Evidence map›Paper›PMID 34908825›Full record

ArticleJournal of public economic theory2021

COVID-19 epidemic and mitigation policies: Positive and normative analyses in a neoclassical growth model.

Luca Gori, Piero Manfredi, Simone Marsiglio, Mauro Sodini

Open access · hybridAbstract read
In one paragraph

Article in Journal of public economic theory, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
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

12 citing papers in PubMed, 30 citations in OpenAlex.

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  7. Vaccine and inclusion.Journal of public economic theory · 2022
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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

4 authors at 2 institutions in 2 countries.

Luca GoriDepartment of Law University of Pisa Pisa PI Italy.ORCID 0000-0003-1967-0840
Piero ManfrediDepartment of Economics and Management University of Pisa Pisa PI Italy.
Simone MarsiglioDepartment of Economics and Management University of Pisa Pisa PI Italy.ORCID 0000-0003-2540-4338
Mauro SodiniDepartment of Law University of Naples 'Federico II' Naples NA Italy.
University of Pisa · ITVSB - Technical University of Ostrava · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic is still ravaging the planet, but its (short-, medium-, and long-term) diverse effects on health, economy, and society are far from being understood. This article investigates the potential impact of a deadly epidemic and its main nonpharmaceutical control interventions (social distancing vs. testing-tracing-isolation, TTI) on capital accumulation and economic development at different time scales. This is done by integrating an epidemiological susceptible-infectious-recovered model with a Solow-type growth model including public expenditure, as a parsimonious setting to offer insights on the trade-off between protecting human lives and the economy and society. The work clarifies (i) the long-term interactions amongst a deadly infection, demography, and capital accumulation, (ii) the lack of viability of persistent social distancing measures also using an analytical characterization, and the threat of policy-enhanced COVID-19 endemicity, (iii) the potentially high return on investments in TTI activities to avoid future lockdowns and related capital disruption. It also quantifies the welfare effects of a range of policies, confirming a counterintuitive role for tax-funded preventive investments aimed at strengthening TTI as more desirable interventions than generalized lockdowns.

Identifiers

PMID34908825
PMCPMC8661658
OpenAlexW3208183980

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.