Evaluation of Internet-Based Dengue Query Data: Google Dengue Trends
PLoS Neglected Tropical Diseases·
- DOI
- 10.1371/journal.pntd.0002713
- PMID
- 24587465
- PMCID
- PMC3937307
- OpenAlex
- W2101915195
- Study type
- Journal article
- Publisher
- Public Library of Science (PLoS)
- Article type
- journal-article
- Integrity
- current
Why this research matters now
Assessing alternative digital tracking mechanisms may help mitigate the operational delays and resource demands inherent in standard reporting networks, assuming regional performance boundaries are clearly defined.
Structured evidence summary
Research question
How accurately does an internet search index track reported dengue cases across different administrative regions compared to conventional reporting systems?
Study design
A retrospective observational assessment correlating digital query metrics with official government case reports across a national scope and multiple subnational jurisdictions over a multi-year period.
Population and setting
Geographic regions within Mexico, encompassing the entire country and seventeen specific states evaluated throughout a nine-year observation window.
Main findings
The digital index mirrored approximately eighty-three percent of national case fluctuations, yet performance differed markedly among individual jurisdictions. Statistical alignment strengthened in locations with elevated baseline transmission and showed strong association with regional temperature and precipitation patterns. Local internet penetration rates demonstrated no measurable impact on the index reliability.
Public-health relevance
Assessing alternative digital tracking mechanisms may help mitigate the operational delays and resource demands inherent in standard reporting networks, assuming regional performance boundaries are clearly defined.
Important limitations
This evaluation depends entirely on the provided abstract and bibliographic details, requiring access to the complete manuscript for thorough methodological verification and decision-grade interpretation.
GIDS interpretation
The publication provides foundational context regarding digital epidemiology methodologies and spatial performance variations applicable to broader infectious disease monitoring frameworks.
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 11 auditable classifier relationships to diseases, places, topics, and study design.