Health surveillance during covid-19 pandemic

Exploring the surveillance technology discourse: a bibliometric analysis and topic modeling approach

The prevention of crime is a multifaceted challenge with legal, political, and cultural implications. Surveillance technologies play a crucial role in assisting law enforcement and other relevant parties in this mission. Drones, cameras, and wiretaps are examples of such devices. As their use increases, it becomes essential to address related challenges involving various stakeholders and consider cultural, political, and legal aspects. The objective of this study was to analyze the impact of surveillance technologies and identify commonalities and differences in perspectives among social media users and researchers. Data extraction was performed from two platforms: Scopus (for academic research papers) and platform X (formerly known as Twitter). The dataset included 88,989 tweets and 4,874 research papers. Topic modeling, an unsupervised machine learning approach, was applied to analyze the content. The research results revealed that privacy received little attention across the datasets, indicating its relatively low prominence. The military applications and their usage have been documented in academic research articles as well as tweets. Based on the empirical evidence, it seems that contemporary surveillance technology may be accurately described as possessing a bi-directional nature, including both sousveillance and surveillance, which aligns with Deleuzian ideas on the Panopticon. The study's findings also indicate that there was a greater level of interest in actual applications of surveillance technologies as opposed to more abstract concepts like ethics and privacy.

Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping Review

BACKGROUND

The COVID-19 pandemic has prompted the deployment of digital technologies for public health surveillance globally. The rapid development and use of these technologies have curtailed opportunities to fully consider their potential impacts (eg, for human rights, civil liberties, privacy, and marginalization of vulnerable groups).

OBJECTIVE

We conducted a scoping review of peer-reviewed and gray literature to identify the types and applications of digital technologies used for surveillance during the COVID-19 pandemic and the predicted and witnessed consequences of digital surveillance.

METHODS

Our methodology was informed by the 5-stage methodological framework to guide scoping reviews: identifying the research question; identifying relevant studies; study selection; charting the data; and collating, summarizing, and reporting the findings. We conducted a search of peer-reviewed and gray literature published between December 1, 2019, and December 31, 2020. We focused on the first year of the pandemic to provide a snapshot of the questions, concerns, findings, and discussions emerging from peer-reviewed and gray literature during this pivotal first year of the pandemic. Our review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guidelines.

RESULTS

We reviewed a total of 147 peer-reviewed and 79 gray literature publications. Based on our analysis of these publications, we identified a total of 90 countries and regions where digital technologies were used for public health surveillance during the COVID-19 pandemic. Some of the most frequently used technologies included mobile phone apps, location-tracking technologies, drones, temperature-scanning technologies, and wearable devices. We also found that the literature raised concerns regarding the implications of digital surveillance in relation to data security and privacy, function creep and mission creep, private sector involvement in surveillance, human rights, civil liberties, and impacts on marginalized groups. Finally, we identified recommendations for ethical digital technology design and use, including proportionality, transparency, purpose limitation, protecting privacy and security, and accountability.

CONCLUSIONS

A wide range of digital technologies was used worldwide to support public health surveillance during the COVID-19 pandemic. The findings of our analysis highlight the importance of considering short- and long-term consequences of digital surveillance not only during the COVID-19 pandemic but also for future public health crises. These findings also demonstrate the ways in which digital surveillance has rendered visible the shifting and blurred boundaries between public health surveillance and other forms of surveillance, particularly given the ubiquitous nature of digital surveillance.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-https://doi.org/10.1136/bmjopen-2021-053962.

Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review

BACKGROUND

Public health surveillance plays a vital role in informing public health decision-making. The onset of the COVID-19 pandemic in early 2020 caused a widespread shift in public health priorities. Global efforts focused on COVID-19 monitoring and contact tracing. Existing public health programs were interrupted due to physical distancing measures and reallocation of resources. The onset of the COVID-19 pandemic intersected with advancements in technologies that have the potential to support public health surveillance efforts.

OBJECTIVE

This scoping review aims to explore emergent public health surveillance methods during the early COVID-19 pandemic to characterize the impact of the pandemic on surveillance methods.

METHODS

A scoping search was conducted in multiple databases and by scanning key government and public health organization websites from March 2020 to January 2022. Published papers and gray literature that described the application of new or revised approaches to public health surveillance were included. Papers that discussed the implications of novel public health surveillance approaches from ethical, legal, security, and equity perspectives were also included. The surveillance subject, method, location, and setting were extracted from each paper to identify trends in surveillance practices. Two public health epidemiologists were invited to provide their perspectives as peer reviewers.

RESULTS

Of the 14,238 unique papers, a total of 241 papers describing novel surveillance methods and changes to surveillance methods are included. Eighty papers were review papers and 161 were single studies. Overall, the literature heavily featured papers detailing surveillance of COVID-19 transmission (n=187). Surveillance of other infectious diseases was also described, including other pathogens (n=12). Other public health topics included vaccines (n=9), mental health (n=11), substance use (n=4), healthy nutrition (n=1), maternal and child health (n=3), antimicrobial resistance (n=2), and misinformation (n=6). The literature was dominated by applications of digital surveillance, for example, by using big data through mobility tracking and infodemiology (n=163). Wastewater surveillance was also heavily represented (n=48). Other papers described adaptations to programs or methods that existed prior to the COVID-19 pandemic (n=9). The scoping search also found 109 papers that discuss the ethical, legal, security, and equity implications of emerging surveillance methods. The peer reviewer public health epidemiologists noted that additional changes likely exist, beyond what has been reported and available for evidence syntheses.

CONCLUSIONS

The COVID-19 pandemic accelerated advancements in surveillance and the adoption of new technologies, especially for digital and wastewater surveillance methods. Given the investments in these systems, further applications for public health surveillance are likely. The literature for surveillance methods was dominated by surveillance of infectious diseases, particularly COVID-19. A substantial amount of literature on the ethical, legal, security, and equity implications of these emerging surveillance methods also points to a need for cautious consideration of potential harm.

Causes of higher levels of stress among students in higher education who used eLearning platforms during the COVID-19 pandemic

Background

This work aims to study the levels of stress among students using e-learning platforms during the COVID-19 pandemic in higher education institutions. The major factors of higher-level stress among the student community focused on this study are: Changes in academic environment, family, social, personal, health and cognitive.

Objective

the objective of this research the Partial Least Squares Structural Equation Modelling (PLS-SEM) procedure was used to explore the relationship and its impact on various levels of stress.

Results

Data were collected by using a total of 1,000 email IDs of students that were made available by teachers from 12 Indian higher education institutions where they were enrolled and by using a random number method. With this procedure, a total of 800 email IDs were selected. The results drawn from this research are that students experienced more stress due to sudden changes in the academic environment, family, and personal factors. The stress levels of cognitive and social were found to be equally distributed among higher education students, but less than academic environment, family and personal. This research intends to fill the gap of short-term individual psychological changes that occur after the outbreak.

Conclusion

Policy-makers can take note of the current study's observations in continuing their fight against COVID-19 pandemic by improving the stability for student risk groups.

Feasibility of digital contact tracing in low-income settings - pilot trial for a location-based DCT app

BACKGROUND

Data about the effectiveness of digital contact tracing are based on studies conducted in countries with predominantly high- or middle-income settings. Up to now, little research is done to identify specific problems for the implementation of such technique in low-income countries.

METHODS

A Bluetooth-assisted GPS location-based digital contact tracing (DCT) app was tested by 141 participants during 14 days in a hospital in Monrovia, Liberia in February 2020. The DCT app was compared to a paper-based reference system. Hits between participants and 10 designated infected participants were recorded simultaneously by both methods. Additional data about GPS and Bluetooth adherence were gathered and surveys to estimate battery consumption and app adherence were conducted. DCT apps accuracy was evaluated in different settings.

