Digital epidemiology and infodemiology of hand-foot-mouth disease (HFMD) in Italy. Disease trend assessment via Google and Wikipedia
Keywords:
Hand-foot-mouth disease, HFMD, Italy, Digital Epidemiology, Google, Wikipedia, Epidemiology, Infectious Diseases, Infodemiology, Medical Informatics ComputingAbstract
Background and aim: The study aimed to evaluate the epidemiological trend of hand, foot and mouth disease (HFMD) in Italy using data on Internet search volume.
Methods: A cross-sectional study design was used. Data on Internet searches were obtained from Google Trends (GT) and Wikipedia. We used the following Italian search term: “Malattia mano-piede-bocca” (Hand-foot-mouth disease, in English). A monthly time-frame was extracted, partly overlapping, from July 2015 to December 2022. GT and Wikipedia were overlapped to perform a linear regression and correlation analyses. Statistical analyses were performed using the Spearman's rank correlation coefficient (rho). A linear regression analysis was performed considering Wikipedia and GT.
Results: Search peaks for both Wikipedia and GT occurred in the months November-December during the autumn-winter season and in June during the spring-summer season, except for the period from June 2020 to June 2021, probably due to the restrictions of the COVID19 pandemic. A temporal correlation was observed between GT and Wikipedia search trends.
Conclusions: This is the first study in Italy that attempts to clarify the epidemiology of HFMD. Google search and Wikipedia can be valuable for public health surveillance; however, to date, digital epidemiology cannot replace the traditional surveillance system.
References
Esposito S, Principi N. Hand, foot and mouth disease: current knowledge on clinical manifestations, epidemiology, aetiology and prevention. Eur J Clin Microbiol Infect Dis. 2018;37(3):391-398. doi:10.1007/s10096-018-3206-x
CDC, Center for Diseases Control and Prevention. USA. Available online: https://www.cdc.gov/hand-foot-mouth/about/transmission.html (last access January 09, 2022)
Solomon T, Lewthwaite P, Perera D, Cardosa MJ, McMinn P, Ooi MH. Virology, epidemiology, pathogenesis, and control of enterovirus 71. Lancet Infect Dis. 2010;10(11):778-790. doi:10.1016/S1473-3099(10)70194-8
Guerra AM, Orille E, Waseem M. Hand, Foot, and Mouth Disease. In: StatPearls. Treasure Island (FL): StatPearls Publishing; October 9, 2022.
Huang J, Liao Q, Ooi MH, et al. Epidemiology of Recurrent Hand, Foot and Mouth Disease, China, 2008-2015. Emerg Infect Dis. 2018;24(3):432-442. doi:10.3201/eid2403.171303
Ruan F, Yang T, Ma H, et al. Risk factors for hand, foot, and mouth disease and herpangina and the preventive effect of hand-washing. Pediatrics. 2011;127(4):e898-e904. doi:10.1542/peds.2010-1497
Wang YR, Sun LL, Xiao WL, Chen LY, Wang XF, Pan DM. Epidemiology and clinical characteristics of hand foot, and mouth disease in a Shenzhen sentinel hospital from 2009 to 2011. BMC Infect Dis. 2013;13:539. doi:10.1186/1471-2334-13-539
Nguyen NT, Pham HV, Hoang CQ, et al. Epidemiological and clinical characteristics of children who died from hand, foot and mouth disease in Vietnam, 2011. BMC Infect Dis. 2014;14:341. doi:10.1186/1471-2334-14-341
Abedi GR, Watson JT, Nix WA, Oberste MS, Gerber SI. Enterovirus and Parechovirus Surveillance - United States, 2014-2016. MMWR Morb Mortal Wkly Rep. 2018;67(18):515-518. doi:10.15585/mmwr.mm6718a2
Santangelo OE, Gianfredi V, Provenzano S. Wikipedia searches and the epidemiology of infectious diseases: A systematic review. Data & Knowledge Engineering. 2022; 142: 102093. doi: 10.1016/j.datak.2022.102093
Provenzano S, Gianfredi V, Santangelo OE. Insight the data: Wikipedia's researches and real cases of arboviruses in Italy. Public Health. 2021;192:21-29. doi:10.1016/j.puhe.2020.12.010
