Rapid Qualitative Approaches in Pandemic Research: Protocol for an Exploratory Qualitative Multimethod Study (VERDIQual) on Mpox in Italy, Nigeria, Thailand, and the United Kingdom
Bibliographic record
Abstract
BACKGROUND: Recent mpox outbreaks have underscored significant gaps in global preparedness for emerging and re-emerging infections. These outbreaks have disproportionately affected vulnerable and marginalized populations, exposing the weaknesses of health systems, particularly in resource-limited settings. The global spread of mpox beyond endemic African countries in 2022 and the emergence of a new Clade Ib in 2024 emphasize the pressing need for comprehensive and context-specific public health responses. We outline the protocol for an innovative multimethod qualitative study (VERDIQual [SARS-CoV-2 (and Mpox) Variants Evaluation in Pregnancy and Paediatrics Cohorts Qualitative Study]). This study is being conducted across 4 different countries and settings-Italy, Nigeria, Thailand, and the United Kingdom. OBJECTIVE: VERDIQual uses multiple qualitative methods to explore the lived experiences of different populations with mpox and frontline health care workers in endemic and nonendemic settings. With this approach, we aim to identify missed and new opportunities for effective public health messaging on prevention and treatment in this and future pandemics. METHODS: VERDIQual's flexible, multimethod approach integrates content analysis of news and social media, focus group discussions, semistructured interviews, and participatory photography. We apply intersectionality theory to capture perspectives from a diverse range of participants, including gay, bisexual, and other men who have sex with men, pregnant women, adolescents with mpox, and frontline health care workers providing mpox services. Data will be collected and analyzed using the rapid assessment procedure approach, enabling real-time data synthesis to provide timely and contextually relevant insights. We use a standardized approach to data integration at the interpretation stage, summarizing findings in a multimethod integration matrix to visualize and synthesize data by objective, method, and site. RESULTS: Data collection tools, including focus group discussions and semistructured interview topic guides, have been developed in collaboration with local community advisory boards. Data collection was completed by October 31, 2025, and analysis is ongoing. Teams across the 4 countries have identified media houses and social media platforms for inclusion in the news and social media analysis. Study results will be disseminated through peer-reviewed journals, scientific conferences, policy briefs, and stakeholder workshops and community events, with a focus on informing equitable and inclusive future public health responses to re-emerging infections. CONCLUSIONS: We expect our principal findings to be applicable to a range of settings. Our use of intersectionality theory will also facilitate considerations for intersecting identities and characteristics in equity-centered pandemic responses. Ultimately, we expect VERDIQual to inform pandemic preparedness, inclusive of people with stigmatized and vulnerable characteristics or identities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/77321.
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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 | 0.092 | 0.078 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.074 | 0.011 |
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".