Evidence map›Paper›PMID 34735496›Full record

ArticlePloS one2021

Social protection and informality in Latin America during the COVID-19 pandemic.

Matias Busso, Juanita Camacho, Julián Messina, Guadalupe Montenegro

Abstract read
In one paragraph

Article in PloS one, 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
–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

12 citing papers in PubMed.

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  12. Analysis of working and health conditions in street vendors of Bogotá, Colombia, in the context of the COVID-19 pandemic.Revista brasileira de medicina do trabalho : publicacao oficial da Associacao Nacional de Medicina do Trabalho-ANAMT
    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

4 authors.

Matias BussoResearch Department, Inter-American Development Bank, Washington, DC, United States of America.
Juanita CamachoResearch Department, Inter-American Development Bank, Washington, DC, United States of America.
Julián MessinaResearch Department, Inter-American Development Bank, Washington, DC, United States of America.ORCID 0000-0002-3635-499X
Guadalupe MontenegroResearch Department, Inter-American Development Bank, Washington, DC, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Latin American governments swiftly implemented income assistance programs to sustain families' livelihoods during COVID-19 stay-at-home orders. This paper analyzes the potential coverage and generosity of these measures and assesses the suitability of current safety nets to deal with unexpected negative income shocks in 10 Latin American countries. The expansion of pre-existing programs (most notably conditional cash transfers and non-contributory pensions) during the COVID-19 crisis was generally insufficient to compensate for the inability to work among the poorest segments of the population. When COVID-19 ad hoc programs are analyzed, the coverage and replacement rates of regular labor income among households in the first quintile of the country's labor income distribution increase substantially. Yet, these programs present substantial coverage challenges among families composed of fundamentally informal workers who are non-poor, but are at a high risk of poverty. These results highlight the limitations of the fragmented nature of social protection systems in the region.

Indexed as

SARS-CoV-2Social WelfareSocioeconomic FactorsCOVID-19Developing CountriesEmergenciesFamily CharacteristicsHumansIncomeLatin AmericaPandemicsPensionsPhysical DistancingPublic Policy

Identifiers

PMID34735496
PMCPMC8568185

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.