Jonas Wallin
Senior lecturer, Director of third cycle studies, Department of Statistics
Nowcasting COVID-19 Statistics Reported with Delay : A Case-Study of Sweden and the UK
Author
Summary, in English
The COVID-19 pandemic has demonstrated the importance of unbiased, real-time statistics of trends in disease events in order to achieve an effective response. Because of reporting delays, real-time statistics frequently underestimate the total number of infections, hospitalizations and deaths. When studied by event date, such delays also risk creating an illusion of a downward trend. Here, we describe a statistical methodology for predicting true daily quantities and their uncertainty, estimated using historical reporting delays. The methodology takes into account the observed distribution pattern of the lag. It is derived from the “removal method”—a well-established estimation framework in the field of ecology.
Department/s
- Department of Statistics
Publishing year
2023-02
Language
English
Publication/Series
International Journal of Environmental Research and Public Health
Volume
20
Issue
4
Document type
Journal article
Publisher
MDPI AG
Topic
- Public Health, Global Health, Social Medicine and Epidemiology
- Probability Theory and Statistics
Keywords
- COVID-19
- nowcasting
- prediction
Status
Published
ISBN/ISSN/Other
- ISSN: 1661-7827