RESULTS

GPS coordinates from 101/141 (71.6%) participants were received. The number of hours recorded by the participants during the study period, true Hours Recorded (tHR), was 496.3 h (1.1% of maximum Hours recordable) during the study period. With the paper-based method 1075 hits and with the DCT app five hits of designated infected participants with other participants have been listed. Differences between true and maximum recording times were due to failed permission settings (45%), data transmission issues (11.3%), of the participants 10.1% switched off GPS and 32.5% experienced other technical or compliance problems. In buildings, use of Bluetooth increased the accuracy of the DCT app (GPS + BT 22.9 m ± 21.6 SD vs. GPS 60.9 m ± 34.7 SD; p = 0.004). GPS accuracy in public transportation was 10.3 m ± 10.05 SD with a significant (p = 0.007) correlation between precision and phone brand. GPS resolution outdoors was 10.4 m ± 4.2 SD.

CONCLUSION

In our study several limitations of the DCT together with the impairment of GPS accuracy in urban settings impede the solely use of a DCT app. It could be feasible as a supplement to traditional manual contact tracing. DKRS, DRKS00029327 . Registered 20 June 2020 - Retrospectively registered.

Nurse, Give Me the News! Understanding Support for and Opposition to a COVID-19 Health Screening System

Helping the sick and protecting the vulnerable has long been the credo of the health profession. In response to the coronavirus-disease-2019 (COVID-19 pandemic), hospitals and healthcare institutions have rapidly employed public health measures to mitigate patient and staff infection. This paper investigates staff and visitor responses to the COVID-19 eGate health screening system; a self-service technology (SST) which aims to protect health care workers and facilities from COVID-19. Our study evaluates the in situ deployment of the eGate, and employs a System Usability Scale (SUS) and questionnaire (n = 220) to understand staff and visitor's acceptance of the eGate. In detailing the themes relevant to those who advocate for the system and those who oppose it, we contribute towards a more detailed understanding of the use and non-use of health-screening SSTs. We conclude with a series of considerations for the design of future interactive screening systems within hospitals.

Resilience and (Dis)empowerment: Use of Social Media Among Female Mainland Low-Skilled Workers in Macao During the COVID-19 Pandemic

The role of social media in a resilient process is associated with the co-constitution of structural forces and users' agency. During COVID-19, how women-particularly low-skilled labor migrants-used social media for empowerment is underexplored. By taking a socio-techno approach, this study qualitatively examines mobile phone-based social media usage among female mainland low-skilled workers in Macao when coping with the pandemic. The enabling yet constraining role of social media has been identified through semi-structured interviews. Social media use is a double-edged sword: on the one hand, social media is appropriated to relieve stress and anxiety, open access to updated COVID-19 related information, and manage contagious risks; on the other hand, it reinforces existing constraints and thus hinders resilience, due to female migrant workers' high risk of addictive social media use and limited information literacy. Moving beyond the Information and Communication Technology empowerment, a more inclusive approach is recommended in the long term to cope with the risks and uncertainties posed by the pandemic.

Can We Communicate Autonomy Support and a Mandate? How Motivating Messages Relate to Motivation for Staying at Home across Time during the COVID-19 Pandemic

A multi-wave study across two months tested changes in motivation for staying at home at the beginning of the COVID-19 outbreak in the UK and US in 683 living-alone older adults (mean age = 53 years), those that might experience greater psychological costs of being isolated for long periods of time. The study was focused on changes in two types of motivation: autonomous motivation- finding importance in the task of staying at home, and controlled motivation- staying at home because of felt pressure or choicelessness, as autonomous motivation predicts effective behavior change better than controlled motivation, especially long-term. Predictions grounded in self-determination theory (SDT) tested whether three motivating aspects of messages to stay at home from governmental and public health agencies, physicians, the news, and family and friends predicted changes in these motivations across time. Perceiving messages to stay at home as controlling predicted increases in controlled motivation and decreases in autonomous motivation over two months. Conversely, perceiving messages to stay at home as autonomy supportive predicted increases in autonomous motivation over two months. Results for mandated orders to stay at home were intriguing: they related to increases in both controlled and autonomous motivations over time. Exploratory analyses revealed that increases in autonomous motivation over time predicted actual time spent at home reported at Wave 2, whereas increases in controlled motivation did not relate. Discussion focuses on contributions to theory and public health messaging about behavioral change.

Nation-Wide Routinely Collected Health Datasets in China: A Scoping Review

Objectives: The potential for using routinely collected data for medical research in China remains unclear. We sought to conduct a scoping review to systematically characterise nation-wide routinely collected datasets in China that may be of value for clinical research.

Methods: We searched public databases and the websites of government agencies, and non-government organizations. We included nation-wide routinely collected databases related to communicable diseases, non-communicable diseases, injuries, and maternal and child health. Database characteristics, including disease area, data custodianship, data volume, frequency of update and accessibility were extracted and summarised.

Results: There were 70 databases identified, of which 46 related to communicable diseases, 20 to non-communicable diseases, 1 to injury and 3 to maternal and child health. The data volume varied from below 1000 to over 100,000 records. Over half (64%) of the databases were accessible for medical research mostly comprising communicable diseases.

Conclusion: There are large quantities of routinely collected data in China. Challenges to using such data in medical research remain with various accessibility. The potential of routinely collected data may also be applicable to other low- and middle-income countries.

Suicidal ideation and attempted suicide among cancer patients during the COVID-19 pandemic

This study aimed to understand the suicidal ideation and suicidal attempts among cancer patients during the COVID-19 pandemic. The data were collected from patients diagnosed with cancer while attending the largest cancer center in the south of China. A structured questionnaire was used to investigate patients' demographic data, suicidal behavior, and factors related to COVID-19. Mental health conditions were measured by the Generalized Anxiety Disorder-7, the Patient Health Questionnaire-9, and the Brief Symptom Inventory. Comorbidities and medical conditions of cancer patients were extracted from the electronic healthcare records. Among the 5670 cancer patients, 755 (13.3%) reported suicidal ideation, and 266 (4.7%) reported suicidal attempts during the COVID-19 pandemic. The age group with the highest risk of suicidal ideation was 20-24 years (23.9%). Lifetime history of suffering from mental disorders, longer time since cancer diagnosis, regional and distant tumor stage, depression, anxiety, hostility, having a higher frequency of worrying about cancer management due to COVID-19, higher frequency feeling of overwhelming psychological pressure due to COVID-19, having a higher level of barriers to manage cancer due to COVID-19, and higher barriers to continue treatment of cancer due to inconveniences caused by COVID-19, were all significantly associated with increased risk of suicidal ideation. We also identified the risk factors of suicide attempts. This is the first study investigating the prevalence and risk factors associated with suicidal ideation and suicidal attempts in Chinese cancer patients during the COVID-19 pandemic. Our findings suggest that it is essential to monitor the mental health conditions of this vulnerable population, especially for cancer patients who have comorbidity with a history of mental disorders. Also, government policymakers should take action to protect cancer patients to avoid any interruption of their continued treatment. Further efforts are urgently required to develop specific psychological interventions to reduce the risk factors among cancer patients during the COVID-19 pandemic.

