Table 6.
Random-effects meta-regression analysis of the crude case fatality risk at the last follow-up date in the extended analysis (February 12, 2021) for 73 countries.
| MODEL 1: a priori model | MODEL 2: bootstrap variable selection | |||||||
|---|---|---|---|---|---|---|---|---|
| Crude case fatality risk | Crude case fatality risk | |||||||
| Covariates | β | SE | P-value | OR | β | SE | P-value | OR |
| Intercept | −9.8586 | 1.9209 | – | – | −10.2149 | 1.6963 | – | – |
| Sociodemographic factors | ||||||||
| GDP per capita ($1,000 USD, 2019) | −0.0105 | 0.0068 | 0.128 | 0.99 | – | – | – | – |
| Urban population (%) | – | – | – | – | −0.0204 | 0.0061 | 0.002 | 0.98 |
| Population density (pop per km2) | – | – | – | – | −0.0002 | 0.0001 | 0.007 | 1.00 |
| Elderly dependency ratio (% of adults) | – | – | – | – | 0.0980 | 0.0754 | 0.199 | 1.10 |
| Proportion over 65 years (%) | −0.0210 | 0.0231 | 0.367 | 0.98 | −0.1731 | 0.1236 | 0.167 | 0.84 |
| Proportion over 80 years (%) | – | – | – | – | – | – | – | – |
| Proportion overweight (%) | – | – | – | – | 0.0283 | 0.0079 | 0.001 | 1.03 |
| Pandemic–related factors | ||||||||
| Time since 1st case (days) | – | – | – | – | – | – | – | – |
| Time since 100 cases (days) | – | – | – | – | – | – | – | – |
| Time since 1st death (days) | 0.0148 | 0.0056 | 0.010 | 1.01 | 0.0137 | 0.0047 | 0.005 | 1.01 |
| Testing coverage (n. tests per 10,000 pop) | −0.0019 | 0.0021 | 0.363 | 1.00 | – | – | – | – |
| Health system strength | ||||||||
| Healthcare workers (n. per 1,000 pop) | −0.0024 | 0.0280 | 0.932 | 1.00 | −0.0399 | 0.0190 | <0.0001 | 0.96 |
| Hospital beds (n. per 1,000 pop) | −0.0167 | 0.0435 | 0.703 | 0.98 | – | – | – | – |
| Health expenditure (% of GDP) | – | – | – | – | 0.0965 | 0.0346 | 0.007 | 1.10 |
| Out–of–pocket health expenditure (%) | – | – | – | – | 0.0096 | 0.0051 | 0.065 | 1.01 |
| Cultural characteristics | ||||||||
| Individualism vs. collectivism | 0.0139 | 0.0050 | 0.007 | 1.01 | 0.0092 | 0.0042 | 0.031 | 1.01 |
| Uncertainty avoidance | 0.0132 | 0.0043 | 0.003 | 1.01 | 0.0055 | 0.0035 | 0.114 | 1.01 |
| Indulgence vs. restraint | – | – | – | – | – | – | – | – |
| Long-term vs. short-term orientation | – | – | – | – | 0.0126 | 0.0043 | 0.005 | 1.01 |
| Power distance | – | – | – | – | – | – | – | – |
| Masculinity vs. femininity | – | – | – | – | – | – | – | – |
| Political characteristics | ||||||||
| Polity (democracy vs. authoritarianism) | 0.0234 | 0.0192 | 0.228 | 1.02 | – | – | – | – |
| pseudo R2: 26% | pseudo R2: 52% | |||||||
| AIC:140.0 BIC:163.6 | AIC:113.7 BIC: 143.0 | |||||||
Dependent variables were logit transformation to stabilize the variance of proportions. Random-effects meta-regression was used to explore the impact of cultural characteristics on fatalities while adjusting for important predefined covariates. Pseudo-R-squared value represent the proportion of heterogeneity explained by predictors included in the model. OR, Odds ratio; AIC, Akaike information criterion; BIC, Bayesian information criterion. Bold font indicates a statistically significant association with outcome at p < 0.05.