tetano
Editor, Senior Moderator
JMIR Public Health Surveill. 2020 May 13. doi: 10.2196/19702. [Epub ahead of print]
Correlations of Online Search Engine Trends with Coronavirus disease (COVID-19) Incidence: Infodemiology Study.
Higgins TS[SUP]1,[/SUP][SUP]2[/SUP], Wu AW[SUP]3[/SUP], Sharma D[SUP]4[/SUP], Illing EA[SUP]4[/SUP], Rubel K[SUP]4[/SUP], Ting JY[SUP]4[/SUP].
Author information
Abstract
BACKGROUND:
Coronavirus disease (COVID-19) is the latest pandemic of the digital age. With the Internet harvesting large amounts of data from the general population in real-time, public databases such as Google Trends (GT) and the Baidu Index (BI) can be an expedient tool to assist public health efforts.
OBJECTIVE:
To apply digital epidemiology to the current COVID-19 pandemic to determine utility in the providing adjunctive epidemiologic information on outbreaks of this disease and evaluate this methodology in the case of future pandemics.
METHODS:
An epidemiologic time-series analysis of online search trends relating to the COVID-19 pandemic was performed from January 9, 2020 to April 6, 2020. BI was used to obtain online search data for China, while GT was utilized for worldwide data, the countries of Italy and Spain and the American states of New York and Washington. These data were compared to real-world confirmed cases and deaths of COVID-19. Chronologic patterns were assessed in relation to disease patterns, significant events, and media reports.
RESULTS:
Worldwide search terms for shortness of breath, anosmia, dysgeusia/ageusia, headache, chest pain, and sneezing had strong correlations (r>.60, P<.001) to both new daily confirmed cases and deaths from COVID-19. GT COVID-19 (search term) and GT coronavirus (virus) searches predated RW confirmed cases by 12 days (r=.85?.10 and r=.76?.09 respectively, P<.001). Searches for symptoms of diarrhea, fever, shortness of breath, cough, nasal obstruction, and rhinorrhea all had a negative lag of greater than one week compared to new daily cases; whereas, searches for anosmia and dysgeusia peaked worldwide and in China with positive lags of 5 days and 6 weeks, respectively, corresponding with widespread media coverage of these symptoms in COVID-19.
CONCLUSIONS:
This study demonstrates the utility of digital epidemiology in providing helpful surveillance data of disease outbreaks like COVID-19. While certain online search trends for this disease were influenced by media coverage, many search terms reflected clinical manifestations of the disease and showed strong correlations with real-world cases and deaths.
CLINICALTRIAL:
PMID:32401211DOI:10.2196/19702
Free full text
Correlations of Online Search Engine Trends with Coronavirus disease (COVID-19) Incidence: Infodemiology Study.
Higgins TS[SUP]1,[/SUP][SUP]2[/SUP], Wu AW[SUP]3[/SUP], Sharma D[SUP]4[/SUP], Illing EA[SUP]4[/SUP], Rubel K[SUP]4[/SUP], Ting JY[SUP]4[/SUP].
Author information
Abstract
BACKGROUND:
Coronavirus disease (COVID-19) is the latest pandemic of the digital age. With the Internet harvesting large amounts of data from the general population in real-time, public databases such as Google Trends (GT) and the Baidu Index (BI) can be an expedient tool to assist public health efforts.
OBJECTIVE:
To apply digital epidemiology to the current COVID-19 pandemic to determine utility in the providing adjunctive epidemiologic information on outbreaks of this disease and evaluate this methodology in the case of future pandemics.
METHODS:
An epidemiologic time-series analysis of online search trends relating to the COVID-19 pandemic was performed from January 9, 2020 to April 6, 2020. BI was used to obtain online search data for China, while GT was utilized for worldwide data, the countries of Italy and Spain and the American states of New York and Washington. These data were compared to real-world confirmed cases and deaths of COVID-19. Chronologic patterns were assessed in relation to disease patterns, significant events, and media reports.
RESULTS:
Worldwide search terms for shortness of breath, anosmia, dysgeusia/ageusia, headache, chest pain, and sneezing had strong correlations (r>.60, P<.001) to both new daily confirmed cases and deaths from COVID-19. GT COVID-19 (search term) and GT coronavirus (virus) searches predated RW confirmed cases by 12 days (r=.85?.10 and r=.76?.09 respectively, P<.001). Searches for symptoms of diarrhea, fever, shortness of breath, cough, nasal obstruction, and rhinorrhea all had a negative lag of greater than one week compared to new daily cases; whereas, searches for anosmia and dysgeusia peaked worldwide and in China with positive lags of 5 days and 6 weeks, respectively, corresponding with widespread media coverage of these symptoms in COVID-19.
CONCLUSIONS:
This study demonstrates the utility of digital epidemiology in providing helpful surveillance data of disease outbreaks like COVID-19. While certain online search trends for this disease were influenced by media coverage, many search terms reflected clinical manifestations of the disease and showed strong correlations with real-world cases and deaths.
CLINICALTRIAL:
PMID:32401211DOI:10.2196/19702
Free full text