tetano
Editor, Senior Moderator
PLoS One
. 2023 Sep 5;18(9):e0290974.
doi: 10.1371/journal.pone.0290974. eCollection 2023. Optimal age-specific vaccination control for COVID-19: An Irish case study
Eleni Zavrakli[SUP] 1 2 3 [/SUP], Andrew Parnell[SUP] 1 2 3 [/SUP], David Malone[SUP] 1 2 [/SUP], Ken Duffy[SUP] 1 [/SUP], Subhrakanti Dey[SUP] 4 [/SUP]
Affiliations
The outbreak of a novel coronavirus causing severe acute respiratory syndrome in December 2019 has escalated into a worldwide pandemic. In this work, we propose a compartmental model to describe the dynamics of transmission of infection and use it to obtain the optimal vaccination control. The model accounts for the various stages of the vaccination, and the optimisation is focused on minimising the infections to protect the population and relieve the healthcare system. As a case study, we selected the Republic of Ireland. We use data provided by Ireland's COVID-19 Data-Hub and simulate the evolution of the pandemic with and without the vaccination in place for two different scenarios, one representative of a national lockdown situation and the other indicating looser restrictions in place. One of the main findings of our work is that the optimal approach would involve a vaccination programme where the older population is vaccinated in larger numbers earlier while simultaneously part of the younger population also gets vaccinated to lower the risk of transmission between groups. We compare our simulated results with those of the vaccination policy taken by the Irish government to explore the advantages of our optimisation method. Our comparison suggests that a similar reduction in cases may have been possible even with a reduced set of vaccinations available for use.
. 2023 Sep 5;18(9):e0290974.
doi: 10.1371/journal.pone.0290974. eCollection 2023. Optimal age-specific vaccination control for COVID-19: An Irish case study
Eleni Zavrakli[SUP] 1 2 3 [/SUP], Andrew Parnell[SUP] 1 2 3 [/SUP], David Malone[SUP] 1 2 [/SUP], Ken Duffy[SUP] 1 [/SUP], Subhrakanti Dey[SUP] 4 [/SUP]
Affiliations
- PMID: 37669287
- DOI: 10.1371/journal.pone.0290974
The outbreak of a novel coronavirus causing severe acute respiratory syndrome in December 2019 has escalated into a worldwide pandemic. In this work, we propose a compartmental model to describe the dynamics of transmission of infection and use it to obtain the optimal vaccination control. The model accounts for the various stages of the vaccination, and the optimisation is focused on minimising the infections to protect the population and relieve the healthcare system. As a case study, we selected the Republic of Ireland. We use data provided by Ireland's COVID-19 Data-Hub and simulate the evolution of the pandemic with and without the vaccination in place for two different scenarios, one representative of a national lockdown situation and the other indicating looser restrictions in place. One of the main findings of our work is that the optimal approach would involve a vaccination programme where the older population is vaccinated in larger numbers earlier while simultaneously part of the younger population also gets vaccinated to lower the risk of transmission between groups. We compare our simulated results with those of the vaccination policy taken by the Irish government to explore the advantages of our optimisation method. Our comparison suggests that a similar reduction in cases may have been possible even with a reduced set of vaccinations available for use.