Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: a Retrospective Infodemiological Analysis (Preprint)

2021 ◽  
Author(s):  
Alessandro Rovetta
Keyword(s):  
Confounding Factor ◽  
Google Trends ◽  
Government Agencies ◽  
Predictive Tool ◽  
Predictive Capacity ◽  
Web Searches ◽  
User Behaviors ◽  
Cross Correlations ◽  
The Impact

BACKGROUND Google Trends is an infoveillance tool widely used by the scientific community to investigate different user behaviors related to COVID-19. However, several limitations regarding its adoption are reported in the literature. OBJECTIVE This brief paper aims to provide an effective and efficient approach to investigating vaccine adherence against COVID-19 via Google Trends. METHODS Through the cross-correlational analysis of well-targeted hypotheses, we investigate the predictive capacity of web searches related to COVID-19 towards vaccinations in Italy from November 2020 to November 2021. The keyword "vaccine reservation" (VRQ) was chosen as it reflects a real intention of being vaccinated (V). Furthermore, the impact of the second most read Italian newspaper on vaccines-related web searches was investigated to evaluate the role of the mass media as a confounding factor. RESULTS Simple and generic keywords are more likely to identify the actual web interest in COVID-19 vaccines than specific and elaborated keywords. Cross-correlations between VRQ and V were very strong and significant (min r² = .460, P<.001, lag = 0 weeks; max r² = .903, P < .001, lag = 6 weeks). Cross-correlations between VRQ and news about COVID-19 vaccines have been markedly lower and characterized by greater lags (min r² = .190, P=.001, lag = 0 weeks; max r² = .493, P < .001, lag = -10 weeks). No correlation between news and vaccinations was sought since the lag would have been too high. CONCLUSIONS This research provides strong evidence in favor of using Google Trends as a surveillance and prediction tool for vaccine adherence against COVID-19 in Italy. These findings prove that the search for suitable keywords is a fundamental step to reduce confounding factors. Additionally, targeting hypotheses helps diminish the likelihood of spurious correlations. It is recommended that Google Trends be leveraged as a complementary infoveillance tool by government agencies to monitor and predict vaccine adherence in this and future crises by following the methods proposed in this manuscript.

scholarly journals Google Trends as a predictive tool for COVID-19 vaccinations in Italy: a retrospective infodemiological analysis.

2021 ◽  
Author(s):  
Alessandro Rovetta
Keyword(s):  
Confounding Factor ◽  
Google Trends ◽  
Predictive Tool ◽  
Predictive Capacity ◽  
Web Searches ◽  
User Behaviors ◽  
Cross Correlations ◽  
National Newspaper ◽  
The Impact

Abstract Background: Google Trends is an infoveillance tool widely used by the scientific community to investigate different user behaviors related to COVID-19. However, several limitations regarding its adoption are reported in the literature. Objective: This brief paper aims to provide an effective and efficient approach to investigating vaccine adherence against COVID-19 via Google Trends. Methods: Through the cross-correlational analysis of well-targeted hypotheses, we investigate the predictive capacity of web searches related to COVID-19 towards vaccinations in Italy from November 2020 to November 2021. The keyword "vaccine reservation" (VRQ) was chosen as it reflects a real intention of being vaccinated (V). Furthermore, the impact of the second-largest Italian national newspaper on vaccines-related web searches was investigated to evaluate the role of the mass media as a confounding factor. Results: Simple and generic keywords are more likely to identify the actual web interest in COVID-19 vaccines than specific and elaborated keywords. Cross-correlations between VRQ and V were very strong and significant (min r^2 = .460, P<.001, lag = 0 weeks; max r^2 = .903, P < .001, lag = 6 weeks). Cross-correlations between VRQ and news about COVID-19 vaccines have been markedly lower and characterized by greater lags (min r^2 = .190, P=.001, lag = 0 weeks; max r^2 = .493, P < .001, lag = -10 weeks). No correlation between news and vaccinations was sought since the lag would have been too high. Conclusions: This research provides strong evidence in favor of using Google Trends as a surveillance and prediction tool for vaccine adherence against COVID-19 in Italy. These findings prove that the search for suitable keywords is a fundamental step to reduce confounding factors. Additionally, targeting hypotheses helps diminish the likelihood of spurious correlations. It is recommended that Google Trends be leveraged as a complementary infoveillance tool by government agencies to monitor and predict vaccine adherence in this and future crises by following the methods proposed in this manuscript.

