Coronavirus-related online web search desire amidst the rising novel coronavirus incidence in Ethiopia: Google Trends-based infodemiology
Terefe, B.; Rovetta, A.; Rajan, A. K.; Awoke, M.
Show abstract
BackgroundDuring disease outbreaks, social communication and behaviors are very important to contain the outbreak. Under such circumstances, individual activities on online platforms will increase tremendously. This will result in the circulation useful or misleading/misinformation (infodemic monikers) in the community. Thus, exploring the online trending information is highly crucial in the process of containing disease outbreak. Therefore, this study aimed to explore users concerns towards coronavirus-related online web search activities and to investigate the extent of misleading terms adopted for identifying the virus in the early stage of COVID-19 spread in Ethiopia. MethodsGoogle Trends was employed in exploring the tendency towards coronavirus-related web search activities in Ethiopia from March 13 to May 8, 2020. Keywords of the different names of COVID-19 and health-related issues were used to investigate the trends of public interest in searching from Google over time. Relative search volume (RSV) and Average peak comparison (APC) were used to compare the trends of online search interests. Pearson correlation coefficient was calculated to check for the presence of correlation. ResultDuring the study period, "corona," "virus," "coronavirus," "corona virus", "China coronavirus," and "COVID-19", were the top names users adopted to identify the virus. In almost all search activities, the users employed infodemic monikers to identify the virus (99%). "Updates" related issues (APC=60, 95% CI, 55 - 66) were the most commonly trending health-related searches on Google followed by mortality (APC=27, 95% CI, 24 - 30) and symptoms (APC=55, 95% CI, 50 - 60) related issues. The regional comparison showed the highest cumulative peak for the Oromia region on querying health-related information from Google. ConclusionThis study revealed an initial increase in the public interest of COVID-19 related Google search, but this interest was declined over time. Tremendous circulation of infodemic monikers for the identification of the virus was also noticed in the country. The authors recommend concerned stakeholders to work immensely to keep the public alert on coronavirus-related issues and to promote the official names of the virus to decrease the circulation of misleading and misinformation amid the outbreak.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Assessing the community risk perception toward COVID-19 outbreak in South Korea: evidence from Google and NAVER relative search volume 94%
- Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: A Digital Topic Modeling Approach 93%
- Fear of Infection and Sufficient Vaccine Reservation Information Might Drive Rapid Coronavirus Disease 2019 Vaccination in Japan: Evidence from Twitter Analysis 93%
Similar papers in this journal
- The knowledge and practice towards COVID-19 pandemic prevention among residents of Ethiopia. An online cross-sectional study. 94%
- Strengthening government’s response to COVID-19 in Indonesia: a modified Delphi study of medical and health academics 94%
- Misinformation on covid-19 origin and its relationship with perception and knowledge about social distancing: A cross-sectional study 94%
Similar papers in this journal
Similar papers in this journal
- Knowledge, attitude and practice toward COVID-19 among healthcare workers in public health facilities, Eastern Ethiopia 92%
- A Web-based, Mobile Responsive Application to Screen Healthcare Workers for COVID Symptoms: Descriptive Study 92%
- Iterative Development of a Mobile Phone Application to Support Community Health Volunteers during Cervical Cancer Screening in Western Kenya 91%
Similar papers in this journal
- NTT Docomo and Apple mobility data compared as countermeasures against COVID-19 outbreak in Japan 91%
- Isolation Considered Epidemiological Model for the Prediction of COVID-19 Trend in Tokyo, Japan 91%
- The relationship between demographic, psychosocial and health-related parameters and the impact of COVID-19: a study of twenty-four Indian regions 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.