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Enregistrement W4296211395 · doi:10.1215/03616878-10171118

The Unequal Pandemic: COVID-19 and Health Inequalities

2022· article· en· W4296211395 sur OpenAlexaff
Daniel Béland

Notice bibliographique

RevueJournal of Health Politics Policy and Law · 2022
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueGlobal Public Health Policies and Epidemiology
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésPandemicCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)InequalityVirologyBetacoronavirusMedicineMathematicsOutbreakInfectious disease (medical specialty)DiseasePathology

Résumé

récupéré en direct d'OpenAlex

The relentless scholarly activity triggered by the COVID-19 crisis has already generated a large number of journal articles and a growing number of books that shed much light on the health effects of the pandemic as well as its social and policy effects. In The Unequal Pandemic, Clare Bambra, Julia Lynch, and Katherine E. Smith draw on the early scholarship on COVID-19 to improve our understanding of health inequality in the pandemic while offering a coherent political perspective on public health, leading to a clear call for action. Focusing primarily on advanced industrial countries, especially the United Kingdom and the United States, they show how the COVID-19 pandemic is highly unequal in four main ways.First, the “pandemic kills unequally” (XIII), as people living in certain neighborhoods and regions, members of ethno-racial minorities, and those belonging to certain occupational and income categories are more likely to die from COVID-19 than other, better-off people. In chapter 2, the authors stress the intersectional nature of these inequalities and their impact over time and across different pandemics, something illustrated by a short discussion of the Spanish flu pandemic of the early 20th century. This discussion of the inequality-mortality nexus during pandemics leads them to explain how “for the most disadvantaged communities, COVID-19 is experienced as a syndemic,” which “exists when risk factors or comorbidities are intertwined, interactive, and cumulative, adversely exacerbating the disease burden and additively increasing its negative effects” (28). Because people belonging to socioeconomically disadvantaged populations face chronic health conditions such as asthma and obesity more frequently and more severely, on average, than people belonging to socioeconomically populations, disadvantaged people are more likely to face complications or die from COVID-19 (28).Second, the “pandemic is experienced unequally” (XIV), as lockdowns have more negative impacts on low-income workers than on members of other income categories. In chapter 3, the authors stress the cross-national variation in lockdown policies adopted during the pandemic while showing how preexisting socioeconomic inequalities shape the ways in which these policies affect specific populations with regard to both physical and mental health. This analysis leads to a discussion of how the pandemic has exacerbated gender inequality in relationship to issues such as care, parenting, spousal violence, and work. In the same chapter, the authors also discuss the negative impact of unequal access to housing and green space before concluding that “those who were already economically disadvantaged have been further disadvantaged by the pandemic” (50), a reality that points to the continuity in socioeconomic patterns and policy legacies between the pre-COVID and post-COVID worlds.Third, the “pandemic impoverishes unequally” (XIV) as a result of the uneven geographical and social distribution of the negative economic impacts of the COVID-19 crisis in terms of unemployment and wage losses, among other things. In chapter 4, the authors turn to the disproportionate impact that the pandemic's economic shock has had on more vulnerable groups, such as women, young people, and ethno-racial minorities. Poverty and regional inequalities tended to increase during the COVID-19 recession, as they did during past recessions, a situation the authors illustrate by turning to the experience of the 2008 financial crisis, which illustrates how austerity policies enacted in response to economic crises can exacerbate inequality and favor a deterioration of the mental health status of increasingly stigmatized poor people living on social assistance.Fourth, the “pandemic inequalities are political” (XIV), as they are the result of contingent policy choices that could be discarded to leave room for more equalitarian economic, fiscal, and social programs. In chapter 5, the authors suggest that the COVID-19 crisis is not an unpredictable “black swan” but a highly predictable reality that reflects existing policy legacies and related patterns of inequality, which could have been altered through different policy choices. The enduring weight of policy legacies and the path dependencies they create over time are well illustrated by the literature on the welfare regimes—liberal, continental, and Nordic—that the authors turn to in the book's penultimate chapter. There is a clear link between the policy legacies embedded in a particular welfare regime and the patterns of health inequalities that are prevalent in countries using that regime. Although intraregime variation can be significant, the welfare regime literature suggests that contingent political choices matter over time, including during the COVID-19 crisis, where cross-national differences in policy responses typically vary from one welfare regime to the next. The importance of these political choices is stressed in chapter 6, which concludes the book on a hopeful note, as the authors suggest the pandemic is a potential window of opportunity for progressive political change, which they hope could occur through a set of reforms aimed at fighting inequalities spelled out in that chapter.Written rapidly during the first year of the pandemic and submitted to the publisher in early 2021, The Unequal Pandemic is a tour de force that is written in an accessible and compelling way. The fact that the book is so short and easy to read makes it the perfect complementary reading for undergraduate classes on public health and social policy, but seasoned scholars, graduate students, and informed readers from outside the ivory tower would certainly gain from reading and engaging with this book, which covers much ground and is surprisingly coherent, considering it was researched and written during such a short and intense period. This book is proof that scholars can respond rapidly to crises with sharp analyses and concrete policy proposals that contribute meaningfully to international policy conversations.This book only has a few limitations. First—and this is the other side of the coin of the book's timeliness—some of the material is quite speculative, as it was written so early during the pandemic. Second, the book devotes surprisingly little space to a discussion about the fate of older people, who have been hit especially hard by the pandemic, especially as far as hospitalization and mortality rates are concerned. In some countries, poor policy choices within long-term care systems also caused much suffering and many avoidable deaths in ways that are directly related to the policy legacies and the preexisting inequalities so central to the book's analysis. Because of all of this, one would have expected at least a short section or two on this dire reality and how it relates to both past political decisions and existing patterns of socioeconomic inequality. Finally, to this reader at least, the last chapter sometimes sounds a bit naïve about the “reasons to be hopeful” (114) about the pandemic: “COVID-19 may have ushered in a ‘new golden age’ of scientific expertise” (115), a claim potentially challenged by the rise of sizable antivax protests and viral conspiracy theories, which point to the ongoing importance—as well as the political vulnerability—of scientific expertise in the wake of the pandemic.Despite these critical remarks, The Unequal Pandemic is an excellent book that students of public heath and social policy should read and engage with as they assess responses to the COVID-19 pandemic and think about ways to fight inequalities in its wake.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,024
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,023
Score d'incertitude au seuil0,051

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,024
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0030,003
Études des sciences et des technologies0,0050,021
Communication savante0,0070,011
Science ouverte0,0010,011
Intégrité de la recherche0,0060,006
Charge utile insuffisante (le modèle a refusé de juger)0,0150,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,147
Tête enseignante GPT0,422
Écart entre enseignants0,274 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations118
Publié2022
Routes d'admission1
Résumé présentnon

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