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IN modern structural design the maximum carrying capacity of a member under non‐uniform static stress at normal temperatures is not necessarily the load which gives a maximum stress equal to that at the limit of proportionality. All experiments have shown the ultimate strength of beams to exceed the value predicted on the basis of the elastic theory. This applies to simply supported and redundant beams made of steel and wrought iron, as well as to beams constructed from other metals such as cast iron, aluminium, magnesium, etc. Investigators differ, however, in the interpretation of this increased strength and in their methods of a more advantageous use of the material. These are usually based on specific experiments and apply to certain conditions only, without embracing all materials and all possible load distributions and types of structures.

MOST previous methods for predicting moments of resistance of beams subjected to pure bending beyond the limit of proportionality involve somewhat complicated and cumbersome calculations and are usually confined to specific materials and cross‐sections.

The primary objective of this paper is to explore the robust determinants influencing the infection rate and case mortality rate of COVID-19 in both developing and developed economies. The analysis is conducted using a dataset encompassing 148 countries.

To achieve this goal, empirical testing utilizes the Sala-i-Martin version of extreme bounds analysis, a method grounded in the cumulative density function. This approach allows for a comprehensive exploration of potential determinants.

The analysis results reveal that, to a large extent, distinct factors contribute to the infection and mortality rates in developed and developing countries. Notwithstanding these differences, certain common factors emerge, such as the risk environment, the number of tests conducted per million people and the percentage of the population over 65.

Despite acknowledging the potential limitations inherent in official data, this study concludes that the presented results offer valuable insights. The identified determinants, both unique and common, contribute to understanding the dynamics of COVID-19 in diverse economic settings. The information gleaned from this research holds significance for decision-makers involved in combating the ongoing pandemic.