Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

COVID-19 predictability in Portugal using Google Trends

View through CrossRef
Abstract Background Infodemiology is a valuable public health tool which analyses internet sources and real-time data to establish populational trends, thus assisting disease surveillance. Google trends (GT) is a popular infodemiology source widely used in previous reports to study the correlation between internet relative search volume (RSV) and surges in various pathologies. This study aims to explore the association between GT and Covid-19 symptoms and to access the possibility of predicting new surges from internet searches. Methods Individual data was extracted from GT RSV on four main Covid-19 related symptoms in the Health category (fever, headache, cough and shortness of breath) in Portugal between 2020/03/02 and 2021/02/15, corresponding to each of the identified surges of daily new cases (DNC) in Portugal, retrieved from GitHub. Pearson's-correlation coefficient was used for assessment. Additionally, a 14 days time-lag correlation analysis between data for the same period of time was performed. Results Statistically significant correlations were found between ‘fever' web searches and the DNC in the first (p = 0.02) and third (p = 0.02) wave. No statistically significant correlations were found between any other variables. Through time lag analysis, we found a maximum Pearson association between web searches for ‘cough' and the DNC during the first wave at 14 days (r = 0.55), as well as during the third wave, with a maximum association at 3 days time lag (r = 0.55). Conclusions Monitoring behaviour and public interest in health related issues, such as crisis, is necessary and may help in the establishment of better and target oriented health policies. Despite previously stated potential, constraints such as the exclusion of social media platforms or internet users' representativeness, could partly explain our limited results for portuguese predictability of new COVID-19 surges. A better understanding of GT's algorithm may lead to more detailed and precise data. Key messages Monitoring behaviour and public interest in health related issues is necessary to establish better and more targeted health policies. Google trends seems to be an helpful infodemiology source, but doesn’t allow for full representation of the population and needs better understanding.
Title: COVID-19 predictability in Portugal using Google Trends
Description:
Abstract Background Infodemiology is a valuable public health tool which analyses internet sources and real-time data to establish populational trends, thus assisting disease surveillance.
Google trends (GT) is a popular infodemiology source widely used in previous reports to study the correlation between internet relative search volume (RSV) and surges in various pathologies.
This study aims to explore the association between GT and Covid-19 symptoms and to access the possibility of predicting new surges from internet searches.
Methods Individual data was extracted from GT RSV on four main Covid-19 related symptoms in the Health category (fever, headache, cough and shortness of breath) in Portugal between 2020/03/02 and 2021/02/15, corresponding to each of the identified surges of daily new cases (DNC) in Portugal, retrieved from GitHub.
Pearson's-correlation coefficient was used for assessment.
Additionally, a 14 days time-lag correlation analysis between data for the same period of time was performed.
Results Statistically significant correlations were found between ‘fever' web searches and the DNC in the first (p = 0.
02) and third (p = 0.
02) wave.
No statistically significant correlations were found between any other variables.
Through time lag analysis, we found a maximum Pearson association between web searches for ‘cough' and the DNC during the first wave at 14 days (r = 0.
55), as well as during the third wave, with a maximum association at 3 days time lag (r = 0.
55).
Conclusions Monitoring behaviour and public interest in health related issues, such as crisis, is necessary and may help in the establishment of better and target oriented health policies.
Despite previously stated potential, constraints such as the exclusion of social media platforms or internet users' representativeness, could partly explain our limited results for portuguese predictability of new COVID-19 surges.
A better understanding of GT's algorithm may lead to more detailed and precise data.
Key messages Monitoring behaviour and public interest in health related issues is necessary to establish better and more targeted health policies.
Google trends seems to be an helpful infodemiology source, but doesn’t allow for full representation of the population and needs better understanding.

Related Results

Process-based analysis of land carbon flux predictability
Process-based analysis of land carbon flux predictability
<p>The land-atmosphere CO<sub>2</sub> exchange exhibits a very high interannual variability which dominates variability in atmospheric CO&...
ERROR ESTIMATION FOR A PIEZOELECTRIC CONTACT PROBLEM WITH WEAR AND LONG MEMORY
ERROR ESTIMATION FOR A PIEZOELECTRIC CONTACT PROBLEM WITH WEAR AND LONG MEMORY
We study a mathematical model for a quasistatic behavior of electro-viscoelastic materials. The problem is related to highly nonlinear and non-smooth phenomena like contact, fricti...
PERSEPSI IBU HAMIL TENTANG VAKSIN COVID-19 TERHADAP PELAKSANAAN VAKSINASI COVID-19
PERSEPSI IBU HAMIL TENTANG VAKSIN COVID-19 TERHADAP PELAKSANAAN VAKSINASI COVID-19
Latar Belakang: kasus positif Covid-19 di Kabupaten Sukoharjo tahun 2021 mencapai 12.350 dan terus mengalami penambahan jumlah. Dari jumlah tersebut terdapat 168 kasus positif Covi...
An Analysis of The Obstacles Found by Teachers in Using Google Meet Application in Online English Learning at SMP Dwijendra Denpasar
An Analysis of The Obstacles Found by Teachers in Using Google Meet Application in Online English Learning at SMP Dwijendra Denpasar
Abstrak- Penelitian ini bertujuan untuk menyelidiki dan menganalisis kendala yang ditemukan oleh guru dalam menggunakan aplikasi Google Meet pada pembelajaran Bahasa Inggris online...
#3498 LONG-COVID IN PATIENTS ON HEMODIALYSIS: A SINGLE CENTER ANALYSIS
#3498 LONG-COVID IN PATIENTS ON HEMODIALYSIS: A SINGLE CENTER ANALYSIS
Abstract Background and Aims It is known that maintenance hemodialysis (MHD) patients have a high risk of initial mortality from...
Using Primary Care Text Data and Natural Language Processing to Monitor COVID-19 in Toronto, Canada
Using Primary Care Text Data and Natural Language Processing to Monitor COVID-19 in Toronto, Canada
AbstractObjectiveTo investigate whether a rule-based natural language processing (NLP) system, applied to primary care clinical text data, can be used to monitor COVID-19 viral act...
CARA PENCEGAHAN PENYEBARAN COVID-19
CARA PENCEGAHAN PENYEBARAN COVID-19
ABSTRAK Covid-19 melanda banyak Negara di dunia termasuk Indonesia. Wabah Covid-19 tidak hanya merupakan masalah nasional dalam suatu Negara, tapi sudah merupakan masalah global. C...
Predictability Characteristics of Landfalling Cyclones along the North American West Coast
Predictability Characteristics of Landfalling Cyclones along the North American West Coast
Abstract The predictability of North Pacific cyclones can vary widely, from highly accurate prediction of storm intensity and location to forecast position errors of...

Back to Top