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1.
Heliyon ; 8(10): e10867, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2105012

ABSTRACT

The COVID-19 pandemic has prompted the re-emergence of staycations to the fore, as many people were forced to spend their vacations at or close to home due to travel restrictions. This phenomenon first went mainstream during the 2008 financial crisis, and has now been further accelerated by the COVID-19 pandemic. This study investigated the growth and practice of staycations during the first two years of the pandemic by analyzing social media and internet search data using Latent Dirichlet Allocation (LDA) topic modeling and Google Trends analytics. Key findings suggest that, while spatially close to home, people tried to achieve a psychological distance away from home. This was demonstrated by a strong global search interest in spending staycations at hotels close to home. The optimal LDA topic model produced 38 topics which were classified under four aggregate dimensions of antecedents, attributes, activities, and consequences of staycations. The findings provide useful insights to managers and policymakers on boosting revenue through this practice, and the role of staycations in promoting leisure activities close to home and sustainable tourism.

2.
BMC Infect Dis ; 22(1): 806, 2022 Oct 29.
Article in English | MEDLINE | ID: covidwho-2098320

ABSTRACT

BACKGROUND: Coronavirus Disease 2019 (COVID-19) pandemic affects common diseases, but its impact on hand, foot, and mouth disease (HFMD) is unclear. Google Trends data is beneficial for approximate real-time statistics and because of ease in access, is expected to be used for infection explanation from an information-seeking behavior perspective. We aimed to explain HFMD cases before and during COVID-19 using Google Trends. METHODS: HFMD cases were obtained from the National Institute of Infectious Diseases, and Google search data from 2009 to 2021 in Japan were downloaded from Google Trends. Pearson correlation coefficients were calculated between HFMD cases and the search topic "HFMD" from 2009 to 2021. Japanese tweets containing "HFMD" were retrieved to select search terms for further analysis. Search terms with counts larger than 1000 and belonging to ranges of infection sources, susceptible sites, susceptible populations, symptoms, treatment, preventive measures, and identified diseases were retained. Cross-correlation analyses were conducted to detect lag changes between HFMD cases and search terms before and during the COVID-19 pandemic. Multiple linear regressions with backward elimination processing were used to identify the most significant terms for HFMD explanation. RESULTS: HFMD cases and Google search volume peaked around July in most years, excluding 2020 and 2021. The search topic "HFMD" presented strong correlations with HFMD cases, except in 2020 when the COVID-19 outbreak occurred. In addition, the differences in lags for 73 (72.3%) search terms were negative, which might indicate increasing public awareness of HFMD infections during the COVID-19 pandemic. The results of multiple linear regression demonstrated that significant search terms contained the same meanings but expanded informative search content during the COVID-19 pandemic. CONCLUSIONS: The significant terms for the explanation of HFMD cases before and during COVID-19 were different. Awareness of HFMD infections in Japan may have improved during the COVID-19 pandemic. Continuous monitoring is important to promote public health and prevent resurgence. The public interest reflected in information-seeking behavior can be helpful for public health surveillance.


Subject(s)
COVID-19 , Hand, Foot and Mouth Disease , Mouth Diseases , Humans , COVID-19/epidemiology , Pandemics , Japan/epidemiology , Search Engine , Hand, Foot and Mouth Disease/epidemiology , Infodemiology
3.
Sisli Etfal Hastan Tip Bul ; 56(3): 323-327, 2022.
Article in English | MEDLINE | ID: covidwho-2091035

