A scoping review of strategies to support public health recovery in the transition to a “new normal” in the age of COVID-19
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, the public health workforce has experienced re-deployment from core functions such as health promotion, disease prevention, and health protection, to preventing and tracking the spread of COVID-19. With continued pandemic deployment coupled with the exacerbation of existing health disparities due to the pandemic, public health systems need to re-start the delivery of core public health programming alongside COVID-19 activities. The purpose of this scoping review was to identify strategies that support the re-integration of core public health programming alongside ongoing pandemic or emergency response. METHODS: The Joanna Briggs Institute methodology for scoping reviews was used to guide this study. A comprehensive search was conducted using: a) online databases, b) grey literature, c) content experts to identify additional references, and d) searching reference lists of pertinent studies. All references were screened by two team members. References were included that met the following criteria: a) involved public health organizations (local, regional, national, and international); b) provided descriptions of strategies to support adaptation or delivery of routine public health measures alongside disaster response; and c) quantitative, qualitative, or descriptive designs. No restrictions were placed on language, publication status, publication date, or outcomes. Data on study characteristics, intervention/strategy, and key findings were independently extracted by two team members. Emergent themes were established through independent inductive analysis by two team members. RESULTS: Of 44,087 records identified, 17 studies were included in the review. Study designs of included studies varied: descriptive (n = 8); qualitative (n = 4); mixed-methods (n = 2); cross-sectional (n = 1); case report (n = 1); single-group pretest/post-test design (n = 1). Included studies were from North America (n = 10), Africa (n = 4), and Asia (n = 3) and addressed various public health disasters including natural disasters (n = 9), infectious disease epidemics (n = 5), armed conflict (n = 2) and hazardous material disasters (n = 1). Five emergent themes were identified on strategies to support the re-integration of core public health services: a) community engagement, b) community assessment, c) collaborative partnerships and coordination, d) workforce capacity development and allocation, and e) funding/resource enhancement. CONCLUSION: Emergent themes from this study can be used by public health organizations as a beginning understanding of strategies that can support the re-introduction of essential public health services and programs in COVID-19 recovery.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.044 | 0.138 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.030 | 0.028 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".