Fast take: A July 10, 2026 PLoS NTDs study of the Sept 2021 mass dog-and-cat vaccination campaign in southern Cercado (Cochabamba, Bolivia) found systemic implementation gaps across 17 health centers and mapped why they happened. In this post we show how AI-enabled qualitative analysis (thematic, cross-segment, and frequency-based) converts that mixed-methods diagnosis into prioritized, reproducible fixes you can run in Evidano. You will learn which fidelity metrics matter, where resource spend will move the needle, and a short workflow to reproduce the study’s insights on your own transcripts, reports, and survey sheets. Ethics note: this is implementation-focused research guidance (non-diagnostic).
Key Takeaways
Evidano is an AI-powered qualitative data analysis platform that ingests transcripts, documents, and audio to accelerate mixed-methods implementation analysis, and it can convert the July 10, 2026 PLoS study of the Sept 2021 campaign in southern Cercado into prioritized fixes.
The July 10, 2026 PLoS study found that no health center reached ≥80% adherence on a 27-item checklist and identified cold-chain instability and understaffed vaccination brigades as primary drivers of low fidelity.
- Study snapshot: the Sept 2021 campaign was analyzed across 17 first-level health centers, with 154 interviews (46 ETD staff and 108 pet owners).
- Fidelity range: adherence to the 27-item checklist was 32%–79%, with no center meeting ≥80% adherence.
- Operational gaps: 13 of 17 centers (76.5%) lacked refrigerators, and 15 of 17 brigades (88.2%) were incomplete.
- Action focus: prioritize cold-chain fixes and brigade completeness, and map Carroll fidelity shortfalls to CFIR-coded barriers for fundable interventions.
Findings snapshot
| Metric | Value | Source / Note |
|---|---|---|
| Study published | July 10, 2026 | PLoS Negl Trop Dis |
| Campaign evaluated | September 2021 | Retrospective data collection (late 2022) |
| Health centers assessed | 17 | All first-level centers in southern Cercado |
| Interviews (ETD) | 46 | Decision-making entity personnel |
| Interviews (pet owners) | 108 | Dog & cat owners |
| Adherence (content) | 32%–79% (none ≥80%) | 27-item checklist (Carroll framework) |
| Lack of refrigerators | 13/17 (76.5%) | Cold chain gap |
| Incomplete brigades | 15/17 (88.2%) | Missing channelers, registry roles |
| Coverage adequate | 12/17 (70.6%) | Vaccine availability & postcampaign continuity |
| Frequency adequate | 14/17 (82.4%) | Campaign frequency components |
| Duration sufficient | 11/17 (64.7%) | ≥8-hour sessions |
What happened, methods and core gaps
This section summarizes what happened, the study methods, and the core gaps found in the Sept 2021 campaign.
This mixed-methods study combined Carroll’s implementation-fidelity framework (content, coverage, frequency, duration) with CFIR-guided qualitative interviews to answer not just whether coverage targets were missed but why.
Researchers used a conservative, documentary-verified 27-point checklist and conducted 154 semi-structured interviews (46 ETD staff, 108 pet owners).
Key operational failings included widespread cold-chain instability (damaged coolers, missing refrigerators), understaffed vaccination brigades, fragmented ETD–OTB coordination, and limited advance communication (only 4 of 17 centers started promotion at least one month early).
- Design: cross-sectional, purposive sampling; retrospective documentary verification (late 2022) of the Sept 2021 campaign.
- Mixed evidence: quantitative fidelity scores (no center ≥80% adherence) combined with CFIR narratives explaining barriers and facilitators.
- Main drivers: infrastructure (cold chain), human resources (brigade composition), coordination (interinstitutional fragmentation), and communication (language and timing).
So what for researchers and program teams
For implementation researchers
Implementation researchers should pair quantitative fidelity metrics with CFIR-coded interviews to produce actionable causal maps.
The study demonstrates how pairing quantitative fidelity metrics with CFIR-coded interviews produces actionable causal maps: not just labels.
Reproducibility depends on standardized checklists, verifiable documentary evidence, and saturation-based qualitative sampling.
For field program leads
Field program leads should prioritize fixes that yield immediate fidelity gains such as cold-chain solutions and complete brigades.
Fixes with immediate ROI include pre-positioning insulated carriers or using thermotolerant vaccines to mitigate cold-chain failures; formalizing ETD–OTB planning agreements; scheduling evening, weekend, or door-to-door sessions for hard-to-reach households; and integrating veterinarians into outreach to increase trust.
