The rapid spread of the novel coronavirus (COVID-19) has severely impacted almost all countries around the world. It not only has caused a tremendous burden on health-care providers to bear, but it has also brought severe impacts on the economy and social life. The presence of reliable data and the results of in-depth statistical analyses provide researchers and policymakers with invaluable information to understand this pandemic and its growth pattern more clearly. This paper combines and processes an extensive collection of publicly available datasets to provide a unified information source for representing geographical regions with regards to their pandemic-related behavior. The features are grouped into various categories to account for their impact based on the higher-level concepts associated with them. This work uses several correlation analysis techniques to observe value and order relationships between features, feature groups, and COVID-19 occurrences. Dimensionality reduction techniques and projection methodologies are used to elaborate on individual and group importance of these representative features. A specific RNN-based inference pipeline called DoubleWindowLSTM-CP is proposed in this work for predictive event modeling. It utilizes sequential patterns and enables concise record representation while using but a minimal amount of historical data. The quantitative results of our statistical analytics indicated critical patterns reflecting on many of the expected collective behavior and their associated outcomes. Predictive modeling with DoubleWindowLSTM-CP instance exhibits efficient performance in quantitative and qualitative assessments while reducing the need for extended and reliable historical information on the pandemic.
The constrained outbreak of COVID-19 in Mainland China has recently been regarded as a successful example of fighting this highly contagious virus. Both the short period (in about three months) of transmission and the sub-exponential increase of confirmed cases in Mainland China have proved that the Chinese authorities took effective epidemic prevention measures, such as case isolation, travel restrictions, closing recreational venues, and banning public gatherings. These measures can, of course, effectively control the spread of the COVID-19 pandemic. Meanwhile, they may dramatically change t…
In this paper, we describe the results of analyzing a large-scale survey, called the Covid19Impact survey, to assess citizens feedback on four areas related to the COVID-19 pandemic in Spain: social contact behavior, financial impact, working situation and health status. A total of 24 questions cover the areas of demographics, their home situation, social contact behavior, personal economic impact, their workplace situation and their health. The survey was responded to by 156,614 participants between the evening of March 28th and April 2nd, 2020. Such a large response enables us to gain new in…
What makes cyber risks arising from connected systems challenging during the management of a pandemic? Assuming that a variety of cyber-physical systems are already operational-collecting, analyzing, and acting on data autonomously-what risks might arise in their application to pandemic management? We already have these systems operational, collecting, and analyzing data autonomously, so how would a pandemic monitoring app be different or riskier? In this review article, we discuss the digitalization of COVID-19 pandemic management and cyber risk from connected systems.
The COVID-19 pandemic has transformed mobile health applications and telemedicine from nice to have tools into essential healthcare infrastructure. This need is particularly great for the elderly who, due to their greater risk for infection, may avoid medical facilities or be required to self-isolate. These are also the very groups at highest risk for cognitive decline. For example, during the COVID-19 pandemic artificially intelligent conversational agents were employed by hospitals and government agencies (such as the CDC) to field queries from patients about symptoms and treatments. Digital…
In this paper, we use SIR model to simulate the COVID-19 pandemic for Cincinnati Tri-State Area. We have built a representative population of Cincinnati that includes movements for traveling to stores, schools, workplaces, and traveling to friends houses. Using this model, we simulate the effect of quarantine, return to work, and panic buying. We show that that there will be a second wave of infections when people return to work and significant increase in number of infections when there is panic buying at stores with the announcement of the quarantine measures.
