Dengue disease outbreak definitions are implicitly variable
Epidemics·
- DOI
- 10.1016/j.epidem.2015.03.002
- PMID
- 25979287
- PMCID
- PMC4429239
- OpenAlex
- —
- Study type
- Journal article
- Publisher
- Elsevier BV
- Article type
- journal-article
- Integrity
- current
Why this research matters now
Establishing precise quantitative thresholds for outbreak identification remains critical for designing effective reactive public health responses. Current policy frameworks require adaptation to reflect local treatment, surveillance, and control capacities to ensure broad applicability.
Structured evidence summary
Research question
This analysis evaluates whether international policy assumptions regarding standardized dengue outbreak definitions hold true by testing multiple candidate metrics against reported case data.
Study design
The research employs an analytical approach utilizing multiple candidate outbreak definitions applied to historical reported case data.
Population and setting
The investigation utilizes reported dengue case data collected within Brazil.
Main findings
Applying various candidate metrics revealed substantial heterogeneity in outbreak frequency, duration, and case burden across different regions and periods. The selected definitions also demonstrated varying timeliness for identifying onset, suggesting potential mismatches with early intervention needs. These results challenge the assumption that a single standardized outbreak definition adequately captures local epidemiological realities.
Public-health relevance
Establishing precise quantitative thresholds for outbreak identification remains critical for designing effective reactive public health responses. Current policy frameworks require adaptation to reflect local treatment, surveillance, and control capacities to ensure broad applicability.
Important limitations
This summary is restricted to the supplied single-article abstract and metadata, requiring examination of the original manuscript for decision-grade interpretation.
GIDS interpretation
The publication addresses foundational methodological debates in infectious disease surveillance by highlighting inconsistencies in outbreak classification frameworks. Its focus on definitional variability provides contextual background for understanding how policy guidelines may diverge from observed epidemiological patterns.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 12 auditable classifier relationships to diseases, places, topics, and study design.