Community engagement in the prevention and control of COVID-19: Insights from Vietnam.

INTRODUCTION: Community engagement (CE) is an effective public health strategy for improving health outcomes. There is limited published knowledge about effective approaches to CE in ensuring effective responses to COVID-19 throughout lockdowns, travel restrictions and social distancing. In this paper, we contribute to bridging this gap by highlighting experience of CE in Vietnam, specifically focusing on migrant workers in Vietnam. METHODS: A cross-sectional qualitative study design was used with qualitative data collection was carried out during August-October 2020. Two districts were purposefully selected from two large industrial zones. Data was collected using in-depth interviews (n = 36) with individuals and households, migrants and owners of dormitories, industrial zone factory representatives, community representatives and health authorities. Data was analyzed using thematic analysis approach. The study received ethics approval from the Hanoi University Institutional Review Board. RESULTS: The government's response to COVID-19 was spearheaded by the multi-sectoral National Steering Committee for the Prevention and Control of COVID-19, chaired by the Vice Prime Minister and comprised different members from 23 ministries. This structure was replicated throughout the province and local levels and all public and private organizations. Different activities were carried out by local communities, following four key principles of infection control: early detection, isolation, quarantine and hospitalization. We found three key determinants of engagement of migrant workers with COVID-19 prevention and control: availability of resources, appropriate capacity strengthening, transparent and continuous communication and a sense of trust in government legitimacy. DISCUSSION AND CONCLUSION: Our results support the current literature on CE in infection control which highlights the importance of context and suggests that future CE should consider five key components: multi-sectoral collaboration with a whole-of-community approach to strengthen governance structures with context-specific partnerships; mobilization of resources and decentralization of decision making to encourage self-reliance and building of local capacity; capacity building through training and supervision to local institutions; transparent and clear communication of health risks and sensitization of local communities to improve compliance and foster trust in the government measures; and understanding the urgent needs ensuring of social security and engaging all parts of the community, specifically the vulnerable groups.

A Literature Review on the GDPR, COVID-19 and the Ethical Considerations of Data Protection During a Time of Crisis.

OBJECTIVE: This survey article presents a literature review of relevant publications aiming to explore whether the EU's General Data Protection Regulation (GDPR) has held true during a time of crisis and the implications that arose during the COVID-19 outbreak. METHOD AND RESULTS: Based on the approach taken and the screening of the relevant articles, the results focus on three themes: a critique on GDPR; the ethics surrounding the use of digital health technologies, namely in the form of mobile applications; and the possibility of cross border transfers of said data outside of Europe. Within this context, the article reviews the arising themes, considers the use of data through mobile health applications, and discusses whether data protection may require a revision when balancing societal and personal interests. CONCLUSIONS: In summary, although it is clear that the GDPR has been applied through a mixed and complex experience with data handling during the pandemic, the COVID-19 pandemic has indeed shown that it was a test the GDPR was designed and prepared to undertake. The article suggests that further review and research is needed to first ensure that an understanding of the state of the art in data protection during the pandemic is maintained and second to subsequently explore and carefully create a specific framework for the ethical considerations involved. The paper echoes the literature reviewed and calls for the creation of a unified and harmonised network or database to enable the secure data sharing across borders.

Use of public datasets in the examination of multimorbidity: Opportunities and challenges.

The interrogation of established, large-scale datasets presents great opportunities in health data science for the linkage and mining of potentially disparate resources to create new knowledge in a fast and cost-efficient manner. The number of datasets that can be queried in the field of multimorbidity is vast, ranging from national administrative and audit datasets, large clinical, technical and biological cohorts, through to more bespoke data collections made available by individual organisations and laboratories. However, with these opportunities also come technical and regulatory challenges that require an informed approach. In this review, we outline the potential benefits of using previously collected data as a vehicle for research activity. We illustrate the added value of combining potentially disparate datasets to find answers to novel questions in the field. We focus on the legal, governance and logistical considerations required to hold and analyse data acquired from disparate sources and outline some of the solutions to these challenges. We discuss the infrastructure resources required and the essential considerations in data curation and informatics management, and briefly discuss some of the analysis approaches currently used.

Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study.

BACKGROUND: Large-scale cancer epidemiology cohorts (CEC) have successfully collected, analyzed, and shared patient-reported data for years. CECs increasingly need to make their data more findable, accessible, interoperable, and reusable, or FAIR. How CECs should approach this transformation is unclear. METHODS: The California Teachers Study (CTS) is an observational CEC of 133,477 participants followed since 1995-1996. In 2014, we began updating our data storage, management, analysis, and sharing strategy. With the San Diego Supercomputer Center, we deployed a new infrastructure based on a data warehouse to integrate and manage data and a secure and shared workspace with documentation, software, and analytic tools that facilitate collaboration and accelerate analyses. RESULTS: Our new CTS infrastructure includes a data warehouse and data marts, which are focused subsets from the data warehouse designed for efficiency. The secure CTS workspace utilizes a remote desktop service that operates within a Health Insurance Portability and Accountability Act (HIPAA)- and Federal Information Security Management Act (FISMA)-compliant platform. Our infrastructure offers broad access to CTS data, includes statistical analysis and data visualization software and tools, flexibly manages other key data activities (e.g., cleaning, updates, and data sharing), and will continue to evolve to advance FAIR principles. CONCLUSIONS: Our scalable infrastructure provides the security, authorization, data model, metadata, and analytic tools needed to manage, share, and analyze CTS data in ways that are consistent with the NCI's Cancer Research Data Commons Framework. IMPACT: The CTS's implementation of new infrastructure in an ongoing CEC demonstrates how population sciences can explore and embrace new cloud-based and analytics infrastructure to accelerate cancer research and translation.See all articles in this CEBP Focus section, "Modernizing Population Science."

