (+12.7%)
The graph above shows the daily increase of reported coronavirus infections in Metropolis in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Normandie of about 15.9% each day. That corresponds to a doubling of the numbers approx. every 4.7 days.
The graph above and the following table show the course of reported coronavirus infections in Normandie assuming that the numbers are following an exponential trend without any slowdown.
174

208
+34 (+19.5%)
241
+33 (+15.9%)
287
+46 (+19.1%)
345
+58 (+20.2%)
462
+117 (+33.9%)
511
+49 (+10.6%)
511
+0 (+0%)
586
+75 (+14.7%)
688
+102 (+17.4%)
794
786  802
+106 (+15.4%)
920
911  930
+126 (+15.9%)
1,070
1,060  1,080
+146 (+15.9%)
1,240
1,220  1,250
+170 (+15.9%)
1,430
1,420  1,450
+197 (+15.9%)
1,660
1,640  1,680
+228 (+15.9%)
1,930
1,910  1,950
+264 (+15.9%)
2,230
2,210  2,250
+306 (+15.9%)
2,590
2,560  2,610
+355 (+15.9%)
3,000
2,970  3,030
+412 (+15.9%)
The graph above shows the daily increase of reported coronavirus infections in Normandie in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in NouvelleAquitaine of about 16.2% each day. That corresponds to a doubling of the numbers approx. every 4.6 days.
The graph above and the following table show the course of reported coronavirus infections in NouvelleAquitaine assuming that the numbers are following an exponential trend without any slowdown.
200

237
+37 (+18.5%)
280
+43 (+18.1%)
432
+152 (+54.3%)
521
+89 (+20.6%)
612
+91 (+17.5%)
676
+64 (+10.5%)
676
+0 (+0%)
789
+113 (+16.7%)
912
+123 (+15.6%)
1,060
1,060  1,070
+150 (+16.4%)
1,230
1,230  1,240
+172 (+16.2%)
1,430
1,430  1,440
+200 (+16.2%)
1,670
1,660  1,670
+232 (+16.2%)
1,940
1,930  1,940
+270 (+16.2%)
2,250
2,240  2,260
+314 (+16.2%)
2,610
2,600  2,620
+364 (+16.2%)
3,040
3,020  3,050
+423 (+16.2%)
3,530
3,510  3,540
+492 (+16.2%)
4,100
4,080  4,120
+572 (+16.2%)
The graph above shows the daily increase of reported coronavirus infections in NouvelleAquitaine in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Occitanie of about 18.6% 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 Occitanie assuming that the numbers are following an exponential trend without any slowdown.
311

371
+60 (+19.3%)
444
+73 (+19.7%)
537
+93 (+20.9%)
611
+74 (+13.8%)
671
+60 (+9.82%)
767
+96 (+14.3%)
767
+0 (+0%)
900
+133 (+17.3%)
1,080
+182 (+20.2%)
1,280
1,260  1,290
+196 (+18.1%)
1,520
1,500  1,530
+238 (+18.6%)
1,800
1,780  1,820
+283 (+18.6%)
2,130
2,110  2,160
+335 (+18.6%)
2,530
2,510  2,560
+398 (+18.6%)
3,000
2,970  3,040
+472 (+18.6%)
3,560
3,530  3,600
+560 (+18.6%)
4,230
4,190  4,270
+664 (+18.6%)
5,020
4,970  5,070
+788 (+18.6%)
5,950
5,890  6,010
+935 (+18.6%)
The graph above shows the daily increase of reported coronavirus infections in Occitanie in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Oversea of about 14.1% each day. That corresponds to a doubling of the numbers approx. every 5.3 days.
The graph above and the following table show the course of reported coronavirus infections in Oversea assuming that the numbers are following an exponential trend without any slowdown.
78

