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Evaluation of Internet-based dengue query data: Google Dengue Trends
Rebecca Tave Gluskin1, Michael A Johansson2, Mauricio Santillana3
1Children's Hospital Informatics Program, Children's Hospital Boston, Boston, Massachusetts, United States of America.
Plos Neglected Tropical Diseases
|March 4, 2014
Summary
Google Dengue Trends (GDT) shows high national accuracy for dengue surveillance but varies by state. Climate factors significantly influence GDT
Area of Science:
- Epidemiology
- Public Health Surveillance
- Digital Epidemiology
Background:
- Dengue fever is a significant global health concern, with traditional surveillance methods being slow and resource-intensive.
- The rise of internet usage has led to the development of novel digital surveillance tools, such as Google Dengue Trends (GDT).
- Existing research indicates GDT correlates well with dengue incidence on a large spatial scale.
Purpose of the Study:
- To assess the accuracy and identify factors influencing Google Dengue Trends (GDT) at the state-level in Mexico.
- To understand the heterogeneity of GDT's performance in smaller geographic areas.
- To inform the use of digital surveillance data for public health decision-making.
Main Methods:
- Utilized Pearson correlation to analyze the association between GDT search query data and traditional dengue surveillance data.
- Evaluated GDT accuracy at both the national and state levels across 17 Mexican states.
- Developed a statistical model incorporating climate variables (temperature, precipitation) to explain variations in GDT accuracy.
Main Results:
- Nationally, GDT explained 83% of the variability in reported dengue cases over nine years.
- State-level GDT accuracy varied significantly, from 1% in Baja California to 88% in Chiapas.
- A climate model, including temperature and precipitation, accounted for 81% of the variability in GDT accuracy between states, with higher accuracy in areas with intense transmission and favorable climates.
- Internet accessibility did not significantly impact GDT accuracy.
Conclusions:
- Google Dengue Trends (GDT) demonstrates strong national correlation with dengue incidence but exhibits significant spatial heterogeneity in accuracy.
- Climate variables are key predictors of GDT's accuracy at the sub-national level, indicating better performance in regions with suitable climate for dengue transmission.
- While GDT may be less reliable for local surveillance in low-incidence or climatically unfavorable areas, it could potentially detect imported cases, highlighting the need to understand its strengths and limitations for effective public health applications.