ABSTRACT

Objectives: The aim of the study was to clarify public interest about cardiovascular disease during the COVID-19 pandemic using Google Trends (GT). Methods: The study was performed between November 20 and December 1, 2021. A total of 21 keywords related to cardiovascular surgery were selected. Public attention to all selected keywords was analyzed by GT with using the filters "web search," "all categories," and "Turkey." In Turkey, three COVID-19 waves (between March 12, 2020, and May 8, 2020, November 24, 2020, and January 20, 2021, and March 20, 2021, and May 16, 2021) were experienced since the beginning of the pandemic. To analyze public attention to cardiovascular surgery during the COVID-19 waves, 8-week periods during the COVID-19 waves were compared with the same times in the past 4 years (2016-2019). Results: Comparisons of March 12-May 8 2020 and the same period between 2016 and 2019 showed that total public interest about cardiovascular surgery was significantly decreased (-28.7%, p=0.001). The comparison of the second COVID-19 wave (November 24, 2020-January 20, 2021 versus November 24-January 20, 2016-2019) revealed that public interest about cardiovascular surgery was significantly lower in the COVID-19 era (-22.2%, p=0.001). Comparison of the third COVID-19 wave and the same periods in the previous 4 years demonstrated that public interest about cardiovascular disease was significantly lower in the COVID-19 era (-8.5%, p=0.001). In contrast, the term coronary angiography was searched significantly more during the third wave of COVID-19 in comparison to the same periods between 2016 and 2019 (17.9%, p=0.015). Conclusion: Our study demonstrated that public interest in cardiovascular diseases was significantly decreased in all waves of the COVID-19 pandemic. However, interest in only the term coronary angiography was significantly increased in the third wave of pandemic.

4.
Embase; 27.
Preprint in English | EMBASE | ID: ppcovidwho-346615

ABSTRACT

Background: COVID-19 pandemic affected common disease infections, while the impact on hand, foot, and mouth disease (HFMD) is unclear. Google Trends data is beneficial in approximately real-time statistics and easily accessed, expecting to be used for infection explanation from information-seeking behavior perspectives. We aimed to explain HFMD cases before and during COVID-19 using Google Trends data. Method(s): HFMD cases were obtained from the National Institute of Infectious Disease, and Google search data from 2009 to 2021 was downloaded using Google Trends in Japan. Pearson correlation coefficients were calculated between HFMD cases and the search topic "HFMD" from 2009 to 2021. Japanese tweets containing "HFMD" were retrieved to select search terms for further analysis. Search terms were retained with counts larger than 1000 and belonging to ranges of infection sources, susceptible sites, susceptible populations, symptoms, treatment, preventive measures, and identified diseases. Cross-correlation analyses were conducted to detect lag changes between HFMD cases and HFMD search terms before and during COVID-19. Multiple linear regressions with backward elimination processing were used to identify the most significant terms for HFMD explanation. Result(s): HFMD cases and Google search volume peaked around July in most years without 2020 and 2021. The search topic "HFMD" presented strong correlations with HFMD cases except in 2020 when COVID-19 outbroke. In addition, differences in lags for 73 (72.3%) search terms were negative, might indicating increasing public awareness of HFMD infections during the COVID-19 pandemic. Results of multiple linear regression demonstrated that significant search terms contained the same meanings but expanded informative search content during COVID-19. Conclusion(s): Significant terms for HFMD cases explanation before and during COVID-19 were different. The awareness of HFMD infection in Japan may improve during the COVID-19 pandemic. Continuous monitoring is important to promote public health and prevent resurgence. Public interest reflected in information-seeking behavior can be helpful for public health surveillance. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

5.
Folia Med Cracov ; 62(2): 71-92, 2022.
Article in English | MEDLINE | ID: covidwho-2081393

ABSTRACT

I n t r o d u c t i o n: The COVID-19 pandemic has put healthcare systems worldwide under huge strain, resulting in a significant loss of their capacity and availability. Patients have become more reluctant to contact their doctors or call an ambulance in case of myocardial infarction (MI) symptoms onset. It has been accompanied by a significant decrease in the number of coronary angiography and PCI procedures performed. O b j e c t i v e s: The aim of the study is to evaluate the role of online health information in the patient- dependent phase of MI management during the COVID-19 lockdown in Europe. Methods: We analyzed Google Trends data on the popularity of phrases related to MI symptoms, respiratory tract infection, urological complaints, and terms unrelated to health, for the period of the first COVID-19 lockdown, along with the data from the corresponding weeks from 2017-2019 in seven European countries. R e s u l t s: The search volume for particular symptoms of myocardial infarction increased in all studied countries, compared to the analogous period from 2017-2019, with a significant increase in for chest pain, shortness of breath, fear, and palpitations in most countries. These changes have not been accompanied by increased interest in terms related to respiratory tract infection symptoms and urological complaints. C o n c l u s i o n s: Our findings suggest that during lockdown, patients with MI symptoms may have tried to manage their complaints on their own, using information from the Internet. This demonstrates the growing role of the Internet in the patient's decision-making process in the emergency situation, indicating a growing need for reliable and freely available online information provided by healthcare professionals.