Toward a digital citizen lab for capturing data about alternative ways of self-managing chronic pain: An attitudinal user study

Background

Myriad psychosocial and cultural factors influence personal ways of coping with chronic pain (CP). Mobile health (mHealth) apps facilitate creation of citizen laboratories outside clinical frameworks. However, issues of safety, privacy and technostress must be addressed. This attitudinal user study aimed to assess whether persons with persistent pain (PwPP) would be open to sharing qualitative and quantitative data about their self-management of CP via mHealth platforms.

Methods

In March 2020, we invited PwPPs, their personal or medical caregivers, or those interested in the development of an app for researching alternative ways of self-managing CP to complete an anonymous survey. We formulated an attitudinal survey within the theoretical framework of stress to estimate whether the novelty, unpredictability, and risks of data-sharing via mHealth apps concerned users. Descriptive statistics (% Part/Group) were used to interpret the survey, and open comments were reflectively analyzed to identify emerging themes.

Results

Of 202 responses (June 2021), 127 identified as PwPPs (average age 43.86 ± 14.97; 100/127 female), and listed several primary and secondary CP diagnoses. In almost 90% of PwPPs, physical and emotional wellbeing were affected by CP. More than 90% of PwPPs used alternative therapies (acupuncture, homeopathy, massage therapy, etc.). Attitude toward mHealth apps were positive even though nearly half of PwPPs were unfamiliar with them. More than 72% of respondents were open to using a health-related app as a research tool for data collection in real life situations. Comprehensive data collection (especially about psychosocial factors) was the most important requirement. More respondents (especially medical professionals) were concerned about health hazards of misinformation communicated via health-related information and communication systems (maximum 80%) than about privacy (maximum 40%). Qualitative analyses revealed several promises and impediments to creation of data-sharing platforms for CP.

Conclusions

This study shows a general willingness among PwPPs to become partners in studying alternative pain management. Despite a generally positive attitude toward the concept of sharing complex personal data to advance research, heterogeneity of attitudes shaped by personal experiences must be considered. Our study underlines the need for any digital strategy for CP research to be person-centered and flexible.

Risk assessment for precise intervention of COVID-19 epidemic based on available big data and spatio-temporal simulation method: Empirical evidence from different public places in Guangzhou, China

Risk assessment of the intra-city spatio-temporal spreading of COVID-19 is important for providing location-based precise intervention measures, especially when the epidemic occurred in the densely populated and high mobile public places. The individual-based simulation has been proven to be an effective method for the risk assessment. However, the acquisition of individual-level mobility data is limited. This study used publicly available datasets to approximate dynamic intra-city travel flows by a spatio-temporal gravity model. On this basis, an individual-based epidemic model integrating agent-based model with the susceptible-exposed-infectious-removed (SEIR) model was proposed and the intra-city spatio-temporal spreading process of COVID-19 in eleven public places in Guangzhou China were explored. The results indicated that the accuracy of dynamic intra-city travel flows estimated by available big data and gravity model is acceptable. The spatio-temporal simulation method well presented the process of COVID-19 epidemic. Four kinds of spatial-temporal transmission patterns were identified and the pattern was highly dependent on the urban spatial structure and location. It indicated that location-based precise intervention measures should be implemented according to different regions. The approach of this research can be used by policy-makers to make rapid and accurate risk assessments and to implement intervention measures ahead of epidemic outbreaks.

COVID-19 Diagnosis: A Review of Rapid Antigen, RT-PCR and Artificial Intelligence Methods

As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, and surveillance. Meanwhile, fast and efficient point-of-care (POC) testing and self-testing kits have become necessary in the fight against COVID-19 and to assist healthcare personnel and governments curb the spread of the virus. This paper presents a review of the various types of COVID-19 detection methods, diagnostic technologies, and surveillance approaches that have been used or proposed. The review provided in this article should be beneficial to researchers in this field and health policymakers at large.

Animal Crossing and COVID-19: A Qualitative Study Examining How Video Games Satisfy Basic Psychological Needs During the Pandemic

The COVID-19 pandemic has affected the way many people live their lives. The increasing amount of time spent indoors and isolated during periods of lockdown has been accompanied by an increase in the time people spend playing video games. One such game which soared in popularity during the early stages of the pandemic was Animal Crossing: New Horizons. Through semi-structured interviews with players, and using a theory-informed qualitative analysis, we document and examine players’ motivations and experiences playing Animal Crossing: New Horizons during the pandemic. Findings suggest that playing the game helped satisfy various psychological needs—autonomy, relatedness, and competence—as described by Self-Determination Theory. Conversely, players stopped playing the game when they found that their psychological needs were thwarted or better met through other activities. Our findings offer support that video games can offer psychological relief in stressful contexts by providing opportunities for people to satisfy key psychological needs. Theoretical and practical implications are discussed.

Social Media and COVID-19—Perceptions and Public Deceptions of Ivermectin, Colchicine and Hydroxychloroquine: Lessons for Future Pandemics

The capacity for social media to influence the utilization of re-purposed medicines to manage COVID-19, despite limited availability of safety and efficacy data, is a cause for concern within health care systems. This study sought to ascertain links between social media reports and utilization for three re-purposed medicines: hydroxychloroquine (HCQ), ivermectin and colchicine. A combined retrospective analysis of social media posts for these three re-purposed medicines was undertaken, along with utilization and clinical trials data, in South Africa, between January 2020 and June 2021. In total, 77,257 posts were collected across key social media platforms, of which 6884 were relevant. Ivermectin had the highest number of posts (55%) followed by HCQ (44%). The spike in ivermectin use was closely correlated to social media posts. Similarly, regarding chloroquine (as HCQ is not available in South Africa), social media interest was enhanced by local politicians. Sentiment analysis revealed that posts regarding the effectiveness of these repurposed medicines were positive. This was different for colchicine, which contributed only a small number of mentions (1%). Of concern is that the majority of reporters in social media (85%) were unidentifiable. This study provides evidence of social media as a driver of re-purposed medicines. Healthcare professionals have a key role in providing evidence-based advice especially with unidentifiable posts.

The Extreme Right as a Defender of Human Rights? Parliamentary Debates on COVID-19 Emergency Legislation in Slovakia

During the COVID-19 pandemic, the protection of public health became a political priority worldwide. Slovakia’s COVID-19 response was initially praised as a global success. However, major rights restrictions were introduced in spring 2020, with some of these endorsed by the parliament. This article uses = Rossiter’s and Schmitt’s concepts of the exception and Agamben’s distinction between life and survival to highlight the risks pertaining to the framing of the protection of public health as contradictory to human rights guarantees. It investigates how human rights were discussed by Slovak parliamentarians in relation to key legislation, that introduced a COVID-19 contact tracing app and allowed repeated prolongation of health emergencies by the executive with parliamentary approval. The findings indicate that democratic parliamentarians prioritized public health considerations framed in terms of security and effectiveness rather than rights, dissociating biological survival from political life. In contrast, extreme political actors became outspoken critics of emergencies, referring to human rights. As such, the deliberations represent a missed opportunity by democratic legislators to justify public health protection via a human rights lens and risk undermining democracy in Slovakia.

An electronic medical records study of population obesity prevalence in El Paso, Texas

BACKGROUND

In this study, we determine the feasibility of using electronic medical record (EMR) data to determine obesity prevalence at the census tract level in El Paso County, Texas, located on the U.S.-Mexico border.

METHODS

2012-2018 Body Mass Index (BMI kg/m²) data from a large university clinic system in was geocoded and aggregated to a census tract level. After cleaning and removing duplicate EMR and unusable data, 143,524 patient records were successful geocoded. Maps were created to assess representativeness of EMR data across census tracts, within El Paso County. Additionally, maps were created to display the distribution of obesity across the same geography.