Data Security for Connected Governments and Organisations

2021 ◽  
pp. 229-251
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

scholarly journals VIOLENCIA DE GÉNERO: EL PAPEL DE LA EMPATÍA Y EL PERDÓN SOBRE LA ACTITUD HACIA VOLVER CON LA EXPAREJA

2017 ◽  
Vol 2 (1) ◽  
pp. 353
Author(s):  
Beatriz Montes-Berges ◽  
María Aranda
Keyword(s):  
Battered Women ◽  
Gender Violence ◽  
The Other ◽  
Predictive Capacity ◽  
Self Forgiveness ◽  
Empathic Ability ◽  
Violent Relationship ◽  
The Impact ◽  
The Relationship

Abstract.GENDER VIOLENCE: EMPATHY AND FORGIVENESS ROLE ON THE ATTITUDE TOWARD RETURNING WITH THE EXPARTNER.In the intervention with battered women, to minimize the impact of the experience and to diminish the possibility of a return to the violent relationship is quite important. To achieve this purpose, working on variables with a restorative effect on the process is the key. Considering the role of forgiveness in other clinical contexts, and the linking of empathy with it, the objective of the study was to analyze the relationship and predictive capacity of empathy and forgiveness (forgiveness of the situation and self-forgiveness, and forgiveness of the other) on the attitude of returning with the ex-partner. The study involved 17 women between 26 and 60 years. It was found that the ability or inability to separate from the emotions of others (reverberation), as empathic ability, influences the attitude of returning or not with the ex-partner. In addition, participants with greater difficulty in self forgiveness and forgive the situation had a higher difficulty of separation or reverberation.Keywords: Gender violence, empathy, forgiveness, attitude toward return.Resumen.En la intervención con mujeres víctimas de violencia de género es fundamental minimizar el impacto de la experiencia sufrida y disminuir la posibilidad de retorno a la relación violenta. Para ello es clave trabajar sobre variables con efecto reparador sobre el proceso. Considerando el papel que se ha otorgado al perdón en otros contextos clínicos y la vinculación de la empatía con éste, el objetivo del presente estudio fue analizar la relación y capacidad predictiva de la empatía y el perdón en sus dos dimensiones (perdón a la situación y autoperdón, y perdón al otro) sobre la actitud de volver con la expareja. Participaron 17 mujeres de entre 26 y 60 años. Se encontró que la capacidad o incapacidad de separarse de las emociones de los demás (reverberación), influye en la actitud de volver o no con la expareja. Además, las participantes con mayor dificultad para perdonarse a sí mismas y a la situación, presentaban también una dificultad más elevada de separación emocional o reverberación.Palabras clave: violencia de género, empatía, perdón, actitud hacia volver.

scholarly journals Multiperspective Bus Route Planning in a Stackelberg Game Framework

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Xinyu Liu ◽  
Jie Yu ◽  
Xiaoguang Yang ◽  
Weijie Tan
Keyword(s):  
Service Providers ◽  
Stackelberg Game ◽  
Route Planning ◽  
Government Agencies ◽  
Fleet Size ◽  
Bisection Algorithm ◽  
Proposed Model ◽  
Bus Route Planning ◽  
The Impact

Bus route planning is a challenging task due to multiple perspective interactions among passengers, service providers, and government agencies. This paper presents a multidimensional Stackelberg-game-based framework and mathematical model to best trade off the decisions of multiple stakeholders that previous literature rarely captures, i.e., governments, service providers, and passengers, in planning a new bus route or adjusting an existing one. The proposed model features a bilevel structure with the upper level reflecting the perspective of government agencies in subsidy allocation and the lower level representing the decisions of service providers in dispatching frequency and bus fleet size design. The bilevel model is framed as a Stackelberg game where government agencies take the role of “leader” and service providers take the role of “follower” with social costs and profits set as payoffs, respectively. This Stackelberg-game-based framework can reflect the decision sequence of both participants as well as their competition or collaboration relationship in planning a bus route. The impact of such decisions on the mode and route choices of passengers is captured by a Nested Logit model. A partition-based bisection algorithm is developed to solve the proposed model. Results from a case study in Shanghai validate the effectiveness and performance of the proposed model and algorithm.

