American Indian/Alaska Native community infrastructure limitations amid the COVID-19 threat
Notice bibliographique
Résumé
Objective: The recent SARS-CoV-2 (COVID-19) pandemic that is spreading throughout the nation is a particular threat to American Indian and Alaska Native (AI/AN) communities. The use of recommended methods to prevent or mitigate the spread of the virus, such as hand washing, social distancing, masks, contact tracing and community education is highly problematic at many of these sites. The objective of this paper is to identify and examine structural or cultural barriers to implementing COVID-19 recommendations on select reservation sites.Methods: A qualitative approach that collected and analyzed data from existing sources including newsletter articles, relevant policies and other published reports was instituted in the Spring of 2020. The Centers for Disease Control and Prevention (CDC) policies regarding COVID-19 recommendations to halt the spread of the virus were selected as the standard for COVID-19 prevention, surveillance and mitigation. News articles between March 1, 2020 and December 1, 2020 were identified using various search engines and tribal websites. Information from news resources, including literature reviews, newsletter articles, social media reports, and tribal policy announcements, were gathered and reviewed. Two U.S. southwestern communities are used as examples for the review.Results: Data collected from various sources paint a picture of American Indian communities that lack adequate community infrastructures, and have problems of residential isolation, close living quarters, and contaminated and scarce water supplies. Unsafe or limited water restricts handwashing. Limited informational tools, such as telephone, internet, computer and newsletters, restricted adequate notification of the novel coronavirus to American Indian reservation communities. Often, the lack of a physical home address can create barriers to healthcare accessibility and surveillance, as it limits the identification and access to households. In addition, many traditional cultures of AI/ANs emphasize the interrelatedness of all in nature and thus require an ecological approach to health education and preventive measures, identified as a limitation for COVID-19 surveillance and mitigation.Conclusions: AI/AN communities face a serious threat of contracting COVID-19. Four key infrastructure limitations to effective COVID-19 prevention, surveillance and mitigation were identified: limited access to safe water, deficient telecommunication networks (telephone, internet, and television), housing isolation and shortages, and inadequate medical services – are experienced by many AI/AN communities. Although there are 574 federally recognized tribes in the United States, the two identified in this study subscribe to an ecological approach to health education and preventive measures in that they believe in the interrelatedness of all things in nature. Surveillance questions may be misunderstood or seem invasive and prevention measures (masks, social distancing, and handwashing) may seem to be extreme measures to groups so close to the environment. Together, these present serious barriers to prevention and mitigation of the COVID-19 virus in this underserved population.
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 | 0,004 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
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 ».