Provenzano S, Santangelo OE, Giordano D, et al. Predicting disease outbreaks: evaluating measles infection with Wikipedia Trends. Recenti Prog Med. 2019;110(6):292-296. doi:10.1701/3182.31610
Gianfredi V, Santangelo OE, Provenzano S. Correlation between flu and Wikipedia's pages visualization. Acta Biomed. 2021;92(1):e2021056. doi:10.23750/abm.v92i1.9790
Santangelo OE, Provenzano S, Gianfredi V. Infodemiology of flu: Google trends-based analysis of Italians' digital behavior and a focus on SARS-CoV-2, Italy. J Prev Med Hyg. 2021;62(3):E586-E591. doi:10.15167/2421-4248/jpmh2021.62.3.1704
Santangelo OE, Provenzano S, Grigis D, Giordano D, Armetta F, Firenze A. Can Google Trends and Wikipedia help traditional surveillance? A pilot study on Measles. Acta Biomed. 2020; 91 (4):e2020190. doi: 10.23750/abm.v91i4.8888
Santangelo OE, Provenzano S, Piazza D, Giordano D, Calamusa G, Firenze A. Digital epidemiology: assessment of measles infection through Google Trends mechanism in Italy. Ann Ig. 2019;31(4):385-391. doi:10.7416/ai.2019.2300
Riccò M, Baldassarre A, Provenzano S, et al. Infodemiology of RSV in Italy (2017-2022): An Alternative Option for the Surveillance of Incident Cases in Pediatric Age?. Children (Basel). 2022;9(12):1984. doi:10.3390/children9121984
Google Trends. Available online: https://trends.google.it/trends/?geo=IT (last access January 9, 2022)
Wikipedia. Available from: https://tools.wmflabs.org/pageviews (last accessed January 9, 2022)
Mukaka MM. Statistics corner: A guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24(3):69-71.
White KJ. The Durbin-Watson Test for Autocorrelation in Nonlinear Models 370 The Review of Economics and Statistics the Durbin-Watson Test for Autocorrelation in Nonlinear Models. Rev Econ Stat. 1992; 74:370–373.
StataCorp. Stata Statistical Software. In: Station C, editor.: StataCorp LP; 2015.
Niu Q, Liu J, Zhao Z, et al. Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study. BMC Infect Dis. 2022;22(1):806. doi:10.1186/s12879-022-07790-9
Kow RY, Mohamad Rafiai N, Ahmad Alwi AA, et al. COVID-19 Infodemiology: Association Between Google Search and Vaccination in Malaysian Population. Cureus. 2022;14(9):e29515. doi:10.7759/cureus.29515
Springer S, Zieger M, Strzelecki A. The rise of infodemiology and infoveillance during COVID-19 crisis. One Health. 2021;13:100288. doi:10.1016/j.onehlt.2021.100288
Nucci D, Santangelo OE, Nardi M, Provenzano S, Gianfredi V. Wikipedia, Google Trends and Diet: Assessment of Temporal Trends in the Internet Users' Searches in Italy before and during COVID-19 Pandemic. Nutrients. 2021;13(11):3683. doi:10.3390/nu13113683
Cai O, Sousa-Pinto B. United States Influenza Search Patterns Since the Emergence of COVID-19: Infodemiology Study. JMIR Public Health Surveill. 2022;8(3):e32364. doi:10.2196/32364
Santangelo OE, Gentile V, Pizzo S, Giordano D, Cedrone F. Machine Learning and Prediction of Infectious Diseases: A Systematic Review. Machine Learning and Knowledge Extraction. 2023; 5(1):175-198. doi:10.3390/make5010013
Gianfredi V, Santangelo OE, Provenzano S. The effects of COVID-19 pandemic on the trend of measles and influenza in Europe. Acta Biomed. 2021;92(4):e2021318. doi:10.23750/abm.v92i4.11558
Gianfredi V, Bragazzi NL, Mahamid M, et al. Monitoring public interest toward pertussis outbreaks: an extensive Google Trends-based analysis. Public Health. 2018;165:9-15. doi:10.1016/j.puhe.2018.09.001
Riccò M, Valente M, Marchesi F. Are symptoms associated with SARS-CoV-2 infections evolving over time?. Infect Dis Now. 2022;52(2):110-112. doi:10.1016/j.idnow.2022.01.006
Salathé M. Digital epidemiology: what is it, and where is it going?. Life Sci Soc Policy. 2018;14(1):1. doi:10.1186/s40504-017-0065-7
Malik S. A Comparative Study of two major Search Engines: Google and Yahoo . Orient J Comp Sci and Technol. 7(1)
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