Subject(s)
COVID-19 , Myocardial Infarction , Percutaneous Coronary Intervention , Humans , COVID-19/epidemiology , Pandemics , Communicable Disease Control , Myocardial Infarction/epidemiology , Myocardial Infarction/therapy , Europe/epidemiology
6.
J Prev Med Hyg ; 63(2): E292-E297, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-2081079

ABSTRACT

Introduction: Viral hepatitis remains a public health concern worldwide, mainly in developing countries. The public's awareness and interest in viral hepatitis information are essential in preventing and controlling this disease. Infodemiology has been used as a surrogate to assess the general understanding of disease and measure public awareness of health topics. However, this analysis has not been applied to viral hepatitis. Thus, this study investigated the online global search interest for viral hepatitis in the last decade, focusing on the period before and during the COVID-19 pandemic. Methods: Global online search interest for hepatitis was measured using the Google Trends™ database. Spearman's rank-order correlation correlated country-specific characteristics and prevalence data with search volume index. Results: There was a significant reduction in online search interest for hepatitis during the COVID-19 pandemic (2020). People searching for hepatitis are also interested in hepatitis vaccination. Search volume index is positively correlated with viral hepatitis and HIV prevalence and negatively correlated with GDP. This correlation mirrors the high burden of viral hepatitis in developing countries and their citizens' desire to be informed about this disease. Conclusions: Our study found decreased global online interest in viral hepatitis during the pandemic. Moreover, higher online interest in hepatitis was observed in countries with a lower gross domestic product and high viral hepatitis and HIV prevalence. We demonstrated that global online interest toward viral hepatitis could be assessed through the infodemiologic approach using Google Trends™.


Subject(s)
COVID-19 , HIV Infections , Hepatitis, Viral, Human , HIV Infections/epidemiology , Hepatitis, Viral, Human/epidemiology , Hepatitis, Viral, Human/prevention & control , Humans , Infodemiology , Information Seeking Behavior , Pandemics
7.
Respiratory Medicine and Research ; : 100967, 2022.
Article in English | ScienceDirect | ID: covidwho-2069629

ABSTRACT

Lung transplant (LT) is a life-saving treatment for patients with end-stage lung disease. In the setting of COVID-19-associated acute respiratory distress syndrome (ARDS), LT emerged as a therapeutic option for select cases. It is challenging to determine the extent of the knowledge and interest the United States (US) general population has on LT as salvage therapy during and following the COVID-19 pandemic. It is the authors’ opinion that patient therapeutic education (PTE) can directly influence established practices by creating an open channel of communication based on needs and expectations for healthcare services. This perspective is a cursory reflection of the nuances between healthcare providers, their services, the interests and expectations of the general population, specifically on LT following COVID-19. The main endpoint of this study is to analyze the US general population's interest in LT as COVID-19 salvage therapy via the Google Trends (GT) web-kit tool.