RESULTS

EMR data represented all but one El Paso census tract. Representation ranged from 0.7% to 34.9%. Greatest representation were among census tracts in and around clinics. The mean EMR data BMI (kg/m²) was 30.1, this is approximately 6% less than the 36.0% estimated for El Paso County using the Behavioral Risk Factor Surveillance Study (BRFSS) estimate. At the census tract level, obesity prevalence ranged from 26.6 to 57.6%. The highest obesity prevalence were in areas that tended to be less affluent, with a higher concentration of immigrants, poverty and Latino ethnic concentration.

CONCLUSIONS

EMR data use for obesity surveillance is feasible in El Paso County, Texas, a U.S.-Mexico border community. Findings indicate substantial obesity prevalence variation between census tracts within El Paso County that may be associated with population distributions related to socioeconomics.

User Privacy, Surveillance and Public Health during COVID-19 - An Examination of Twitterverse

Online users frequently rely on social networking platforms to transmit public concerns and raise awareness about societal issues. With many government organizations actively employing social media data in recent times, the need for processing public concerns on social media has become a critical topic of interest across academic scholars and practitioners. However, the growing volume of social media data makes it difficult to process all the issues under a single umbrella, causing to overlook the main topic of interest within communication technologies, such as privacy. For example, during the COVID-19 pandemic, arguments on privacy and health issues exploded on Twitter, with several threads centered on contact tracking, health data gathering, and its usage by government agencies. To address the challenges of rising data volumes and to understand the importance of privacy concerns, particularly among users seeking greater privacy protection during this pandemic, we conduct a focused empirical analysis of user tweets about privacy. In this two-part research, our first study reveals three macro privacy issues of discussion distilled from the Twitter corpus, subsequently subdivided into 12 user privacy categories. The second study builds on the findings of the first study, focusing on the primary difficulties highlighted in the macro privacy subjects-contact tracing and digital surveillance. Using a document clustering approach, we present implications for the focal privacy topics that policymakers, agencies, and governments should consider for offering better privacy protections and help the community rebuild.

New approach in SARS-CoV-2 surveillance using biosensor technology: a review

Biosensors are analytical tools that transform the bio-signal into an observable response. Biosensors are effective for early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection because they target viral antigens to assess clinical development and provide information on the severity and critical trends of infection. The biosensors are capable of being on-site, fast, and extremely sensitive to the target viral antigen, opening the door for early detection of SARS-CoV-2. They can screen individuals in hospitals, airports, and other crowded locations. Microfluidics and nanotechnology are promising cornerstones for the development of biosensor-based techniques. Recently, due to high selectivity, simplicity, low cost, and reliability, the production of biosensor instruments have attracted considerable interest. This review article precisely provides the extensive scientific advancement and intensive look of basic principles and implementation of biosensors in SARS-CoV-2 surveillance, especially for human health. In this review, the importance of biosensors including Optical, Electrochemical, Piezoelectric, Microfluidic, Paper-based biosensors, Immunosensors, and Nano-Biosensors in the detection of SARS-CoV-2 has been underscored. Smartphone biosensors and calorimetric strips that target antibodies or antigens should be developed immediately to combat the rapidly spreading SARS-CoV-2. Wearable biosensors can constantly monitor patients, which is a highly desired feature of biosensors. Finally, we summarized the literature, outlined new approaches and future directions in diagnosing SARS-CoV-2 by biosensor-based techniques.

COVID-19 experiences predicting high anxiety and depression among a sample of BRCA1/BRCA2-positive women in the US

During the COVID-19 pandemic, breast and ovarian cancer survivors experienced more anxiety and depression than before the pandemic. Studies have not investigated the similarities of this trend among BRCA1/2-positive women who are considered high risk for these cancers. The current study examines the impact of COVID-19 experiences on anxiety and depression in a sample of BRCA1/2-positive women in the U.S. 211 BRCA1/2-positive women from medically underserved backgrounds completed an online survey. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression for associations between COVID-19 experiences and self-reported anxiety and depression stratified by demographic factors. Overall, women who reported COVID-19 stigma or discrimination (aOR, 5.14, 95% CI [1.55, 17.0]) experienced significantly more depressive symptoms than women who did not report this experience. Racial/ethnic minority women caring for someone at home during COVID-19 were 3.70 times more likely (95% CI [1.01, 13.5]) to report high anxiety while non-Hispanic white women were less likely (aOR, 0.34, 95% CI [0.09, 1.30], p interaction = 0.011). To date, this is the first study to analyze anxiety and depression considering several COVID-19 predictors among BRCA1/2-positive women. Our findings can be used to inform future research and advise COVID-19-related mental health resources specific to these women.

Prosociality and endorsement of liberty: Communal and individual predictors of attitudes towards surveillance technologies

BACKGROUND

During the coronavirus disease 2019 (COVID-19) pandemic, digital tracking technologies were recognised as one of the key tools in preventing the spread of the virus and maintaining health security. However, they also raised numerous controversies because of their potential to endanger civil rights and privacy. Most studies on the acceptance of anti-COVID-19 tracking technologies did not include important social factors and did not examine the directionality between variables. We aimed to fill this gap in the present study.

METHODS

We conducted a four-wave, representative longitudinal panel survey among Polish citizens on the relationship between acceptance of anti-COVID-19 tracking technologies and prosociality, national identification, and endorsement of individual liberty. Analyses were performed using random-intercept cross-lagged panel models.

RESULTS

We observed bidirectional cross-lagged relationships between prosociality and acceptance of anti-COVID 19 tracking technologies, with a stronger path from prosociality to acceptance than the other way around. Endorsement of individual liberty predicted negative attitudes towards technologies and this relation was strengthened by perceived threat of future technological surveillance. We did not find a significant relationship between acceptance of technologies and national identification at the within-subject level.

CONCLUSIONS

This is the first study to analyse dynamic within-person relationships between communal and individual aspects and acceptance of anti-COVID-19 surveillance technologies. We conclude that prosocial attitude may lead to social acceptance of technology that, while helpful to fight with a pandemic, might also infringe on personal rights.

Relational autonomy: lessons from COVID-19 and twentieth-century philosophy

COVID-19 has turned many ethical principles and presuppositions upside down. More precisely, the principle of respect for autonomy has been shown to be ill suited to face the ethical challenges posed by the current health crisis. Individual wishes and choices have been subordinated to public interests. Patients have received trial therapies under extraordinary procedures of informed consent. The principle of respect for autonomy, at least in its mainstream interpretation, has been particularly questioned during this pandemic. Further reflection on the nature and value of autonomy is urgently needed. Relational autonomy has been proposed as an alternative account of autonomy that can more adequately respond to contemporary ethical issues in general and to a pandemic such as the one we are currently facing in particular. As relational autonomy is an emerging notion in current bioethics, it requires further consideration and development to be properly operationalized. This paper aims to show how six different philosophical branches--namely, philosophy of nature, philosophical anthropology, existential phenomenology, discourse ethics, hermeneutics, and cultural anthropology--have incorporated the category of relation throughout the twentieth century. We first delve into primary philosophical sources and then apply their insights to the specific field of medical ethics. Learning from the historical developments of other philosophical fields may provide illumination that will enable bioethics to experience a successful "relational turn", which has been partially initiated in contemporary bioethics but not yet achieved.

Contact tracing apps for the COVID-19 pandemic: a systematic literature review of challenges and future directions for neo-liberal societies

PURPOSE

The COVID-19 pandemic has spread with increased fatalities around the world and has become an international public health crisis. Public health authorities in many countries have introduced contact tracing apps to track and trace infected persons as part of measures to contain the spread of the Severe Acute Respiratory Syndrome-Coronavirus 2. However, there are major concerns about its efficacy and privacy which affects mass acceptance amongst a population. This systematic literature review encompasses the current challenges facing this technology and recommendations to address such challenges in the fight against the COVID-19 pandemic in neo-liberal societies.

