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Forecasting of COVID-19 spread in Poland as part of health needs mapping
The development of a robust model for COVID-19 forecasting was a crucial task undertaken by the Ministry of Health of the Republic of Poland in response to the pandemic. High-quality forecasting rendered the inclusion of COVID-19 modelling in health needs assessment indispensable at the regional as...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10596718/ http://dx.doi.org/10.1093/eurpub/ckad160.1046 |
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author | Witczak, K Raczyńska, M Kozioł-Rostkowska, M Śmiglewska, A |
author_facet | Witczak, K Raczyńska, M Kozioł-Rostkowska, M Śmiglewska, A |
author_sort | Witczak, K |
collection | PubMed |
description | The development of a robust model for COVID-19 forecasting was a crucial task undertaken by the Ministry of Health of the Republic of Poland in response to the pandemic. High-quality forecasting rendered the inclusion of COVID-19 modelling in health needs assessment indispensable at the regional as well as country level. The model served as a basis for data-driven policy-making, such as the introduction or lifting of non-pharmaceutical interventions and the management of hospital resource allocation. The proposed model draws upon the population-adjusted infection fatality rates, vaccine-induced immunity, reported test positivity rates, and COVID-19-related mortality to infer the dark figure of cases. The estimates of the true number of infections lay the foundations for the computation of variant-dependent effective reproduction numbers, which constitute the workhorse of the model. The algorithm utilises the Bayesian prediction of those metrics along with the estimation of hybrid immunity levels to arrive at a short-term forecast of the course of the pandemic. The implemented model yields reliable results throughout the outbreak, allowing for the assessment of the strain of consecutive epidemic waves on the healthcare system. KEY MESSAGES: • Forecasting of COVID-19 spread is vital for health needs assessment and health crisis management policy-making. • Short-term forecasting of COVID-19 spread using effective reproduction numbers yields high-quality results. |
format | Online Article Text |
id | pubmed-10596718 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-105967182023-10-25 Forecasting of COVID-19 spread in Poland as part of health needs mapping Witczak, K Raczyńska, M Kozioł-Rostkowska, M Śmiglewska, A Eur J Public Health Poster Displays The development of a robust model for COVID-19 forecasting was a crucial task undertaken by the Ministry of Health of the Republic of Poland in response to the pandemic. High-quality forecasting rendered the inclusion of COVID-19 modelling in health needs assessment indispensable at the regional as well as country level. The model served as a basis for data-driven policy-making, such as the introduction or lifting of non-pharmaceutical interventions and the management of hospital resource allocation. The proposed model draws upon the population-adjusted infection fatality rates, vaccine-induced immunity, reported test positivity rates, and COVID-19-related mortality to infer the dark figure of cases. The estimates of the true number of infections lay the foundations for the computation of variant-dependent effective reproduction numbers, which constitute the workhorse of the model. The algorithm utilises the Bayesian prediction of those metrics along with the estimation of hybrid immunity levels to arrive at a short-term forecast of the course of the pandemic. The implemented model yields reliable results throughout the outbreak, allowing for the assessment of the strain of consecutive epidemic waves on the healthcare system. KEY MESSAGES: • Forecasting of COVID-19 spread is vital for health needs assessment and health crisis management policy-making. • Short-term forecasting of COVID-19 spread using effective reproduction numbers yields high-quality results. Oxford University Press 2023-10-24 /pmc/articles/PMC10596718/ http://dx.doi.org/10.1093/eurpub/ckad160.1046 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the European Public Health Association. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Poster Displays Witczak, K Raczyńska, M Kozioł-Rostkowska, M Śmiglewska, A Forecasting of COVID-19 spread in Poland as part of health needs mapping |
title | Forecasting of COVID-19 spread in Poland as part of health needs mapping |
title_full | Forecasting of COVID-19 spread in Poland as part of health needs mapping |
title_fullStr | Forecasting of COVID-19 spread in Poland as part of health needs mapping |
title_full_unstemmed | Forecasting of COVID-19 spread in Poland as part of health needs mapping |
title_short | Forecasting of COVID-19 spread in Poland as part of health needs mapping |
title_sort | forecasting of covid-19 spread in poland as part of health needs mapping |
topic | Poster Displays |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10596718/ http://dx.doi.org/10.1093/eurpub/ckad160.1046 |
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