Data Security for Connected Governments and Organisations

2022 ◽  
pp. 191-213
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

scholarly journals The Influence of Mass Media on Italian Web Users during COVID-19: an Infodemiological Analysis.

2021 ◽  
Author(s):  
Alessandro Rovetta ◽  
Lucia Castaldo
Keyword(s):  
Mass Media ◽  
Google Trends ◽  
The Novel ◽  
Average Correlation ◽  
Web Searches ◽  
Information Giving ◽  
The Press ◽  
Novel Coronavirus ◽  
The Impact ◽  
The Web

Background: Alongside the COVID-19 pandemic, the world has had to face a growing infodemic, which has caused severe damage to economic and health systems and has often compromised the effectiveness of infection containment regulations. Although this has spread mainly through social media, there are numerous occasions in which the mass media have shared dangerous information, giving resonance to statements without a scientific basis. For these reasons, infoveillance and infodemiology methods are increasingly exploited to monitor online information traffic. The same tools have also been used to make epidemiological predictions. Among these, Google Trends - a service by GoogleTM that quantifies the web interest of users in the form of relative search volume - has often been adopted by the scientific community. Objective: The purpose of this paper is to use Google Trends to estimate the impact of Italian mass media on users' web searches in order to understand the role of press and television channels in both the infodemic and the interest of Italian netizens on COVID-19.Methods: First, from January 2020 to March 2021, we collected the headlines containing specific COVID-19-related keywords published on PubMed, Google, the Ministry of Health, and the most read newspapers in Italy. These keywords were selected based on previous literature and the related queries of Google Trends. Second, we evaluated the percentage of infodemic terms on these platforms. Third, through Google Trends, we looked for correlations between newspaper headlines and Google searches related to COVID-19. We assessed the significance and intensity of changes in user web searches through Welch's t-test and percentage differences or increases. We also highlighted the presence of trends via the Mann-Kendall test. Finally, we analyzed the web interest in infodemic content posted on YouTube. In particular, we counted the number of views of videos containing disinformation for each channel considered.Results: During the first COVID-19 wave, the Italian press preferred to draw on infodemic terms (from 1.6% to 6.3%) and moderately infodemic terms (from 88% to 94%), while scientific sources favored the correct names (from 65% to 88%). The correlational analysis showed that the press heavily influenced users in adopting the terms to identify the novel coronavirus (best average correlation = 0.91, P-value &lt;.001). The use of scientific denominations by the press reached acceptable values only during the third wave (about 80% except for Rai and Mediaset). Web queries about COVID-19 symptoms also appeared to be influenced by the press (best average correlation = .92, P&lt;.007). Furthermore, users have shown a pronounced web interest in YouTube videos of an infodemic nature. Finally, the press gave resonance to serious fake news on COVID-19 that caused pronounced spikes of interest from web users.Conclusions: Our results suggest that the Italian mass media have played a decisive role both in the spread of the infodemic and in addressing netizens' web interest, thus favoring the adoption of terms unsuitable for identifying the novel coronavirus (COVID- 19 disease). Therefore, it is highly advisable that the directors of news channels and newspapers be more cautious and government dissemination agencies exert more control over such news.

scholarly journals The impact of COVID-19 on Italy Web users: a quantitative analysis of regional hygiene interest and emotional response

2020 ◽  
Author(s):  
Alessandro Rovetta ◽  
Lucia Castaldo
Keyword(s):  
Physical Health ◽  
Well Being ◽  
Google Trends ◽  
P Value ◽  
Online Information ◽  
The Novel ◽  
Web Searches ◽  
Novel Coronavirus ◽  
The Impact ◽  
Mental And Physical Health

