Modelling and Predicting of Minimal CFR During Initial COVID-19 Epidemics from 214 Nations

Background: The basic integrating responding capacity (IRC) against the COVID-19 epidemics is essential fundament for national responding strategy and can’t be evaluated quantitatively worldwide. To explore the applicable parameter labeling IRC from national daily CFRs and predicting method of minimal CFR during initial COVID-19 epidemic. Methods: Daily case fatality rates of COVID-19 cases since the first COVID-19 death in 214 nations were explored and found that similar falling zones marked with two turning points within the fitting curves occurred for many nations. The turning points could be quantified with parameters for the day duration (T1, T2 and ΔT) and for the three-day moving arithmetic average CFRs (CFR1, CFR2, and ΔCFR) under wave theory for 71 nations after screening. Two prediction models of CFR2 were established with multiple linear regressions (M1) and multi-order curve regressions (M2). Findings: Among the 92 nations, the 3DMA CFRs curves were arising continuously for 21 nations. Three types of falling zones could be classified with strong, moderate and weak IRC in the other 71 nations, the range of CFR2 was 0·0682~32·5804 percent. Only the minimal CFR showed significant correlations with 9 independent national indicators in 65 nations with CFRs under 7 percent. Model M1 showed that Log(POPU), B1K, and HHS made significant positive contributions, and Log(GDP), A65, DGDP, P1K, N1K and BMI (21·8 ~ 29·5) made negative contributions to the minimal CFR against COVID-19 epidemics for most nations. CFR2 was predicted well with model M1 for 57 nations and with model M2 for 59 nations for internal evaluation. Interpretation: The national minimal CFR could be predicted with models successfully for most nations based on some national, which provided the essential information in advance to establish suitable national responding strategies against COVID-19 epidemics worldwide. Funding Statement: This study was supported by National Natural Science Foundation of China (21976169) and Beijing Natural Science Foundation Project (8182055). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: Data collection and analysis to be part of a continuing public health outbreak were thus considered exempt from institutional review board approval.