8.
Int J Environ Res Public Health ; 19(19)2022 Sep 29.
Article in English | MEDLINE | ID: covidwho-2065963

ABSTRACT

The probability of future Coronavirus Disease (COVID)-19 waves remains high, thus COVID-19 surveillance and forecasting remains important. Online search engines harvest vast amounts of data from the general population in real time and make these data publicly accessible via such tools as Google Trends (GT). Therefore, the aim of this study was to review the literature about possible use of GT for COVID-19 surveillance and prediction of its outbreaks. We collected and reviewed articles about the possible use of GT for COVID-19 surveillance published in the first 2 years of the pandemic. We resulted in 54 publications that were used in this review. The majority of the studies (83.3%) included in this review showed positive results of the possible use of GT for forecasting COVID-19 outbreaks. Most of the studies were performed in English-speaking countries (61.1%). The most frequently used keyword was "coronavirus" (53.7%), followed by "COVID-19" (31.5%) and "COVID" (20.4%). Many authors have made analyses in multiple countries (46.3%) and obtained the same results for the majority of them, thus showing the robustness of the chosen methods. Various methods including long short-term memory (3.7%), random forest regression (3.7%), Adaboost algorithm (1.9%), autoregressive integrated moving average, neural network autoregression (1.9%), and vector error correction modeling (1.9%) were used for the analysis. It was seen that most of the publications with positive results (72.2%) were using data from the first wave of the COVID-19 pandemic. Later, the search volumes reduced even though the incidence peaked. In most countries, the use of GT data showed to be beneficial for forecasting and surveillance of COVID-19 spread.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , Disease Outbreaks , Forecasting , Humans , Search Engine
9.
23rd IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2022 ; : 178-183, 2022.
Article in English | Scopus | ID: covidwho-2063270

ABSTRACT

COVID-19 pandemic has resulted in excess mortality globally and presented an unprecedented challenge to people's lives. Despite the benefits of getting a COVID-19 vaccine, there have been arguments against the available vaccines and vaccine hesitancy worldwide. In this work, we analyze the information published by the public on Reddit as a digital forum, using unsupervised natural language processing to discover useful insights from the collected data related to COVID-19 vaccines, and validate the results of our study using Google Trends. Our results show that the government's contributions to the vaccination process, vaccine side-effects, and opposition to vaccine mandate and lock-downs are the main concerns shared by the public on digital forums. Moreover, we provide our collected data publicly available for further infodemiology studies by researchers and practitioners. © 2022 IEEE.

10.
Front Res Metr Anal ; 7: 1003972, 2022.
Article in English | MEDLINE | ID: covidwho-2055102

ABSTRACT

Infodemiologic methods could be used to enhance modeling infectious diseases. It is of interest to verify the utility of these methods using a Nigerian case study. We used Google Trends data to track COVID-19 incidences and assessed whether they could complement traditional data based solely on reported case numbers. Data on the Nigerian weekly COVID-19 cases spanning through March 1, 2020, to May 31, 2021, were matched with internet search data from Google Trends. The reported weekly incidence numbers and the GT data were split into training and testing sets. ARIMA models were fitted to describe reported weekly COVID cases using the training set. Several COVID-related search terms were theoretically and empirically assessed for initial screening. The utilized Google Trends (GT) variable was added to the ARIMA model as a regressor. Model forecasts, both with and without GTD, were compared with weekly cases in the test set over 13 weeks. Forecast accuracies were compared visually and using RMSE (root mean square error) and MAE (mean average error). Statistical significance of the difference in predictions was determined with the two-sided Diebold-Mariano test. Preliminary results of contemporaneous correlations between COVID-related search terms and weekly COVID cases reveal "loss of smell," "loss of taste," "fever" (in order of magnitude) as significantly associated with the official cases. Predictions of the ARIMA model using solely reported case numbers resulted in an RMSE (root mean squared error) of 411.4 and mean absolute error (MAE) of 354.9. The GT expanded model achieved better forecasting accuracy (RMSE: 388.7 and MAE = 340.1). Corrected Akaike Information Criteria also favored the GT expanded model (869.4 vs. 872.2). The difference in predictive performances was significant when using a two-sided Diebold-Mariano test (DM = 6.75, p < 0.001) for the 13 weeks. Google trends data enhanced the predictive ability of a traditionally based model and should be considered a suitable method to enhance infectious disease modeling.