Background: Between the end of February and the beginning of June 2020, Italy was certainly one of the worst affected countries in the world by the COVID-19 pandemic. During this period, web interest in the novel coronavirus has undergone a drastic surge. Objective: The aim of this study was to quantitatively analyze the impact of COVID-19 on Web searches related to hygiene-preventive measures and emotional-psychological aspects as well as to estimate the effectiveness and limits of online information during an epidemic. We looked for significant correlations between COVID-19 relative search volumes and cases per region to understand the interest of the average Italian Web user during international, national, and regional COVID-19 situations. By doing so, from the analysis of Web searches, it will be possible to deduce the mental and physical health of the population. Methods: To conduct this research, we used the "Google Trends" tool, which returns normalized values, called "relative search volumes" (RSVs), ranging from 0 to 100 according to the Web popularity of a group of queries. By comparing the RSVs in periods before and after the outbreak of the novel coronavirus in Italy, we derived the impact of COVID-19 on the activity of Italian netizens towards novel coronavirus itself, specifically regarding hygiene, prevention, and psychological well-being. Furthermore, we calculated Pearson's correlations ρ ; between all these queries and COVID-19 cases for each region. We chose a p-value (p) threshold α=.1. Results: After the two initial spikes that occurred on February 23 and March 9, 2020, the general web interest in COVID-19 in Italy waned, as did the correlation with the official number of cases per region (p< .1 only until March 14, 2020). However, web interest was similarly distributed across the regions (ASV=92,SD=6). We also found that all trends depend significantly on the number of COVID-19 cases at national but not international or regional levels. Between February 20 and June 10, 2020, web interest relating to hygiene and prevention increased by 116% and 901%, respectively, compared to those from January 1 to February 19, 2020 (95% CIs: [115.3,116.3],[850.3,952,2]). Significant correlations between regional cumulative web searches and COVID-19 cases were found only between February 26 and March 7, 2020 (ρ-best= .43, 95% CI:[.42,.44],p= .07). During the COVID-19 pandemic until June 10, 2020, national web searches of the generic terms "fear" and "anxiety" grew by 8% and 21%, respectively (95% CIs: [8.0,8.2],[20.4,20.6]) compared to those of the period January 1, 2018 - December 29, 2019. We found cyclically significant correlations between negative emotions related to the novel coronavirus and COVID-19 official data. Conclusions: Italian netizens showed a marked interest in the COVID-19 pandemic only when this became a direct national problem. In general, web searches have rarely been correlated with the number of cases per region; we conclude that the danger, once it arrived in the country, was perceived similarly in all regions. We can state that the period of maximum effectiveness of online information, in relation to this type of situation, is limited to 3-4 days from a specific key event. If such a scenario were to occur again, we suggest that all government agencies focus their web disclosure efforts over that time. Despite this, we found cyclical correlations with web searches related to negative feelings such as anxiety, depression, fear, and stress. Therefore, to identify mental and physical health problems among the population, it suffices to observe slight variations in the trend of related web queries. Keywords: COVID-19, Google Trends, web interests, Italy, novel coronavirus.

scholarly journals Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study

10.2196/19611 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e19611 ◽  
Author(s):  
Bernardo Sousa-Pinto ◽  
Aram Anto ◽  
Wienia Czarlewski ◽  
Josep M Anto ◽  
João Almeida Fonseca ◽  
...  
Keyword(s):  
Media Coverage ◽  
Google Trends ◽  
Web Based ◽  
The Media ◽  
The Impact

