Information dissemination during public health emergencies: analysing the international flow of COVID-19-related news.

A large-scale exchange of information between media across national borders is frequently observed when a worldwide public health emergency occurs. This study investigated the global news citation network in the early stage of the COVID-19 pandemic by analysing the network structure at different levels to identify important nodes and the relationships among news organisations. The results show that COVID-19-related international news flow had a complex and unequal pattern, with a few countries and media outlets occupying a prominent place in the network and three media groups played key but different roles in disseminating the news. It was jointly influenced by national traits, the relatedness between countries, and the pandemic emergency with public health risks. From a global perspective, the media of the United States, mainland China, and the United Kingdom played the most important parts in collaboration within the world media system in the early stage of the COVID-19 pandemic.

Risk Communication in the Alert Phase of the COVID-19 Pandemic: Analysis of News Flow at National and Global Levels.

This study examined the global media citation network of COVID-19-related news at two stages of the pandemic alert phase, i.e., the national level alert stage and the global level alert stage. The findings reveal that the small-world pattern and scale-free property of media citation networks contributed to the rapid spread of COVID-19-related news around the world. Within the networks, a small number of media outlets from a few countries formed the backbone of the network to control the risk communication; meanwhile, many media of geographical and cultural similarities formed cross-border collaborative cliques in the periphery of the network. When the alert phase escalated from the national level to the global level, the network demonstrated a number of changes. The findings contribute to the understanding of risk communication for international public health emergencies by taking into account the network perspective and evolutionary nature of public health emergencies in analysis.

Integrating online and offline data for crisis management: Online geolocalized emotion, policy response, and local mobility during the COVID crisis.

Integrating online and offline data is critical for uncovering the interdependence between policy and public emotional and behavioral responses in order to aid the development of effective spatially targeted interventions during crises. As the COVID-19 pandemic began to sweep across the US it elicited a wide spectrum of responses, both online and offline, across the population. Here, we analyze around 13 million geotagged tweets in 49 cities across the US from the first few months of the pandemic to assess regional dependence in online sentiments with respect to a few major COVID-19 related topics, and how these sentiments correlate with policy development and human mobility. In this study, we observe universal trends in overall and topic-based sentiments across cities over the time period studied. We also find that this online geolocalized emotion is significantly impacted by key COVID-19 policy events. However, there is significant variation in the emotional responses to these policies across the cities studied. Online emotional responses are also found to be a good indicator for predicting offline local mobility, while the correlations between these emotional responses and local cases and deaths are relatively weak. Our findings point to a feedback loop between policy development, public emotional responses, and local mobility, as well as provide new insights for integrating online and offline data for crisis management.