Computational modeling study demonstrates multi-wave COVID-19 transmission dynamics in Israel, highlighting the combined impact of public health interventions and vaccination.
Key Points
To develop an explanatory modeling framework combining Bayesian inference and compartmental epidemic modeling to evaluate multi-wave COVID-19 transmission under vaccination rollout.
Coupled a modified SEIR compartmental model with Bayesian inference to analyze multi-wave COVID-19 case trajectories.
Integrated empirical real-time vaccination data alongside piecewise transmission and infectious rates defined by intervention change points.
Fitted multi-wave infection trajectories reliably mapped to critical checkpoints representing major policy announcements and social events.
Quantified shifts in transmission dynamics reflecting mitigation strategy effectiveness and vaccination impact to enable short-term scenario forecasting.