Background The influence of media coverage on web-based searches may hinder the role of Google Trends (GT) in monitoring coronavirus disease (COVID-19). Objective The aim of this study was to assess whether COVID-19–related GT data, particularly those related to ageusia and anosmia, were primarily related to media coverage or to epidemic trends. Methods We retrieved GT query data for searches on coronavirus, cough, anosmia, and ageusia and plotted them over a period of 5 years. In addition, we analyzed the trends of those queries for 17 countries throughout the year 2020 with a particular focus on the rises and peaks of the searches. For anosmia and ageusia, we assessed whether the respective GT data correlated with COVID-19 cases and deaths both throughout 2020 and specifically before March 16, 2020 (ie, the date when the media started reporting that these symptoms can be associated with COVID-19). Results Over the last five years, peaks for coronavirus searches in GT were only observed during the winter of 2020. Rises and peaks in coronavirus searches appeared at similar times in the 17 different assessed countries irrespective of their epidemic situations. In 15 of these countries, rises in anosmia and ageusia searches occurred in the same week or 1 week after they were identified in the media as symptoms of COVID-19. When data prior to March 16, 2020 were analyzed, anosmia and ageusia GT data were found to have variable correlations with COVID-19 cases and deaths in the different countries. Conclusions Our results indicate that COVID-19–related GT data are more closely related to media coverage than to epidemic trends.

scholarly journals Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study (Preprint)

2020 ◽  
Author(s):  
Bernardo Sousa-Pinto ◽  
Aram Anto ◽  
Wienia Czarlewski ◽  
Josep M Anto ◽  
João Almeida Fonseca ◽  
...  
Keyword(s):  
Media Coverage ◽  
Google Trends ◽  
Web Based ◽  
The Media ◽  
The Impact

BACKGROUND The influence of media coverage on web-based searches may hinder the role of Google Trends (GT) in monitoring coronavirus disease (COVID-19). OBJECTIVE The aim of this study was to assess whether COVID-19–related GT data, particularly those related to ageusia and anosmia, were primarily related to media coverage or to epidemic trends. METHODS We retrieved GT query data for searches on <i>coronavirus</i>, <i>cough</i>, <i>anosmia</i>, and <i>ageusia</i> and plotted them over a period of 5 years. In addition, we analyzed the trends of those queries for 17 countries throughout the year 2020 with a particular focus on the rises and peaks of the searches. For <i>anosmia</i> and <i>ageusia</i>, we assessed whether the respective GT data correlated with COVID-19 cases and deaths both throughout 2020 and specifically before March 16, 2020 (ie, the date when the media started reporting that these symptoms can be associated with COVID-19). RESULTS Over the last five years, peaks for <i>coronavirus</i> searches in GT were only observed during the winter of 2020. Rises and peaks in <i>coronavirus</i> searches appeared at similar times in the 17 different assessed countries irrespective of their epidemic situations. In 15 of these countries, rises in <i>anosmia</i> and <i>ageusia</i> searches occurred in the same week or 1 week after they were identified in the media as symptoms of COVID-19. When data prior to March 16, 2020 were analyzed, <i>anosmia</i> and <i>ageusia</i> GT data were found to have variable correlations with COVID-19 cases and deaths in the different countries. CONCLUSIONS Our results indicate that COVID-19–related GT data are more closely related to media coverage than to epidemic trends.

What It Takes to Avert a Regional Crisis: Understanding the Uzbek Government’s Responses to the June 2010 Violence in South Kyrgyzstan

2015 ◽  
Vol 2 (2) ◽  
pp. 168-188 ◽  
Author(s):  
Alisher Khamidov
Keyword(s):  
Alternative Explanation ◽  
Humanitarian Assistance ◽  
Bureaucratic Politics ◽  
Government Agencies ◽  
Interethnic Violence ◽  
External Actors ◽  
The Impact ◽  
Domestic Level

Uzbekistan played an important role during the June 2010 interethnic violence in South Kyrgyzstan by tightly controlling borders, allowing thousands of Kyrgyzstani refugees to cross into Uzbek territory, assisting in the shipment of international humanitarian assistance to Kyrgyzstan, and collaborating with the osce in the investigation of the causes of the violence. What explains Uzbekistan’s approach to the unrest in South Kyrgyzstan? Some scholars suggest that Uzbekistan’s response was shaped largely by external actors such as Russia. Others posit that domestic pressures account for the response. This article advances an alternative explanation: Tashkent’s response was largely a result of a consensus achieved at two levels: international and domestic. In explaining the impact of domestic level, the article emphasizes the role of bureaucratic politics—competition among various government agencies.

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