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BACKGROUND: Concurrently with the COVID-19 pandemic, the world has been facing 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 infodemic has spread mainly through social media, there are numerous occasions on which mass media outlets have shared dangerous information, giving resonance to statements without a scientific basis. For these reasons, infoveillance and infodemiology methods are increasingly exploited to monitor information traffic on the web and make epidemiological predictions. OBJECTIVE: The purpose of this paper is to estimate the impact of Italian mass media on users' web searches to understand the role of press and television channels in both the infodemic and the interest of Italian netizens in COVID-19. METHODS: We collected the headlines published from January 2020 to March 2021 containing specific COVID-19-related keywords published on PubMed, Google, the Italian Ministry of Health website, and the most-read newspapers in Italy. We evaluated the percentages of infodemic terms on these platforms. Through Google Trends, we searched for cross-correlations between newspaper headlines and COVID-19-related web searches. Finally, we analyzed the web interest in infodemic content posted on YouTube. RESULTS: During the first wave of COVID-19, the Italian press preferred to draw on infodemic terms (rate of adoption: 1.6%-6.3%) and moderately infodemic terms (rate of adoption: 88%-94%), while scientific sources favored the correct names (rate of adoption: 65%-88%). The correlational analysis showed that the press heavily influenced users in adopting terms to identify the novel coronavirus (cross-correlations of ≥0.74 to ≤0.89, P value <.001; maximum lag=1 day). The use of scientific denominations by the press reached acceptable values only during the third wave (approximately 80%, except for the television services Rai and Mediaset). Web queries about COVID-19 symptoms also appeared to be influenced by the press (best average correlation=0.92, P<.007). Furthermore, web users showed pronounced interest in YouTube videos of an infodemic nature. Finally, the press gave resonance to serious "fake news" on COVID-19, which caused pronounced spikes of interest from web users. CONCLUSIONS: Our results suggest that the Italian mass media have played a decisive role in spreading the COVID-19 infodemic and addressing netizens' web interest, thus favoring the adoption of terms that are unsuitable for identifying COVID-19. Therefore, the directors of news channels and newspapers should be more cautious, and government dissemination agencies should exert more control over such news stories.
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BACKGROUND: Since January 2020, the coronavirus disease 2019 (COVID-19) pandemic has raged around the world, causing nearly a million deaths and hundreds of severe economic crises. In this scenario, Italy has been one of the most affected countries. OBJECTIVE: This study investigated significant correlations between COVID-19 cases and demographic, geographical, and environmental statistics of each Italian region from February 26 to August 12, 2020. We further investigated the link between the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and particulate matter (PM) 2.5 and 10 concentrations before the lockdown in Lombardy. METHODS: All demographic data were obtained from the AdminStat Italia website, and geographic data were from the Il Meteo website. The collection frequency was one week. Data on PM2.5 and PM10 average daily concentrations were collected from previously published articles. We used Pearson's coefficients to correlate the quantities that followed a normal distribution, and Spearman's coefficient to correlate quantities that did not follow a normal distribution. RESULTS: We found significant strong correlations between COVID-19 cases and population number in 60.0% of the regions. We also found a significant strong correlation between the spread of SARS-CoV-2 in the various regions and their latitude, and with the historical averages (last 30 years) of their minimum temperatures. We identified a significant strong correlation between the number of COVID-19 cases until August 12 and the average daily concentrations of PM2.5 in Lombardy until February 29, 2020. No significant correlation with PM10 was found in the same long periods. However, we found that 40 µg/m^3 for PM2.5 and 50 µg/m^3 for PM10 are plausible thresholds beyond which particulate pollution clearly favors the spread of SARS-CoV-2. CONCLUSION: Since SARS-CoV-2 is correlated with historical minimum temperatures and PM10 and 2.5, health authorities are urged to monitor pollution levels and to invest in precautions for the arrival of autumn. Furthermore, we suggest creating awareness campaigns for the recirculation of air in enclosed places and to avoid exposure to the cold.
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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 coronavirus disease 2019 (COVID-19) pandemic. During this period, Web interest in the novel coronavirus underwent 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, it will be possible to deduce the mental and physical health of the population. METHODS: We used the Google Trends tool, which returns normalized values called relative search volumes (RSV), ââranging 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 ([Formula: see text]) threshold α=.1. RESULTS: 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). Web interest was similarly distributed across the regions (average search volume [ASV]=92, standard deviation [SD]=6). We found that all trends depend significantly on the number of COVID-19 cases at the national but not international or regional levels. Between February 20 and June 10, Web interest related 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 between February 26 and March 7 ([Formula: see text]=.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 of 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. Web searches have rarely been correlated with the number of cases per region; we conclude that the danger was perceived similarly in all regions. The period of maximum effectiveness of online information in relation to this type of situation is limited to three to four days from a specific key event. We suggest that all government agencies focus their Web disclosure efforts over that time. 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.
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[This corrects the article DOI: 10.7759/cureus.9884.].
ABSTRACT
As of May 14, 2020, Italy has been one of the red hotspots for the COVID-19 pandemic. In particular, the regions of Emilia Romagna, Piedmont, and especially Lombardy were the most affected and had to face very serious health emergencies, which brought them to the brink of collapse. Since the virus has demonstrated local properties, i.e., greater severity and contagiousness in specific regions, the aim of this study is to model the complex behavior of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Italy. In particular, we further investigated the results of other articles on the correlation with particulate matter pollution 10 (PM 10) and 2.5 (PM 2.5) by extending the research at the intra-regional level, as well as calculated a more plausible number of those infected compared to those officially declared by Civil Protection. Through a computational simulation of the Susceptible-Exposed-Infectious-Recovered (S.E.I.R.) model, we also estimated the most representative basic reproduction number [Formula: see text] for these three regions from February 22 to March 14, 2020. In doing so, we have been able to evaluate the consistency of the first containment measures until the end of April, as well as identify possible SARS-CoV-2 local behavior mutations and specificities.