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      Google Health Trends performance reflecting dengue incidence for the Brazilian states

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          Abstract

          Background

          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.

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          Most cited references44

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          Dengue, Urbanization and Globalization: The Unholy Trinity of the 21st Century

          Dengue is the most important arboviral disease of humans with over half of the world’s population living in areas of risk. The frequency and magnitude of epidemic dengue have increased dramatically in the past 40 years as the viruses and the mosquito vectors have both expanded geographically in the tropical regions of the world. There are many factors that have contributed to this emergence of epidemic dengue, but only three have been the principal drivers: 1) urbanization, 2) globalization and 3) lack of effective mosquito control. The dengue viruses have fully adapted to a human-Aedes aegypti-human transmission cycle, in the large urban centers of the tropics, where crowded human populations live in intimate association with equally large mosquito populations. This setting provides the ideal home for maintenance of the viruses and the periodic generation of epidemic strains. These cities all have modern airports through which 10s of millions of passengers pass each year, providing the ideal mechanism for transportation of viruses to new cities, regions and continents where there is little or no effective mosquito control. The result is epidemic dengue. This paper discusses this unholy trinity of drivers, along with disease burden, prevention and control and prospects for the future.
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            Using internet searches for influenza surveillance.

            The Internet is an important source of health information. Thus, the frequency of Internet searches may provide information regarding infectious disease activity. As an example, we examined the relationship between searches for influenza and actual influenza occurrence. Using search queries from the Yahoo! search engine ( http://search.yahoo.com ) from March 2004 through May 2008, we counted daily unique queries originating in the United States that contained influenza-related search terms. Counts were divided by the total number of searches, and the resulting daily fraction of searches was averaged over the week. We estimated linear models, using searches with 1-10-week lead times as explanatory variables to predict the percentage of cultures positive for influenza and deaths attributable to pneumonia and influenza in the United States. With use of the frequency of searches, our models predicted an increase in cultures positive for influenza 1-3 weeks in advance of when they occurred (P < .001), and similar models predicted an increase in mortality attributable to pneumonia and influenza up to 5 weeks in advance (P < .001). Search-term surveillance may provide an additional tool for disease surveillance.
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              Economic Impact of Dengue Illness in the Americas

              The growing burden of dengue in endemic countries and outbreaks in previously unaffected countries stress the need to assess the economic impact of this disease. This paper synthesizes existing studies to calculate the economic burden of dengue illness in the Americas from a societal perspective. Major data sources include national case reporting data from 2000 to 2007, prospective cost of illness studies, and analyses quantifying underreporting in national routine surveillance systems. Dengue illness in the Americas was estimated to cost $2.1 billion per year on average (in 2010 US dollars), with a range of $1–4 billion in sensitivity analyses and substantial year to year variation. The results highlight the substantial economic burden from dengue in the Americas. The burden for dengue exceeds that from other viral illnesses, such as human papillomavirus (HPV) or rotavirus. Because this study does not include some components (e.g., vector control), it may still underestimate total economic consequences of dengue.
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                Author and article information

                Contributors
                daromero88@gmail.com , da.romero@ku.edu , dan_rom@lanl.gov
                Journal
                BMC Infect Dis
                BMC Infect. Dis
                BMC Infectious Diseases
                BioMed Central (London )
                1471-2334
                26 March 2020
                26 March 2020
                2020
                : 20
                : 252
                Affiliations
                [1 ]GRID grid.266515.3, ISNI 0000 0001 2106 0692, Department of Ecology & Evolutionary Biology and Biodiversity Institute, , University of Kansas, ; Lawrence, Kansas USA
                [2 ]GRID grid.148313.c, ISNI 0000 0004 0428 3079, Information Systems and Modeling (A-1), Los Alamos National Laboratory, ; Los Alamos, NM USA
                [3 ]GRID grid.148313.c, ISNI 0000 0004 0428 3079, Statistical Sciences (CCS-6), Los Alamos National Laboratory, ; Los Alamos, NM USA
                [4 ]GRID grid.254549.b, ISNI 0000 0004 1936 8155, Applied Math and Statistics, Colorado School of Mines, ; Golden, CO USA
                [5 ]GRID grid.148313.c, ISNI 0000 0004 0428 3079, National Security & Defense Program Office (GS-NSD), Los Alamos National Laboratory, ; Los Alamos, NM USA
                Article
                4957
                10.1186/s12879-020-04957-0
                7104526
                5e090949-c44f-4e3b-8c1d-e1ecf1938748
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 11 November 2019
                : 10 March 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: R01GM130668
                Funded by: FundRef http://dx.doi.org/10.13039/100008902, Los Alamos National Laboratory;
                Award ID: Laboratory Directed Research Development Program
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Infectious disease & Microbiology
                google health trends,digital epidemiology,brazil,volatility,epidemiology,internet data streams,internet penetration

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