ArticleJournal of econometrics2021
Sparse HP filter: Finding kinks in the COVID-19 contact rate.
Article in Journal of econometrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- The spread of COVID-19 in London: Network effects and optimal lockdowns.Journal of econometrics · 2023Article
- How many asymptomatic cases were unconfirmed in the US COVID-19 pandemic? The evidence from a serological survey.Chaos, solitons, and fractals · 2022Article
- Modeling and forecasting the COVID-19 pandemic with heterogeneous autoregression approaches: South Korea.Results in physics · 2021Article
- Discussion on selecting the number of breaks in the pattern of spread of COVID-19 (a reply to Zhao and Liang).International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we estimate the time-varying COVID-19 contact rate of a Susceptible-Infected-Recovered (SIR) model. Our measurement of the contact rate is constructed using data on actively infected, recovered and deceased cases. We propose a new trend filtering method that is a variant of the Hodrick-Prescott (HP) filter, constrained by the number of possible kinks. We term it the
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