Internet searching may predict novel symptoms, but not new outbreaks. A long-term evaluation of infoveillance in COVID-19

Simple item record

Full item record

dc.contributor.authorRadziwon, Jakub Aleksander
dc.contributor.authorLubiejewski, Maciej
dc.contributor.authorWaszak, Przemysław M.
dc.contributor.authorHeleniak, Zbigniew
dc.contributor.authorDębska-Ślizień, Maria Alicja
dc.contributor.organizationScientific Circle of Adult Neurology, Medical University of Gdańsk, Polanden
dc.contributor.organizationStudent Scientific Group of Nephrology, Department of Nephrology, Transplantology and Internal Diseases, Medical University of Gdańsk, Polanden
dc.contributor.organizationDepartment of Hygiene and Epidemiology, Medical University of Gdańsk, Polanden
dc.contributor.organizationDepartment of Nephrology, Transplantology and Internal Diseases, Medical University of Gdańsk, Polanden
dc.date.accessioned2024-01-15T14:42:29Z
dc.date.available2024-01-15T14:42:29Z
dc.date.issued2023-11-09
dc.description.abstractBackground: At the beginning of COVID-19 pandemic authors in several countries reported the possibility of predicting disease outbreaks using internet analysis and search tools like GoogleTrends™. Our aim was to investigate the impact of changes in COVID-19 symptomatology and pandemic intensity on those predictions. Material and methods: GoogleTrends™ was utilized to track online searches for COVID-19 symptoms in Poland during two years of the pandemic. Search volumes were then assessed for correlation with daily cases in each wave of infection separately. Results: The symptoms that correlated strongly with new cases were anosmia and ageusia (Spearman’s rho = 0.5230 and rho = 0.4483 respectively, p < 0.01). Searches for these symptoms preceded an outbreak by 12 days during the first wave of infections, but this gap was later shortened to five days. The frequency of searching for these symptoms markedly diminished during the last phase and was no longer adequate. Stronger correlations were then shown for fever, sore throat, and headache. Conclusions: In conclusion, COVID-19 case prediction using GoogleTrends™ did not remain possible later on in the pandemic course. However, noticeable changes reflecting novel features of emerging SARS-CoV-2 variants were observed. Therefore, monitoring symptom changes and virus evolution might be a promising application of internet search analysis in the future.en
dc.identifier.citationRadziwon JA, Lubiejewski M, Waszak P, Heleniak Z, Dębska-Ślizień MA. Internet searching may predict novel symptoms, but not new outbreaks. A long-term evaluation of infoveillance in COVID-19. Eur J Transl Clin Med. 2023;6(2):71-77.en
dc.identifier.doi10.31373/ejtcm/173451
dc.identifier.issn2657-3156
dc.identifier.urihttps://open.icm.edu.pl/handle/123456789/23606
dc.language.isoen
dc.publisherMedical University of Gdańsken
dc.rightsUznanie autorstwa-Na tych samych warunkach 4.0 Międzynarodowe*
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/*
dc.subjectpredictionen
dc.subjectCOVID-19en
dc.subjectinfodemiologyen
dc.titleInternet searching may predict novel symptoms, but not new outbreaks. A long-term evaluation of infoveillance in COVID-19en
dc.typearticleen
Files for this record
Original bundle
Now showing 1 - 1 of 1
Name: EJTCM_2023_6_2_Radziwon.pdf
Size: 724.24 KB
Format: Adobe Portable Document Format
Description:
Download
License files
Name: license.txt
Size: 452 B
Format: Plain Text
Description:
Download
Belongs to collection
Artykuły / Articles