Communicable Disease Surveillance Ethics in the Age of Big Data and New Technology

Analysis of the Spread and Evolution of COVID-19 Mutations in Ecuador Using Open Data

Currently, the analyses of and prediction using COVID-19-related data extracted from patient information repositories compiled by hospitals and health organizations are of paramount importance. These efforts significantly contribute to vaccine development and the formulation of contingency techniques, providing essential tools to prevent resurgence and to effectively manage the spread of the disease. In this context, the present research focuses on analyzing the biological information of the SARS-CoV-2 viral gene sequences and the clinical data of COVID-19-affected patients using publicly accessible data from Ecuador. This involves considering variables such as age, gender, and geographical location to understand the evolution of mutations and their distributions across Ecuadorian provinces. The Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology is applied for data analysis. Various data preprocessing and statistical analysis techniques are employed, including Pearson correlation, the chi-square test, and analysis of variance (ANOVA). Statistical diagrams and charts are used to facilitate a better visualization of the results. The results illuminate the genetic diversity of the virus and its correlation with clinical variables, offering a comprehensive understanding of the dynamics of COVID-19 spread in Ecuador. Critical variables influencing population vulnerability are highlighted, and the findings underscore the significance of mutation monitoring and indicate a need for global expansion of the research area.

The Application of Australian Rights Protections to the Use of Hepatitis C Notification Data to Engage People 'Lost to Follow Up'

Hepatitis C is a global public health threat, affecting 56 million people worldwide. The World Health Organization has committed to eliminating hepatitis C by 2030. Although new treatments have revolutionised the treatment and care of people with hepatitis C, treatment uptake has slowed in recent years, drawing attention to the need for innovative approaches to reach elimination targets. One approach involves using existing notifiable disease data to contact people previously diagnosed with hepatitis C. Within these disease surveillance systems, however, competing tensions exist, including protecting individual rights to privacy and autonomy, and broader public health goals. We explore these issues using hepatitis C and Australia's legislative and regulatory frameworks as a case study. We examine emerging uses of notification data to contact people not yet treated, and describe some of the ethical dilemmas associated with the use and non-use of this data and the protections that exist to preserve individual rights and public health. We reveal weaknesses in rights protections and processes under Australian public health and human rights legislation and argue for consultation with and involvement of affected communities in policy and intervention design before notification data is used to increase hepatitis C treatment coverage.

Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk

In its AI Act, the European Union chose to understand trustworthiness of AI in terms of the acceptability of its risks. Based on a narrative systematic literature review on institutional trust and AI in the public sector, this article argues that the EU adopted a simplistic conceptualization of trust and is overselling its regulatory ambition. The paper begins by reconstructing the conflation of "trustworthiness" with "acceptability" in the AI Act. It continues by developing a prescriptive set of variables for reviewing trust research in the context of AI. The paper then uses those variables for a narrative review of prior research on trust and trustworthiness in AI in the public sector. Finally, it relates the findings of the review to the EU's AI policy. Its prospects to successfully engineer citizen's trust are uncertain. There remains a threat of misalignment between levels of actual trust and the trustworthiness of applied AI.

Primary Care Physicians' and Patients' Perspectives on Equity and Health Security of Infectious Disease Digital Surveillance

PURPOSE

The coronavirus disease 2019 (COVID-19) pandemic facilitated the rapid development of digital detection surveillance (DDS) for outbreaks. This qualitative study examined how DDS for infectious diseases (ID) was perceived and experienced by primary care physicians and patients in order to highlight ethical considerations for promoting patients' autonomy and health care rights.

METHODS

In-depth interviews were conducted with a purposefully selected group of 16 primary care physicians and 24 of their patients. The group was reflective of a range of ages, educational attainment, and clinical experiences from urban areas in northern and southern China. Interviews were audio recorded, transcribed, and translated. Two researchers coded data and organized it into themes. A third researcher reviewed 15% of the data and discussed findings with the other researchers to assure accuracy.

RESULTS

Five themes were identified: ambiguity around the need for informed consent with usage of DDS; importance of autonomous decision making; potential for discrimination against vulnerable users of DDS for ID; risk of social inequity and disparate care outcomes; and authoritarian institutions' responsibility for maintaining health data security. The adoption of DDS meant some patients would be reluctant to go to the hospital for fear of either being discriminated against or forced into quarantine. Certain groups (older people and children) were thought to be vulnerable to DDS misappropriation.

