Integrated Analysis of Behavioral and Health Data: A Comparative Study of COVID19 Data in Israel and Italy

The response to the COVID19 pandemic has been highly variable, both in terms of between-nations variation and within the same nation, at different waves. In this context, governments applied different mitigation policy responses with varying impact on social and economic measures over time. This article examines the effect of mobility restriction measures in Italy and Israel and compares the association between health and population mobility data. Facing the pandemic, Israel and Italy implemented different policy measures and experienced different public activity patterns. The analysis we conducted is a staged approach using Bayesian Networks and Structural Equations Models to investigate these patterns. The goal is to assess the impact of pandemic management and mitigation policies on pandemic spread and population activity. We propose a methodology that first models data from health registries and Google mobility data and then shows how decision makers can conduct scenario analysis to help support pandemic management policies.