11.
2022 International Conference on Data Science and Its Applications, ICoDSA 2022 ; : 220-225, 2022.
Article in English | Scopus | ID: covidwho-2052016

ABSTRACT

The COVID-19 pandemic has impacted many sectors. For example, in the aviation sector, flight traffic went down drastically with no certainty of being recovered. This calls for a methodology to predict the flight traffic to provide strategic planning on flight schedules operational, route structuring, and flight navigation service cost determination. However, current developments mainly focus on flight traffic forecasting based on historical data without considering external factors. In this study, we propose the Long Short-Term Memory (LSTM) technique to forecast flight traffic in Indonesia involving external variables such as macroeconomic variables and Google Trends. LSTM is proposed because of its flexibility to model non-linear time series data and has a good reputation for predictive accuracy. We first select a few among Google Trends and macroeconomic variables using nonlinearity analysis and cross-correlation function (CCF). We then employ the selected variables to forecast the flight traffic and compare it to the one using only historical flight traffic data. Our results concluded, based on the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), that the model involving google trend outperforms the other three models, i.e., the model with only historical data, the model with macroeconomics, and the model with both macroeconomic and Google Trends. It is because, in this digital era, Google Trends can reflect population psychology in an up-to-date manner. © 2022 IEEE.

12.
JMIR Form Res ; 6(9): e36525, 2022 Sep 14.
Article in English | MEDLINE | ID: covidwho-2029897

ABSTRACT

BACKGROUND: Recently, the use of telehealth for patient treatment under the COVID-19 pandemic has gained interest around the world. As a result, many infodemiology and infoveillance studies using web-based sources such as Google Trends were reported, focusing on the first wave of the COVID-19 pandemic. Although public interest in telehealth has increased in many countries during this time, the long-term interest has remained unknown among people living in Japan. Moreover, various mobile telehealth apps have become available for remote areas in the COVID-19 era, but the accessibility of these apps in epidemic versus nonepidemic regions is unknown. OBJECTIVE: We aimed to investigate the public interest in telehealth during the first pandemic wave and after the wave in the first part of this study, and the accessibility of medical institutions using telehealth in the epidemic and nonepidemic regions, in the second part. METHODS: We examined and compared the first wave and after the wave with regards to severe cases, number of deaths, relative search volume (RSV) of telehealth and COVID-19, and the correlation between RSV and COVID-19 cases, using open sources such as Google Trends and the Japanese Ministry of Health, Labour and Welfare (JMHLW) data. The weekly mean and the week-over-week change rates of RSV and COVID-19 cases were used to examine the correlation coefficients. In the second part, the prevalence of COVID-19 cases, severe cases, number of deaths, and the telehealth accessibility rate were compared between epidemic regions and nonepidemic regions, using the JMHLW data. We also examined the regional correlation between telehealth accessibility and the prevalence of COVID-19 cases. RESULTS: Among the 83 weeks with 5 pandemic waves, the overall mean for the RSV of telehealth and COVID-19 was 11.3 (95% CI 8.0-14.6) and 30.7 (95% CI 27.2-34.2), respectively. The proportion of severe cases (26.54% vs 18.16%; P<.001), deaths (5.33% vs 0.99%; P<.001), RSV of telehealth (mean 33.1, 95% CI 16.2-50.0 vs mean 7.3, 95% CI 6.7-8.0; P<.001), and RSV of COVID-19 (mean 52.1, 95% CI 38.3-65.9 vs mean 26.3, 95% CI 24.4-29.2; P<.001) was significantly higher in the first wave compared to after the wave. In the correlation analysis, the public interest in telehealth was 0.899 in the first wave and -0.300 overall. In Japan, the accessibility of telehealth using mobile apps was significantly higher in epidemic regions compared to nonepidemic regions in both hospitals (3.8% vs 2.0%; P=.004) and general clinics (5.2% vs 3.1%; P<.001). In the regional correlation analysis, telehealth accessibility using mobile apps was 0.497 in hospitals and 0.629 in general clinics. CONCLUSIONS: Although there was no long-term correlation between the public interest in telehealth and COVID-19, there was a regional correlation between mobile telehealth app accessibility in Japan, especially for general clinics. We also revealed that epidemic regions had higher mobile telehealth app accessibility. Further studies about the actual use of telehealth and its effect after the COVID-19 pandemic are necessary.