91
+13 (+16.7%)
124
+33 (+36.3%)
153
+29 (+23.4%)
177
+24 (+15.7%)
208
+31 (+17.5%)
241
+33 (+15.9%)
241
+0 (+0%)
277
+36 (+14.9%)
313
+36 (+13%)
358
355  361
+45 (+14.4%)
408
405  411
+50 (+14.1%)
466
462  469
+57 (+14.1%)
531
527  535
+65 (+14.1%)
606
601  610
+75 (+14.1%)
691
686  696
+85 (+14.1%)
788
782  794
+97 (+14.1%)
899
892  905
+111 (+14.1%)
1,030
1,020  1,030
+126 (+14.1%)
1,170
1,160  1,180
+144 (+14.1%)
The graph above shows the daily increase of reported coronavirus infections in Oversea in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Pays de la Loire of about 12.5% 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 Pays de la Loire assuming that the numbers are following an exponential trend without any slowdown.
126

128
+2 (+1.59%)
160
+32 (+25%)
190
+30 (+18.8%)
234
+44 (+23.2%)
270
+36 (+15.4%)
293
+23 (+8.52%)
293
+0 (+0%)
343
+50 (+17.1%)
368
+25 (+7.29%)
421
405  437
+53 (+14.3%)
473
456  491
+53 (+12.5%)
533
513  553
+59 (+12.5%)
599
577  622
+67 (+12.5%)
674
650  700
+75 (+12.5%)
759
731  787
+84 (+12.5%)
854
822  886
+95 (+12.5%)
960
925  997
+107 (+12.5%)
1,080
1,040  1,120
+120 (+12.5%)
1,220
1,170  1,260
+135 (+12.5%)
The graph above shows the daily increase of reported coronavirus infections in Pays de la Loire in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in ProvenceAlpesCôte d’Azur of about 12.3% 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 ProvenceAlpesCôte d’Azur assuming that the numbers are following an exponential trend without any slowdown.
478

574
+96 (+20.1%)
693
+119 (+20.7%)
826
+133 (+19.2%)
1,040
+215 (+26%)
1,370
+331 (+31.8%)
1,510
+138 (+10.1%)
1,510
+0 (+0%)
1,600
+85 (+5.63%)
1,930
+332 (+20.8%)
2,110
1,990  2,240
+184 (+9.57%)
2,370
2,240  2,510
+259 (+12.3%)
2,660
2,510  2,820
+291 (+12.3%)
2,990
2,820  3,160
+327 (+12.3%)
3,360
3,170  3,550
+367 (+12.3%)
3,770
3,560  3,990
+412 (+12.3%)
4,230
3,990  4,480
+463 (+12.3%)
4,750
4,490  5,030
+519 (+12.3%)
5,330
5,040  5,650
+583 (+12.3%)
5,990
5,650  6,340
+655 (+12.3%)
The graph above shows the daily increase of reported coronavirus infections in ProvenceAlpesCôte d’Azur in the previous days.
The graph above and the following table show the course of reported coronavirus infections in SaintBarthélémy assuming that the numbers are following an exponential trend without any slowdown.
3

3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
3
+0 (+0%)
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 SaintBarthélémy in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in SaintMartin of about 15.6% each day. That corresponds to a doubling of the numbers approx. every 4.8 days.
The graph above and the following table show the course of reported coronavirus infections in SaintMartin assuming that the numbers are following an exponential trend without any slowdown.
3

4
+1 (+33.3%)
4
+0 (+0%)
4
+0 (+0%)
5
+1 (+25%)
6
+1 (+20%)
8
+2 (+33.3%)
8
+0 (+0%)
8
+0 (+0%)
11
+3 (+37.5%)
12
10  14
+0 (+9.07%)
14
12  16
+2 (+15.6%)
16
14  18
+2 (+15.6%)
19
16  21
+2 (+15.6%)
21
19  25
+3 (+15.6%)
25
22  28
+3 (+15.6%)
29
25  33
+4 (+15.6%)
33
29  38
+4 (+15.6%)
38
33  44
+5 (+15.6%)
44
39  51
+6 (+15.6%)
The graph above shows the daily increase of reported coronavirus infections in SaintMartin in the previous days.
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