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Enregistrement W4383652616 · doi:10.1093/eurpub/ckad114

No country is safe from a pandemic: insights into small countries’ COVID-19 experiences

2023· editorial· en· W4383652616 sur OpenAlexaff
Sarah Cuschieri, Dritan Bejko, Saverio Stranges

Notice bibliographique

RevueEuropean Journal of Public Health · 2023
Typeeditorial
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueCOVID-19 Pandemic Impacts
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)BetacoronavirusDevelopment economicsEconomic growthGeographyVirologyPolitical scienceMedicineBusinessEconomicsOutbreakInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

The end of 2019—beginning of 2020 imposed unprecedented stress on every country as the severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) spread across the globe resulting in the Coronavirus 2019 (COVID-19) pandemic. Every country, large and small, fell victim to this burden resulting in governments instituting various mitigation measures to curb the viral spread and protect their population. Small countries, defined as having 2 million or less inhabitants, are regularly overlooked in public health circles and considered featuring similar characteristics as larger countries but at a smaller scale. While this may be true for some aspects, small countries face unique challenges and advantages related to public health governance, healthcare services delivery and economic sustainability. The COVID-19 pandemic is a great example to highlight these factors, while bringing forward lessons learnt that may be translated as crucial evidence for future pandemic preparedness. During the first COVID-19 wave, small countries fared well with low case numbers and fatalities, attributed to the swift implementation of restrictions including lockdowns and closure of borders, especially feasible for island states.1,2 In addition, the reliance on centralized public health systems in most small countries allows for more rapid and coordinated responses, as compared to larger countries often characterized by decentralization and fragmentation of healthcare and surveillance systems.2 Small counties share additional advantageous characteristics that potentially provided the upper hand in the pandemic preparedness including the ease of seeking information transnationally. Public health professionals sit on multiple international round table discussions which provides them with a large network of contacts.3 The geographical size of these countries enables public health systems to adopt swiftly to deal with a crisis including a pandemic. Although small countries face limited public health resources and are highly susceptible to system overwhelm including hospital capacity.2 This results in shifting public health strategies from containment to mitigation,2 with high probability of viral resurgence once restrictions are eased. Tourism plays a crucial role for most small countries, especially those with limited natural resources, for sustainability of their economy, healthcare systems along with other public services.2 Therefore, the closure of borders, airports and seaports (in islands) as part of the COVID-19 restrictions negatively impacted on small countries’ economic sector. This led to an urgency to lift COVID-19 measures as cases subsided, to open the tourism sector. It was anticipated that such actions will induce COVID-19 resurgence. However, those choosing to abruptly lift measures experienced an early increase in case load and mortality burden.1,2 Consequently, instead of luring tourists towards the country, the tourism sector suffered a blow due to the spike in COVID-19 incidence. However, for small countries, whose economy could rely on good budgetary margins, with a strong component of tertiary sector mainly business, financial and communication services it was easier to cope with the pandemic shock and the new working environment imposed by the restrictions. Dependency on neighbour larger countries for goods and workforce is another struggle experienced by small countries especially during COVID-19 lockdown periods. This is vital if an important part of the essential workforce, including hospital and primary care health professionals, are cross border workers. Indeed, one may argue the effectiveness of such measures as landlocked small countries were observed to have experienced similar epidemiological trends as that of their larger country/countries neighbours.1 Although this highlights the importance of cross-country governance and the need for countries not to work in silos. Clear communication between authorities and the public was imperative to ascertain the population follows mandates and later to get inoculated with COVID-19 vaccination. Small countries’ public health authorities have direct contact with central government which limits their public communication independency with the narrative commonly deviated towards the ruling government, irrespective whether it is for the population’s health benefit.4 COVID-19 vaccine access differed across small countries, with those forming part of the European Union procurement agreement having earlier access to approved vaccines.1,5 Procurement of vaccines varied for the rest of the small countries, some undertaking direct agreements with vaccines’ companies, while others relaying on their neighbouring countries.1,5 Although similar vaccination strategies and campaigns were implemented across small European countries, with an overall successful vaccination population coverage even if countries struggled to vaccinate individuals with restricted mobility that could not easily reach the vaccination sites.5 The pandemic challenged every country irrespective of the country size, yet small countries experienced additional hardships pertaining to their ‘smallness’, that is typically overlooked when transnational agendas are formulated. Despite this, it is evident that swift implementation of measures and dissemination of unilateral authorities’ communication to the public are advantages characteristics that could be executed across any country, small or large. Conflicts of interest: None declared.

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)0,008
score de la tête « metaresearch » (Gemma)0,036
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,044

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,036
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0030,004
Communication savante0,0090,007
Science ouverte0,0010,002
Intégrité de la recherche0,0060,008
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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 Opus0,112
Tête enseignante GPT0,323
Écart entre enseignants0,210 · 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'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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