Lessons learned from the polio eradication initiative in the Democratic Republic of Congo and Ethiopia: analysis of implementation barriers and strategies
Bibliographic record
Abstract
BACKGROUND: Since its inception in 1988, the Global Polio Eradication Initiative (GPEI) has partnered with 200 countries to vaccinate over 2.5 billion children against poliomyelitis. The polio eradication approach has adapted to emerging challenges and diverse contexts. Knowledge assets gained from these experiences can inform implementation of future health programs, but only if efforts are made to systematically map barriers, identify strategies to overcome them, identify unintended consequences, and compare experiences across country contexts. METHODS: A sequential explanatory mixed methods design, including an online survey followed by key informant interviews (KIIs), was utilized to map tacit knowledge derived from the polio eradication experience from 1988 to 2019. The survey and KIIs were conducted between September 2018 and March 2019. A cross-case comparison was conducted of two study countries, the Democratic Republic of Congo (DRC) and Ethiopia, which fit similar epidemiological profiles for polio. The variables of interest (implementation barriers, strategies, unintended consequences) were compared for consistencies and inconsistencies within and across the two country cases. RESULTS: Surveys were conducted with 499 and 101 respondents, followed by 23 and 30 KIIs in the DRC and Ethiopia, respectively. Common implementation barriers included accessibility issues caused by political insecurity, population movement, and geography; gaps in human resources, supply chain, finance and governance; and community hesitancy. Strategies for addressing these barriers included adapting service delivery approaches, investing in health systems capacity, establishing mechanisms for planning and accountability, and social mobilization. These investments improved system infrastructure and service delivery; however, resources were often focused on the polio program rather than strengthening routine services, causing community mistrust and limiting sustainability. CONCLUSIONS: The polio program investments in the DRC and Ethiopia facilitated program implementation despite environmental, system, and community-level barriers. There were, however, missed opportunities for integration. Remaining pockets of low immunization coverage and gaps in surveillance must be addressed in order to prevent importation of wild poliovirus and minimize circulating vaccine-derived poliovirus. Studying these implementation processes is critical for informing future health programs, including identifying implementation tools, strategies, and principles which can be adopted from polio eradication to ensure health service delivery among hard-to-reach populations. Future disease control or eradication programs should also consider strategies which reduce parallel structures and define a clear transition strategy to limit long-term external dependency.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".