Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: A dynamic intensity model

Otilia Boldea, Adriana Cornea-Madeira, Joao Madeira

Research output: Contribution to journalArticleScientificpeer-review

Abstract

In this paper, we estimate the path of daily SARS-CoV-2 infections in England from the beginning of the pandemic until the end of 2021. We employ a dynamic intensity model, where the mean intensity conditional on the past depends both on past intensity of infections and past realized infections. The model parameters are time-varying, and we employ a multiplicative specification along with logistic transition functions to disentangle the time-varying effects of nonpharmaceutical policy interventions, of different variants, and of protection (waning) of vaccines/boosters. Our model results indicate that earlier interventions and vaccinations are key to containing an infection wave. We consider several scenarios that account for more infectious variants and different protection levels of vaccines/boosters. These scenarios suggest that, as vaccine protection wanes, containing a new wave in infections and an associated increase in hospitalizations in the near future may require further booster campaigns and/or nonpharmaceutical interventions.
Original languageEnglish
Pages (from-to)444-466
Number of pages23
JournalEconometrics Journal
Volume26
Issue number3
DOIs
Publication statusPublished - Sept 2023

Keywords

  • Bayesian Hamiltonian Monte Carlo
  • Covid-19
  • Npi
  • Omicron
  • Booster
  • Vaccines
  • Variants of concern

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