Evidence map›Paper›PMID 34521433›Full record

ArticleInternational journal for equity in health2021

PREparedness, REsponse and SySTemic transformation (PRE-RE-SyST): a model for disability-inclusive pandemic responses and systemic disparities reduction derived from a scoping review and thematic analysis.

Tiago S Jesus, Sureshkumar Kamalakannan, Sutanuka Bhattacharjya, Yelena Bogdanova, Juan Carlos Arango-Lasprilla, Jacob Bentley, Michel D Landry, Christina Papadimitriou, Refugee Empowerment Task Force and International Networking Group of the American Congress of Rehabilitation Medicine

Abstract readScoping Review
In one paragraph

Article in International journal for equity in health, 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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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.

Tiago S JesusGlobal Health and Tropical Medicine (GHTM) & WHO Collaborating Centre for Health Workforce Policy and Planning, Institute of Hygiene and Tropical Medicine - NOVA University of Lisbon, Lisbon, Portugal.
Sureshkumar KamalakannanPublic Health Foundation of India (PHFI), South Asia Centre for Disability Inclusive Development and Research (SACDIR), Indian Institute of Public Health - Hyderabad (IIPH-H), Hyderabad, India. suresh.kumar@iiphh.org.ORCID 0000-0001-6970-4952
Sutanuka BhattacharjyaDepartment of Occupational Therapy, Byrdine F. Lewis College of Nursing and Health Professions, Georgia State University, Atlanta, USA.
Yelena BogdanovaPhysical Medicine & Rehabilitation Service, VA Boston Healthcare System, Boston, MA, USA.
Juan Carlos Arango-LasprillaIKERBASQUE. Basque Foundation for Science, Bilbao, Spain.
Jacob BentleyDepartment of Clinical Psychology Seattle Pacific University, Seattle WA, USA.
Michel D LandryDuke Global Health Institute (DGHI), School of Medicine, Duke University, Durham, NC, USA.
Christina PapadimitriouSchool of Health Sciences, Departments of Interdisciplinary Health Sciences, and Sociology, Oakland University, Rochester, MI, USA.
Refugee Empowerment Task Force and International Networking Group of the American Congress of Rehabilitation Medicine

Funding

DBT-Wellcome Trust India Alliance IA/CPHE/16/1/502650The Wellcome Trust DBT India Alliance IA/CPHE/16/1/502650
6 · The paper itself

Abstract

backgroundPeople with disabilities (PwD) have been facing multiple health, social, and economic disparities during the COVID-19 pandemic, stemming from structural disparities experienced for long time. This paper aims to present the PREparedness, RESponse and SySTemic transformation (PRE-RE-SyST): a model for a disability-inclusive pandemic responses and systematic disparities reduction.

methodsScoping review with a thematic analysis was conducted on the literature published up to mid-September 2020, equating to the initial stages of the COVID-19 pandemic. Seven scientific databases and three preprint databases were searched to identify empirical or perspective papers addressing health and socio-economic disparities experienced by PwD as well as reporting actions to address them. Snowballing searches and experts' consultation were also conducted. Two independent reviewers made eligibility decisions and performed data extractions on any action or recommended action to address disparities. A thematic analysis was then used for the model construction, informed by a systems-thinking approach (i.e., the Iceberg Model).

resultsFrom 1027 unique references, 84 were included in the final analysis. The PRE-RE-SyST model articulates a four-level strategic action to: 1) Respond to prevent or reduce disability disparities during a pandemic crisis; 2) Prepare ahead for pandemic and other crises responses; 3) Design systems and policies for a structural disability-inclusiveness; and 4) Transform society's cultural assumptions about disability. 'Simple rules' and literature-based examples on how these strategies can be deployed are provided.

conclusionThe PRE-RE-SyST model articulates main strategies, 'simple rules' and possible means whereby public health authorities, policy-makers, and other stakeholders can address disability disparities in pandemic crises, and beyond. Beyond immediate pandemic responses, disability-inclusiveness is needed to develop everyday equity-oriented policies and practices that can transform societies towards greater resiliency, as a whole, to pandemic and other health and social emergencies.

Indexed as

COVID-19PandemicsPersons with DisabilitiesPublic Health PracticeHealth Status DisparitiesHumansModels, OrganizationalCOVID-19Disabled personsHealth equityPublic healthSocial determinants of health

Identifiers

PMID34521433
PMCPMC8438560

What OpenQuestion holds

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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.