METHODS

The systematic literature review was conducted by searching databases of Google Scholar, Web of Science, PubMed, IEEE Xplore Digital Library, PsycInfo and ScienceDirect using the search terms ("Contact Tracing" OR "Contact Tracing apps") AND ("COVID-19" OR "Coronavirus") to identify relevant literature. The searches were run against the title, keywords, or abstract, depending on the search platforms. The searches were conducted between January 1, 2020, through 31st January 2021. Further inputs were also taken from preprints, published government and technical reports. We explore and discuss from the selected literature, the key challenges and issues that influence unwillingness to use these contact tracing apps in neo-liberal societies which include the plausibility of abuse of user privacy rights and lack of trust in the government and public health authorities by their citizens. Other challenges identified and discussed include ethical issues, security vulnerabilities, user behaviour and participation, and technical constraints.

RESULTS AND CONCLUSION

Finally, in the analysis of this systematic literature review, recommendations to address these challenges, future directions, and considerations in the use of digital contact tracing apps and related technologies to contain the spread of future pandemic outbreaks are presented. For policy makers in neo-liberal societies, this study provides an in-depth review of issues that must be addressed. We highlight recommendations to improve the willingness to use such digital technologies and could facilitate mass acceptance amongst users.

Nanodiagnostics to Face SARS-CoV-2 and Future Pandemics: From an Idea to the Market and Beyond

The COVID-19 pandemic made clear how our society requires quickly available tools to address emerging healthcare issues. Diagnostic assays and devices are used every day to screen for COVID-19 positive patients, with the aim to decide the appropriate treatment and containment measures. In this context, we would have expected to see the use of the most recent diagnostic technologies worldwide, including the advanced ones such as nano-biosensors capable to provide faster, more sensitive, cheaper, and high-throughput results than the standard polymerase chain reaction and lateral flow assays. Here we discuss why that has not been the case and why all the exciting diagnostic strategies published on a daily basis in peer-reviewed journals are not yet successful in reaching the market and being implemented in the clinical practice.

Privacy and surveillance attitudes during health crises: Acceptance of surveillance and privacy protection behaviours

The wide deployment of digital technologies for the management of the COVID-19 pandemic has triggered concerns about privacy and intrusion from government surveillance. This study investigates individual privacy and surveillance attitudes by developing a theoretical model to explain acceptance of government surveillance and privacy protection behaviours during health-crises, such as the COVID-19 pandemic. Results from a US sample reveal that people are concerned about the collection and use of their personal information via mobile applications and the monitoring of their online activities by authorities. Findings reveal the important roles of political trust and belief that governments' need to be proactive in protecting peoples' welfare during a crisis that can increase acceptance of surveillance and thus assist in the management of the health crisis. Implications for research and practice are discussed.

Post-COVID Public Health Surveillance and Privacy Expectations in the United States: Scenario-Based Interview Study

BACKGROUND

Smartphone-based apps designed and deployed to mitigate the COVID-19 pandemic may become infrastructure for postpandemic public health surveillance in the United States. Through the lenses of privacy concerns and user expectations of digital pandemic mitigation techniques, we identified possible long-term sociotechnical implications of such an infrastructure.

OBJECTIVE

We explored how people in the United States perceive the possible routinization of pandemic tracking apps for public health surveillance in general. Our interdisciplinary analysis focused on the interplay between privacy concerns, data practices of surveillance capitalism, and trust in health care providers. We conducted this analysis to achieve a richer understanding of the sociotechnical issues raised by the deployment and use of technology for pandemic mitigation.

METHODS

We conducted scenario-based, semistructured interviews (n=19) with adults in the United States. The interviews focused on how people perceive the short- and long-term privacy concerns associated with a fictional smart thermometer app deployed to mitigate the "outbreak of a contagious disease." In order to elicit future-oriented discussions, the scenario indicated that the app would continue functioning "after the disease outbreak has dissipated." We analyzed interview transcripts using reflexive thematic analysis.

RESULTS

In the context of pandemic mitigation technology, including app-based tracking, people perceive a core trade-off between public health and personal privacy. People tend to rationalize this trade-off by invoking the concept of "the greater good." The interplay between the trade-off and rationalization forms the core of sociotechnical issues that pandemic mitigation technologies raise. Participants routinely expected that data collected through apps related to public health would be shared with unknown third parties for the financial gain of the app makers. This expectation suggests a perceived alignment between an app-based infrastructure for public health surveillance and the broader economics of surveillance capitalism. Our results highlight unintended and unexpected sociotechnical impacts of routinizing app-based tracking on postpandemic life, which are rationalized by invoking a nebulous concept of the greater good.

CONCLUSIONS

While technologies such as app-based tracking could be useful for pandemic mitigation and preparedness, the routinization of such apps as a form of public health surveillance may have broader, unintentional sociotechnical implications for individuals and the societies in which they live. Although technology has the potential to increase the efficacy of pandemic mitigation, it exists within a broader network of sociotechnical concerns. Therefore, it is necessary to consider the long-term implications of pandemic mitigation technologies beyond the immediate needs of addressing the COVID-19 pandemic. Potential negative consequences include the erosion of patient trust in health care systems and providers, grounded in concerns about privacy violations and overly broad surveillance.

Not everything is as it seems: Digital technology affordance, pandemic control, and the mediating role of sociomaterial arrangements

An overly favorable narrative has developed around the role played by digital technologies in containing Covid-19, which oversimplifies the complexity of technology adoption. This narrative takes sociomaterial arrangements for granted and conceptualizes technology affordance - the problem-solving capability of a technology - as a standard built-in feature that automatically activates during technology deployment, leading to undiversified and predetermined collective benefits. This paper demonstrates that not everything is as it seems; implementing a technology is a necessary but insufficient condition for triggering its potential problem-solving capability. The potential affordance and effects of a technology are mediated by the sociomaterial arrangements that users assemble to connect their goals to the materiality of technological artifacts and socio-organizational context in which technology deployment takes place. To substantiate this argument and illustrate the mediating role of sociomaterial arrangements, we build on sociomateriality and technology affordance theory, and we present the results of a systematic review of Covid-19 literature in which 2187 documents are examined. The review combines text data mining, co-occurrence pattern recognition, and inductive coding, and it focuses on four digital technologies that public authorities have deployed as virus containment measures: infrared temperature-sensing devices; ICT-based surveillance and contact-tracing systems; bioinformatic tools and applications for laboratory testing; and electronic mass communications media. Reporting on our findings, we add nuances to the academic debate on sociomateriality, technology affordance, and the governance of technology in public health crises. In addition, we provide public authorities with practical recommendations on how to strengthen their approach to digital technology deployment for pandemic control.

Tracking Self-reported Symptoms and Medical Conditions on Social Media During the COVID-19 Pandemic: Infodemiological Study

BACKGROUND

Harnessing health-related data posted on social media in real time can offer insights into how the pandemic impacts the mental health and general well-being of individuals and populations over time.

OBJECTIVE

This study aimed to obtain information on symptoms and medical conditions self-reported by non-Twitter social media users during the COVID-19 pandemic, to determine how discussion of these symptoms and medical conditions changed over time, and to identify correlations between frequency of the top 5 commonly mentioned symptoms post and daily COVID-19 statistics (new cases, new deaths, new active cases, and new recovered cases) in the United States.

