Evidence map›Paper›PMID 33558783›Full record

ArticleJournal of mathematical economics2021

The optimal lockdown intensity for COVID-19.

Jonathan P Caulkins, Dieter Grass, Gustav Feichtinger, Richard F Hartl, Peter M Kort, Alexia Prskawetz, Andrea Seidl, Stefan Wrzaczek

Abstract read
In one paragraph

Article in Journal of mathematical economics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Path integral control of a stochastic multi-risk SIR pandemic model.Theory in biosciences = Theorie in den Biowissenschaften · 2023
    Article
  10. Optimal timing of non-pharmaceutical interventions during an epidemic.European journal of operational research · 2023
    Article
  11. Intervention uncertainty, household health, and pandemic.Journal of mathematical economics · 2023
    Article
  12. Optimal vaccination strategies using a distributed model applied to COVID-19.Central European journal of operations research · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jonathan P CaulkinsHeinz College, Carnegie Mellon University, 4800 Forbes Avenue, Pittsburgh PA 15213, USA.
Dieter GrassInternational Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, 2361 Laxenburg, Austria.
Gustav FeichtingerDepartment for Operations Research and Control Systems, Institute of Statistics and Mathematical Methods in Economics, TU Wien, Wiedner Hauptstraße 8, 1040 Vienna, Austria.
Richard F HartlDepartment of Business Decisions and Analytics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria.
Peter M KortTilburg School of Economics and Management, Tilburg University, Warandelaan 2, 5037 AB Tilburg, Netherlands.
Alexia PrskawetzResearch Group Economics, Institute of Statistics and Mathematical Methods in Economics, TU Wien, Wiedner Hauptstraße 8, 1040, Austria.
Andrea SeidlDepartment of Business Decisions and Analytics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria.
Stefan WrzaczekWittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna), Vordere Zollamtsstraße 3, 1030 Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the principal ways nations are responding to the COVID-19 pandemic is by locking down portions of their economies to reduce infectious spread. This is expensive in terms of lost jobs, lost economic productivity, and lost freedoms. So it is of interest to ask: What is the optimal intensity with which to lockdown, and how should that intensity vary dynamically over the course of an epidemic? This paper explores such questions with an optimal control model that recognizes the particular risks when infection rates surge beyond the healthcare system's capacity to deliver appropriate care. The analysis shows that four broad strategies emerge, ranging from brief lockdowns that only "smooth the curve" to sustained lockdowns that prevent infections from spiking beyond the healthcare system's capacity. Within this model, it can be optimal to have two separate periods of locking down, so returning to a lockdown after initial restrictions have been lifted is not necessarily a sign of failure. Relatively small changes in judgments about how to balance health and economic harms can alter dramatically which strategy prevails. Indeed, there are constellations of parameters for which two or even three of these distinct strategies can all perform equally well for the same set of initial conditions; these correspond to so-called triple Skiba points. The performance of trajectories can be highly nonlinear in the state variables, such that for various times

Indexed as

COVID-19LockdownOptimal controlSIR modelSkiba threshold

Identifiers

PMID33558783
PMCPMC7857053

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.