13.
Journal of Official Statistics (JOS) ; 38(3):733-765, 2022.
Article in English | Academic Search Complete | ID: covidwho-2029921

ABSTRACT

In this article, we present a new approach based on dynamic factor models (DFMs) to perform accurate nowcasts for the percentage annual variation of the Mexican Global Economic Activity Indicator (IGAE), the commonly used variable as an approximation of monthly GDP. The procedure exploits the contemporaneous relationship of the timely traditional macroeconomic time series and nontraditional variables as Google Trends with respect to the IGAE. We evaluate the performance of the approach in a pseudo real-time framework, which includes the pandemic of COVID-19, and conclude that the procedure obtains accurate estimates, for one and two-steps ahead, above all, given the use of Google Trends. Another contribution for economic nowcasting is that the approach allows to disentangle the key variables in the DFM by estimating the confidence interval for the factor loadings, hence allows to evaluate the statistical significance of the variables in the DFM. This approach is used in official statistics to obtain preliminary and accurate estimates for IGAE up to 40 days before the official data release. [ FROM AUTHOR] Copyright of Journal of Official Statistics (JOS) is the property of Journal of Official Statistics (JOS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

14.
JMIR Public Health Surveill ; 8(8): e37656, 2022 08 29.
Article in English | MEDLINE | ID: covidwho-2022376

ABSTRACT

BACKGROUND: The human papillomavirus (HPV) vaccine is recommended for adolescents and young adults to prevent HPV-related cancers and genital warts. However, HPV vaccine uptake among the target age groups is suboptimal. OBJECTIVE: The aim of this infodemiology study was to examine public online searches in the United States related to the HPV vaccine from January 2010 to December 2021. METHODS: Google Trends (GT) was used to explore online searches related to the HPV vaccine from January 1, 2010, to December 31, 2021. Online searches and queries on the HPV vaccine were investigated using relative search volumes (RSVs). Analysis of variance was performed to investigate quarterly differences in HPV vaccine searches in each year from 2010 to 2021. A joinpoint regression was used to identify statistically significant changes over time; the α level was set to .05. RESULTS: The year-wise online search volume related to the HPV vaccine increased from 2010 to 2021, often following federal changes related to vaccine administration. Joinpoint regression analysis showed that HPV vaccine searches significantly increased on average by 8.6% (95% CI 5.9%-11.4%) across each year from 2010 to 2021. Moreover, HPV vaccine searches demonstrated a similar pattern across years, with search interest increasing through August nearly every year. At the state level, the highest 12-year mean RSV was observed in California (59.9, SD 14.3) and the lowest was observed in Wyoming (17.4, SD 8.5) during the period of 2010-2021. CONCLUSIONS: Online searches related to the HPV vaccine increased by an average of 8.6% across each year from 2010 to 2021, with noticeable spikes corresponding to key changes in vaccine recommendations. We identified patterns across years and differences at the state level in the online search interest related to the HPV vaccine. Public health organizations can use GT as a tool to characterize the public interest in and promote the HPV vaccine in the United States.


Subject(s)
Papillomavirus Infections , Papillomavirus Vaccines , Adolescent , Humans , Infodemiology , Papillomavirus Infections/prevention & control , Papillomavirus Vaccines/therapeutic use , Search Engine , United States , Vaccination , Young Adult
15.
J Pediatr Nurs ; 66: 191-195, 2022.
Article in English | MEDLINE | ID: covidwho-2000658