CONCLUSIONS

These findings indicate the paramount importance of establishing national and international ethical frameworks for DDS implementation. Frameworks should guide all aspects of ID surveillance, addressing privacy protection and health security, and underscored by principles of social equity and accountability.Annals "Online First" article.

Internet search data with spatiotemporal analysis in infectious disease surveillance: Challenges and perspectives

With the rapid development of the internet, the application of internet search data has been seen as a novel data source to offer timely infectious disease surveillance intelligence. Moreover, the advancements in internet search data, which include rich information at both space and time scales, enable investigators to sufficiently consider the spatiotemporal uncertainty, which can benefit researchers to better monitor infectious diseases and epidemics. In the present study, we present the necessary groundwork and critical appraisal of the use of internet search data and spatiotemporal analysis approaches in infectious disease surveillance by updating the current stage of knowledge on them. The study also provides future directions for researchers to investigate the combination of internet search data with the spatiotemporal analysis in infectious disease surveillance. Internet search data demonstrate a promising potential to offer timely epidemic intelligence, which can be seen as the prerequisite for improving infectious disease surveillance.

Protecting privacy in mandatory reporting of infectious diseases during the COVID-19 pandemic: perspectives from a developing country

Mandatory reporting of infectious diseases (MRID) is an essential practice to prevent disease outbreaks. Disease notification is a mandatory procedure for most infectious diseases, even during non-pandemic periods in healthcare. The main rationale behind MRID is the protection of public health. The information and data provided by infectious disease reports are used for many purposes, such as preventing the spread and potential negative impact of infectious diseases, assessing the national and global situation regarding reported diseases, conducting scientific research and planning health policy. In this context, the relevant information benefits public health, health systems and scientific work. Additionally, the follow up and treatment of individuals with infectious diseases is a necessity in certain cases to protect those who cohabit with them. However, these benefits cannot be accepted as unrestricted justifications for MRID, since it is evident that reporting should be conducted within ethical and legal boundaries. MRID should only be devised and implemented with due regard to balancing potential benefits between all individuals, as well as between the individual and the rest of society. Disease notification systems that are not designed with a balancing and harm-reductionist approach may lead to stigmatisation and discrimination. This study aims to investigate the legal framework and ethical issues regarding the reporting of individuals diagnosed with COVID-19 in Turkey-which is a primary example of a developing country.

Knowledge, practices, and patterns of data confidentiality among pharmacists in a developing country

Background

Increased application of electronic health information systems led to the buildup of patient information and facilitated access to this data. Consequently, the confidentiality of this information became an ethical challenge to medical teams' members including pharmacists. However, no study has been conducted to assess pharmacists' knowledge or practices of data confidentiality. Thus, the aim of this study was to assess the current practices and knowledge of pharmacists concerning data confidentiality.

Methods

This was a cross sectional study that included clinical pharmacists in tertiary hospitals and health care centers in Jordan. Data was collected through phone or face to face interviews using a data collection sheet. All continuous data was presented as median ± interquartile range (IQR) and categorical data as frequency (%). One way Chi square was used to check significant differences among categorical groups. Predictors that may affect knowledge and behavior scores were screened using simple linear regression.

Results

A total of 388 pharmacists were interviewed with a mean age of 39.59 ± 8.32 years, with an average experience of 12.55 ± 7.30 years. Pharmacists relied on their personal experience to resolve ethical dilemmas (n = 274, 70.3%), and when they seek advice, their work colleagues (n = 180, 46.4%) %), followed by the head of departments (144 n; 37.1%), were the main source of advice on ethical issues. The overall median knowledge score of pharmacists about data confidentiality was 2.0 out of 5.0 (IQR = 2.0). A considerable percentage of the pharmacists was willing to share information with family members without asking for permission from the patient (n = 98, 25.3%). Pharmacists had a median behavior score of 3.5 out of 4.0 (IQR = 0.4) regarding practices related to data confidentiality, where the majority of them handled medical information from the patient with great confidentiality (304 n, 78.4%), and 85.8% of them (n = 333) gave patient's sexual diseases-related medical information the highest confidentiality. However, based on univariate and multivariate linear regression analysis, none of the examined sociodemographic variables significantly predicted pharmacists' knowledge or behaviors (P > 0.05).