Rapid and affordable methods of summarizing the multitude of data relating to the pandemic can be useful to health authorities and policy makers who are dealing with the COVID-19 pandemic at various levels in the territories affected by SARSCoV-2. This is the goal of the Synthetic COVID Index, an index based on an ensemble of Unsupervised Machine Learning techniques which focuses on the identification of a latent variable present in data that contains measurement errors. This estimated latent variable can be interpreted as "the strength of the pandemic". An application to the Italian case show…
Older adults are at greater risk of experiencing negative physical and psychological impacts of the novel coronavirus 2019 (COVID-19) pandemic. Our ongoing study is assessing COVID-19 information exposure in adults aged 55 and above compared to other age groups living in Massachusetts and Georgia. This work investigates the potential association between information exposure and wellbeing as well as adherence to COVID-19 protective measures. Our initial results show that older adults received information related to COVID-19 less frequently than the middle-aged group, yet they feel more content …
We present and begin to explore a collection of social data that represents part of the COVID-19 pandemic's effects on the United States. This data is collected from a range of sources and includes longitudinal trends of news topics, social distancing behaviors, community mobility changes, web searches, and more. This multimodal effort enables new opportunities for analyzing the impacts such a pandemic has on the pulse of society. Our preliminary results show that the number of COVID-19-related news articles published immediately after the World Health Organization declared the pandemic on Mar…
The aims of this study are to identify risk factors and develop a composite risk factor of initial stage of COVID-19 pandemic in regency level in Indonesia. Three risk factors, i.e., exposure, transmission and susceptibility, are investigated. Multivariate regression, and Canonical correlation analysis are implemented to measure the association between the risk factors and the initial stage of reported COVID -19 cases. The result reveals strong correlation between the composite risk factor and the number of COVID-19 cases at the initial stage of pandemic. The influence of population density, p…
The ongoing COVID-19 global pandemic is affecting every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and citywide implemented lockdown measures are affecting virus transmission, people's travel patterns, and air quality. Many studies have been conducted to predict the COVID-19 diffusion, assess the impacts of the pandemic on human mobility and air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This review study aims to analyze results from past res…
The COVID-19 pandemic has profoundly impacted the world, having taken the lives of over 6 million individuals. Accordingly, this pandemic has caused a shift in conversations surrounding the burden of diseases worldwide, welcoming insights from multidisciplinary fields including digital health and artificial intelligence. Africa faces a heavy disease burden that exacerbates the current COVID-19 pandemic and limits the scope of public health preparedness, response, containment, and case management. Herein, we examined the potential impact of transformative digital health technologies in mitigati…
The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 214 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 13 July 2020, from a total number of around 13.1 million positive cases, 571, 527 deaths were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI)…
The Internet of Things, often known as IoT, is an innovative technology that connects digital devices all around us, allowing Machine to Machine (M2M) communication between digital devices all over the world. Due to the convenience, connectivity, and affordability, this IoT is being served in various domains including healthcare where it brings exceptional benefits to improve patient care, uplifting medical resources to the next level. Some of these examples include surveillance networks, healthcare delivery technologies, and smart thermal detection. As of now, the IoT is served in various asp…
Cloud computing has become the infrastructure that supports people's daily activities, business operations, and education delivery around the world. Cloud computing-based education platforms have been widely applied to assist online teaching during the COVID-19 pandemic. This paper examines the impact and importance of cloud computing in remote learning and education. This study conducted multiple-case analyses of 22 online platforms of higher education in Chinese universities during the epidemic. A comparative analysis of the 22 platforms revealed that they applied different cloud computing m…
In this study, we investigate the scientific research response from the early stages of the pandemic, and we review key findings on how the early warning systems developed in previous epidemics responded to contain the virus. The data records are analysed with commutable statistical methods, including R Studio, Bibliometrix package, and the Web of Science data mining tool. We identified few different clusters, containing references to exercise, inflammation, smoking, obesity and many additional factors. From the analysis on Covid-19 and vaccine, we discovered that although the USA is leading i…
The COVID-19 pandemic has changed the ways many people use computational systems. We conducted an empirical study, using qualitative and quantitative analyses of free-response surveys completed by 62 US residents, to explore how COVID-19 affected their computer use across work, education, home life, and social life. Nearly all participants experienced an increase in computer usage for themselves or a family member in one or more of the four domains. The increases involved both increasing frequency of existing uses as well as the adoption of new types of use. Changes in usage impacted many aspe…
The time when everyone is struggling in the cruel hands of COVID19, we present the holistic view on the effects of this pandemic in certain aspects of life. A lot of literature exists in COVID-19, but most of them talk about the social and psychological side of the COVID problems. COVID-19 has affected our day-to-day life and its effects are extensive. Most of the literature presents the adverse effect of the pandemic, but there are very few state-of-the-art approaches that discuss its beneficial effects. We see the multiple faces of the pandemic in this paper. To the best of our knowledge, th…
