Jasmina Panovska-Griffiths1, Sonya Crowe2, Christina Pagel3, Tinevimbo Shiri4, Peter Grove5, Martin Utley2. 1. Clinical Operational Research Unit, Department of Mathematics, University College London, WC1E 6BT, UK; Department of Applied Health Research, University College London, WC1E 6BT, UK; Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, WC1H 9SH, UK. Electronic address: j.panovska-griffiths@ucl.ac.uk. 2. Clinical Operational Research Unit, Department of Mathematics, University College London, WC1E 6BT, UK. 3. Clinical Operational Research Unit, Department of Mathematics, University College London, WC1E 6BT, UK; Department of Applied Health Research, University College London, WC1E 6BT, UK. 4. Warwick Medical School, Clinical Trials Unit, University of Warwick, Coventry, CV4 7AL, UK. 5. Department of Health, Area 330, Wellington House, 133 - 155 Waterloo Road, London, SE1 8UG, UK.
Abstract
BACKGROUND: In the UK, the childhood immunisation programme is given in the first 5 years of life and protects against 12 vaccine-preventable diseases. Recently, this programme has undergone changes with addition of vaccination against Meningitis B from September 2015 and the removal of the primary dose of protection against Meningitis C from July 2016. These hanges have direct impact on the associated diseases but in addition may induce indirect effects on the vaccines that are given simultaneously or later in the programme. In this work, we developed a novel formal method to evaluate the impact of vaccination changes to one aspect of the programme across an entire vaccine programme. METHODS: Firstly, we combined transmission modelling (for four diseases) and historic data synthesis (for eight diseases) to project, for each disease, the disease burden at different levels of effective coverage against the associated disease. Secondly, we used a simulation model to determine the vector of effective coverage against each disease under three variations of the current childhood schedule. Combining these, we calculated the vector of disease burden across the programme under different scenarios, and assessed the direct and indirect effects of the schedule changes. RESULTS: Through illustrative application of our novel framework to three scenarios of the current childhood immunisation programme in the UK, we demonstrated the feasibility of this unifying approach. For each disease in the programme, we successfully quantified the residual disease burden due to the change. For some diseases, the change was indirectly beneficial and reduced the burden, whereas for others the effect was adverse and the change increased the disease burden. CONCLUSIONS: Our results demonstrate the potential benefit of considering the programme-wide impact of changes to an immunisation schedule, and our framework is an important step in the development of a means for systematically doing so.
BACKGROUND: In the UK, the childhood immunisation programme is given in the first 5 years of life and protects against 12 vaccine-preventable diseases. Recently, this programme has undergone changes with addition of vaccination against Meningitis B from September 2015 and the removal of the primary dose of protection against Meningitis C from July 2016. These hanges have direct impact on the associated diseases but in addition may induce indirect effects on the vaccines that are given simultaneously or later in the programme. In this work, we developed a novel formal method to evaluate the impact of vaccination changes to one aspect of the programme across an entire vaccine programme. METHODS: Firstly, we combined transmission modelling (for four diseases) and historic data synthesis (for eight diseases) to project, for each disease, the disease burden at different levels of effective coverage against the associated disease. Secondly, we used a simulation model to determine the vector of effective coverage against each disease under three variations of the current childhood schedule. Combining these, we calculated the vector of disease burden across the programme under different scenarios, and assessed the direct and indirect effects of the schedule changes. RESULTS: Through illustrative application of our novel framework to three scenarios of the current childhood immunisation programme in the UK, we demonstrated the feasibility of this unifying approach. For each disease in the programme, we successfully quantified the residual disease burden due to the change. For some diseases, the change was indirectly beneficial and reduced the burden, whereas for others the effect was adverse and the change increased the disease burden. CONCLUSIONS: Our results demonstrate the potential benefit of considering the programme-wide impact of changes to an immunisation schedule, and our framework is an important step in the development of a means for systematically doing so.
Authors: Marta Garrido-Jareño; Leonor Puchades-Carrasco; Leticia Orti-Pérez; José Miguel Sahuquillo-Arce; María Del Carmen Meyer-García; Joan Mollar-Maseres; Carmina Lloret-Sos; Ana Gil-Brusola; José Luis López-Hontangas; José Manuel Beltrán-Garrido; Javier Pemán-García; Antonio Pineda-Lucena Journal: Sci Rep Date: 2021-03-22 Impact factor: 4.379