Table 1  Drivers of the COVID-19 spread in relation to the country types.
Country types were defined by the patterns of COVID-19 spread (cases per 1 million population) (see Fig 3). Type A, countries that had a peak in the number of COVID-19 cases per week before the middle of April and had more than 1,000 COVID-19 cases per 1 million population; type B, countries that exhibited an increase in the number of COVID-19 cases per week after the middle of June and had more than 1,000 COVID-19 cases per 1 million population; type C, countries that had a peak in the number of COVID-19 cases per week before the middle of April and had less than 1,000 COVID-19 cases per 1 million population; and type D, countries that exhibited an increase in the number of COVID-19 cases per week after the middle of June and had less than 1,000 COVID-19 cases per 1 million population. The statistical significance of differences between the country types was tested by a Bonferroni’s multiple comparison test. Different letters indicate the values that are significantly different (p < 0.05) from each other.
Factor  Type A  Type B  Type C  Type D
Mean annual temperature  11.1 (±3.88) a  14.6 (±8.87) b  18.5 (±7.96) c  21.4 (±6.81) d
Mean annual precipitation  865 (±368) a  806 (±541) a  1250 (±629) b  1290 (±869) b
Population density  485 (±1060)  342 (±1400)  391 (±1500)  164 (±243)
Relative frequency of visitors  154 (±329) a  36.1 (±65.4) b  73.8 (±97.4) b  16.4 (±27.2) b
GDP per person  50200 (±21500) a  18500 (±18300) b  22200 (±18100) b  5690 (±5430) c
BCG vaccination effect  -1.37 (±1.42) a  0.752 (±1.37) b  0.467 (±1.51) b  0.88 (±0.694) b
Relative frequency of people infected by malaria  0.163 (±1.26) a  2180 (±14200) a  2950 (±31800) a  40100 (±85000) b
Relative frequency of people ≥ 65 years old  18.9 (±3.17) a  11.6 (±4.92) b  14.8 (±6.51) c  7.33 (±4.5) d