Using “Google trends” for dengue surveillance and epidemiological research
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20222587Keywords:
Google trends, Dengue, Public health surveillance, Epidemiology, Information technologyAbstract
Millions of people worldwide search online for health-related information and search engines have become an increasingly popular resource for accessing health-related information and provides valuable source. Key words used as well as the number and geographic location of searches can provide trend data, available by Google trends. In this study exploring this resource using dengue disease as an example. Objectives were to use Google trends data for comparison across different locations in India for the past 5 years, and to assess the specific search terms used in Google trends data and to correlate the real time dengue outbreak of Tamil Nadu with Google trend search. It was a cross sectional study. Data collection was done via Google search queries and record was included. Weekly trends were accessed from Google Trends. Data is a randomly collected sample of real time and non-real time Google search queries. Search traffic for the string “dengue fever” reflected increased likelihood of exposure and the string “dengue symptoms and treatment” had higher relative traffic during rainy season. Cities and states with the highest amount of search traffic for “dengue disease” overlapped where dengue is endemic. Found that search trend data produced by Google to approximate the seasonality, spikes at September to November every year and geographic distribution also identified in dengue disease. Web search query data were found to be capable of tracking dengue activity and predict periods of large incidence of dengue with high accuracy and may prove useful.
References
Park K. Textbook of Preventive and Social Medicine. 25th Edition. Jabalpur: Bhanot; 2019;269.
Dengue and severe dengue. 2020 [cited 4 November 2020]. Available from: https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue
Ministry of Health & Family Welfare, Government of India. Integrated Disease Surveillance Programme [Internet].New Delhi: Ministry of Health & Family Welfare; [cited at 2020 Jul 4]. Available from: http://www.idsp.nic.in/.
Ministry of health & family welfare. National vector borne disease control programme. Available at: https://nvbdcp.gov.in/index4.php?lang=1&level=0&linkid=431&lid=3715. Accessed on 8 July 2020.
Gunasekaran P, Kaveri K, Mohana S, et al. Dengue disease status in Chennai (2006-2008): a retrospective analysis. Indian J Med Res. 2011;133(3):322-325.
Tewari SC, Thenmozhil V, Katholi CR, Manavalan1 R, Munirathinam A, Gajanana A. Dengue vector prevalence and virus infection in a rural area in south India. Trop Med Int Health. 2004;9:499–507.
Lee HS, Nguyen-Viet H, Nam VS, Lee M, Won S, Duc PP, Grace D. Seasonal patterns of dengue fever and associated climate factors in 4 provinces in Vietnam from 1994 to 2013. BMC Infect Dis. 2017;17(1):218.
Chandy S, Ramanathan K, Manoharan A, Mathai D, Baruah K. Assessing effect of climate on the incidence of dengue in Tamil Nadu. Indian J Med Microbiol 2013;31:283-6
Gluskin R, Johansson M, Santillana M, Brownstein J. Evaluation of Internet-Based Dengue Query Data: Google Dengue Trends. PLoS Neglected Tropical Diseases. 2014;8(2):e2713.
Chan EH, Sahai V, Conrad C, Brownstein JS (2011) Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. PLoS Negl Trop Dis 5: e1206.
Althouse BM, Ng YY, Cummings DA (2011) Prediction of dengue incidence using search query surveillance. PLoS Negl Trop Dis 5: e1258.
Chan EH, Sahai V, Conrad C, et al. Using web search query data to monitor dengue epidemics: a new model for neglected tropical disease surveillance. PLoS Negl Trop Dis. 2011;5.
Verma M, Kishore K, Kumar M, Sondh A, Aggarwal G, Kathirvel S. Google Search Trends Predicting Disease Outbreaks: An Analysis from India. Healthcare Informatics Research. 2018;24(4):300.
Yang S, Santillana M, Kou S. Accurate estimation of influenza epidemics using Google search data via ARGO. Proceedings of the National Academy of Sciences. 2015;112(47):14473-14478.
Polgreen PM, Chen Y, Pennock DM, Nelson FD, Weinstein RA Using Internet searches for influenza surveillance. Clin Infect Dis 2008; 47(11):1443–1448.
Cervellin G, Comelli I, Lippi G. Is Google Trends a reliable tool for digital epidemiology? Insights from different clinical settings. Journal of Epidemiology and Global Health. 2017;7(3):185.
Husnayain A, Fuad A, Lazuardi L. Correlation between Google Trends on dengue fever and national surveillance report in Indonesia. Global Health Action. 2019;12(1):1552652.