Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Canada of about 3.81% each day. That corresponds to a doubling of the numbers approx. every 19 days.
The graph above and the following table show the course of reported coronavirus infections in Canada assuming that the numbers are following an exponential trend without any slowdown.
28,200

30,800
+2,600 (+9.22%)
32,800
+2,010 (+6.51%)
34,400
+1,540 (+4.7%)
35,600
+1,280 (+3.72%)
37,700
+2,030 (+5.68%)
39,400
+1,740 (+4.63%)
41,700
+2,250 (+5.71%)
43,300
+1,640 (+3.93%)
44,100
+770 (+1.78%)
46,200
45,300  47,100
+2,120 (+4.81%)
47,900
47,000  48,900
+1,760 (+3.81%)
49,800
48,800  50,700
+1,820 (+3.81%)
51,700
50,700  52,600
+1,890 (+3.81%)
53,600
52,600  54,600
+1,970 (+3.81%)
55,700
54,600  56,700
+2,040 (+3.81%)
57,800
56,700  58,900
+2,120 (+3.81%)
60,000
58,800  61,100
+2,200 (+3.81%)
62,300
61,100  63,400
+2,280 (+3.81%)
64,600
63,400  65,900
+2,370 (+3.81%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Canada of about 7.74% each day. That corresponds to a doubling of the numbers approx. every 9.3 days.
The graph above and the following table show the course of reported deaths by coronavirus in Canada assuming that the numbers are following an exponential trend without any slowdown.
1,010

1,260
+251 (+24.9%)
1,360
+97 (+7.71%)
1,400
+45 (+3.32%)
1,560
+164 (+11.7%)
1,730
+162 (+10.4%)
1,910
+183 (+10.6%)
2,080
+168 (+8.8%)
2,240
+164 (+7.9%)
2,390
+145 (+6.47%)
2,590
2,560  2,610
+199 (+8.35%)
2,790
2,760  2,820
+200 (+7.74%)
3,000
2,970  3,030
+215 (+7.74%)
3,230
3,200  3,270
+232 (+7.74%)
3,480
3,450  3,520
+250 (+7.74%)
3,750
3,710  3,790
+269 (+7.74%)
4,040
4,000  4,090
+290 (+7.74%)
4,360
4,310  4,400
+313 (+7.74%)
4,690
4,640  4,740
+337 (+7.74%)
5,060
5,000  5,110
+363 (+7.74%)
In Canada, approx. 0.87% of the population die each year. With a population of roughly 37,100,000 people in Canada, that corresponds to about 883 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 Canada would be approx. 7.3%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Canada in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Canada in the previous days.
The graph tries to predict the number of required intensive care units in Canada. We assume the following:
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Alberta of about 9.11% each day. That corresponds to a doubling of the numbers approx. every 7.9 days.
The graph above and the following table show the course of reported coronavirus infections in Alberta assuming that the numbers are following an exponential trend without any slowdown.
1,870

2,000
+126 (+6.74%)
2,400
+401 (+20.1%)
2,560
+165 (+6.88%)
2,800
+241 (+9.41%)
2,910
+105 (+3.75%)
3,100
+187 (+6.43%)
3,400
+306 (+9.89%)
3,720
+319 (+9.38%)
4,020
+297 (+7.98%)
4,400
4,360  4,440
+387 (+9.63%)
4,810
4,760  4,850
+401 (+9.11%)
5,240
5,200  5,290
+438 (+9.11%)
5,720
5,670  5,770
+478 (+9.11%)
6,240
6,190  6,300
+521 (+9.11%)
6,810
6,750  6,870
+569 (+9.11%)
7,430
7,360  7,500
+620 (+9.11%)
8,110
8,040  8,180
+677 (+9.11%)
8,850
8,770  8,930
+739 (+9.11%)
9,650
9,570  9,740
+806 (+9.11%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Alberta of about 5.41% 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 deaths by coronavirus in Alberta assuming that the numbers are following an exponential trend without any slowdown.
48

