Understanding media's response to epidemics

The impact of epidemic information on the public's worries and attitude toward epidemic prevention measures during the COVID-19 outbreak

Since the outbreak of 2019 coronavirus disease (COVID-19) in December 2019, the Chinese government has implemented effective epidemic prevention measures. To provide useful information for governments to manage this public health crisis, we conducted an online survey among Chinese general population from February 24 to 28, 2020. In this study, we examined the impact of epidemic information and rumors on public's worries and attitude toward prevention measures during the outbreak of COVID-19. A total of 853 valid questionnaires (641 women, 75.1%) were collected from 24 provincial regions in China. Most respondents' ages ranged from 18 to 60 (833 participants, 97.66%). A mediation model was built to analyze the influence of epidemic information and rumors on worries and attitude. The results showed that the amount of epidemic information positively predicted public's worries, which in turn predicted a supportive attitude toward the prevention measures. Worries partially mediated the relationship between the amount of epidemic information and the supportive attitude. The amount of rumors negatively predicted the supportive attitude. The results of this study implied the importance of timely and credible information providing to evoke a certain level of worry and promote public cooperation, and the necessary attention to refute and resist rumors for effective risk communication in a public health crisis.

Smart City Data Sensing during COVID-19: Public Reaction to Accelerating Digital Transformation

The article presents the results of the analysis of the adaptation of metropolis IT technologies to solve operational problems in extreme conditions during the COVID-19 pandemic. The material for the study was Russian-language data from social networks, microblogging, blogs, instant messengers, forums, reviews, video hosting services, thematic portals, online media, print media and TV related to the first wave of the COVID-19 pandemic in Russia. The data were collected between 1 March 2020 and 1 June 2020. The database size includes 85,493,717 characters. To analyze the content of social media, a multimodal approach was used involving neural network technologies, text analysis, sentiment-analysis and analysis of lexical associations. The transformation of old digital services and applications, as well as the emergence of new ones were analyzed in terms of the perception of digital communications by actors.

The Global Public Health Intelligence Network and early warning outbreak detection: a Canadian contribution to global public health

The recent SARS epidemic has renewed widespread concerns about the global transmission of infectious diseases. In this commentary, we explore novel approaches to global infectious disease surveillance through a focus on an important Canadian contribution to the area--the Global Public Health Intelligence Network (GPHIN). GPHIN is a cutting-edge initiative that draws on the capacity of the Internet and newly available 24/7 global news coverage of health events to create a unique form of early warning outbreak detection. This commentary outlines the operation and development of GPHIN and compares it to ProMED-mail, another Internet-based approach to global health surveillance. We argue that GPHIN has created an important shift in the relationship of public health and news information. By exiting the pyramid of official reporting, GPHIN has created a new monitoring technique that has disrupted national boundaries of outbreak notification, while creating new possibilities for global outbreak response. By incorporating news within the emerging apparatus of global infectious disease surveillance, GPHIN has effectively responded to the global media's challenge to official country reporting of outbreak and enhanced the effectiveness and credibility of international public health.