Conclusion

Pharmacists are aware of the importance of confidentiality issues of their patients. However, a number of gaps in their knowledge and practices of data confidentiality were identified. Training that targets these gaps in their knowledge, and rectifies incorrect practices is needed during university education and as part of their continuous medical education.

China's COVID‐19 pandemic response: A first anniversary assessment

The literature on crisis management reports that crises can be critical for organizations, including state and extra‐state actors; they either break down or reinvent themselves. Successful organizations, those that do not break down, use situations of crisis to restructure themselves and improve their performance. Applicable to all crises, this reasoning is also valid for the COVID‐19 pandemic and for government organizations in China. Drawing on documentary analysis, this article examines China's pandemic response from the social–political, technological and psychological perspectives using a holistic crisis management framework. It demonstrates that the Chinese state bureaucracy has assembled, expanded and strengthened its surveillance strategies to strive for comprehensive crisis response.

Crisis management, surveillance, and digital ethics in the COVID‐19 era

In this special issue, we reflect on the global coronavirus disease 2019 (COVID‐19) crisis and the containment measures put in place by formal authorities, combining both theoretically and empirically three different fields of study: crisis management, surveillance studies, and digital ethics. The special issue shows how the intersection of these fields provides a great opportunity to better understand challenges that are of critical importance to today's societies, as well as opening up new avenues for innovation. The focus of this special issue is to unpack and understand the debate on crisis management measures, surveillance, and ethical consequences during the ongoing, enduring COVID‐19 crisis. Building on crisis management literature, surveillance studies, and digital ethics research the articles included in this special issue reflect on issues of governance, space, as well as moral and ethical considerations, which were often overlooked in the public discourse in relation to the COVID‐19 pandemic. The special issue provides a deeper and clearer understanding of intended and unintended ethical and political consequences of crisis management practices, such as a politics of visibility that makes the operation of power invisible and fails to combat inequality, whilst ignoring the potential positive power of digital data and surveillance for empowerment and resilience

Verification of De-Identification Techniques for Personal Information Using Tree-Based Methods with Shapley Values

With the development of big data and cloud computing technologies, the importance of pseudonym information has grown. However, the tools for verifying whether the de-identification methodology is correctly applied to ensure data confidentiality and usability are insufficient. This paper proposes a verification of de-identification techniques for personal healthcare information by considering data confidentiality and usability. Data are generated and preprocessed by considering the actual statistical data, personal information datasets, and de-identification datasets based on medical data to represent the de-identification technique as a numeric dataset. Five tree-based regression models (i.e., decision tree, random forest, gradient boosting machine, extreme gradient boosting, and light gradient boosting machine) are constructed using the de-identification dataset to effectively discover nonlinear relationships between dependent and independent variables in numerical datasets. Then, the most effective model is selected from personal information data in which pseudonym processing is essential for data utilization. The Shapley additive explanation, an explainable artificial intelligence technique, is applied to the most effective model to establish pseudonym processing policies and machine learning to present a machine-learning process that selects an appropriate de-identification methodology.

Challenges in the development of digital public health interventions and mapped solutions: Findings from a scoping review

Background

“Digital public health” has emerged from an interest in integrating digital technologies into public health. However, significant challenges which limit the scale and extent of this digital integration in various public health domains have been described. We summarized the literature about these challenges and identified strategies to overcome them.

Methods

We adopted Arksey and O’Malley's framework (2005) integrating adaptations by Levac et al. (2010). OVID Medline, Embase, Google Scholar, and 14 government and intergovernmental agency websites were searched using terms related to “digital” and “public health.” We included conceptual and explicit descriptions of digital technologies in public health published in English between 2000 and June 2020. We excluded primary research articles about digital health interventions. Data were extracted using a codebook created using the European Public Health Association's conceptual framework for digital public health.

Results and analysis

Overall, 163 publications were included from 6953 retrieved articles with the majority (64%, n = 105) published between 2015 and June 2020. Nontechnical challenges to digital integration in public health concerned ethics, policy and governance, health equity, resource gaps, and quality of evidence. Technical challenges included fragmented and unsustainable systems, lack of clear standards, unreliability of available data, infrastructure gaps, and workforce capacity gaps. Identified strategies included securing political commitment, intersectoral collaboration, economic investments, standardized ethical, legal, and regulatory frameworks, adaptive research and evaluation, health workforce capacity building, and transparent communication and public engagement.

