Temporal Clustering of Disorder Events During the COVID-19 Pandemic
Gian Maria Campedelli, Maria Rita D'Orsogna

TL;DR
This study analyzes the temporal and geographic patterns of disorder events during COVID-19 in India, Israel, and Mexico, revealing self-excitation and clustering behaviors that vary by country and influence public response.
Contribution
It applies Poisson and Hawkes process models to pandemic-related disorder data, uncovering inter-dependent, self-exciting, and geographically clustered disorder dynamics across countries.
Findings
Disorder events are inter-dependent and self-excite in all three countries.
Geographic clustering confirms self-excitation at subnational levels.
Israel shows the highest reactivity and nationwide synchrony.
Abstract
The COVID-19 pandemic has unleashed multiple public health, socio-economic, and institutional crises. Measures taken to slow the spread of the virus have fostered significant strain between authorities and citizens, leading to waves of social unrest and anti-government demonstrations. We study the temporal nature of pandemic-related disorder events as tallied by the "COVID-19 Disorder Tracker" initiative by focusing on the three countries with the largest number of incidents, India, Israel, and Mexico. By fitting Poisson and Hawkes processes to the stream of data, we find that disorder events are inter-dependent and self-excite in all three countries. Geographic clustering confirms these features at the subnational level, indicating that nationwide disorders emerge as the convergence of meso-scale patterns of self-excitation. Considerable diversity is observed among countries when…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Yersinia bacterium, plague, ectoparasites research · Terrorism, Counterterrorism, and Political Violence
