Ethical issues in public health surveillance: a systematic qualitative review

Klingler, Corinna; Silva, Diego S.; Schuermann, Christopher; Reis, Andreas; Saxena, Abha; Strech, Daniel

doi:10.1186/s12889-017-4200-4

Cited by 60 publications

(52 citation statements)

References 37 publications

(44 reference statements)

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“…The implementation of a digital infectious disease detection system based on self-recorded data poses serious challenges that require special attention, such as user privacy and security, data confidentiality, user acceptance, and motivations [ 26 , 101 ], especially during data collection, transmission, and data storage [ 102 , 103 ]. Personal health–related data are sensitive, and the data collection, transmission, and data storage procedure need to follow the standards and regulations provided by the major governing bodies, such as General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) [ 104 , 105 ].…”

Section: Discussionmentioning

confidence: 99%

Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System

Woldaregay¹,

Launonen²,

Årsand³

et al. 2020

J Med Internet Res

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Background Type 1 diabetes is a chronic condition of blood glucose metabolic disorder caused by a lack of insulin secretion from pancreas cells. In people with type 1 diabetes, hyperglycemia often occurs upon infection incidences. Despite the fact that patients increasingly gather data about themselves, there are no solid findings that uncover the effect of infection incidences on key parameters of blood glucose dynamics to support the effort toward developing a digital infectious disease detection system. Objective The study aims to retrospectively analyze the effect of infection incidence and pinpoint optimal parameters that can effectively be used as input variables for developing an infection detection algorithm and to provide a general framework regarding how a digital infectious disease detection system can be designed and developed using self-recorded data from people with type 1 diabetes as a secondary source of information. Methods We retrospectively analyzed high precision self-recorded data of 10 patient-years captured within the longitudinal records of three people with type 1 diabetes. Obtaining such a rich and large data set from a large number of participants is extremely expensive and difficult to acquire, if not impossible. The data set incorporates blood glucose, insulin, carbohydrate, and self-reported events of infections. We investigated the temporal evolution and probability distribution of the key blood glucose parameters within a specified timeframe (weekly, daily, and hourly). Results Our analysis demonstrated that upon infection incidence, there is a dramatic shift in the operating point of the individual blood glucose dynamics in all the timeframes (weekly, daily, and hourly), which clearly violates the usual norm of blood glucose dynamics. During regular or normal situations, higher insulin and reduced carbohydrate intake usually results in lower blood glucose levels. However, in all infection cases as opposed to the regular or normal days, blood glucose levels were elevated for a prolonged period despite higher insulin and reduced carbohydrates intake. For instance, compared with the preinfection and postinfection weeks, on average, blood glucose levels were elevated by 6.1% and 16%, insulin (bolus) was increased by 42% and 39.3%, and carbohydrate consumption was reduced by 19% and 28.1%, respectively. Conclusions We presented the effect of infection incidence on key parameters of blood glucose dynamics along with the necessary framework to exploit the information for realizing a digital infectious disease detection system. The results demonstrated that compared with regular or normal days, infection incidence substantially alters the norm of blood glucose dynamics, which are quite significant changes that could possibly be detected through personalized modeling, for example, prediction models and anomaly detection algorithms. Generally, we foresee that these findings can benefit the efforts toward building next generation digital infectious disease detection systems and provoke further thoughts in this challenging field.

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Section: Discussionmentioning

confidence: 99%

Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System

Woldaregay¹,

Launonen²,

Årsand³

et al. 2020

J Med Internet Res

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“…We operationalized these terms in order to formulate criteria for the inclusion and exclusion of publications in the review. As in other systematic qualitative reviews conducted on normative questions [ 7 , 9 , 11 ], we understood ‘ethical issue’ in a principlist [ 12 ] sense as either the ‘risk’ of not satisfying an ethical principle or a ‘conflict’ between 2 ethical principles. Since we were also interested in identifying management strategies, we also targeted safeguards for preventing a risk from materializing and conditions that justify solving a conflict between ethical principles.…”

Section: Methodsmentioning

confidence: 99%

“…Systematic literature reviews can help in providing such comprehensive overviews. Systematic reviews on normative issues are still rare [ 6 ], but some have been conducted in areas such as dementia care [ 7 ], patient safety research [ 8 ], and public health surveillance [ 9 ]. Since no adequate overviews of ethical issues for the present context existed, the World Health Organization (WHO) commissioned a qualitative literature review in support of the development and refinement of Zika response efforts.…”

Section: Introductionmentioning

confidence: 99%

Rapid qualitative review of ethical issues surrounding healthcare for pregnant women or women of reproductive age in epidemic outbreaks

Hummel

Saxena

Klingler³

2018

Epidemiol Health

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This article describes, categorizes, and discusses the results of a rapid literature review aiming to provide an overview of the ethical issues and corresponding solutions surrounding pregnancies in epidemic outbreaks. The review was commissioned by the World Health Organization to inform responses to the Zika outbreak that began in 2015. Due to the urgency of the response efforts that needed to be informed by the literature search, a rapid qualitative review of the literature published in PubMed was conducted. The search and analysis were based on the operationalization of 3 key concepts: ethics, pregnancy, and epidemic outbreak. Ethical issues and solutions were interpreted within a principlist framework. The data were analyzed using qualitative content analysis. The search identified 259 publications, of which the full text of 23 papers was read. Of those, 20 papers contained a substantive part devoted to the topic of interest and were therefore analyzed further. We clustered the ethical issues and solutions around 4 themes: uncertainty, harms, autonomy/liberty, and effectiveness. Recognition of the identified ethical issues and corresponding solutions can inform and improve response efforts, public health planning, policies, and decision-making, as well as the activities of medical staff and counselors who practice before, during, or after an epidemic outbreak that affects pregnant women or those of reproductive age. The rapid review format proved to be useful despite its limited data basis and expedited review process.

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“…It is time to move from the idea of de-identification to the application of appropriate technologies. The aim is to strike a balance between the public use of data and personal privacy [55,56]. Technologies such as secure multi-party computation and homomorphic encryption are emerging.…”

Section: B Balancing Personal Privacy and Public Safetymentioning

confidence: 99%

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

et al. 2020

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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.

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Ethical issues in public health surveillance: a systematic qualitative review

Cited by 60 publications

References 37 publications

Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System

Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System

Rapid qualitative review of ethical issues surrounding healthcare for pregnant women or women of reproductive age in epidemic outbreaks

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

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