For UX and data teams doing qualitative analysis
UX and data teams should map CFIR constructs to Carroll fidelity shortfalls as a segmentation, theme, and quote-frequency exercise.
The core analytic job is mapping which CFIR constructs align with Carroll fidelity shortfalls, an exercise ideal for AI-enabled workflows that combine transcript ingestion, automated code suggestion, and cross-segment comparisons.
Do more, faster with Evidano
Reproduce the paper’s mixed-methods analysis
This subsection explains how to reproduce the paper’s mixed-methods analysis in Evidano.
Import PDFs, meeting minutes, WhatsApp logs, and interview audio into Evidano.
Auto-transcribe Spanish and Quechua audio with a custom dictionary to preserve local terms and auto-detect document types and tag by source (ETD vs. owner).
Map fidelity constructs to themes in minutes
This subsection explains how to map fidelity constructs to themes quickly in Evidano.
Use Evidano thematic analysis to extract CFIR domains (values, inner setting, expected impact, communication) and Carroll constructs.
Generate frequency tables and cross-segment comparisons (for example, centers with refrigerators versus without) to prioritize interventions.
Evidence-ready visuals and quotes
This subsection explains how to produce evidence-ready visuals and source-linked quotes in Evidano.
Generate co-occurrence networks (for example, 'cold chain' ↔ 'cooler damage' ↔ 'coverage'), hierarchical code trees, and exportable stakeholder-ready summaries with clickable source quotes, suitable for grant requests or joint planning meetings.
Secure, research-grade data handling
This subsection explains Evidano’s approach to secure, research-grade data handling.
Data is encrypted at rest and in transit; custom dictionaries for Quechua and local terms preserve translation accuracy.
Evidano uses proprietary LLMs tuned for qualitative research and does not share customer data to third-party model training.
Quick 7-step workflow to run this analysis in Evidano
This section lists a quick 7-step workflow to replicate the study’s actionable insights using Evidano.
- 1) Ingest sources: upload transcripts, PDFs, WhatsApp exports, and spreadsheets (vaccine logs, staffing rosters).
- 2) Auto-transcribe audio (Spanish/Quechua) with custom dictionary and PII redaction.
- 3) Auto-translate where needed and normalize terminology (for example, 'brigade' synonyms).
- 4) Import the 27-item checklist as a codebook; run automated coding and review AI-suggested code assignments.
- 5) Run thematic, frequency, and cross-segment analyses (by center, by OTB, by neighborhood) to map fidelity gaps to CFIR constructs.
- 6) Produce visuals: word clouds, co-occurrence networks, hierarchical code trees, and exportable executive briefs with source-linked quotes.
- 7) Share a reproducible report and set follow-up AI-avatar interviews to fill data gaps (for example, absent national-level actor perspectives).
FAQ: qualitative analysis of vaccination campaigns
What is qualitative analysis of vaccination campaigns?
Qualitative analysis of vaccination campaigns is the systematic coding and interpretation of interview, document, and field-note data to explain why campaigns meet or miss fidelity targets.
It is the systematic coding and interpretation of interview, document, and field-note data to explain why campaigns meet or miss fidelity targets, and it complements quantitative coverage metrics.
How do I compare centers reliably?
You compare centers reliably by using a shared checklist, normalizing logs, and running cross-segment analyses.
Use a shared checklist (like the 27-item instrument used in the study), normalize logs, and run cross-segment frequency and co-occurrence analyses to surface common failure modes.
Can Evidano handle Quechua and mixed-language transcripts?
Evidano can transcribe and translate Quechua and mixed-language transcripts using custom dictionaries to preserve local terms.
Evidano supports transcription and translation with custom dictionaries to preserve local terms and ensure accurate thematic coding.
How secure is AI-enabled research?
AI-enabled research on Evidano is encrypted and uses proprietary models that do not train on customer data for third parties.
Evidano encrypts data and uses proprietary LLMs tuned for qualitative work; customer data is not used to train third-party models.
Conclusion, two immediate moves
This conclusion gives two immediate operational moves to raise fidelity quickly.
1) Prioritize cold-chain fixes and brigade completeness for immediate fidelity gains, using thermotolerant vaccines and community volunteers for quick wins.
2) Run a reproducible CFIR × Carroll analysis on your own campaign documents to convert storytelling into ranked, fundable actions.
- Reproduce this PLoS analysis quickly by uploading your transcripts and checklists to Evidano.
- Read the original study for full methods and data: PLoS Negl Trop Dis.
- Try Evidano for free.