Related papers: An Interactive Data Visualization and Analytics To…

Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding spreading pattern of COVID-19 has been widely recognized as a vital step for implementing…

During the COVID-19 pandemic, a number of data visualizations were created to inform the public about the rapidly evolving crisis. Data dashboards, a form of information dissemination used during the pandemic, have facilitated this process…

In the new paradigm of health-centric governance, policy makers are in a constant need for appropriate metrics and estimates in order to determine the best policies in a non-arbitrary fashion. Thus, in this paper, a compartmentalized model…

The policies implemented to hinder the COVID-19 outbreak represent one of the largest critical events in history. The understanding of this process is fundamental for crafting and tailoring post-disaster relief. In this work we perform a…

People mobility data sets played a role during the COVID-19 pandemic in assessing the impact of lockdown measures and correlating mobility with pandemic trends. Two global data sets were Apple's Mobility Trends Reports and Google's…

In their response to the COVID-19 outbreak, governments face the dilemma to balance public health and economy. Mobility plays a central role in this dilemma because the movement of people enables both economic activity and virus spread. We…

To prevent the outbreak of the Coronavirus disease (COVID-19), many countries around the world went into lockdown and imposed unprecedented containment measures. These restrictions progressively produced changes to social behavior and…

Fighting the COVID-19 pandemic, most countries have implemented non-pharmaceutical interventions like wearing masks, physical distancing, lockdown, and travel restrictions. Because of their economic and logistical effects, tracking mobility…

The coronavirus disease, also known as the COVID-19, is an ongoing pandemic of a severe acute respiratory syndrome. The pandemic has led to the cancellation of many religious, political, and cultural events around the world. A huge number…

Predicting human displacements is crucial for addressing various societal challenges, including urban design, traffic congestion, epidemic management, and migration dynamics. While predictive models like deep learning and Markov models…

Since the outbreak of COVID-19, it has rapidly evolved into a sudden and major public health emergency globally. With the variants of COVID-19, the difficulty of pandemic control continues to increase, which has brought significant costs to…

The spread of COVID-19 has been greatly impacted by regulatory policies and behavior patterns that vary across counties, states, and countries. Population-level dynamics of COVID-19 can generally be described using a set of ordinary…

Sweden has adopted far less restrictive social distancing policies than most countries following the COVID-19 pandemic. This paper uses data on all mobile phone users, from one major Swedish mobile phone network, to examine the impact of…

In this work, we examine a novel forecasting approach for COVID-19 case prediction that uses Graph Neural Networks and mobility data. In contrast to existing time series forecasting models, the proposed approach learns from a single…

The fast transmission rate of COVID-19 worldwide has made this virus the most important challenge of year 2020. Many mitigation policies have been imposed by the governments at different regional levels (country, state, county, and city) to…

The COVID-19 pandemic and the resulting economic recession negatively affected many people's physical, social, and psychological health and has been shown to change population-level mobility, but little attention has been given to park…

The global pandemic of COVID-19 over the last 2.5 years have produced an enormous amount of epidemic/public health datasets, which may also be useful for studying the underlying structure of our globally connected world. Here we used the…

We develop a novel temporal complex network approach to quantify the US county level spread dynamics of COVID-19. The objective is to study the effects of the local spread dynamics, COVID-19 cases and death, and Google search activities on…

In March 2020, the Austrian government introduced a widespread lock-down in response to the COVID-19 pandemic. Based on subjective impressions and anecdotal evidence, Austrian public and private life came to a sudden halt. Here we assess…

The spread of COVID-19 disease affected people's lives worldwide, particularly their travel behaviours and how they performed daily activities. During the first wave of the pandemic, spring 2020, countries adopted different strategies to…