The outbreak of the COVID-19 pandemic has led to a resurgence of protests. Various societal conditions of social systems, such as economic stability, demographic ageing, and political elites, are often associated to the emergence of civil resistance movements. Several qualitative and quantitative models have been developed to analyse the relationship between societal conditions and the emergence of protests. The existing models use the underlying assumptions that these conditions operate in similar time-scales. However, the analysis of social systems also shows the importance of considering explicitly the inherent time-scales particularly slow-fast dynamics. The sudden and dramatic disruptive force of the pandemic has yield fine-grained data sets that can be used to better grasp the different dynamics of this social phenom. This paper proposes an integrated approach to explore the relationship between societal conditions and the emergence of protests in the context of the COVID-19 pandemic. First, a literature based causal-loop-diagram is constructed to conceptualise the emergence of civil resistance as a result of intertwined dynamics. Based on the derived factors in the literature study, a data set is constructed to enable this analysis. Furthermore, by means of statistical and computational modelling we conduct a quantitative analysis in which we compare the emergence of protests for 27 countries during the pandemic. Also based on the factors found in literature we have constructed a system dynamics model that explicitly models the development of societal strains and social mobilisation in order to provide a better quantitative explanation of the emergence of protests. We found that while fast-changing factors are better estimators for ‘when’ civil resistance emerges, slow-changing factors are better estimators of ‘how’ civil resistance manifests itself in terms of the relative intensity of the protests in specific countries.