Estimating the SARS-CoV-2 infected population fraction and the infection-to-fatality ratio: a data-driven case study based on Swedish time series data
Artikel i vetenskaplig tidskrift, 2021

We demonstrate that finite impulse response (FIR) models can be applied to analyze the time evolution of an epidemic with its impact on deaths and healthcare strain. Using time series data for COVID-19-related cases, ICU admissions and deaths from Sweden, the FIR model gives a consistent epidemiological trajectory for a simple delta filter function. This results in a consistent scaling between the time series if appropriate time delays are applied and allows the reconstruction of cases for times before July 2020, when RT-PCR testing was not widely available. Combined with randomized RT-PCR study results, we utilize this approach to estimate the total number of infections in Sweden, and the corresponding infection-to-fatality ratio (IFR), infection-to-case ratio (ICR), and infection-to-ICU admission ratio (IIAR). Our values for IFR, ICR and IIAR are essentially constant over large parts of 2020 in contrast with claims of healthcare adaptation or mutated virus variants importantly affecting these ratios. We observe a diminished IFR in late summer 2020 as well as a strong decline during 2021, following the launch of a nation-wide vaccination program. The total number of infections during 2020 is estimated to 1.3 million, indicating that Sweden was far from herd immunity.


Andreas Wacker

Lunds universitet

Anna Jöud

Lunds universitet

Bo Bernhardsson

Department of Automatic Control

Philip Gerlee

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

F. Gustafsson

Linköpings universitet

Kristian Soltesz

Department of Automatic Control

Scientific Reports

2045-2322 (ISSN) 20452322 (eISSN)

Vol. 11 1 23963


Sannolikhetsteori och statistik

Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi



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