Innovative shortcuts and initiatives in primary health care for rural/remote localities: a scoping review on how to overcome the COVID-19 pandemic
Bibliographic record
Abstract
INTRODUCTION: The COVID-19 pandemic has emerged as one of the greatest challenges to societies, world health systems and science in the past century, making it imperative to restructure care networks. Therefore, it is essential to discuss the role and initiatives of primary health care (PHC) to deal with it. However, regarding the response to the pandemic, including the current global effort against COVID-19, the nuances of the rural/remote PHC context in the pandemic is barely visible. Rural and remote communities have differentiated health risks, such as socioeconomic disadvantages, difficulties in mobility and access to health services, in addition to linguistic and cultural barriers. This scoping review aimed to analyze the set of individual and collective initiatives and innovations developed to face the COVID-19 pandemic, within the PHC scope, in rural and remote areas. METHODS: A scoping review methodology was applied to peer-reviewed articles. Eight databases were searched to identify scientific articles published in English, Spanish and Portuguese, initially from January 2020 to July 2021, complemented by a rapid review of articles published from January 2022 to April 2023. The main focus sought in the literature was the set of initiatives and innovations carried out within the PHC scope in rural and remote locations during the pandemic, as well as the comparison with pre-pandemic situations and between different countries. The bibliographic information of each search result was imported into Rayyan (Intelligent Systematic Review), followed by the screening and eligibility stages, performed independently by two reviewers, with a third reviewer being accessed in case of conflicts. RESULTS: This review included 54 studies, with publications mostly from Australia, Canada, the US and India. The main PHC initiatives were related to access; to the roles of community health workers and health surveillance; and to the importance of placing, retaining and valuing human resources in health. Cultural, equity and vulnerability issues occupy a major place among the initiatives. Regarding the innovations, telehealth and customized communication are highlighted. From an organizational point of view, rural and remote locations showed enormous flexibility to deal with the pandemic and to improve intersectoral activities at the local level. The description of rurality and remoteness is practically coincident with that of the specific populations, present in geographic areas of difficult sociospatial and cultural access. Rarely, there is an index to measure rurality, or its description deals with the need to overcome distances and obstacles. CONCLUSION: The findings highlight and summarize knowledge about initiatives and innovations developed to face the COVID-19 pandemic, within the PHC scope in rural and remote areas in the world. This review has identified collective, clinical, intersectoral and, mainly, organizational health initiatives. An articulation between different government levels would be paramount in evaluating the implementation of policies and protocols in rural and remote locations for future sanitary crises. Innovations and lessons learned are equally relevant in strengthening health services and systems. This issue calls for considerable further exploration by new reviews and empirical research that seek evidence to assess the sustainability and effectiveness of the implemented measures to face post-pandemic difficulties and other adversities.
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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 | 0.016 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".