Evidence map›Paper›PMID 40477531›Full record

ArticleJournal of the knowledge economy2023

How the COVID-19 Pandemic Affected Developing Countries: the Tunisian Investigation.

Mohamed Ali Labidi

Abstract read
In one paragraph

Article in Journal of the knowledge economy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

1 author.

Mohamed Ali LabidiLaboratory of Valorization of Natural and Cultural Heritage, University of Jendouba, Jendouba, Tunisia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The consequences of COVID-19 vary considerably from country to country and from sector to sector. In this paper, we examine how employment in sectors of Tunisian economy is being affected by the COVID-19 pandemic. For this purpose, we apply the Markov chain approach. This method has the merit to model a system that changes states according to a transition rule that depends only on the current state. We find that the COVID-19 have a negative impact on the employment in industry and in service. Moreover, the agricultural sector benefits most from COVID-19. It is important to plan for economic measures in order to support the resilience of economic establishments, particularly small- and medium-sized enterprises.

Indexed as

AgricultureCOVID-19EmploymentIndustryMarkov chainsTunisia

Identifiers

PMID40477531
PMCPMC8739550

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.