ABSTRACT

OBJECTIVES: The objective was to analyze in silico public search interest during the COVID-19 pandemic for some classic infectious childhood diseases, e.g., measles, mumps, chickenpox, scarlet fever, and inflammatory diseases like Kawasaki disease and the pediatric inflammatory multisystem syndrome (PIMS). STUDY DESIGN: In this study, a comparison of five childhood diseases in public search trends with the pediatric inflammatory multisystem syndrome was performed. METHODS: Google Trends data for the period of five years for six childhood diseases were used. We used topics coverings all languages worldwide and all connected search queries. RESULTS: Public search interest decreased during the COVID-19 pandemic for some classic infectious childhood diseases. Search interest for the pediatric inflammatory multisystem syndrome, despite strong indication of a connection with COVID-19, remained relatively low compared to Kawasaki disease. PRACTICE IMPLICATIONS: Better understanding of Google Trends can map public awareness of childhood diseases in terms of time course and search intensity. CONCLUSIONS: Public interest during the pandemic was generated for diseases with suspected connection to COVID-19, presumably due to media triggers.


Subject(s)
COVID-19 , Mucocutaneous Lymph Node Syndrome , Pandemics , Systemic Inflammatory Response Syndrome , COVID-19/epidemiology , Child , Humans , Syndrome
16.
Revista Cubana de Informacion en Ciencias de la Salud ; 33, 2022.
Article in Spanish | Scopus | ID: covidwho-1989489

ABSTRACT

The COVID-19 pandemic has generated a global health crisis;mental health has been one of the most affected. The objective of this research was to determine the relationship between the number of new cases and daily deaths from COVID-19, as well as Internet search trends on mental health concerns in Latin America. Google Trends was used to determine the relative volume of searches. Regarding the number of new cases and daily deaths from COVID-19, the figures were obtained from the coronavirus disease 2019 (COVID-19) dashboard, prepared by the World Health Organization. The evaluation period was from 12/01/2019 to 01/31/2021. The Pearson correlation coefficient with significance level of p < 0.05 was used to obtain the correlation between quantitative variables. The most searched terms in the selected countries were «anxiety» and «unemployment». The correlation analysis showed that the relative search volume of the evaluated terms had slight to moderate correlation with the number of confirmed cases and daily deaths from COVID-19. Slight to moderate correlation was found between the relative search volume of the evaluated terms and the total number of confirmed cases and deaths per day due to COVID-19. © 2022, Centro Nacional de Informacion de Ciencias Medicas. All rights reserved.

17.
Rep Pract Oncol Radiother ; 27(3): 387-391, 2022.
Article in English | MEDLINE | ID: covidwho-1979570

ABSTRACT

Background: COVID-19 has significantly impacted cancer care. While previous studies have emphasized treatment modification and prioritized the delivery of cancer care, few have examined this issue from the public perspective. Materials and methods: In the following study, we examine how public interest in various forms of cancer treatment has evolved during the pandemic using Google Trends. One-way ANOVA and linear regression tests were used to compare the mean search volume indices of three periods: pre-lockdown, lockdown, and reopening. Results/Conclusions: Our findings suggest that public interest in cancer treatments decreased during lockdown and returned after reopening but, in general, is still lower than pre-lockdown levels. Despite that, healthcare professionals should strive to provide timely cancer care, assuage patients' fears of healthcare settings, and encourage patients to continue proper cancer screenings.

