Chaos theory applied to the outbreak of Covid-19: an ancillary approach to decision-making in pandemic context

Mangiarotti, Sylvain; Peyre, Marisa; Zhang, Yan; Huc, Mireille; Roger, Francois; Kerr, Yann

Predicting the course of an epidemic is difficult, predicting the course of a pandemic from an emerging virus even more so. The validity of most predictive models relies on numerous parameters, involving biological and social characteristics often unknown or highly uncertain. COVID-19 pandemic brings additional factors such as population density and movements, behaviours, quality of the health system. Data from the COVID-19 epidemics in China, Japan and South Korea were used to build up data-driven deterministic models. Epidemics occurring in selected European countries rapidly evolved to overtake most Chinese provinces, to overtake South Korean model for France and even Hubei in the case of Italy and Spain. This approach was applied to other European countries and provides relevant information to inform disease control decision-making.