tetano
Editor, Senior Moderator
- Don Klinkenberg[SUP]1[/SUP]
, Jantien Backer[SUP]1[/SUP] , Nicolette de Keizer[SUP]2,3[/SUP] , Jacco Wallinga[SUP]1,4[/SUP]
Model projections of coronavirus disease 2019 (COVID-19) incidence help policymakers about decisions to implement or lift control measures. During the pandemic, policymakers in the Netherlands were informed on a weekly basis with short-term projections of COVID-19 intensive care unit (ICU) admissions.
Aim
We aimed at developing a model on ICU admissions and updating a procedure for informing policymakers.
Method
The projections were produced using an age-structured transmission model. A consistent, incremental update procedure integrating all new surveillance and hospital data was conducted weekly. First, up-to-date estimates for most parameter values were obtained through re-analysis of all data sources. Then, estimates were made for changes in the age-specific contact rates in response to policy changes. Finally, a piecewise constant transmission rate was estimated by fitting the model to reported daily ICU admissions, with a changepoint analysis guided by Akaike's Information Criterion.
Results
The model and update procedure allowed us to make weekly projections. Most 3-week prediction intervals were accurate in covering the later observed numbers of ICU admissions. When projections were too high in March and August 2020 or too low in November 2020, the estimated effectiveness of the policy changes was adequately adapted in the changepoint analysis based on the natural accumulation of incoming data.
Conclusion
The model incorporates basic epidemiological principles and most model parameters were estimated per data source. Therefore, it had potential to be adapted to a more complex epidemiological situation with the rise of new variants and the start of vaccination.
https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2024.29.10.2300336