18.
PeerJ ; 10: e13747, 2022.
Article in English | MEDLINE | ID: covidwho-1975334

ABSTRACT

Background: Since the beginning of the new coronavirus pandemic, there has been much information about the disease and the virus has been in the spotlight, shared and commented upon on the Internet. However, much of this information is infodemics and can interfere with the advancement of the disease and that way that populations act. Thus, Brazil is a country that requires attention, as despite the fact that in almost two years of pandemic it has shown a devastating numbers of deaths and number of cases, and generates false, distorted and malicious news about the pandemic. This work intends to understand the attitudes of the Brazilian population using infodemic queries from the Google Trends search tool and social and income variables. Methods: Data from infodemic research carried out on Google Trends, between January 1, 2020 and June 30, 2021, with socioeconomic data, such as income and education, were unified in a single database: standardization and exploratory and multivalued techniques based on grouping were used in the study. Results: In the analysis of the search trend of infodemic terms, it is clear that the categories of Prevention and Beliefs should stand out in Brazil, where there is a diverse culture. It is followed by the COVID-19 Treatment category, with treatments that were not those recommended by the authorities. Income transfer programs and information on socioeconomic variables did not have much impact on infodemic surveys, but it was observed that states where President Bolsonaro has more supporters had researched more infodemic information. Conclusions: In a country as geographically large as Brazil, it is important that political authorities go to great lengths to disseminate reliable information and monitor the infodemic in the media and on the internet. It was concluded that the denial of the pandemic and the influence of political leaders influenced the search for infodemic information, contributing to a disorganization in the control of the disease and prevention measures.

19.
Journal of Medical Artificial Intelligence ; 5, 2022.
Article in English | Scopus | ID: covidwho-1975579

ABSTRACT

Background: In response to the coronavirus disease 2019 (COVID-19) pandemic, the use of Telemedicine has skyrocketed. This study aimed to assess the relationship between the changes in Google relative search volume (RSV) of telehealth and COVID-19 worldwide and in different Italian regions over 18 months during the pandemic. Methods: Data about the Google searches Telemedicine and COVID-19 were analysed (01/12/2019– 31/08/2021). The number of Google searches was measured in RSV (range, 0–100). Results: Mean worldwide RSV was 52.2±17.6 for the Telemedicine and 57.7±19.5 for COVID-19;mean Italian RSV was 17.5±21.6 for the Telemedicine and 42.0±20.0 for COVID-19. The maximum interest for Telemedicine was observed on 16/02/2020, while the maximum interest for COVID-19 was registered on 25/10/2020. The RSV curve of COVID-19 presented two nadirs during the summer periods. On the other hand, the RSV curve of Telemedicine presented a single peak in May 2020. After the peak, interest in Telemedicine continued declining (mean RSV =18). Conclusions: COVID-19 has expanded the use of all telemedicine modalities. Future research is required to improve the understanding of user needs and the effects of Telemedicine on providers at various levels of experience to guide efforts to encourage telemedicine adoption and usage after the COVID-19 pandemic. © Journal of Medical Artificial Intelligence. All rights reserved.

20.
Frontiers in Communication ; 7, 2022.
Article in English | Scopus | ID: covidwho-1963410

ABSTRACT

Since the emergence of COVID-19 in 2020, various actions have been taken by governments and agencies globally to curtail its spread and devastating effects. Risk communication is an essential component of such actions. Examination of public interest, risk perception and new cases of COVID-19 is vital to understanding the effectiveness of risk communication strategies implemented. With data paucity plaguing policymaking in Nigeria, there is a need to examine new data sources to support the enhancement of risk communication. The study explored Google Trends (GT) and Google Mobility Reports (GMR) in monitoring public restlessness and risk perception, respectively, toward COVID-19 in Nigeria. This is geared toward understanding the effectiveness of the national risk communication strategy. COVID-19 case statistics, stringency index, mobility, and search indices for selected terms were collated (February 28 to June 30, 2020). Temporal dynamics were examined while correlation analysis was carried out to examine the association. Public attention peaked just around the commencement of the nationwide lockdown and declined considerably afterwards despite increasing new cases. Mobility toward most place categories showed a sharp decline at the beginning of the pandemic, except for residential areas. This trend also reversed soon after the lockdown. COVID-19 case statistics were found to be negatively correlated with the public interest. Public interest had a weak but both negative and positive association with the stringency index, while mobility exhibited a weak negative association with the case statistics (except residential area mobility). The results indicated that the risk communication efforts were inadequate in providing a prolonged health behavior change. The initial risk communication and lockdown created a positive outcome, however, the impact soon faded out. The evidence suggests that risk perception may have been poorly targeted by risk communication interventions. It is recommended that continuous monitoring of public interest and risk perception is implemented during an emergency and risk communication adjusted accordingly. Copyright © 2022 Lawal.

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