The joint determination of morbidity and vaccination in the spatiotemporal epidemiology of COVID-19.

This paper examines the mutual dependence between COVID-19 morbidity and vaccination rollout. A theory of endogenous immunization is proposed in which the decision to become vaccinated varies directly with the risks of contagion, and the public self-selects into self-protection. Hence, COVID-19 morbidity varies inversely with vaccination rollout, and vaccination rollout varies directly with COVID-19 morbidity. The paper leverages the natural sequencing between morbidity and immunization to identify the causal order in the dynamics of this relationship. A modified SIR model is estimated using spatial econometric methods for weekly panel data for Israel at a high level of spatial granularity. Connectivity between spatial units is measured using physical proximity and a unique mobility-based measure. Spatiotemporal models for morbidity and vaccination rollout show that not only does morbidity vary inversely with vaccination rollout, vaccination rollout varies directly with morbidity. The utility of the model for public health policy targeting, is highlighted.

Agent-based simulation of COVID-19 containment measures: the case of lockdowns in cities.

The effectiveness and political feasibility of COVID-19 containment measures such as lockdowns, are contentious. This stems in part from an absence of tools for their rigorous evaluation. Common epidemiological models such as the SEIR model generally lack the spatial resolution required for micro-level containment actions, the visualization capabilities for communicating measures such as localized lockdowns and the scenario-testing capabilities for assessing different alternatives. We present an individual-level ABM that generates geo-social networks animated by agent-agent and agent-building interactions. The model simulates real-world contexts and is demonstrated for the city of Jerusalem. Simulation outputs yield much useful information for evaluating the effectiveness of lockdowns. These include network-generated socio-spatial contagion chains for individual agents, dynamic building level contagion processes and neighborhood-level patterns of COVID-19 imports and exports useful in identifying super-spreader neighborhoods. The policy implications afforded by these various outputs are discussed. Supplementary Information: The online version contains supplementary material available at 10.1007/s12076-023-00336-w.

Cascades - Mapping the multi-disciplinary landscape in a post-pandemic world.

This paper introduces the Special Issue on Cascading Effects in Disaster Risk Management. It reviews the contributions and highlights their multi-disciplinary interpretations of cascades. It proceeds to discuss whether the on-going unfolding of the COVID-19 pandemic illustrates the cascades metaphor.