The year 2020 is experiencing a global health and economic crisis due to the COVID-19 pandemic. Countries across the world are using digital technologies to fight this global crisis. These digital technologies, in one way or another, strongly rely on the availability of wireless communication technologies. In this paper, we present the role of wireless communications in the COVID-19 pandemic from different perspectives. First, we show how these technologies are helping to combat this pandemic, including monitoring of the virus spread, enabling healthcare automation, and allowing virtual educat…
Governments and businesses worldwide deployed a variety of technological measures to help prevent and track the spread of COVID-19. In Australia, these applications contained usability, accessibility, and security flaws that hindered their effectiveness and adoption. Australia, like most countries, has transitioned to treating COVID as endemic. However it is yet to absorb lessons from the technological issues with its approach to the pandemic. In this short paper we provide a systematization of the most notable events; identify and review different failure modes of these applications; and deve…
COVID-19 represented a major shock to global health systems, not the least to resource-challenged regions in the Global South. We report on a case of digital, information system resilience in the response to data needs from the COVID-19 pandemic in two countries in the Global South. In contrast to dominant perspectives where digital resilience enables bounce back or maintenance of a status quo, we identify five bounce forward resilience preconditions (i) distributed training, (ii) local expertise (iii) local autonomy and ownership (iv) local infrastructure and (v) platform design infrastructur…
In recent years, the Internet of Things (IoT) has drawn convincing research ground as a new research topic in a wide variety of academic and industrial disciplines, especially in healthcare. The IoT revolution is reshaping modern healthcare systems by incorporating technological, economic, and social prospects. It is evolving healthcare systems from conventional to more personalized healthcare systems through which patients can be diagnosed, treated, and monitored more easily. The current global challenge of the pandemic caused by the novel severe contagious respiratory syndrome coronavirus 2 …
The objective of this article is to explore the Information and Communication Technology (ICT) interventions and its strengths, weaknesses, opportunities and threats for the containment of the pandemic spread of novel Coronavirus. The research adopted a qualitative research approach, while the study data were collected through online content review and Focus Group Discussion (FGD). Starting with a preliminary set of about 1200 electronic resources or contents, 56 were selected for review study, applying an inclusion and exclusion criteria. The review study revealed ICT interventions that inclu…
Several contact tracing solutions have been proposed and implemented all around the globe to combat the spread of COVID-19 pandemic. But, most of these solutions endanger the privacy rights of the individuals and hinder their widespread adoption. We propose a privacy-preserving contact tracing protocol for the efficient tracing of the spread of the global pandemic. It is based on the private set intersection (PSI) protocol and utilizes the homomorphic properties to preserve the privacy at the individual level. A hierarchical model for the representation of landscapes and rate-limiting factor o…
The COVID-19 pandemic has changed the way we act, interact and move around in the world. The pandemic triggered a worldwide health crisis that has been tackled using a variety of strategies across Europe. Whereas some countries have taken strict measures, others have avoided lock-downs altogether. In this paper, we report on findings obtained by combining data from different publicly available sources in order to shed light on the changes in mobility patterns in Europe during the pandemic. Using that data, we show that mobility patterns have changed in different counties depending on the strat…
The COVID-19 pandemic has significantly influenced all modes of transportation. However, it is still unclear how the pandemic affected the demand for ridesourcing services and whether these effects varied between small towns and large cities. We analyzed over 220 million ride requests in the City of Chicago (population: 2.7 million), Illinois, and 52 thousand in the Town of Innisfil (population: 37 thousand), Ontario, to investigate the impact of the COVID-19 pandemic on the ridesourcing demand in the two locations. Overall, the pandemic resulted in fewer trips in areas with higher proportions…
The COVID-19 pandemic has resulted in significant social and economic impacts throughout the world. In addition to the health consequences, the impacts on traffic behaviors have also been sudden and dramatic. We have analyzed how the road traffic safety of New York City, Los Angeles, and Boston in the U.S. have been impacted by the pandemic and corresponding local government orders and restrictions. To be specific, we have studied the accident hotspots' distributions before and after the outbreak of the pandemic and found that traffic accidents have shifted in both location and time compared t…
The outbreak of the COVID-19 pandemic triggers infodemic over online social media, which significantly impacts public health around the world, both physically and psychologically. In this paper, we study the impact of the pandemic on the mental health of influential social media users, whose sharing behaviours significantly promote the diffusion of COVID-19 related information. Specifically, we focus on subjective well-being (SWB), and analyse whether SWB changes have a relationship with their bridging performance in information diffusion, which measures the speed and wideness gain of informat…
A comprehensive bibliographic review with R statistical methods of the COVID pandemic in PubMed literature and Web of Science Core Collection, supported with Google Scholar search. In addition, a case study review of emerging new approaches in different regions, using medical literature, academic literature, news articles and other reliable data sources. Public responses of mistrust about privacy data misuse differ across countries, depending on the chosen public communication strategy.
