scholarly journals The Emergence and Future of Public Health Data Science

2021 ◽  
Vol 42 ◽  
Author(s):  
Jeff Goldsmith ◽  
Yifei Sun ◽  
Linda P. Fried ◽  
Jeannette Wing ◽  
Gary W. Miller ◽  
...  
Keyword(s):  
Public Health ◽  
Health Research ◽  
Data Science ◽  
Public Health Research ◽  
Health Data ◽  
Science Methods ◽  
Critical Component ◽  
Public Health Perspective ◽  
Public Health Data ◽  
Term Data

Data science is a newly‐formed and, as yet, loosely‐defined discipline that has nonetheless emerged as a critical component of successful scientific research. We seek to provide an understanding of the term “data science,” particularly as it relates to public health; to identify ways that data science methods can strengthen public health research; to propose ways to strengthen education for public health data science; and to discuss issues in data science that may benefit from a public health perspective.

Framing Public Health Research Ethics

2019 ◽  
pp. 330-341
Author(s):  
Holly A. Taylor
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Research Ethics ◽  
Health Research ◽  
Public Health Research ◽  
Health Data ◽  
Respect For Persons ◽  
Ethical Implications ◽  
Public Health Data ◽  
Systematic Collection

The systematic collection and analysis of data is central to public health. Some public health activities are easily classified as either research or nonresearch, while the distinction is more nuanced for other activities. How an activity gets classified has ethical implications—additional oversight, requirements for consent of participants, and potentially whether the activity can be undertaken at all. Scholarly analysis of this issue suggests that an important aspect distinguishing research from other public health data collection activities is to consider the intent of the activity and whether experimentation is involved. The three ethical principles of respect for persons, beneficence, and (distributive) justice guide researchers in their relationships with individual participants. Because public health research can be directed at an entire community, this chapter posits that these three principles must be extended to appropriately include and consider the community as a stakeholder.

An Overview of Ethics and Public Health Data Collection

2019 ◽  
pp. 313-319
Author(s):  
Holly A. Taylor
Keyword(s):  
Public Health ◽  
Data Collection ◽  
Health Research ◽  
Public Health Practice ◽  
Community Based Participatory Research ◽  
Public Health Research ◽  
Health Data ◽  
Community Based ◽  
Public Health Data ◽  
Research Questions

Collection of data is essential to the practice of public health. This chapter provides a brief introduction to ethics and public health data collection, as well as an overview of chapters in the related section of The Oxford Handbook on Public Health Ethics. A key ethics challenge has been, and will remain, how best to balance the health of the community with the respect owed to individual citizens. The four chapters in this section examine various aspects of those ethics challenges, including those related to the scope of public health surveillance activities, the distinction between public health practice and public health research, community-based participatory research (CBPR), and the use of big data to answer public health research questions.

scholarly journals Factors Related to Personal Health Data Sharing: Data Usefulness, Sensitivity and Anonymity

2021 ◽  
Author(s):  
Samar Helou ◽  
Victoria Abou-Khalil ◽  
Elie El Helou ◽  
Ken Kiyono
Keyword(s):  
Public Health ◽  
Data Sharing ◽  
Health Research ◽  
Online Survey ◽  
Public Health Research ◽  
Health Data ◽  
Perceived Usefulness ◽  
Personal Health ◽  
Sociodemographic Characteristics ◽  
Region Of Residence

Using an online survey, we examined the relationships between the perceived usefulness, sensitivity, and anonymity of personal health data and people’s willingness to share it with researchers. An analysis of 112 responses showed that people’s willingness and perceptions are related to the type of the data, their trust in the data’s anonymity, and their personal sociodemographic characteristics. In general, we found that people do not completely trust that their identities remain anonymous when sharing data anonymously with researchers. We also found that they are more willing to share personal health data with researchers if they perceive it as useful for public health research, not sensitive, and if they trust that their identity will remain anonymous after sharing it. We also found that people’s age, gender, occupation, and region of residence may be related to their perceptions regarding the sharing of personal health data.

scholarly journals Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science

2020 ◽  
Vol 29 (01) ◽  
pp. 231-234
Author(s):  
Sébastien Cossin ◽  
Rodolphe Thiébaut ◽  
Keyword(s):  
Public Health ◽  
Rural Communities ◽  
Low Income ◽  
Disease Surveillance ◽  
Data Science ◽  
Health Data ◽  
Low Income Countries ◽  
Editorial Committee ◽  
Disease Surveillance System ◽  
Public Health Data

