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In the context of natural disasters, human responses inevitably intertwinewith natural factors. The COVID-19 pandemic, as a significant stress factor,has brought to light profound variations among different countries in terms oftheir adaptive dynamics in addressing the spread of infection outbreaks acrossdifferent regions. This emphasizes the crucial role of cultural characteristicsin natural disaster analysis. The theoretical understanding of large-scaleepidemics primarily relies on mean-field kinetic models. However, conventionalSIR-like models failed to fully explain the observed phenomena at the onset ofthe COVID-19 outbreak. These phenomena included the unexpected cessation ofexponential growth, the reaching of plateaus, and the occurrence of multi-wavedynamics. In situations where an outbreak of a highly virulent and unfamiliarinfection arises, it becomes crucial to respond swiftly at a non-medical levelto mitigate the negative socio-economic impact. Here we present a theoreticalexamination of the first wave of the epidemic based on a simple SIRSS model(SIR with Social Stress). We conduct an analysis of the socio-cultural featuresof na\"ive population behaviors across various countries worldwide. The uniquecharacteristics of each country/territory are encapsulated in only a fewconstants within our model, derived from the fitted COVID-19 statistics. Theseconstants also reflect the societal response dynamics to the external stressfactor, underscoring the importance of studying the mutual behavior of humanityand natural factors during global social disasters. Based on these distinctivecharacteristics of specific regions, local authorities can optimize theirstrategies to effectively combat epidemics until vaccines are developed.

Exploring the impact of social stress on the adaptive dynamics of COVID-19: Typing the behavior of na\"ive populations faced with epidemics