Evidence map›Paper›PMID 42150014›Full record

ArticleThe International journal of health planning and management2026

Economic Impact Evaluation of COVID-19 Public Health Management Across Countries.

Yunhao Wang, Yixuan Liu, Dongping Bai, Zhe Hu, Zhaoyang Shang, Wei Gao

Abstract read
In one paragraph

Article in The International journal of health planning and management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Yunhao WangSchool of Statistics and Data Science, Jilin University of Finance and Economics, Changchun, China.
Yixuan LiuSchool of Transportation, Jilin University, Changchun, China.
Dongping BaiLSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
Zhe HuKey Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun, China.
Zhaoyang ShangSchool of Accounting, Zhongnan University of Economics and Law, Wuhan, China.
Wei GaoKey Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun, China.ORCID https://orcid.org/0000-0003-0752-1602

Funding

National Natural Science Foundation of China 12371263
6 · The paper itself

Abstract

COVID-19 crisis has significantly impacted global economic growth. Assessing the economic impacts of various policies is crucial to better public health management (PHM). To incorporate specific PHM policies into a unified framework, prevention and control intensity (PCI) is introduced to quantify the intensity of PHM. Under different PCI, we construct a statistical framework to estimate each economy's counterfactual output, thereby providing two indicators to assess the effectiveness of PHM adopted by certain economies. Empirical analysis measures the effectiveness of PHM in each of the 137 economies during COVID-19 in 2020. Further analysis is conducted through robustness tests and regression discontinuity design. Aggregated results from 137 economies indicate that COVID-19 may have caused global economic losses far exceeding 5.47 trillion US dollars in 2020. Statistical indicators reveal that 39 economies reduced economic loss through PHM, while 25 economies achieved relatively ideal economic output targets. These findings suggest that moderate prevention and control measures can significantly reduce economic losses and highlight the necessity for most countries to strengthen their PHM strategies to enhance economic resilience and recovery.

Indexed as

COVID-19Public HealthPublic Health AdministrationHumansSARS-CoV-2counterfactual frameworkCOVID‐19economic impact evaluationprevention and control intensitypublic health management

Identifiers

PMID42150014
PMCPMC13551547

What OpenQuestion holds

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Registered trials

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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.