From: Bioinformatic modelling of SARS-CoV-2 pandemic with a focus on country-specific dynamics
Country | D30 [\(\gamma /\beta\)] | D60 [\(\gamma /\beta\)] | D150 [\(\gamma /\beta\)] | D300 [\(\gamma /\beta\)] |
---|---|---|---|---|
Algeria | 0.138/0.343 | |||
Austria | 0.005/0.006 | |||
Belgium | 0.158/0.262 | 0.037/0.045 | ||
Belize | 0.123/0.039 | 0.011/0.113 | ||
Bolivia | 0.064/0.008 | |||
Botswana | 0.002/0.101 | |||
Brunei | 0.007/0.673 | |||
Burundi | 0.113/0.352 | |||
Chad | 0.063/0.853 | |||
Chile | 0.001/0.012 | |||
Cyprus | 0.006/0.156 | |||
Ecuador | 0.073/0.825 | |||
Equatorial Guinea | 0.008/0.030 | |||
Finland | 0.005/0.012 | |||
France | 0.147/0.332 | 0.035/0.107 | ||
Guinea-Bissau | 0.005/0.036 | |||
Guyana | 0.153/0.154 | |||
Haiti | 0.060/0.006 | |||
Honduras | 0.065/0.018 | 0.030/0.122 | ||
Hungary | 0.133/0.571 | 0.025/0.311 | ||
Indonesia | 0.088/0.051 | |||
Ireland | 0.013/0.003 | |||
Italy | 0.140/0.556 | 0.064/0.472 | ||
Liberia | 0.112/0.076 | |||
Libya | 0.020/0.128 | |||
Liechtenstein | 0.010/0.841 | 0.010/0.841 | 0.012/0.949 | |
Lithuania | 0.010/0.000 | |||
Maldives | 0.003/0.042 | |||
Mauritania | 0.169/0.355 | |||
Mexico | 0.116/0.762 | 0.099/0.788 | ||
Namibia | 0.005/0.133 | |||
Netherlands | 0.111/0.002 | 0.122/0.004 | 0.021/0.014 | |
Nicaragua | 0.302/0.400 | 0.302/0.400 | ||
Norway | 0.004/0.001 | 0.019/0.004 | ||
San Marino | 0.097/0.024 | |||
Serbia | 0.010/0.004 | |||
South Sudan | 0.010/0.007 | |||
Spain | 0.113/0.565 | 0.039/0.172 | ||
Sudan | 0.175/0.159 | 0.063/0.530 | ||
the United Kingdom | 0.052/0.006 | 0.145/0.005 | 0.060/0.003 | |
the US | 0.018/0.006 | |||
Yemen | 0.178/0.034 | 0.223/0.041 | 0.282/0.497 | 0.288/0.615 |
Zimbabwe | 0.159/0.041 | 0.119/0.207 |