The Firearms Data Gap.

The firearms data infrastructure in the United States is severely limited in scope and fragmented in nature. Improved data systems are needed in order to address gun violence and promote productive conversation about gun policy. In the absence of federal leadership in firearms data systems improvement, motivated states may take proactive steps to stitch gaps in data systems. We propose that states evaluate the gaps in their systems, expand data collection, and improve data presentation and availability.

Process trumps potential public good: better vaccine safety through linked cross-jurisdictional immunisation data in Australia.

OBJECTIVE: To provide insights into complexities of seeking access to state and federal cross-jurisdictional data for linkage with the Australian Childhood Immunisation Register (ACIR). We provide recommendations for improving access and receipt of linked datasets involving Australian Government-administered data. METHODS: We describe requirements for linking eleven federal and state data sources to establish a national linked dataset for safety evaluation of vaccines. The required data linkage methodology for integrating cross-jurisdictional data sources is also described. RESULTS: Extensive negotiation was required with 18 different agencies for 21 separate authorisations and 12 ethics approvals. Three variations of the 'best practice' linkage model were implemented. Australian Government approval requests spanned nearly four years from initial request for data, with a further year before ACIR data transfer to the linkage agency. CONCLUSIONS: Integration of immunisation registers with other data collections is achievable in Australia but infeasible for routine and rapid identification of vaccine safety concerns. Lengthy authorisation requirements, convoluted disparate application processes and inconsistencies in data supplied all contribute to delayed data availability. Implications for public health: Delayed data access for safety surveillance prevents timely epidemiological reviews. Poor responsiveness to safety concerns may erode public confidence, compromising effectiveness of vaccination programs through reduced participation.

Completeness of death registration in the Civil Registration System, India (2005 to 2015).

Background & objectives: In many developing countries including India, the civil registration data are incomplete, inadequate and not timely, therefore, compromising the usefulness of these data. The completeness of registration of death (CoRD) in the Indian Civil Registration System (CRS) was assessed from 2005 to 2015 at State level to understand its current status and trends over time and also to identify gaps in data to improve CRS data quality. Methods: CoRD for each year for each State was calculated from the CRS reports for 2005-2015. Data were analyzed nationally by geographic region and individual State. The availability of CoRD by age group and sex was also reported. Results: About 40 per cent increase in CoRD was documented for India between 2005 and 2015, with CoRD of 76.6 per cent in 2015. CoRD was >90 per cent in the western and southern regions and the eastern, central and northeastern regions had CoRD lower than the Indian average in 2015. Among the 29 States, 16 (55.2%) State had CoRD >80 per cent and five (17.2%) <50 per cent and 10 States recorded 100 per cent CoRD. Despite the highest per cent increase during 2005-2015 (108.5%), CoRD in Uttar Pradesh was 44.2 per cent in 2015. Varying levels of progress in 2015 were seen between the State with similar CoRD estimates in 2015. Nagaland (-63.3%), Manipur (-33.1%) and Tripura (-30.3%) were the only States that documented a decrease in CoRD during 2005-2015. The age non-availability for India ranged from 37.0 per cent in 2009 to 37.9 per cent in 2015, an average of 41.5 per cent over the seven years and was an average of 35.6 and 36.6 per cent for males and females, respectively. Age was available for all registered deaths only in five (17.2%) of the 29 States in 2009 and four (13.8%) in 2015. Sex non-availability for the recorded deaths was much lower as compared with that for age. Interpretation & conclusions: Despite the significant progress made in CoRD in India, critical differences between the States within the CRS remain, with poor availability of reporting by age and sex. Concentrated efforts to assess the strengths and weaknesses at the State level of the CRS processes, quality of data and plausibility of information generated are needed in India.

Early Access to Medicines Scheme: real-world data collection.

Real-world data (RWD) generated during the pre-approval phase could be supplementary to primary clinical trial outcomes; however, as we discuss here, a data collection framework is needed to ensure the validity and applicability of these data.

Participatory governance over research in an academic research network: the case of Diabetes Action Canada.