The purpose of this case study is to leverage the concepts and tools presented in the preceding chapters and apply them in a real world social cybersecurity context. With the COVID-19 pandemic emerging as a defining event of the 21st Century and a magnet for disinformation maneuver, we have selected the pandemic and its related social media conversation to focus our efforts on. This chapter therefore applies the tools of information operation maneuver, bot detection and characterization, meme detection and characterization, and information mapping to the COVID-19 related conversation on Twitte…
The COVID-19 pandemic is an unprecedented global crisis that has impacted virtually everyone. We conducted a nationwide online longitudinal survey in the United States to collect information about the shifts in travel-related behavior and attitudes before, during, and after the pandemic. The survey asked questions about commuting, long distance travel, working from home, online learning, online shopping, pandemic experiences, attitudes, and demographic information. The survey has been deployed to the same respondents thrice to observe how the responses to the pandemic have evolved over time. T…
This cross-sectional study characterizes users' attitudes towards the face mask requirements introduced by the Russian government as a response to the COVID-19 pandemic. We study how they relate to other users' characteristics such as age, gender, and political attitudes. Our results indicate that men and elder individuals - demographic groups that are most vulnerable to COVID-19 -- underestimate the benefits of wearing face masks. We also discovered that users in opposition to the Russian government highly approve of this anti-COVID-19 measure -- an oppositionist will approve of the face mask…
The spread of misinformation, conspiracy, and questionable content and information manipulation by foreign adversaries on social media has surged along with the COVID-19 pandemic. Such malicious cyber-enabled actions may cause increasing social polarization, health crises, and property loss. In this paper, using fine-tuned contextualized embedding trained on Reddit, we tackle the detection of the propaganda of such user accounts and their targeted issues on Twitter during March 2020 when the COVID-19 epidemic became recognized as a pandemic. Our result shows that the pro-China group appeared t…
Justifying draconian measures during the Covid-19 pandemic was difficult not only because of the restriction of individual rights, but also because of its economic impact. The objective of this work is to present a machine learning approach to identify regions that should implement similar health policies. For that end, we successfully developed a system that gives a notion of economic impact given the prediction of new incidental cases through unsupervised learning and time series forecasting. This system was built taking into account computational restrictions and low maintenance requirement…
With the emergence of a new pandemic worldwide, a novel strategy to approach it has emerged. Several initiatives under the umbrella of "open science" are contributing to tackle this unprecedented situation. In particular, the "R Language and Environment for Statistical Computing" offers an excellent tool and ecosystem for approaches focusing on open science and reproducible results. Hence it is not surprising that with the onset of the pandemic, a large number of R packages and resources were made available for researches working in the pandemic. In this paper, we present an R package that all…
Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）；IBM（国际商业机器公司）
As a reaction to the high infectiousness and lethality of the COVID-19 virus, countries around the world have adopted drastic policy measures to contain the pandemic. However, it remains unclear which effect these measures, so-called non-pharmaceutical interventions (NPIs), have on the spread of the virus. In this article, we use machine learning and apply drift detection methods in a novel way to predict the time lag of policy interventions with respect to the development of daily case numbers of COVID-19 across 9 European countries and 28 US states. Our analysis shows that there are, on aver…
Since the World Health Organization (WHO) characterized COVID-19 as a pandemic in March 2020, there have been over 600 million confirmed cases of COVID-19 and more than six million deaths as of October 2022. The relationship between the COVID-19 pandemic and human behavior is complicated. On one hand, human behavior is found to shape the spread of the disease. On the other hand, the pandemic has impacted and even changed human behavior in almost every aspect. To provide a holistic understanding of the complex interplay between human behavior and the COVID-19 pandemic, researchers have been emp…
Tracking suspected cases of COVID-19 is crucial to suppressing the spread of COVID-19 pandemic. Active monitoring and proactive inspection are indispensable to mitigate COVID-19 spread, though these require considerable social and economic expense. To address this issue, we introduce CareCall, a call-based dialog agent which is deployed for active monitoring in Korea and Japan. We describe our system with a case study with statistics to show how the system works. Finally, we discuss a simple idea which uses CareCall to support proactive inspection.
