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dc.contributor.authorRomero-Alvarez, Daniel
dc.contributor.authorParikh, Nidhi
dc.contributor.authorOsthus, Dave
dc.contributor.authorMartinez, Kaitlyn
dc.contributor.authorGenerous, Nicholas
dc.contributor.authorValle, Sara del
dc.contributor.authorManore, Carrie A.
dc.date.accessioned2020-06-18T19:07:41Z
dc.date.available2020-06-18T19:07:41Z
dc.date.issued2020-03-26
dc.identifier.citationRomero-Alvarez, D., Parikh, N., Osthus, D., Martinez, K., Generous, N., Del Valle, S., & Manore, C. A. (2020). Google Health Trends performance reflecting dengue incidence for the Brazilian states. BMC infectious diseases, 20(1), 252. https://doi.org/10.1186/s12879-020-04957-0en_US
dc.identifier.urihttp://hdl.handle.net/1808/30547
dc.descriptionThis work is licensed under a Creative Commons Attribution 4.0 International License.en_US
dc.description.abstractBackground Dengue fever is a mosquito-borne infection transmitted by Aedes aegypti and mainly found in tropical and subtropical regions worldwide. Since its re-introduction in 1986, Brazil has become a hotspot for dengue and has experienced yearly epidemics. As a notifiable infectious disease, Brazil uses a passive epidemiological surveillance system to collect and report cases; however, dengue burden is underestimated. Thus, Internet data streams may complement surveillance activities by providing real-time information in the face of reporting lags.

Methods We analyzed 19 terms related to dengue using Google Health Trends (GHT), a free-Internet data-source, and compared it with weekly dengue incidence between 2011 to 2016. We correlated GHT data with dengue incidence at the national and state-level for Brazil while using the adjusted R squared statistic as primary outcome measure (0/1). We used survey data on Internet access and variables from the official census of 2010 to identify where GHT could be useful in tracking dengue dynamics. Finally, we used a standardized volatility index on dengue incidence and developed models with different variables with the same objective.

Results From the 19 terms explored with GHT, only seven were able to consistently track dengue. From the 27 states, only 12 reported an adjusted R squared higher than 0.8; these states were distributed mainly in the Northeast, Southeast, and South of Brazil. The usefulness of GHT was explained by the logarithm of the number of Internet users in the last 3 months, the total population per state, and the standardized volatility index.

Conclusions The potential contribution of GHT in complementing traditional established surveillance strategies should be analyzed in the context of geographical resolutions smaller than countries. For Brazil, GHT implementation should be analyzed in a case-by-case basis. State variables including total population, Internet usage in the last 3 months, and the standardized volatility index could serve as indicators determining when GHT could complement dengue state level surveillance in other countries.
en_US
dc.publisherBMCen_US
dc.rights© The Author(s) 2020.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectGoogle health trendsen_US
dc.subjectDigital epidemiologyen_US
dc.subjectBrazilen_US
dc.subjectVolatilityen_US
dc.subjectEpidemiologyen_US
dc.subjectInternet data streamsen_US
dc.subjectInternet penetrationen_US
dc.titleGoogle Health Trends performance reflecting dengue incidence for the Brazilian statesen_US
dc.typeArticleen_US
kusw.kuauthorRomero-Alvarez, Daniel
kusw.kudepartmentEcology & Evolutionary Biologyen_US
kusw.kudepartmentBiodiversity Instituteen_US
dc.identifier.doi10.1186/s12879-020-04957-0en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.identifier.pmidPMC7104526en_US
dc.rights.accessrightsopenAccessen_US


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