48
+0 (+0%)
50
+2 (+4.17%)
51
+1 (+2%)
51
+0 (+0%)
59
+8 (+15.7%)
61
+2 (+3.39%)
66
+5 (+8.2%)
68
+2 (+3.03%)
72
+4 (+5.88%)
76
74  78
+4 (+5.58%)
80
79  82
+4 (+5.41%)
84
83  86
+4 (+5.41%)
89
87  91
+5 (+5.41%)
94
92  96
+5 (+5.41%)
99
97  101
+5 (+5.41%)
104
102  106
+5 (+5.41%)
110
108  112
+6 (+5.41%)
116
114  118
+6 (+5.41%)
122
120  125
+6 (+5.41%)
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 Alberta would be approx. 3%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Alberta in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Alberta in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in British Columbia of about 2.35% each day. That corresponds to a doubling of the numbers approx. every 30 days.
The graph above and the following table show the course of reported coronavirus infections in British Columbia assuming that the numbers are following an exponential trend without any slowdown.
1,520

1,560
+44 (+2.9%)
1,580
+14 (+0.897%)
1,620
+43 (+2.73%)
1,650
+29 (+1.79%)
1,650
+0 (+0%)
1,720
+77 (+4.68%)
1,800
+71 (+4.12%)
1,820
+29 (+1.62%)
1,850
+29 (+1.59%)
1,910
1,880  1,930
+53 (+2.86%)
1,950
1,920  1,980
+45 (+2.35%)
2,000
1,970  2,020
+46 (+2.35%)
2,040
2,020  2,070
+47 (+2.35%)
2,090
2,060  2,120
+48 (+2.35%)
2,140
2,110  2,170
+49 (+2.35%)
2,190
2,160  2,220
+50 (+2.35%)
2,240
2,210  2,270
+52 (+2.35%)
2,300
2,270  2,330
+53 (+2.35%)
2,350
2,320  2,380
+54 (+2.35%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in British Columbia 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 deaths by coronavirus in British Columbia assuming that the numbers are following an exponential trend without any slowdown.
72

75
+3 (+4.17%)
77
+2 (+2.67%)
78
+1 (+1.3%)
81
+3 (+3.85%)
82
+1 (+1.23%)
87
+5 (+6.1%)
90
+3 (+3.45%)
94
+4 (+4.44%)
98
+4 (+4.26%)
102
101  102
+4 (+3.95%)
106
106  107
+4 (+4.09%)
110
110  111
+4 (+4.09%)
115
114  115
+5 (+4.09%)
120
119  120
+5 (+4.09%)
124
124  125
+5 (+4.09%)
130
129  130
+5 (+4.09%)
135
134  135
+5 (+4.09%)
140
140  141
+6 (+4.09%)
146
145  147
+6 (+4.09%)
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 British Columbia would be approx. 6.2%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in British Columbia in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in British Columbia in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Grand Princess assuming that the numbers are following an exponential trend without any slowdown.
13

13
+0 (+0%)
13
+0 (+0%)
13
+0 (+0%)
13
+0 (+0%)
13
+0 (+0%)
13
+0 (+0%)
13
+0 (+0%)
13
+0 (+0%)
13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
13
13  13
+0 (+0%)
The graph above and the following table show the course of reported deaths by coronavirus in Grand Princess 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%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
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 Grand Princess would be approx. 0%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Grand Princess in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Grand Princess in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Manitoba of about 1.13% each day. That corresponds to a doubling of the numbers approx. every 62 days.
The graph above and the following table show the course of reported coronavirus infections in Manitoba assuming that the numbers are following an exponential trend without any slowdown.
246

250
+4 (+1.63%)
250
+0 (+0%)
253
+3 (+1.2%)
254
+1 (+0.395%)
254
+0 (+0%)
255
+1 (+0.394%)
257
+2 (+0.784%)
262
+5 (+1.95%)
263
+1 (+0.382%)
267
265  268
+4 (+1.36%)
270
268  271
+3 (+1.13%)
273
271  274
+3 (+1.13%)
276
274  277
+3 (+1.13%)
279
277  281
+3 (+1.13%)
282
280  284
+3 (+1.13%)
285
283  287
+3 (+1.13%)
288
286  290
+3 (+1.13%)
292
290  293
+3 (+1.13%)
295
293  297
+3 (+1.13%)
The graph above and the following table show the course of reported deaths by coronavirus in Manitoba assuming that the numbers are following an exponential trend without any slowdown.
5