Objectives: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics. Methods: PubMed searches of 2019 literature concerning public health and epidemiology informatics were conducted and the returned references were reviewed by the two section editors to select 14 candidate best papers. These papers were then peer-reviewed by external reviewers to allow the Editorial Committee a curated selection of the best papers. Results: Among the 835 references retrieved from PubMed, two were finally selected as best papers. The first best paper leverages satellite images and deep learning to identify remote rural communities in low-income countries; the second paper describes the development of a worldwide human disease surveillance system based on near real-time news data from the GDELT project. Internet data and electronic health records are still widely used to detect and monitor disease activity. Identifying and targeting specific audiences for public health interventions is a growing subject of interest. Conclusions: The ever-increasing amount of data available offers endless opportunities to develop methods and tools that could assist public health surveillance and intervention belonging to the growing field of public health Data Science. The transition from proofs of concept to real world applications and adoption by health authorities remains a difficult leap to make.

How to Draft Successful Memorandums of Understanding and Data-Sharing Agreements

2019 ◽  
pp. 191-204
Author(s):  
Matthew Penn ◽  
Rachel Hulkower
Keyword(s):  
Public Health ◽  
Health Care ◽  
Health System ◽  
Data Sharing ◽  
Data Use ◽  
Health Data ◽  
Critical Component ◽  
The Public ◽  
Goods And Services ◽  
Public Health Data

This chapter offers tips on crafting data-sharing agreements. Improving and increasing cross-sector collaboration in public health can be facilitated through the use of a memorandum of understanding (MOU). The chapter looks at the benefits of MOUs, and also drawbacks. It provides some case studies of successful MOUs. Cross-sector collaboration is an increasingly critical component of the public health system, the chapter concludes. Community partnerships can involve complex arrangements, with reciprocal promises to exchange goods and services, and MOUs can help organizations negotiate, organize, and maintain those relationships. For partnerships that need health care or public health data to function, a data use agreements (DUA) can provide a mechanism to define the data needed and the parameters around the intended release and use of the data.

scholarly journals Workshop: Cohorts: coordinated tools for decision support

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
Keyword(s):  
Public Health ◽  
Decision Support ◽  
Health Research ◽  
Policy Decision ◽  
Public Health Research ◽  
Care Patient ◽  
Health Data ◽  
Healthcare Intervention ◽  
Health Events ◽  
The Impact

Abstract Longitudinal cohorts, by allowing to follow over the time a group of persons with common characteristics to identify the occurrence of health events, have proven to be very valuable instruments in medical and public health research. For instance, it is possible to investigate links between exposures (demographic, biological, behavioral, environmental, or genetic) and the occurrence of observed health events. And indeed the applications of the cohorts are multiple: besides public health research (links between risk factors or exposures and disease, health effects of unusual or still unknown exposures), it is possible, for example, to investigate the impact of a therapeutic strategy or complex healthcare intervention on the population status. Therefore, observations resulting from cohort studies are now often at the heart of public policy decision-making. In addition, health-data collections are increasingly broad in our societies (data from research, care, patient communities, or using personal initiatives such as smartphone applications and connected objects) and heterogeneous (genomic, physiological, biological, clinical, social and environmental). However, the efficiency of these epidemiological studies is limited by many factors, while resources required to develop them are very important. The lack of knowledge of the European landscape, the lack of harmonization of practices or governance or the lack of communication between various stakeholders, have an impact on the strategy to adopt. It would be essential to consider procedures to optimize resources, harmonize methodologies and coordination between structures, in such a context where epidemiological expertise is sometimes scarce and under-resourced. Furthermore, possibilities of international cross-cohorts linkages and collaborations could allow for unique and fruitful research opportunities, impossible to achieve in the setting of a stand-alone cohort. During this workshop, we propose to present different European initiatives and coordination models, but also to highlight collaborations between these cohorts. This brainstorming would allow us 1) to expose methodologies and best practices, which are developed by the various stakeholders; 2) to identify common or transposable procedures in order to participate in sustainable European strategy and at last, to address the challenges of developing future cohorts and using personal health data. For this purpose, four speakers will present the French landscape developed over the past ten years and three models of cohort coordination and data mining in Europe: the French cohort Constances, the Swedish consortium Cohorts.se and the German National Cohort. Each participant will speak for 15 minutes. Then the chairperson will lead the workshop’s joint discussion with the four speakers and the audience. Key messages cohorts are one of the reference instruments for epidemiological and public health research, and represent a significant advantage in decision support. efforts are need to improve the coordination of these cohorts, both nationally and internationally, to sustain these expensive instruments and foster the development of international collaborations.

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