Conclusion

Developing and implementing digital public health interventions requires efforts that leverage identified strategies to overcome diverse challenges encountered in integrating digital technologies in public health.

'Personal Health Surveillance': The Use of mHealth in Healthcare Responsibilisation

There is an ongoing increase in the use of mobile health (mHealth) technologies that patients can use to monitor health-related outcomes and behaviours. While the dominant narrative around mHealth focuses on patient empowerment, there is potential for mHealth to fit into a growing push for patients to take personal responsibility for their health. I call the first of these uses 'medical monitoring', and the second 'personal health surveillance'. After outlining two problems which the use of mHealth might seem to enable us to overcome-fairness of burdens and reliance on self-reporting-I note that these problems would only really be solved by unacceptably comprehensive forms of personal health surveillance which applies to all of us at all times. A more plausible model is to use personal health surveillance as a last resort for patients who would otherwise independently qualify for responsibility-based penalties. However, I note that there are still a number of ethical and practical problems that such a policy would need to overcome. The prospects of mHealth enabling a fair, genuinely cost-saving policy of patient responsibility are slim.

Ethics, Integrity, and Retributions of Digital Detection Surveillance Systems for Infectious Diseases: Systematic Literature Review

Background

The COVID-19 pandemic has increased the importance of the deployment of digital detection surveillance systems to support early warning and monitoring of infectious diseases. These opportunities create a “double-edge sword,” as the ethical governance of such approaches often lags behind technological achievements.

Objective

The aim was to investigate ethical issues identified from utilizing artificial intelligence–augmented surveillance or early warning systems to monitor and detect common or novel infectious disease outbreaks.

Methods

In a number of databases, we searched relevant articles that addressed ethical issues of using artificial intelligence, digital surveillance systems, early warning systems, and/or big data analytics technology for detecting, monitoring, or tracing infectious diseases according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, and further identified and analyzed them with a theoretical framework.

Results

This systematic review identified 29 articles presented in 6 major themes clustered under individual, organizational, and societal levels, including awareness of implementing digital surveillance, digital integrity, trust, privacy and confidentiality, civil rights, and governance. While these measures were understandable during a pandemic, the public had concerns about receiving inadequate information; unclear governance frameworks; and lack of privacy protection, data integrity, and autonomy when utilizing infectious disease digital surveillance. The barriers to engagement could widen existing health care disparities or digital divides by underrepresenting vulnerable and at-risk populations, and patients’ highly sensitive data, such as their movements and contacts, could be exposed to outside sources, impinging significantly upon basic human and civil rights.

Conclusions

Our findings inform ethical considerations for service delivery models for medical practitioners and policymakers involved in the use of digital surveillance for infectious disease spread, and provide a basis for a global governance structure.

Trial Registration

PROSPERO CRD42021259180; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=259180

Data and Digital Solutions to Support Surveillance Strategies in the Context of the COVID-19 Pandemic

Background: In order to prevent spread and improve control of infectious diseases, public health experts need to closely monitor human and animal populations. Infectious disease surveillance is an established, routine data collection process essential for early warning, rapid response, and disease control. The quantity of data potentially useful for early warning and surveillance has increased exponentially due to social media and other big data streams. Digital epidemiology is a novel discipline that includes harvesting, analysing, and interpreting data that were not initially collected for healthcare needs to enhance traditional surveillance. During the current COVID-19 pandemic, the importance of digital epidemiology complementing traditional public health approaches has been highlighted. Objective: The aim of this paper is to provide a comprehensive overview for the application of data and digital solutions to support surveillance strategies and draw implications for surveillance in the context of the COVID-19 pandemic and beyond. Methods: A search was conducted in PubMed databases. Articles published between January 2005 and May 2020 on the use of digital solutions to support surveillance strategies in pandemic settings and health emergencies were evaluated. Results: In this paper, we provide a comprehensive overview of digital epidemiology, available data sources, and components of 21st-century digital surveillance, early warning and response, outbreak management and control, and digital interventions. Conclusions: Our main purpose was to highlight the plausible use of new surveillance strategies, with implications for the COVID-19 pandemic strategies and then to identify opportunities and challenges for the successful development and implementation of digital solutions during non-emergency times of routine surveillance, with readiness for early-warning and response for future pandemics. The enhancement of traditional surveillance systems with novel digital surveillance methods opens a direction for the most effective framework for preparedness and response to future pandemics.