5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
6
+1 (+20%)
6
+0 (+0%)
6
+0 (+0%)
6
+0 (+0%)
6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
6
6  6
+0 (+0%)
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 Manitoba would be approx. 2.4%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Manitoba in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Manitoba in the previous days.
The graph above and the following table show the course of reported coronavirus infections in New Brunswick assuming that the numbers are following an exponential trend without any slowdown.
117

117
+0 (+0%)
117
+0 (+0%)
117
+0 (+0%)
118
+1 (+0.855%)
118
+0 (+0%)
118
+0 (+0%)
118
+0 (+0%)
118
+0 (+0%)
118
+0 (+0%)
118
118  118
+0 (+4.44e14%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
118
118  118
+0 (+0%)
The graph above and the following table show the course of reported deaths by coronavirus in New Brunswick 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%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
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 New Brunswick would be approx. 0%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in New Brunswick in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in New Brunswick in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Newfoundland and Labrador of about 0.117% each day. That corresponds to a doubling of the numbers approx. every ,590 days.
The graph above and the following table show the course of reported coronavirus infections in Newfoundland and Labrador assuming that the numbers are following an exponential trend without any slowdown.
247

252
+5 (+2.02%)
256
+4 (+1.59%)
257
+1 (+0.391%)
257
+0 (+0%)
257
+0 (+0%)
257
+0 (+0%)
256
+1 (+0.389%)
256
+0 (+0%)
256
+0 (+0%)
256
255  256
+0 (+0.195%)
255
255  256
+0 (+0.117%)
255
254  255
+0 (+0.117%)
255
254  255
+0 (+0.117%)
254
254  255
+0 (+0.117%)
254
253  255
+0 (+0.117%)
254
253  254
+0 (+0.117%)
253
253  254
+0 (+0.117%)
253
253  254
+0 (+0.117%)
253
252  253
+0 (+0.117%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Newfoundland and Labrador 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 deaths by coronavirus in Newfoundland and Labrador 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 (+7.28e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
3
3  3
+0 (+2.91e10%)
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 Newfoundland and Labrador would be approx. 1.2%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Newfoundland and Labrador in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Newfoundland and Labrador in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Northwest Territories 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 Northwest Territories assuming that the numbers are following an exponential trend without any slowdown.
5

5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
+0 (+0%)
5
5  5
+0 (+7.28e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
5
5  5
+0 (+2.91e10%)
The graph above and the following table show the course of reported deaths by coronavirus in Northwest Territories 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%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
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 Northwest Territories would be approx. 0%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Northwest Territories in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Northwest Territories in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Nova Scotia of about 4.69% 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 Nova Scotia assuming that the numbers are following an exponential trend without any slowdown.
517

549
+32 (+6.19%)
579
+30 (+5.46%)
606
+27 (+4.66%)
649
+43 (+7.1%)
675
+26 (+4.01%)
721
+46 (+6.81%)
737
+16 (+2.22%)
772
+35 (+4.75%)
827
+55 (+7.12%)
856
836  876
+29 (+3.48%)
896
875  917
+40 (+4.69%)
938
916  960
+42 (+4.69%)
982
959  1,010
+44 (+4.69%)
1,030
1,000  1,050
+46 (+4.69%)
1,080
1,050  1,100
+48 (+4.69%)
1,130
1,100  1,150
+50 (+4.69%)
1,180
1,150  1,210
+53 (+4.69%)
1,230
1,210  1,260
+55 (+4.69%)
1,290
1,260  1,320
+58 (+4.69%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Nova Scotia of about 21% 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 deaths by coronavirus in Nova Scotia assuming that the numbers are following an exponential trend without any slowdown.
3