METHODS

We used natural language processing (NLP) algorithms to identify symptom- and medical condition-related topics being discussed on social media between June 14 and December 13, 2020. The sample posts were geotagged by NetBase, a third-party data provider. We calculated the positive predictive value and sensitivity to validate the classification of posts. We also assessed the frequency of health-related discussions on social media over time during the study period, and used Pearson correlation coefficients to identify statistically significant correlations between the frequency of the 5 most commonly mentioned symptoms and fluctuation of daily US COVID-19 statistics.

RESULTS

Within a total of 9,807,813 posts (nearly 70% were sourced from the United States), we identified a discussion of 120 symptom-related topics and 1542 medical condition-related topics. Our classification of the health-related posts had a positive predictive value of over 80% and an average classification rate of 92% sensitivity. The 5 most commonly mentioned symptoms on social media during the study period were anxiety (in 201,303 posts or 12.2% of the total posts mentioning symptoms), generalized pain (189,673, 11.5%), weight loss (95,793, 5.8%), fatigue (91,252, 5.5%), and coughing (86,235, 5.2%). The 5 most discussed medical conditions were COVID-19 (in 5,420,276 posts or 66.4% of the total posts mentioning medical conditions), unspecified infectious disease (469,356, 5.8%), influenza (270,166, 3.3%), unspecified disorders of the central nervous system (253,407, 3.1%), and depression (151,752, 1.9%). Changes in posts in the frequency of anxiety, generalized pain, and weight loss were significant but negatively correlated with daily new COVID-19 cases in the United States (r=-0.49, r=-0.46, and r=-0.39, respectively; P<.05). Posts on the frequency of anxiety, generalized pain, weight loss, fatigue, and the changes in fatigue positively and significantly correlated with daily changes in both new deaths and new active cases in the United States (r ranged=0.39-0.48; P<.05).

CONCLUSIONS

COVID-19 and symptoms of anxiety were the 2 most commonly discussed health-related topics on social media from June 14 to December 13, 2020. Real-time monitoring of social media posts on symptoms and medical conditions may help assess the population's mental health status and enhance public health surveillance for infectious disease.

COVID-19 Experiences Predicting High Anxiety and Depression Among a Sample of BRCA1/BRCA2-positive Women in the US

Purpose.

During the COVID-19 pandemic, breast and ovarian cancer survivors experienced more anxiety and depression than before the pandemic. Studies have not investigated the similarities of this trend among BRCA1/2-positive women who are considered high risk for these cancers. The current study examines the impact of COVID-19 experiences on anxiety and depression in a sample of BRCA1/2-positive women in the U.S.

Methods.

211 BRCA1/2-positive women from medically underserved backgrounds completed an online survey. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression for associations between COVID-19 experiences and self-reported anxiety and depression stratified by demographic factors.

Results.

Overall, women who reported quarantining/isolation (aOR, 0.46, 95% CI, 0.24–0.88) experienced significantly fewer depressive symptoms than women who did not report this experience. Racial/ethnic minority women caring for someone at home during COVID-19 were 3.78 times more likely (95% CI, 1.04–13.6) to report high anxiety while non-Hispanic white women were less likely (aOR, 0.36, 95% CI, 0.10–1.33, p-interaction=0.011).

Conclusions.

To date, this is the first study to analyze anxiety and depression considering several COVID-19 predictors among BRCA1/2-positive women. Our findings can be used to inform future research and advise COVID-19-related mental health resources specific to these women.

Digital contact tracing, community uptake, and proximity awareness technology to fight COVID-19: a systematic review

Digital contact tracing provides an expeditious and comprehensive way to collect and analyze data on people's proximity, location, movement, and health status. However, this technique raises concerns about data privacy and its overall effectiveness. This paper contributes to this debate as it provides a systematic review of digital contact tracing studies between January 1, 2020, and March 31, 2021. Following the PRISMA protocol for systematic reviews and the CHEERS statement for quality assessment, 580 papers were initially screened, and 19 papers were included in a qualitative synthesis. We add to the current literature in three ways. First, we evaluate whether digital contact tracing can mitigate COVID-19 by either reducing the effective reproductive number or the infected cases. Second, we study whether digital is more effective than manual contact tracing. Third, we analyze how proximity/location awareness technologies affect data privacy and population participation. We also discuss proximity/location accuracy problems arising when these technologies are applied in different built environments (i.e., home, transport, mall, park). This review provides a strong rationale for using digital contact tracing under specific requirements. Outcomes may inform current digital contact tracing implementation efforts worldwide regarding the potential benefits, technical limitations, and trade-offs between effectiveness and privacy.

Navigating the ethics of remote research data collection

COVID-19 has accelerated broad trends already in place toward remote research data collection and monitoring. This move implicates novel ethical and regulatory challenges which have not yet received due attention. Existing work is preliminary and does not seek to identify or grapple with the issues in a rigorous and sophisticated way. Here, we provide a framework for identifying and addressing challenges that we believe can help the research community realize the benefits of remote technologies while preserving ethical ideals and public trust. We organize issues into several distinct categories and provide points to consider in a table that can help facilitate ethical design and review of research studies using remote health instruments.

Prediction model for the spread of the COVID-19 outbreak in the global environment

COVID-19 has long become a worldwide pandemic. It is responsible for the death of over two million people and posed an economic recession. This paper studies the spread pattern of COVID-19, aiming to establish a prediction model for this event. We harness Data Mining and Machine Learning methodologies to train regression models to predict the number of confirmed cases in a spatial-temporal space. We introduce an innovative concept ‒ the Center of Infection Mass (CoIM) ‒ adapted from the field of physics. We empirically evaluated our model on western European countries, based on the CoIM index and other features, and showed that a relatively high accurate prediction of the spread can be obtained. Our contribution is twofold: first, we introduced a prediction methodology and proved empirically that a prediction can be made even to the range of over a month; second, we showed promise in adopting the CoIM index to prediction models, when models that adopt the CoIM yield significantly better results than those that discard it. By applying our model, and better controlling the inherent tradeoff between life-saving and economy, we believe that decision-makers can take close to optimal measures. Thus, this methodology may contribute to public welfare.

Utilizing Health Behavior Change and Technology Acceptance Models to Predict the Adoption of COVID-19 Contact Tracing Apps: Cross-sectional Survey Study

Background

To combat the global COVID-19 pandemic, contact tracing apps have been discussed as digital health solutions to track infection chains and provide appropriate information. However, observational studies point to low acceptance in most countries, and few studies have yet examined theory-based predictors of app use in the general population to guide health communication efforts.

Objective

This study utilizes established health behavior change and technology acceptance models to predict adoption intentions and frequency of current app use.

Methods

We conducted a cross-sectional online survey between May and July 2020 in a German convenience sample (N=349; mean age 35.62 years; n=226, 65.3% female). To inspect the incremental validity of model constructs as well as additional variables (privacy concerns, personalization), hierarchical regression models were applied, controlling for covariates.

Results

The theory of planned behavior and the unified theory of acceptance and use of technology predicted adoption intentions (R²=56%-63%) and frequency of current app use (R²=33%-37%). A combined model only marginally increased the predictive value by about 5%, but lower privacy concerns and higher threat appraisals (ie, anticipatory anxiety) significantly predicted app use when included as additional variables. Moreover, the impact of perceived usefulness was positive for adoption intentions but negative for frequency of current app use.

Conclusions

This study identified several theory-based predictors of contact tracing app use. However, few constructs, such as social norms, have a consistent positive effect across models and outcomes. Further research is required to replicate these observations, and to examine the interconnectedness of these constructs and their impact throughout the pandemic. Nevertheless, the findings suggest that promulgating affirmative social norms and positive emotional effects of app use, as well as addressing health concerns, might be promising strategies to foster adoption intentions and app use in the general population.

Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance

COVID-19 was first discovered in December 2019 and has continued to rapidly spread across countries worldwide infecting thousands and millions of people. The virus is deadly, and people who are suffering from prior illnesses or are older than the age of 60 are at a higher risk of mortality. Medicine and Healthcare industries have surged towards finding a cure, and different policies have been amended to mitigate the spread of the virus. While Machine Learning (ML) methods have been widely used in other domains, there is now a high demand for ML-aided diagnosis systems for screening, tracking, predicting the spread of COVID-19 and finding a cure against it. In this paper, we present a journey of what role ML has played so far in combating the virus, mainly looking at it from a screening, forecasting, and vaccine perspective. We present a comprehensive survey of the ML algorithms and models that can be used on this expedition and aid with battling the virus.

Predictors of well-being and productivity among software professionals during the COVID-19 pandemic - a longitudinal study

The COVID-19 pandemic has forced governments worldwide to impose movement restrictions on their citizens. Although critical to reducing the virus' reproduction rate, these restrictions come with far-reaching social and economic consequences. In this paper, we investigate the impact of these restrictions on an individual level among software engineers who were working from home. Although software professionals are accustomed to working with digital tools, but not all of them remotely, in their day-to-day work, the abrupt and enforced work-from-home context has resulted in an unprecedented scenario for the software engineering community. In a two-wave longitudinal study (N = 192), we covered over 50 psychological, social, situational, and physiological factors that have previously been associated with well-being or productivity. Examples include anxiety, distractions, coping strategies, psychological and physical needs, office set-up, stress, and work motivation. This design allowed us to identify the variables that explained unique variance in well-being and productivity. Results include (1) the quality of social contacts predicted positively, and stress predicted an individual's well-being negatively when controlling for other variables consistently across both waves; (2) boredom and distractions predicted productivity negatively; (3) productivity was less strongly associated with all predictor variables at time two compared to time one, suggesting that software engineers adapted to the lockdown situation over time; and (4) longitudinal analyses did not provide evidence that any predictor variable causal explained variance in well-being and productivity. Overall, we conclude that working from home was per se not a significant challenge for software engineers. Finally, our study can assess the effectiveness of current work-from-home and general well-being and productivity support guidelines and provides tailored insights for software professionals.

Web-Based Apps for Responding to Acute Infectious Disease Outbreaks in the Community: Systematic Review

Background

Web-based technology has dramatically improved our ability to detect communicable disease outbreaks, with the potential to reduce morbidity and mortality because of swift public health action. Apps accessible through the internet and on mobile devices create an opportunity to enhance our traditional indicator-based surveillance systems, which have high specificity but issues with timeliness.

Objective

The aim of this study is to describe the literature on web-based apps for indicator-based surveillance and response to acute communicable disease outbreaks in the community with regard to their design, implementation, and evaluation.

Methods

We conducted a systematic search of the published literature across four databases (MEDLINE via OVID, Web of Science Core Collection, ProQuest Science, and Google Scholar) for peer-reviewed journal papers from January 1998 to October 2019 using a keyword search. Papers with the full text available were extracted for review, and exclusion criteria were applied to identify eligible papers.

Results

Of the 6649 retrieved papers, 23 remained, describing 15 web-based apps. Apps were primarily designed to improve the early detection of disease outbreaks, targeted government settings, and comprised either complex algorithmic or statistical outbreak detection mechanisms or both. We identified a need for these apps to have more features to support secure information exchange and outbreak response actions, with a focus on outbreak verification processes and staff and resources to support app operations. Evaluation studies (6 out of 15 apps) were mostly cross-sectional, with some evidence of reduction in time to notification of outbreak; however, studies lacked user-based needs assessments and evaluation of implementation.

Conclusions

Public health officials designing new or improving existing disease outbreak web-based apps should ensure that outbreak detection is automatic and signals are verified by users, the app is easy to use, and staff and resources are available to support the operations of the app and conduct rigorous and holistic evaluations.

Primary care-based health surveillance actions in response to the COVID-19 pandemic: contributions to the debate

We conducted an integrated literature review aimed at reflecting on the challenges related to primary care-based health surveillance actions in response to the COVID-19 pandemic in selected countries. The study included countries with different PHC models that adopted surveillance as an approach to control the transmission of COVID-19. We performed a search in October 2020 for relevant literature and norms and guidelines related to the organization of primary health care (PHC) in response to the pandemic on official government websites and the databases Web of Science and Science Direct. The integrated health surveillance actions demonstrated that efforts were more focused on risks, with some countries adopting innovative and effective measures to respond to COVID-19, considering emerging needs within PHC. However, in addition to ethical controversies and operational difficulties, access to technology was a challenge in actions developed by some countries due to social inequalities.

Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic

Between March and April 2020, Cyprus and Greece health authorities enforced three escalated levels of public health interventions to control the COVID-19 pandemic. We quantified compliance of 108 asthmatic schoolchildren (53 from Cyprus, 55 from Greece, mean age 9.7 years) from both countries to intervention levels, using wearable sensors to continuously track personal location and physical activity. Changes in 'fraction time spent at home' and 'total steps/day' were assessed with a mixed-effects model adjusting for confounders. We observed significant mean increases in 'fraction time spent at home' in Cyprus and Greece, during each intervention level by 41.4% and 14.3% (level 1), 48.7% and 23.1% (level 2) and 45.2% and 32.0% (level 3), respectively. Physical activity in Cyprus and Greece demonstrated significant mean decreases by - 2,531 and - 1,191 (level 1), - 3,638 and - 2,337 (level 2) and - 3,644 and - 1,961 (level 3) total steps/day, respectively. Significant independent effects of weekends and age were found on 'fraction time spent at home'. Similarly, weekends, age, humidity and gender had an independent effect on physical activity. We suggest that wearable technology provides objective, continuous, real-time location and activity data making possible to inform in a timely manner public health officials on compliance to various tiers of public health interventions during a pandemic.

Structural Racism in the COVID-19 Pandemic: Moving Forward

The COVID-19 pandemic has taken a substantial human, social and economic toll globally, but its impact on Black/African Americans, Latinx, and American Indian/Alaska Native communities in the U.S. is unconscionable. As the U.S. continues to combat the current COVID-19 cycle and prepares for future pandemics, it will be critical to learn from and rectify past and contemporary wrongs. Drawing on experiences in genomic research and intersecting areas in medical ethics, health disparities, and human rights, this article considers three key COVID-19-related issues: research to identify remedies; testing, contact tracing and surveillance; and lingering health needs and disability. It provides a pathway for the future: community engagement to develop culturally-sensitive responses to the myriad genomic/bioethical dilemmas that arise, and the establishment of a Truth and Reconciliation Commission to transition the country from its contemporary state of segregation in healthcare and health outcomes into an equitable and prosperous society for all.

Turn to the Internet First? Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend

The surveillance and forecast of newly confirmed cases are important to mobilize medical resources and facilitate policymaking during a public health emergency. Digital surveillance using data available online has increasingly become a trend with the advancement of the Internet. In this study, we assessed the predictive value of multiple online medical behavioral data, including online medical consultation (OMC), online medical appointment (OMA), and online medical search (OMS) for the regional outbreak of coronavirus disease 2019 in Shenzhen, China during January 1, 2020 to March 5, 2020. Multivariate vector autoregression models were used for the prediction. The results identified a novel predictor, OMC, which can forecast the disease trend up to 2 days ahead of the official reports of confirmed cases from the local health department. OMS data had relatively weaker predictive power than OMC in our model, and OMA data failed to predict the confirmed cases. This study highlights the importance of OMC data and has implication in providing evidence-based guidelines for local authorities to evaluate risks and allocate resources during the pandemic.

