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Interest in Covid-19 in Latin America and the Caribbean

An infodemiological study using Google Trends

Bibliographic Data

ID5168680
AuthorsCarlos Jesús Aragón-Ayala (0000-0001-9536-2247, Universidad Nacional de San Agustin de Arequipa), Julissa Copa-Uscamayta (0000-0002-2268-8577, Universidad Nacional de San Agustin de Arequipa), L Herrera (0000-0001-7634-3016, Universidad Nacional de San Agustin de Arequipa), Frank Zela-Coila (0000-0003-2805-9162, Universidad Nacional de San Agustin de Arequipa), Cender Udai Quispe-Juli (0000-0003-0633-8339, Universidad Peruana Cayetano Heredia)
Year2021
Volume37
Issue10
Pagese00270720-e00270720
Publication date2021-01-01
Open AccessYes
TypeARTICLE
VenueCadernos de Saude Publica (JOURNAL)
Journal identifiersISSN: 0102-311X • E-ISSN: 1678-4464
PublisherFapUNIFESP (SciELO) (PUBLISHER)
DOI10.1590/0102-311x00270720
PMID34730692
OpenAlexW3209845332
SciELOS0102-311X2021001005017
LanguageEN
Citations received1
References cited27

Infodemiology has been widely used to assess epidemics. In light of the recent pandemic, we use Google Search data to explore online interest about COVID-19 and related topics in 20 countries of Latin America and the Caribbean. Data from Google Trends from December 12, 2019, to April 25, 2020, regarding COVID-19 and other related topics were retrieved and correlated with official data on COVID-19 cases and with national epidemiological indicators. The Latin American and Caribbean countries with the most interest for COVID-19 were Peru (100%) and Panama (98.39%). No correlation was found between this interest and national epidemiological indicators. The global and local response time were 20.2 ± 1.2 days and 16.7 ± 15 days, respectively. The duration of public attention was 64.8 ± 12.5 days. The most popular topics related to COVID-19 were: the country's situation (100 ± 0) and coronavirus symptoms (36.82 ± 16.16). Most countries showed a strong or moderated (r = 0.72) significant correlation between searches related to COVID-19 and daily new cases. In addition, the highest significant lag correlation was found on day 13.35 ± 5.76 (r = 0.79). Interest shown by Latin American and Caribbean countries for COVID-19 was high. The degree of online interest in a country does not clearly reflect the magnitude of their epidemiological indicators. The response time and the lag correlation were greater than in European and Asian countries. Less interest was found for preventive measures. Strong correlation between searches for COVID-19 and daily new cases suggests a predictive utility

2019-20 coronavirus outbreak · Coronavirus disease 2019 (COVID-19) · Geography · Latin Americans · Outbreak · Pandemic · Political science · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) · Sociology · Data-Driven Disease Surveillance · Demography · Epidemiology · Influenza Virus Research Studies · Medicine · Misinformation and Its Impacts · Virology

  • Orientações contemporâneas da Ciência da Informação

    Open Access•Maria Nelida González De Gómez•Museologia & Interdisciplinaridade•2022

  • Infodemiology and Infoveillance

    Open Access•Gunther Eysenbach•Journal of Medical Internet…•2009

  • Interpretation of the Correlation Coefficient

    Open Access•Richard Taylor•Journal of Diagnostic Medical…•1990

  • An interactive web-based dashboard to track Covid-19 in real time

    Open Access•Erdan Dong, Ensheng Dong et al.•The Lancet Infectious Diseases•2020

  • More effective strategies are required to strengthen public awareness of Covid-19

    Open Access•Dingtao Hu, Xiaoqi Lou et al.•Journal of Global Health•2020

  • Correlation between Google Trends on dengue fever and national surveillance report in Indonesia

    Open Access•Atina Husnayain, Anis Fuad et al.•Global Health Action•2019

Citations per year0.25
Citation span2022 - 2022 (1)
Highly citedNo

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