Stricter containment policies in the second quarter of 2021 are associated with lower excess mortality
Notice bibliographique
Résumé
In the wake of the COVID-19 pandemic, societies and health systems in Latin America and the Caribbean (LAC) continue to face large-scale threats with far-reaching consequences for the health and well-being of its population.More than ever, health systems in the region need to be strengthened to not only deliver high performance in typical times, but also to be resilient against major shocks, such as pandemics, the effects of climate change, or financial crises.While the pandemic laid bare the vulnerabilities of even the most highly funded and well-prepared health systems in high-income OECD countries, the tragic health outcomes of COVID-19 in the LAC region were in large part associated with structural limitations and chronic underinvestment in health.LAC countries had to tackle COVID-19 with far fewer doctors, nurses, and hospital beds than the average of OECD countries.In such context, while policy responses mitigated the loss of many lives in the region, in 2020 and 2021 there were still 2.3 million more deaths in LAC than was expected for those years in absence of the pandemic.Furthermore, the weaknesses of the health systems in LAC were further compounded by a range of social challenges, including high levels of poverty, income inequality, and labour informality; large swaths of the population living in informal settlements without access to essential services; and the growing threats to the region's rich ecosystems that also affect the populations that are most directly integrated with them.The consequences of climate change add a layer of complexity to health systems in a geographically diverse region, which includes high-altitude mountains and glaciers, the world's largest tropical rainforest, several small island nations, and megalopolises with tens of millions of people each.Health systems in the region must prepare for changing patterns of infectious diseases, exposure to extreme temperatures and catastrophic weather events, and rising sea levels, or risk dire consequences for societies in the region.In the face of these multiple challenges, it is imperative to develop effective health strategies that consider the complex realities of the LAC region.The limited budget available for health in the region makes the task of providing high-quality health services more challenging, requiring innovative solutions that are based on data, evidence, and the best ideas.However, the investments that were needed to strengthen health systems are a fraction of what the pandemic cost the economies of LAC countries.Similarly, making health systems in the region greener and resilient to face the challenges of climate change is urgent.As we move forward, more and better investment in health will be necessary in order to ensure that the health requirements of the population are met with greater efficiency and focused on people's needs.This volume, jointly prepared by the OECD and the World Bank, aims to offer an important contribution to these efforts by combining a retrospective analysis of lessons to be learned from the response to the pandemic in the region with a prospective look at how health systems can prepare for the future challenge of climate change.It further brings together the most complete and up-to-date set of data and indicators on all aspects of health systems in the LAC region.The OECD and the World Bank will continue to work together and reach out to key partners, such as the Pan-American Health Organization, to support governments and societies in the region to improve the performance of their health systems.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,003 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».