strobe-check

name: strobe-check description: > Review a manuscript against STROBE reporting guidelines for observational studies. Use when checking a draft manuscript for completeness, preparing for journal submission, or responding to reviewer comments about reporting quality. Adapted for infectious disease and forecast evaluation studies. disable-model-invocation: true user-invocable: true argument-hint: "[path-to-manuscript]"

STROBE Reporting Checklist Review

Instructions

1. Read the manuscript file provided as $ARGUMENTS
2. Load references/strobe-checklist.md for the full adapted checklist
3. Work through each of the 22 STROBE items systematically
4. For each item, identify the relevant section of the manuscript and assess coverage

Assessment process

For each STROBE item:

1. Locate: Find where in the manuscript this item is addressed
2. Assess: Rate as Present, Partial, or Missing
3. Note: For Partial or Missing items, provide specific guidance on what to add or improve
4. Adapt: Some items need reinterpretation for non-standard study types (see below)

Adaptations for common study types

Forecast evaluation studies

• Participants (Item 6): "Participants" are forecasting models/teams, not human subjects. Describe model selection criteria, inclusion/exclusion, and the forecasting platform.
• Variables (Item 7): Exposure = model characteristics (method, geographic scope). Outcome = forecast accuracy (scoring rule). Confounders = prediction difficulty factors (horizon, location, trend).
• Data sources (Item 8): The forecasting hub or platform, observation data sources, and any secondary data (variant classifications, population data).
• Bias (Item 9): Selection bias from model participation patterns. Information bias from varying submission completeness. Confounding by prediction difficulty.

Secondary data analysis

• Setting (Item 5): Describe the original data collection, not just your analysis
• Participants (Item 6): Describe the original study population and your inclusion criteria for the secondary analysis
• Data sources (Item 8): Cite the original data source and any linking or transformation steps

Output format

Present results as a markdown table:

| Item | Topic | Status | Location | Notes |
|------|-------|--------|----------|-------|
| 1a | Title: study design | Present | Title | ... |
| 1b | Abstract: informative | Partial | Abstract | Missing: sample size |

After the table, provide:

1. Summary: Count of Present / Partial / Missing items
2. Priority fixes: The 3-5 most important gaps to address, ordered by impact on manuscript quality
3. Not applicable: Any items genuinely not applicable, with justification

Common gaps to watch for

These items are most frequently missing or weak in infectious disease manuscripts:

• Item 6 (Participants): Selection criteria for models/data often implicit
• Item 7 (Variables): Exposure classification and confounder identification under-specified
• Item 9 (Bias): Often omitted entirely or treated superficially
• Item 12e (Sensitivity analyses): Often missing or not pre-specified
• Item 16a (Main results): Unadjusted vs adjusted comparison absent
• Item 19 (Limitations): Direction and magnitude of potential bias rarely discussed