COVID-19 Misinformation Spread in Eight Countries: Exponential Growth Modeling Study.
COVID-19
internet
misinformation
rumors
social media
Journal
Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882
Informations de publication
Date de publication:
15 12 2020
15 12 2020
Historique:
received:
18
09
2020
accepted:
30
11
2020
revised:
30
10
2020
pubmed:
3
12
2020
medline:
16
1
2021
entrez:
2
12
2020
Statut:
epublish
Résumé
The epidemic of misinformation about COVID-19 transmission, prevention, and treatment has been going on since the start of the pandemic. However, data on the exposure and impact of misinformation is not readily available. We aim to characterize and compare the start, peak, and doubling time of COVID-19 misinformation topics across 8 countries using an exponential growth model usually employed to study infectious disease epidemics. COVID-19 misinformation topics were selected from the World Health Organization Mythbusters website. Data representing exposure was obtained from the Google Trends application programming interface for 8 English-speaking countries. Exponential growth models were used in modeling trends for each country. Searches for "coronavirus AND 5G" started at different times but peaked in the same week for 6 countries. Searches for 5G also had the shortest doubling time across all misinformation topics, with the shortest time in Nigeria and South Africa (approximately 4-5 days). Searches for "coronavirus AND ginger" started at the same time (the week of January 19, 2020) for several countries, but peaks were incongruent, and searches did not always grow exponentially after the initial week. Searches for "coronavirus AND sun" had different start times across countries but peaked at the same time for multiple countries. Patterns in the start, peak, and doubling time for "coronavirus AND 5G" were different from the other misinformation topics and were mostly consistent across countries assessed, which might be attributable to a lack of public understanding of 5G technology. Understanding the spread of misinformation, similarities and differences across different contexts can help in the development of appropriate interventions for limiting its impact similar to how we address infectious disease epidemics. Furthermore, the rapid proliferation of misinformation that discourages adherence to public health interventions could be predictive of future increases in disease cases.
Sections du résumé
BACKGROUND
The epidemic of misinformation about COVID-19 transmission, prevention, and treatment has been going on since the start of the pandemic. However, data on the exposure and impact of misinformation is not readily available.
OBJECTIVE
We aim to characterize and compare the start, peak, and doubling time of COVID-19 misinformation topics across 8 countries using an exponential growth model usually employed to study infectious disease epidemics.
METHODS
COVID-19 misinformation topics were selected from the World Health Organization Mythbusters website. Data representing exposure was obtained from the Google Trends application programming interface for 8 English-speaking countries. Exponential growth models were used in modeling trends for each country.
RESULTS
Searches for "coronavirus AND 5G" started at different times but peaked in the same week for 6 countries. Searches for 5G also had the shortest doubling time across all misinformation topics, with the shortest time in Nigeria and South Africa (approximately 4-5 days). Searches for "coronavirus AND ginger" started at the same time (the week of January 19, 2020) for several countries, but peaks were incongruent, and searches did not always grow exponentially after the initial week. Searches for "coronavirus AND sun" had different start times across countries but peaked at the same time for multiple countries.
CONCLUSIONS
Patterns in the start, peak, and doubling time for "coronavirus AND 5G" were different from the other misinformation topics and were mostly consistent across countries assessed, which might be attributable to a lack of public understanding of 5G technology. Understanding the spread of misinformation, similarities and differences across different contexts can help in the development of appropriate interventions for limiting its impact similar to how we address infectious disease epidemics. Furthermore, the rapid proliferation of misinformation that discourages adherence to public health interventions could be predictive of future increases in disease cases.
Identifiants
pubmed: 33264102
pii: v22i12e24425
doi: 10.2196/24425
pmc: PMC7744144
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
e24425Informations de copyright
©Elaine Okanyene Nsoesie, Nina Cesare, Martin Müller, Al Ozonoff. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.12.2020.
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