Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes - PubMed (original) (raw)

Cristiano Alicino et al. Infect Dis Poverty. 2015.

Abstract

Background: The 2014 Ebola epidemic in West Africa has attracted public interest worldwide, leading to millions of Ebola-related Internet searches being performed during the period of the epidemic. This study aimed to evaluate and interpret Google search queries for terms related to the Ebola outbreak both at the global level and in all countries where primary cases of Ebola occurred. The study also endeavoured to look at the correlation between the number of overall and weekly web searches and the number of overall and weekly new cases of Ebola.

Methods: Google Trends (GT) was used to explore Internet activity related to Ebola. The study period was from 29 December 2013 to 14 June 2015. Pearson's correlation was performed to correlate Ebola-related relative search volumes (RSVs) with the number of weekly and overall Ebola cases. Multivariate regression was performed using Ebola-related RSV as a dependent variable, and the overall number of Ebola cases and the Human Development Index were used as predictor variables.

Results: The greatest RSV was registered in the three West African countries mainly affected by the Ebola epidemic. The queries varied in the different countries. Both quantitative and qualitative differences between the affected African countries and other Western countries with primary cases were noted, in relation to the different flux volumes and different time courses. In the affected African countries, web query search volumes were mostly concentrated in the capital areas. However, in Western countries, web queries were uniformly distributed over the national territory. In terms of the three countries mainly affected by the Ebola epidemic, the correlation between the number of new weekly cases of Ebola and the weekly GT index varied from weak to moderate. The correlation between the number of Ebola cases registered in all countries during the study period and the GT index was very high.

Conclusion: Google Trends showed a coarse-grained nature, strongly correlating with global epidemiological data, but was weaker at country level, as it was prone to distortions induced by unbalanced media coverage and the digital divide. Global and local health agencies could usefully exploit GT data to identify disease-related information needs and plan proper communication strategies, particularly in the case of health-threatening events.

PubMed Disclaimer

Figures

Fig. 1

Fig. 1

a Google Trends curve as RSVs for “Ebola” and Ebola-related terms (as “search term” or “search interest”) from December 2013 to June 2015; b Regional interest heat map for Ebola-related activities worldwide

Fig. 2

Fig. 2

Google Trends curve as RSV for “Ebola” from December 2013 to June 2015 searched worldwide (dotted blue line), and in all countries where primary cases of Ebola were registered (red lines)

Fig. 3

Fig. 3

Regional interest heat map for Ebola-related activities in all countries where primary cases of Ebola were registered over the entire period of the outbreak; a) Guinea, b) Sierra Leone, c) Liberia, d) Mali, e) Nigeria, f) Senegal, g) US, h) Spain, i) UK, j) Italy

Fig. 4

Fig. 4

Correlation between GT curves as weekly RSVs for “Ebola” from December 2013 to June 2015, searched worldwide (upper), Liberia, Sierra Leone and Guinea (below), and the weekly number of new Ebola cases

Fig. 5

Fig. 5

Scatterplot visualising the correlation between RSV for “Ebola” from December 2013 to June 2015, the total number of Ebola cases per country registered over the entire period of the outbreak, and the HDI in all countries where primary cases of Ebola were registered

Similar articles

Cited by

References

    1. World Health Organization. Ebola Situation Report - 12 August 2015. Available at http://apps.who.int/ebola/current-situation/ebola-situation-report-12-au.... Accessed 17th August 2015.
    1. Yahoo Tech. Top 10 Searches of 2014. Available at https://www.yahoo.com/tech/top-10-searches-of-2014-c1417565661893.html. Accessed 17th August 2015.
    1. Google. Available at http://www.google.co.uk/trends/2014/story/ebola.html. Accessed 17th August 2015.
    1. Fernández-Luque L, Bau T. Health and social media: perfect storm of information. Health Inform Res. 2015;21:67–73. doi: 10.4258/hir.2015.21.2.67. - DOI - PMC - PubMed
    1. Fung IC, Fu KW, Ying Y, Schaible B, Hao Y, Chan CH, et al. Chinese social media reaction to the MERS-CoV and avian influenza A(H7N9) outbreaks. Infect Dis Poverty. 2013;2:31. doi: 10.1186/2049-9957-2-31. - DOI - PMC - PubMed

MeSH terms

LinkOut - more resources