Dynamic time series modelling and forecasting of COVID-19 in Norway

IF 6.9 2区经济学 Q1 ECONOMICS

International Journal of Forecasting Pub Date : 2024-05-25 DOI:10.1016/j.ijforecast.2024.05.004

Gunnar Bårdsen , Ragnar Nymoen

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引用次数: 0

Abstract

A framework for forecasting new COVID-19 cases jointly with hospital admissions and hospital beds with COVID-19 cases is presented. This project, dubbed CovidMod, produced 21 days ahead forecasts each working day from March 2021 to April 2022. Comparison of RMSFEs from that period, with the RMSFEs of the Norwegian Institute of Public Health (NIPH), favours the CovidMod forecasts, both for new cases and for hospital beds. Another comparison, with the short term forecasts produced by the Cardt method, shows little difference. Next, we present a new model where smooth transition regression is used as a feasible method to include forecasted effects of non-linear policy responses to the deviation between hospital beds and hospital bed capacity, on the forecasts of the original three variables. The forecasting performance of the model with endogenous policy effects is demonstrated retrospectively. It is suggested as a complementary approach to follow when the forecasted variables are generated from processes that include policy responses as realistic features.

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挪威 COVID-19 的动态时间序列建模和预测

本文提出了一个框架，用于预测 COVID-19 新病例以及 COVID-19 病例的入院人数和病床数。该项目被称为CovidMod，在2021年3月至2022年4月期间的每个工作日提前21天进行预测。将这一时期的RMSFE与挪威公共卫生研究所（NIPH）的RMSFE进行比较后发现，CovidMod对新病例和医院床位的预测更有利。另一项比较显示，与 Cardt 方法得出的短期预测结果相比，两者差异不大。接下来，我们提出了一个新模型，该模型采用平滑过渡回归作为可行方法，将对医院床位与医院床位容量之间偏差的非线性政策反应的预测效果纳入对原有三个变量的预测中。该模型的预测性能与内生政策效应进行了回顾性验证。建议在预测变量由包含政策反应这一现实特征的过程生成时，将其作为一种补充方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Forecasting Multiple-

CiteScore

17.10

自引率

11.40%

发文量

189

审稿时长

77 days

期刊介绍： The International Journal of Forecasting is a leading journal in its field that publishes high quality refereed papers. It aims to bridge the gap between theory and practice, making forecasting useful and relevant for decision and policy makers. The journal places strong emphasis on empirical studies, evaluation activities, implementation research, and improving the practice of forecasting. It welcomes various points of view and encourages debate to find solutions to field-related problems. The journal is the official publication of the International Institute of Forecasters (IIF) and is indexed in Sociological Abstracts, Journal of Economic Literature, Statistical Theory and Method Abstracts, INSPEC, Current Contents, UMI Data Courier, RePEc, Academic Journal Guide, CIS, IAOR, and Social Sciences Citation Index.