From: Factors shaping the COVID-19 epidemic curve: a multi-country analysis
Cases per 100,000 | |||||||||
---|---|---|---|---|---|---|---|---|---|
Country level | India | Nepal | Nigeria | Colombia | Mexico | South Korea | Italy | Germany | Sweden |
Baseline trend | 0.0001* | −0.001 | 7.9 × 10–6 | 0.001* | 0.006* | 0.004 | 0.002 | 0.136* | 0.025* |
At intervention 1 | −0.148* | −0.01 | 0.003 | 0.561* | −2.676* | 8.160* | −12.819* | 61.896* | −0.073a |
Trend after intervention 1 | 0.042* | 0.004* | 0.006* | 0.114* | 0.461* | −0.181* | 3.135* | −1.368* | 1.787* |
At intervention 2 | – | – | – | – | – | 0.626 | 31.33* | – | −3.262 |
Trend after intervention 2 | – | – | – | – | – | 0.124* | −4.857* | – | −0.718 |
At intervention 3 | 0.384 | −0.509 | 0.604* | 0.946 | – | −0.119 | −4.98 | −1.213 | −6.781 |
Trend after intervention 3 | 0.098* | 0.142* | 0.02* | 0.316* | – | −0.069* | 0.557 | 0.973* | −1.303 |
General trend after all levels of intervention | 0.14* | 0.146* | 0.025* | 0.432* | 0.467* | 0.016* | −1.163* | −0.232* | −0.21 |
Sub-country level | Kerala | Kathmandu | Abuja | North Santander | Nuevo León | Daegu | Lombardy | Baden-Württemberg | Västra Götaland |
Baseline trend | 0.005* | 0.006 | 0.014* | 0.022* | 0.021* | 6.33* | 3.33* | 0.838* | 0.401* |
At intervention 1 | 0.33* | −0.117 | 0.091 | 0.432 | −1.214* | 105.136* | 130.759* | 75.703* | 12.026a |
Trend after intervention 1 | −0.011* | −0.006 | 0.076 | −0.021 | 0.164* | −10.589* | −5.785* | −2.468* | 0.433 |
At intervention 2 | – | – | – | – | – | – | – | – | – |
Trend after intervention 2 | – | – | – | – | – | – | – | – | – |
At intervention 3 | 0.395* | 0.127 | 0.91 | 0.439 | – | 30.13 | −3.432 | 7.368 | 14.163 |
Trend after intervention 3 | 0.170* | 0.026 | −0.069 | −0.02 | – | 4.223* | 0.934 | 1.646* | −0.639 |
General trend after all levels of intervention | 0.165* | 0.026 | 0.021 | −0.019 | 0.185* | −0.036* | −1.52* | 0.016 | 0.195 |