The local governance of COVID-19: Disease prevention and social security in rural India

Countries around the world have undertaken a wide range of strategies to halt the spread of COVID-19 and control the economic fallout left in its wake. Rural areas of developing countries pose particular difficulties for developing and implementing effective responses owing to underdeveloped health infrastructure, uneven state capacity for infection control, and endemic poverty. This paper makes the case for the critical role of local governance in coordinating pandemic response by examining how state authorities are attempting to bridge the gap between the need for rapid, vigorous response to the pandemic and local realities in three Indian states - Rajasthan, Odisha, and Kerala. Through a combination of interviews with mid and low-level bureaucrats and a review of policy documents, we show how the urgency of COVID-19 response has galvanized new kinds of cross-sectoral and multi-scalar interaction between administrative units involved in coordinating responses, as local governments have assumed central responsibility in the implementation of disease control and social security mechanisms. Evidence from Kerala in particular suggests that the state's long term investment in democratic local government and arrangements for incorporating women within grassroots state functions (through its Kudumbashree program) has built a high degree of public trust and cooperation with state actors, while local authorities embrace an ethic of care in the implementation of state responses. These observations, from the early months of the pandemic in South Asia, can serve as a foundation for future studies of how existing institutional arrangements and their histories pattern the long-term success of disease control and livelihood support as the pandemic proceeds. Governance, we argue, will be as important to understanding the trajectory of COVID-19 impacts and recovery as biology, demography, and economy.

Information Safety Assurances Increase Intentions to Use COVID-19 Contact Tracing Applications, Regardless of Autonomy-Supportive or Controlling Message Framing

Promoting the use of contact tracing technology will be an important step in global recovery from the COVID-19 pandemic. Across two studies, we assessed two messaging strategies as motivators of intended contact tracing uptake. In one sample of 1117 Australian adults and one sample of 888 American adults, we examined autonomy-supportive and controlling message framing and the presence or absence of information safety as predictors of intended contact tracing application uptake, using an online randomized 2 × 2 experimental design. The results suggested that the provision of data safety assurances may be key in affecting people’s intentions to use contact tracing technology, an effect we found in both samples regardless of whether messages were framed as autonomy-supportive or controlling. Those in high information safety conditions consistently reported higher intended uptake and more positive perceptions of the application than those in low information safety conditions. In Study 2, we also found that perceptions of government legitimacy related positively to intended application uptake, as did political affiliation. In sum, individuals appeared more willing to assent to authority regarding contact tracing insofar as their data safety can be assured. Yet, public messaging strategies alone may be insufficient to initiate intentions to change behavior, even in these unprecedented circumstances.

Conclusions

This chapter presents the usage of data science, which further helps in exploring the global pandemic COVID-19. This disease suppresses an overwhelming burden, not only to healthcare systems but to the world's economy too. In this era of techniques and technologies, it is believed that data science can better utilize scarce healthcare resources. In this chapter, we provide an introduction of data science and its applications, which helps in combating different aspects of COVID-19. Publicly available datasets related to disease are used as community resources. Different kinds of datasets are used to analyze various aspects of pandemic at different scales. These different kinds of datasets can be audio, video, textual, speech, and sensor data. More than hundreds of research articles are also studied to prepare a bibliometric study. Apart from grabbing all the advantages from datasets, this paper highlights a few challenges, such as surety of correct data, need of multidisciplinary collaboration, new data modality, security issues, and availability of data.

The Role of Basic Psychological Needs in Well-Being During the COVID-19 Outbreak: A Self-Determination Theory Perspective

Due to the coronavirus outbreak, people around the world are facing various challenges in maintaining their well-being, which can be compromised due to risk of illness and harsh measures of social distancing. As proposed by the Self-Determination Theory, basic psychological needs are essential nutrients of well-being. The aim of this study was to examine the role of basic psychological needs in well-being during the pandemic. A sequential mediation model was examined, that links positive and negative affectivity to well-being (satisfaction with life and general distress) through satisfaction and frustration of the basic psychological needs (for autonomy, competence, and relatedness). The study involved 965 participants (Mage = 29; 57% females) from Serbia. The Basic Psychological Needs Satisfaction and Frustration scale, Satisfaction with Life Scale, Depression Anxiety Stress Scale 21, and The Serbian Inventory of Affect based on the Panas-X were used. All the tested models were statistically significant. Controlling for age, gender, having children, health, employment, and marital status, direct effects in all models were highly significant, explaining up to 59% of criteria variance. The proportion of the explained variance was even higher when accounting for indirect effects. Sequential mediation models revealed that the indirect relationships between positive and negative affectivity and satisfaction with life and general distress were serially mediated by autonomy satisfaction, competence frustration, relatedness satisfaction, and relatedness frustration. This study raised an important question on how the disposition to experience more positive or negative emotions affects the change in subjective well-being. These results, coherent with the Self-Determination Theory postulates, add to the understanding of human functioning in the times of extraordinary circumstances during a pandemic, by suggesting that satisfaction and frustration of basic psychological needs might have a key role in obtaining optimal well-being.

Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature

BACKGROUND

The COVID-19 pandemic is favoring digital transitions in many industries and in society as a whole. Health care organizations have responded to the first phase of the pandemic by rapidly adopting digital solutions and advanced technology tools.

OBJECTIVE

The aim of this review is to describe the digital solutions that have been reported in the early scientific literature to mitigate the impact of COVID-19 on individuals and health systems.

METHODS

We conducted a systematic review of early COVID-19-related literature (from January 1 to April 30, 2020) by searching MEDLINE and medRxiv with appropriate terms to find relevant literature on the use of digital technologies in response to the pandemic. We extracted study characteristics such as the paper title, journal, and publication date, and we categorized the retrieved papers by the type of technology and patient needs addressed. We built a scoring rubric by cross-classifying the patient needs with the type of technology. We also extracted information and classified each technology reported by the selected articles according to health care system target, grade of innovation, and scalability to other geographical areas.

RESULTS

The search identified 269 articles, of which 124 full-text articles were assessed and included in the review after screening. Most of the selected articles addressed the use of digital technologies for diagnosis, surveillance, and prevention. We report that most of these digital solutions and innovative technologies have been proposed for the diagnosis of COVID-19. In particular, within the reviewed articles, we identified numerous suggestions on the use of artificial intelligence (AI)-powered tools for the diagnosis and screening of COVID-19. Digital technologies are also useful for prevention and surveillance measures, such as contact-tracing apps and monitoring of internet searches and social media usage. Fewer scientific contributions address the use of digital technologies for lifestyle empowerment or patient engagement.

CONCLUSIONS

In the field of diagnosis, digital solutions that integrate with traditional methods, such as AI-based diagnostic algorithms based both on imaging and clinical data, appear to be promising. For surveillance, digital apps have already proven their effectiveness; however, problems related to privacy and usability remain. For other patient needs, several solutions have been proposed, such as telemedicine or telehealth tools. These tools have long been available, but this historical moment may actually be favoring their definitive large-scale adoption. It is worth taking advantage of the impetus provided by the crisis; it is also important to keep track of the digital solutions currently being proposed to implement best practices and models of care in future and to adopt at least some of the solutions proposed in the scientific literature, especially in national health systems, which have proved to be particularly resistant to the digital transition in recent years.