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Record W4309875105 · doi:10.1016/j.hpopen.2022.100086

Examining priority setting in the national COVID-19 pandemic plans: A case study from countries in the WHO- South-East Asia Region (WHO-SEARO)

2022· article· en· W4309875105 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHealth Policy OPEN · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsWestern UniversityPublic Health OntarioMcMaster University
FundersMcMaster University
KeywordsPreparednessPandemicContext (archaeology)Coronavirus disease 2019 (COVID-19)StakeholderSample (material)GeographyQuality (philosophy)East AsiaBusinessPolitical scienceEconomic growthMedicineChinaEconomicsPublic relationsDisease

Abstract

fetched live from OpenAlex

Background: The World Health Organization- South-East Asia Region (WHO-SEARO) accounted for almost 17% of all the confirmed cases and deaths of COVID-19 worldwide. While the literature has documented a weak COVID-19 response in the WHO-SEARO, there has been no discussion of the degree to which this could have been influenced/ mitigated with the integration of priority setting (PS) in the region's COVID-19 response. The purpose of this paper is to describe the degree to which the COVID-19 plans from a sample of WHO-SEARO countries included priority setting. Methods: The study was based on an analysis of national COVID-19 pandemic response and preparedness planning documents from a sample of seven (of the eleven) countries in WHO-SEARO. We described the degree to which the documented priority setting processes adhered to twenty established quality indicators of effective PS and conducted a cross-country comparison. Results: All of the reviewed plans described the required resources during the COVID-19 pandemic. Most, but not all of the plans demonstrated political will, and described stakeholder involvement. However, none of the plans presented a clear description of the PS process including a formal PS framework, and PS criteria. Overall, most of the plans included only a limited number of quality indicators for effective PS. Discussion and conclusion: There was wide variation in the parameters of effective PS in the reviewed plans. However, there were no systematic variations between the parameters presented in the plans and the country's economic, health system and pandemic and PS context and experiences. The political nature of the pandemic, and its high resource demands could have influenced the inclusion of the parameters that were apparent in all the plans. The finding that the plans did not include most of the evidence-based parameters of effective PS highlights the need for further research on how countries operationalize priority setting in their respective contexts as well as deeper understanding of the parameters that are deemed relevant. Further research should explore and describe the experiences of implementing defined priorities and the impact of this decision-making on the pandemic outcomes in each country.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.079
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0790.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.715
GPT teacher head0.552
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it