Evidence map›Paper›PMID 35787511›Full record

ArticleBMJ global health2022

Coverage of social assistance in Ethiopia during the COVID-19 pandemic: a time-to-event analysis.

Ashwini Sunil Deshpande, Addis Kassahun Mulat, Wenhui Mao, Mohamed M Diab, Osondu Ogbuoji

Open access · goldAbstract read
In one paragraph

Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. COVID-19 impacts on healthcare access in sub-Saharan Africa: an overview.The journal of venomous animals and toxins including tropical diseases · 2023
    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

5 authors at 1 institution in 1 country.

Ashwini Sunil DeshpandeDuke Center for Policy Impact in Global Health, Duke Global Health Institute, Duke University, Durham, North Carolina, USA ashwinisunil.deshpande@duke.edu.ORCID 0000-0001-9842-989X
Addis Kassahun MulatConsulting, Kilimanjaro Trading, Addis Ababa, Ethiopia.
Wenhui MaoDuke Center for Policy Impact in Global Health, Duke Global Health Institute, Duke University, Durham, North Carolina, USA.ORCID 0000-0001-9214-7787
Mohamed M DiabDuke Center for Policy Impact in Global Health, Duke Global Health Institute, Duke University, Durham, North Carolina, USA.
Osondu OgbuojiDuke Center for Policy Impact in Global Health, Duke Global Health Institute, Duke University, Durham, North Carolina, USA.
Duke University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveIn a pandemic, government assistance is essential to support the most vulnerable households as they face health and economic challenges. However, government assistance is effective only when it reaches vulnerable households in time. In this paper, we estimated the timeliness of government assistance for the most vulnerable households (ie, the poor households) in Ethiopia during its COVID-19 response of 2020. In particular, we conducted a time-to-event analysis to compare the time to receive government assistance between poor and non-poor households in Ethiopia.

methodsWe used a semiparametric Cox proportional model to evaluate whether the time to first receipt of government assistance during the COVID-19 response in 2020 differed between poor and non-poor Ethiopian households. We used the Schoenfeld test to check the proportionality assumption and conducted the stratified Cox regression analysis to adjust for non-proportional variables. The data from World Bank's High-Frequency Phone Surveys on COVID-19 and the 2019 Ethiopian Socioeconomic Survey were used for this analysis.

resultsWe found that the poor households in rural areas were 88% (HR: 1.88; 95% CI: 1.19 to 2.98) more likely to receive government assistance than non-poor households at any point within 10 months after the start of the pandemic. However, there was no significant difference between urban poor and non-poor households' likelihood of receiving government assistance during this timeframe.

conclusionThe Ethiopian government has leveraged its existing social protection network to quickly reach poor households in rural areas during the COVID-19 response of 2020. The country will need to continue strengthening and scaling the existing social protection systems to accurately target the wider vulnerable population in urban areas.

Indexed as

COVID-19Cross-Sectional StudiesEthiopiaFamily CharacteristicsHumansPandemicsCOVID-19Health policy

Identifiers

PMID35787511
PMCPMC9254660
OpenAlexW4283816909

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.