Changes in public preferences for technologically enhanced surveillance following the COVID-19 pandemic: a discrete choice experiment

OBJECTIVES

As governments attempt to navigate a path out of COVID-19 restrictions, robust evidence is essential to inform requirements for public acceptance of technologically enhanced communicable disease surveillance systems. We examined the value of core surveillance system attributes to the Australian public, before and during the early stages of the current pandemic.

DESIGN

A discrete choice experiment was conducted in Australia with a representative group of respondents, before and after the WHO declared COVID-19 a Public Health Emergency of International Concern. We identified and investigated the relative importance of seven attributes associated with technologically enhanced disease surveillance: respect for personal autonomy; privacy/confidentiality; data certainty/confidence; data security; infectious disease mortality prevention; infectious disease morbidity prevention; and attribution of (causal) responsibility. Specifically, we explored how the onset of the COVID-19 outbreak influenced participant responses.

SETTING AND PARTICIPANTS

2008 Australians (general public) completed the experiment: 793 before COVID-19 outbreak onset (mean age 45.9 years, 50.2% male) and 1215 after onset (mean age 47.2 years, 49% male).

RESULTS

All seven attributes significantly influenced respondents' preferences for communicable disease surveillance systems. After onset, participants demonstrated greater preference for a surveillance system that could prevent a higher number of illnesses and deaths, and were less concerned about their personal autonomy. However, they also increased their preference for a system with high data security.

CONCLUSIONS

Public acceptance of technology-based communicable disease surveillance is situation dependent. During an epidemic, there is likely to be greater tolerance of technologically enhanced disease surveillance systems that result in restrictions on personal activity if such systems can prevent high morbidity and mortality. However, this acceptance of lower personal autonomy comes with an increased requirement to ensure data security. These findings merit further research as the pandemic unfolds and strategies are put in place that enable individuals and societies to live with SARS-CoV-2 endemicity.

Balancing Personal Privacy and Public Safety During COVID-19: The Case of South Korea

There has been vigorous debate on how different countries responded to the COVID-19 pandemic. To secure public safety, South Korea actively used personal information at the risk of personal privacy whereas France encouraged voluntary cooperation at the risk of public safety. In this article, after a brief comparison of contextual differences with France, we focus on South Korea's approaches to epidemiological investigations. To evaluate the issues pertaining to personal privacy and public health, we examine the usage patterns of original data, de-identification data, and encrypted data. Our specific proposal discusses the COVID index, which considers collective infection, outbreak intensity, availability of medical infrastructure, and the death rate. Finally, we summarize the findings and lessons for future research and the policy implications.

In defence of digital contact-tracing: human rights, South Korea and Covid-19

Purpose

The media has even been very critical of some East Asian countries’ use of digital contact-tracing to control Covid-19. For example, South Korea has been criticised for its use of privacy-infringing digital contact-tracing. However, whether their type of digital contact-tracing was unnecessarily harmful to the human rights of Korean citizens is open for debate. The purpose of this paper is to examine this criticism to see if Korea’s digital contact-tracing is ethically justifiable.

Design/methodology/approach

This paper will evaluate Korea’s digital contact-tracing through the lens of the four human rights principles to determine if their response is ethically justifiable. These four principles were originally outlined in the European Court of Human Rights, namely, necessary, proportional, scientifically valid and time-bounded (European Court of Human Rights 1950).

Findings

The paper will propose that while the use of Korea’s digital contact-tracing was scientifically valid and proportionate (albeit, in need for improvements), it meets the necessity requirement, but is too vague to meet the time-boundedness requirement.

Originality/value

The Covid-19 pandemic has proven to be one of the worst threats to human health and the global economy in the past century. There have been many different strategies to tackle the pandemic, from somewhat laissez-faire approaches, herd immunity, to strict draconian measures. Analysis of the approaches taken in the response to the pandemic is of high scientific value and this paper is one of the first to critically engage with one of these methods – digital contact-tracing in South Korea.