3
+0 (+0%)
3
+0 (+0%)
4
+1 (+33.3%)
7
+3 (+75%)
9
+2 (+28.6%)
9
+0 (+0%)
10
+1 (+11.1%)
12
+2 (+20%)
16
+4 (+33.3%)
18
17  20
+2 (+15.5%)
22
20  24
+4 (+21%)
27
25  30
+5 (+21%)
33
30  36
+6 (+21%)
40
36  43
+7 (+21%)
48
44  53
+8 (+21%)
58
53  64
+10 (+21%)
70
64  77
+12 (+21%)
85
78  93
+15 (+21%)
103
94  113
+18 (+21%)
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 Nova Scotia would be approx. 2.8%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Nova Scotia in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Nova Scotia in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Ontario of about 4.39% each day. That corresponds to a doubling of the numbers approx. every 16 days.
The graph above and the following table show the course of reported coronavirus infections in Ontario assuming that the numbers are following an exponential trend without any slowdown.
8,450

9,840
+1,390 (+16.5%)
10,500
+616 (+6.26%)
11,000
+557 (+5.33%)
11,600
+548 (+4.98%)
12,100
+502 (+4.34%)
12,700
+652 (+5.4%)
13,700
+1,000 (+7.89%)
14,100
+350 (+2.55%)
14,600
+482 (+3.43%)
15,300
14,900  15,700
+755 (+5.19%)
16,000
15,600  16,400
+672 (+4.39%)
16,700
16,300  17,100
+701 (+4.39%)
17,400
17,000  17,800
+732 (+4.39%)
18,200
17,700  18,600
+764 (+4.39%)
19,000
18,500  19,500
+798 (+4.39%)
19,800
19,300  20,300
+833 (+4.39%)
20,700
20,200  21,200
+869 (+4.39%)
21,600
21,100  22,100
+908 (+4.39%)
22,500
22,000  23,100
+947 (+4.39%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Ontario of about 7.32% each day. That corresponds to a doubling of the numbers approx. every 9.8 days.
The graph above and the following table show the course of reported deaths by coronavirus in Ontario assuming that the numbers are following an exponential trend without any slowdown.
385

490
+105 (+27.3%)
524
+34 (+6.94%)
564
+40 (+7.63%)
591
+27 (+4.79%)
624
+33 (+5.58%)
694
+70 (+11.2%)
762
+68 (+9.8%)
806
+44 (+5.77%)
862
+56 (+6.95%)
929
913  945
+67 (+7.77%)
997
980  1,010
+68 (+7.32%)
1,070
1,050  1,090
+73 (+7.32%)
1,150
1,130  1,170
+78 (+7.32%)
1,230
1,210  1,250
+84 (+7.32%)
1,320
1,300  1,350
+90 (+7.32%)
1,420
1,400  1,440
+97 (+7.32%)
1,520
1,500  1,550
+104 (+7.32%)
1,630
1,610  1,660
+112 (+7.32%)
1,750
1,720  1,780
+120 (+7.32%)
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 Ontario would be approx. 8.2%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Ontario in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Ontario in the previous days.
The graph above and the following table show the course of reported coronavirus infections in Prince Edward Island assuming that the numbers are following an exponential trend without any slowdown.
26

26
+0 (+0%)
26
+0 (+0%)
26
+0 (+0%)
26
+0 (+0%)
26
+0 (+0%)
26
+0 (+0%)
26
+0 (+0%)
26
+0 (+0%)
26
+0 (+0%)
26
26  26
+0 (+2.22e14%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
26
26  26
+0 (+0%)
The graph above and the following table show the course of reported deaths by coronavirus in Prince Edward Island 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%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
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 Prince Edward Island would be approx. 0%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Prince Edward Island in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Prince Edward Island in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Quebec 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 coronavirus infections in Quebec assuming that the numbers are following an exponential trend without any slowdown.
14,900