Successful navigation of the Covid-19 pandemic is predicated on public cooperation with safety measures and appropriate perception of risk, in which emotion and attention play important roles. Signatures of public emotion and attention are present in social media data, thus natural language analysis of this text enables near-to-real-time monitoring of indicators of public risk perception. We compare key epidemiological indicators of the progression of the pandemic with indicators of the public perception of the pandemic constructed from ~20 million unique Covid-19-related tweets from 12 countr…
University of Michigan（密歇根大学）；University of Maryland（马里兰大学）
While many organizations have shifted to working remotely during the COVID-19 pandemic, how the remote workforce and the remote teams are influenced by and would respond to this and future shocks remain largely unknown. Software developers have relied on remote collaborations long before the pandemic, working in virtual teams (GitHub repositories). The dynamics of these repositories through the pandemic provide a unique opportunity to understand how remote teams react under shock. This work presents a systematic analysis. We measure the overall effect of the early pandemic on public GitHub rep…
The coronavirus disease (COVID-19) has caused enormous disruptions to not only the United States, but also the global economy. Due to the pandemic, issues in the supply chain and concerns about food shortage drove up the food prices. According to the U.S. Bureau of Labor Statistics, the prices for food increased 4.1% and 3.7% over the year ended in August 2020 and August 2021, respectively, while the amount of annual increase in the food prices prior to the COVID-19 pandemic is less than 2.0%. Previous studies show that such kinds of exogenous disasters, including the 2011 Tohoku Earthquake, 9…
A considerable amount of various types of data have been collected during the COVID-19 pandemic, the analysis and interpretation of which have been indispensable for curbing the spread of the disease. As the pandemic moves to an endemic state, the data collected during the pandemic will continue to be rich sources for further studying and understanding the impacts of the pandemic on various aspects of our society. On the other hand, naïve release and sharing of the information can be associated with serious privacy concerns. In this study, we use three common but distinct data types collected …
The COVID-19 global pandemic and resulted lockdown policies have forced education in nearly every country to switch from a traditional co-located paradigm to a pure online 'distance learning from home' paradigm. Lying in the center of this learning paradigm shift is the emergence and wide adoption of distance communication tools and live streaming platforms for education. Here, we present a mixed-methods study on live streaming based education experience during the COVID-19 pandemic. We focus our analysis on Chinese higher education, carried out semi-structured interviews on 30 students, and 7…
There are many sectors which have moved to Cloud and are planning aggressively to move their workloads to Cloud since the world entered Covid-19 pandemic. There are various reasons why Cloud is an essential irresistible technology and serves as an ultimate solution to access IT software and systems. It has become a new essential catalyst for Enterprise Organisations which are looking for Digital Transformation. Remote working is a common phenomenon now across all the IT companies making the services available all the time. Covid-19 has made cloud adoption an immediate priority for Organisation…
The COVID-19 pandemic was a remarkable unprecedented event which altered the lives of billions of citizens globally resulting in what became commonly referred to as the new-normal in terms of societal norms and the way we live and work. Aside from the extraordinary impact on society and business as a whole, the pandemic generated a set of unique cyber-crime related circumstances which also affected society and business. The increased anxiety caused by the pandemic heightened the likelihood of cyber-attacks succeeding corresponding with an increase in the number and range of cyber-attacks. This…
The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of the general public and the healthcare system of the society. As a promising approach to address the emerging challenges caused by the epidemic of infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed in hospitals, clinics, and healthcare centers can save the diagnosis time and improve the efficiency of medical resources though privacy and security concerns of IoMT stall the wide adoption. In order to tackle the privacy, security, and interoperability issues of IoMT, we propose a framework of bl…
University of Toronto（多伦多大学）；University of Pittsburgh（匹兹堡大学）；Chinese Academy of Sciences（中国科学院）
The objective of the study is to examine coronavirus disease (COVID-19) related discussions, concerns, and sentiments that emerged from tweets posted by Twitter users. We analyze 4 million Twitter messages related to the COVID-19 pandemic using a list of 25 hashtags such as "coronavirus," "COVID-19," "quarantine" from March 1 to April 21 in 2020. We use a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigram, bigrams, salient topics and themes, and sentiments in the collected Tweets. Popular unigrams include "virus," "lockdown," and "quarantine." Popular big…
Bloodstock shortages and its uncertain demand has become a major problem for all countries worldwide. Therefore, this study aims to provide solution to the issues of blood distribution during the Covid-19 Pandemic at Bengkulu, Indonesia. The Backpropagation algorithm was used to improve the possibility of discovering available and potential donors. Furthermore, the distances, age, and length of donation were measured to obtain the right person to donate blood when it needed. The Backpropagation uses three input layers to classify eligible donors, namely age, body, weight, and bias. In addition…
