Evidence map›Paper›PMID 36537837›Full record

ArticleGlobal health action2023

Community engagement and involvement in managing the COVID-19 pandemic among urban poor in low-and middle-income countries: a systematic scoping review and stakeholders mapping.

Krushna Chandra Sahoo, Mili Roopchand Sahay, Shubhankar Dubey, Subhasish Nayak, Sapna Negi, Pranab Mahapatra, Debdutta Bhattacharya, Mariam Otmani Del Barrio, Sanghamitra Pati

Open access · goldAbstract readScoping Review
In one paragraph

Article in Global health action, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
6.3field-weighted citation impact, top 3% 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, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.

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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

9 authors at 3 institutions in 2 countries.

Krushna Chandra SahooHealth Technology Assessment in India (HTAIn), ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.ORCID 0000-0003-3504-6132
Mili Roopchand SahayHealth Technology Assessment in India (HTAIn), ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.ORCID 0000-0003-0123-3431
Shubhankar DubeyHealth Technology Assessment in India (HTAIn), ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.ORCID 0000-0002-6184-6662
Subhasish NayakHealth Technology Assessment in India (HTAIn), ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.ORCID 0000-0003-2911-1890
Sapna NegiHealth Technology Assessment in India (HTAIn), ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.ORCID 0000-0002-6432-6830
Pranab MahapatraDepartment of Psychiatry, Kalinga Institute of Medical Sciences, Bhubaneswar, Odisha, India.ORCID 0000-0002-3736-4268
Debdutta BhattacharyaHealth Technology Assessment in India (HTAIn), ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.ORCID 0000-0001-5199-5288
Mariam Otmani Del BarrioUNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, Geneva, Switzerland.
Sanghamitra PatiHealth Technology Assessment in India (HTAIn), ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.ORCID 0000-0002-7717-5592
Regional Medical Research Centre · INAll India Institute of Medical Sciences Bhubaneswar · INWorld Health Organization · CH

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundCommunity engagement and involvement (CEI) was crucial for the COVID-19 pandemic response, particularly among the urban poor in low-and middle-income countries (LMICs). However, no evidence synthesis explores how CEI can benefit public health emergencies.

objectiveWe conducted a systematic scoping review of the CEI with an emphasis on stakeholder identification, accountability mapping, the support system, and the engagement process among urban poor populations in LMICs during the COVID-19 pandemic.

methodsWe searched eleven databases, including PubMed, Embase, Web of Science, and CINAHL, following the PRISMA-2020 guidelines to find articles published between November 2019 and August 2021. PROSPERO registration No: CRD42021283599. We performed the quality assessment using a mixed-method appraisal tool. We synthesized the findings using thematic framework analysis.

resultsWe identified 6490 records. After the title and abstract screening, 133 studies were selected for full-text review, and finally, we included 30 articles. Many stakeholders were involved in COVID-19 support, particularly for health care, livelihoods, and WASH infrastructure, and their accountability mapping by adopting an interest - influence matrix. This review emphasizes the significance of meaningful CEI in designing and implementing public health efforts for pandemic management among urban slum populations. The interest - influence matrix findings revealed that specific community volunteers, community-based organizations, and civil society organizations had high interest but less influence, indicating that it is necessary to recognize and engage them.

conclusionMotivation is crucial for those with high influence but less interest, such as corporate responsibility/conscience and private food supply agencies, for the health system's preparedness plan among urban populations.

Indexed as

COVID-19Developing CountriesCommunity ParticipationDelivery of Health CareHumansPandemicsCommunity engagement and involvementCOVID-19low-and middle-income countriesstakeholder mappingurban-poor

Identifiers

PMID36537837
PMCPMC9769144
OpenAlexW4312082046

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.