Digital data generated in the course of clinical care are increasingly being leveraged for a wide range of secondary purposes. Researchers need to develop governance policies that can assure the public that their information is being used responsibly. Our aim was to develop a generalisable model for governance of research emanating from health data repositories that will invoke the trust of the patients and the healthcare professionals whose data are being accessed for health research. We developed our governance principles and processes through literature review and iterative consultation with key actors in the research network including: a data governance working group, the lead investigators and patient advisors. We then recruited persons to participate in the governing and advisory bodies. Our governance process is informed by eight principles: (1) transparency; (2) accountability; (3) follow rule of law; (4) integrity; (5) participation and inclusiveness; (6) impartiality and independence; (7) effectiveness, efficiency and responsiveness and (8) reflexivity and continuous quality improvement. We describe the rationale for these principles, as well as their connections to the subsequent policies and procedures we developed. We then describe the function of the Research Governing Committee, the majority of whom are either persons living with diabetes or physicians whose data are being used, and the patient and data provider advisory groups with whom they consult and communicate. In conclusion, we have developed a values-based information governance framework and process for Diabetes Action Canada that adds value over-and-above existing scientific and ethics review processes by adding a strong patient perspective and contextual integrity. This model is adaptable to other secure data repositories.

Limitations for health research with restricted data collection from UK primary care.

PURPOSE: UK primary care provides a rich data source for research. The impact of proposed data collection restrictions is unknown. This study aimed to assess the impact of restricting the scope of electronic health record (EHR) data collection on the ability to conduct research. The study estimated the consequences of restricted data collection on published Clinical Practice Research Datalink studies from high impact journals or referenced in clinical guidelines. METHODS: A structured form was used to systematically analyse the extent to which individual studies would have been possible using a database with data collection restrictions in place: (1) retrospective collection of specified diseases only; (2) retrospective collection restricted to a 6- or 12-year period; (3) prospective and retrospective collection restricted to non-sensitive data. Outcomes were categorised as unfeasible (not reproducible without major bias); compromised (feasible with design modification); or unaffected. RESULTS: Overall, 91% studies were compromised with all restrictions in place; 56% studies were unfeasible even with design modification. With restrictions on diseases alone, 74% studies were compromised; 51% were unfeasible. Restricting collection to 6/12 years had a major impact, with 67 and 22% of studies compromised, respectively. Restricting collection of sensitive data had a lesser but marked impact with 10% studies compromised. CONCLUSION: EHR data collection restrictions can profoundly reduce the capacity for public health research that underpins evidence-based medicine and clinical guidance. National initiatives seeking to collect EHRs should consider the implications of restricting data collection on the ability to address vital public health questions.

Data Governance and Stewardship.

School nurses collect, manage, and report on school health data, which is covered by student privacy laws. School nurses and other district employees who collect and manage sensitive data must understand their responsibilities throughout the data life cycle. Nurses must identify who is accountable for data governance in their school and the process for influencing data governance policies and procedures. Every school district is accountable for the integrity and the security of the data it collects about students, families, and staff. Data governance encompasses all decisions about data throughout the data life cycle from defining what data are needed, to collecting, storing, protecting, using, sharing, and retiring and destroying data and who is accountable for those decisions. The data governance in schools is prescribed by the U.S. Department of Education, state education departments, and local school districts. The Student Privacy Policy Office at the U.S. Department of Education publishes clear and precise guidance on the treatment of data collected in schools.

The Dark Data Quandary.

The digital universe remains a black box. Despite attaining high-technology capabilities like artificial intelligence and cognitive computing, "Big Data" analytics have failed to keep pace with surging data production. At the same time, the falling costs of cloud storage and distributed systems have made mass data storage cheaper and more accessible. These effects have produced a chasm between data that is stored and data that can be readily analyzed and understood. Enticed by the promise of extracting future value from rising data stockpiles, organizations now retain massive quantities of data that they cannot presently know or effectively manage. This rising sea of "dark data" now represents the vast majority of the digital universe. Dark data presents a quandary for organizations and the judicial system. For organizations, the inability to know the contents of retained dark data produces invisible risk under a spreading patchwork of digital privacy and data governance laws, most notably in the medical and consumer protection areas. For courts increasingly confronted with Big Data-derived evidence, dark data may shield critical information from judicial view while embedding subjective influences within seemingly objective methods. To avoid obscuring organizational risk and producing erroneous outcomes in the courtroom, decision-makers must achieve a new awareness of dark data's presence and its ability to undermine Big Data's vaunted advantages.

Using Drones to Study Human Beings: Ethical and Regulatory Issues.

Researchers have used drones to track wildlife populations, monitor forest fires, map glaciers, and measure air pollution but have only begun to consider how to use these unmanned aerial vehicles to study human beings. The potential use of drones to study public gatherings or other human activities raises novel issues of privacy, confidentiality, and consent, which this article explores in depth. It argues that drone research could fall into several different categories: non-human subjects research (HSR), exempt HSR, or non-exempt HSR. In the case of non-exempt HSR, it will be difficult for institutional review boards to approve studies unless they are designed so that informed consent can be waived. Whether drone research is non-HSR, exempt HSR, or non-exempt HSR, it is important for investigators to consult communities which could be affected by the research.