From: Predicting the incidence of COVID-19 using data mining
Date | Across all 252 geographic regions | Percent error | |
---|---|---|---|
Predicted | Actual | ||
30-Mar | 68,185 | 65,321 | 4.38% |
31-Mar | 65,092 | 76,799 | 15.24% |
1-Apr | 67,988 | 76,657 | 11.31% |
2-Apr | 72,902 | 81,340 | 10.37% |
3-Apr | 83,865 | 83,272 | 0.71% |
4-Apr | 85,140 | 80,392 | 5.91% |
5-Apr | 82,224 | 71,994 | 14.21% |
6-Apr | 79,481 | 73,285 | 8.45% |
7-Apr | 84,871 | 77,773 | 9.13% |
8-Apr | 89,239 | 84,275 | 5.89% |
9-Apr | 89,652 | 86,461 | 3.69% |
10-Apr | 86,993 | 87,520 | 0.60% |
11-Apr | 90,463 | 76,217 | 18.69% |
12-Apr | 87,923 | 95,353 | 7.79% |
Total number of confirmed cases | 1,134,018 | 1,116,659 | 1.55% |