15,900
+997 (+6.71%)
16,800
+941 (+5.93%)
17,500
+723 (+4.3%)
18,000
+429 (+2.45%)
19,300
+1,370 (+7.63%)
20,100
+807 (+4.18%)
21,000
+839 (+4.17%)
21,800
+873 (+4.16%)
22,600
+778 (+3.56%)
23,600
23,500  23,600
+942 (+4.17%)
24,500
24,400  24,600
+939 (+3.98%)
25,500
25,400  25,600
+976 (+3.98%)
26,500
26,400  26,600
+1,020 (+3.98%)
27,500
27,500  27,600
+1,060 (+3.98%)
28,600
28,500  28,700
+1,100 (+3.98%)
29,800
29,700  29,900
+1,140 (+3.98%)
31,000
30,900  31,100
+1,190 (+3.98%)
32,200
32,100  32,300
+1,230 (+3.98%)
33,500
33,400  33,600
+1,280 (+3.98%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Quebec of about 8.77% each day. That corresponds to a doubling of the numbers approx. every 8.2 days.
The graph above and the following table show the course of reported deaths by coronavirus in Quebec assuming that the numbers are following an exponential trend without any slowdown.
487

630
+143 (+29.4%)
688
+58 (+9.21%)
688
+0 (+0%)
820
+132 (+19.2%)
939
+119 (+14.5%)
1,040
+105 (+11.2%)
1,130
+90 (+8.62%)
1,240
+109 (+9.61%)
1,340
+97 (+7.8%)
1,460
1,450  1,470
+122 (+9.12%)
1,590
1,580  1,600
+128 (+8.77%)
1,730
1,720  1,740
+139 (+8.77%)
1,880
1,870  1,890
+152 (+8.77%)
2,050
2,030  2,060
+165 (+8.77%)
2,230
2,210  2,240
+179 (+8.77%)
2,420
2,400  2,440
+195 (+8.77%)
2,630
2,620  2,650
+212 (+8.77%)
2,860
2,840  2,880
+231 (+8.77%)
3,120
3,090  3,140
+251 (+8.77%)
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 Quebec would be approx. 8%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Quebec in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Quebec in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Saskatchewan of about 2.08% each day. That corresponds to a doubling of the numbers approx. every 34 days.
The graph above and the following table show the course of reported coronavirus infections in Saskatchewan assuming that the numbers are following an exponential trend without any slowdown.
304

305
+1 (+0.329%)
307
+2 (+0.656%)
313
+6 (+1.95%)
315
+2 (+0.639%)
316
+1 (+0.317%)
320
+4 (+1.27%)
326
+6 (+1.88%)
331
+5 (+1.53%)
341
+10 (+3.02%)
347
344  349
+6 (+1.7%)
354
352  356
+7 (+2.08%)
361
359  364
+7 (+2.08%)
369
366  371
+8 (+2.08%)
377
374  379
+8 (+2.08%)
384
382  387
+8 (+2.08%)
392
390  395
+8 (+2.08%)
401
398  403
+8 (+2.08%)
409
406  412
+8 (+2.08%)
417
415  420
+9 (+2.08%)
Using loglinear regression on the data of the previous days, we could infer an increase of reported deaths by coronavirus in Saskatchewan 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 deaths by coronavirus in Saskatchewan assuming that the numbers are following an exponential trend without any slowdown.
4

4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
4
+0 (+0%)
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%)
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 Saskatchewan would be approx. 1.3%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Saskatchewan in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Saskatchewan in the previous days.
Using loglinear regression on the data of the previous days, we could infer an increase of reported coronavirus infections in Yukon of about 5.82e10% each day. That corresponds to a doubling of the numbers approx. every ,120,000,000,000 days.
The graph above and the following table show the course of reported coronavirus infections in Yukon assuming that the numbers are following an exponential trend without any slowdown.
8

8
+0 (+0%)
8
+0 (+0%)
9
+1 (+12.5%)
9
+0 (+0%)
11
+2 (+22.2%)
11
+0 (+0%)
11
+0 (+0%)
11
+0 (+0%)
11
+0 (+0%)
11
11  11
+0 (+1.46e9%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
11
11  11
+0 (+5.82e10%)
The graph above and the following table show the course of reported deaths by coronavirus in Yukon 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%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
0
+0 (+0%)
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 Yukon would be approx. 0%.
The graph aboves shows the mortality depending on different presumed lag.
The graph above shows the daily increase of reported coronavirus infections in Yukon in the previous days.
The graph shows the daily increase of reported deaths by coronavirus in Yukon in the previous days.
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