The Perfect Moral Storm: Diverse Ethical Considerations in the COVID-19 Pandemic

The COVID-19 pandemic has both exposed and created deep rifts in society. It has thrust us into deep ethical thinking to help justify the difficult decisions many will be called upon to make and to protect from decisions that lack ethical underpinnings. This paper aims to highlight ethical issues in six different areas of life highlighting the enormity of the task we are faced with globally. In the context of COVID-19, we consider health inequity, dilemmas in triage and allocation of scarce resources, ethical issues associated with research, ethical considerations relating to tracing apps, and exit strategies such as immunity passports and COVID-19 vaccines. Finally, we consider environmental issues in light of COVID-19. The paper also offers some ethical reflection on these areas as many parts of the world contemplate the recovery phase.

Community perspectives on the benefits and risks of technologically enhanced communicable disease surveillance systems: a report on four community juries

Background

Outbreaks of infectious disease cause serious and costly health and social problems. Two new technologies – pathogen whole genome sequencing (WGS) and Big Data analytics – promise to improve our capacity to detect and control outbreaks earlier, saving lives and resources. However, routinely using these technologies to capture more detailed and specific personal information could be perceived as intrusive and a threat to privacy.

Method

Four community juries were convened in two demographically different Sydney municipalities and two regional cities in New South Wales, Australia (western Sydney, Wollongong, Tamworth, eastern Sydney) to elicit the views of well-informed community members on the acceptability and legitimacy of:

making pathogen WGS and linked administrative data available for public health research

using this information in concert with data linkage and machine learning to enhance communicable disease surveillance systems

Fifty participants of diverse backgrounds, mixed genders and ages were recruited by random-digit-dialling and topic-blinded social-media advertising. Each jury was presented with balanced factual evidence supporting different expert perspectives on the potential benefits and costs of technologically enhanced public health research and communicable disease surveillance and given the opportunity to question experts.

Results

Almost all jurors supported data linkage and WGS on routinely collected patient isolates for the purposes of public health research, provided standard de-identification practices were applied. However, allowing this information to be operationalised as a syndromic surveillance system was highly contentious with three juries voting in favour, and one against by narrow margins. For those in favour, support depended on several conditions related to system oversight and security being met. Those against were concerned about loss of privacy and did not trust Australian governments to run secure and effective systems.

Conclusions

Participants across all four events strongly supported the introduction of data linkage and pathogenomics to public health research under current research governance structures. Combining pathogen WGS with event-based data surveillance systems, however, is likely to be controversial because of a lack of public trust, even when the potential public health benefits are clear. Any suggestion of private sector involvement or commercialisation of WGS or surveillance data was unanimously rejected.

Healthcare Digitalization and Pay-For-Performance Incentives in Smart Hospital Project Financing

This study aims to explore the impact of healthcare digitalization on smart hospital project financing (PF) fostered by pay-for-performance (P4P) incentives. Digital platforms are a technology-enabled business model that facilitates exchanges between interacting agents. They represent a bridging link among disconnected nodes, improving the scalable value of networks. Application to healthcare public-private partnerships (PPPs) is significant due to the consistency of digital platforms with health issues and the complexity of the stakeholder's interaction. In infrastructural PPPs, public and private players cooperate, usually following PF patterns. This relationship is complemented by digitized supply chains and is increasingly patient-centric. This paper reviews the literature, analyzes some supply chain bottlenecks, addresses solutions concerning the networking effects of platforms to improve PPP interactions, and investigates the cost-benefit analysis of digital health with an empirical case. Whereas diagnostic or infrastructural technology is an expensive investment with long-term payback, leapfrogging digital applications reduce contingent costs. "Digital" savings can be shared by key stakeholders with P4P schemes, incentivizing value co-creation patterns. Efficient sharing may apply network theory to a comprehensive PPP ecosystem where stakeholding nodes are digitally connected. This innovative approach improves stakeholder relationships, which are re-engineered around digital platforms that enhance patient-centered satisfaction and sustainability. Digital technologies are useful even for infectious disease surveillance, like that of the coronavirus pandemic, for supporting massive healthcare intervention, decongesting hospitals, and providing timely big data.