Public Health Surveillance: Ethical Considerations

2019 ◽  
pp. 319-330
Author(s):  
Lisa M. Lee
Keyword(s):  
Public Health ◽  
Health Professionals ◽  
Data Science ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Surveillance Systems ◽  
Ethical Considerations ◽  
Science Data ◽  
Public Health Professionals ◽  
Ethical Conflicts

Public health surveillance is one approach used by public health professionals to gather evidence to inform public health policies and actions. Related ethical considerations have evolved over time, from those common to infectious disease surveillance, such as privacy and confidentiality, consent, discrimination, and stigma, to additional considerations related to the surveillance of noncommunicable conditions, such as self-determination justice, and provision of benefit. Recent advances in technology, data science, data collection, and expectations of how public health surveillance can serve the public good have substantial implications for how public health professionals should design and conduct ethical surveillance systems. Public health professionals can anticipate, address, and potentially avoid ethical conflicts by integrating ethical considerations throughout the development and implementation of a public health surveillance system.

scholarly journals Evaluation of Advanced Field Epidemiology Training Programs in the Eastern Mediterranean Region: A Multi-Country Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Mohannad Al Nsour ◽  
Yousef Khader ◽  
Haitham Bashier ◽  
Majd Alsoukhni
Keyword(s):  
Public Health ◽  
Health Professionals ◽  
Public Health Surveillance ◽  
Training Programs ◽  
Eastern Mediterranean ◽  
Eastern Mediterranean Region ◽  
Health Surveillance ◽  
Surveillance Systems ◽  
Field Epidemiology ◽  
Public Health Professionals

Field Epidemiology Training Programs (FETPs) are competency-based training programs aiming to strengthen the epidemiologic capacity of the public health workforce. This study aimed to evaluate the impact of the advanced FETPs in the Eastern Mediterranean region (EMR) and ascertain whether the expected objectives of the programs are met. A descriptive study was conducted based on Kirkpatrick's model for evaluating training programs. Data were collected from FETP graduates and FETP technical advisers on the practices of FETP graduates, their engagement in key areas of field epidemiology, and their perceived skills and capacity to perform such activities. A total of 166 FETP graduates responded to the online survey. Almost two-thirds of FETP graduates reported that they are often engaged in managing public health surveillance systems (n = 119, 71.7%), analyzing the surveillance data (n = 116, 69.9%), training public health professionals (n = 113, 68.1%), investigations on and response to outbreaks (n = 109, 65.7%), and managing staff and resources (n = 106, 63.9%). However, only 28.3% reported that they are often engaged in writing scientific research articles. More than two-thirds of graduates reported that the FETP helped them to perform most of the field epidemiology activities and rate their skills as good. In conclusion, the FETP graduates in the EMR were well engaged in many field epidemiology activities including managing public health surveillance systems, surveillance data analysis, training public health professionals, and investigations on and response to outbreaks. Therefore, the FETPs should continue supporting the graduates to work toward strengthening surveillance systems and investigating outbreaks and to participate in regional and global efforts as part of the Global Health Security.

scholarly journals Potential Applications of Emerging Technologies in Disease Surveillance

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Jay Huang ◽  
Wayne Loschen
Keyword(s):  
Public Health ◽  
Health Professionals ◽  
Disease Surveillance ◽  
Public Health Surveillance ◽  
New Technologies ◽  
Emerging Technologies ◽  
Surveillance Systems ◽  
The Public ◽  
Public Health Professionals ◽  
Health Field

ObjectiveThe objective of this presentation is to explore emerging technologies and how they will impact the public health field. New technologies such as blockchain, artificial intelligence (AI), and the Internet of Things (IoT) will likely be incorporated into epidemiological methods and processes. This presentation will provide an overview of these technologies and focus on how they may impact public health surveillance in the future.IntroductionWith the increase in the amount of public health data along with the growth of public health informatics, it is important for epidemiologists to understand the current trends in technology and the impact they may have in the field. Because it is unfeasible for public health professionals to be an expert in every emerging technology, this presentation seeks to provide them with a better understanding of how emerging technologies may impact the field and the level of expertise required to realize benefits from the new technologies. Furthermore, understanding the capabilities provided by emerging technologies may guide future training and continuing education for public health professionals.MethodsAnalysis of current capabilities and potential advances in emerging technologies such as blockchain, AI, and IoT were performed by reviewing articles and whitepapers. In addition to a literature review, interviews will be performed with public health experts to determine how the emerging technologies align with current practices and the extent to which they may solve existing public health surveillance challenges.ResultsThe literature review revealed many emerging technologies and potential applications in the public health field, including:BlockchainBlockchains can serve as electronic health information exchanges that hold the metadata and access information for patient electronic health records (EHRs).1 These systems can ensure data privacy protections while also facilitate relevant data sharing from EHRs to disease surveillance systems. Furthermore, blockchain technology can be used in food supply chain management systems. During food contamination events, epidemiologists can trace through the blockchain to identify possible sources of the contamination.2AIAI can be used to improve the prediction and detection capabilities of disease surveillance systems. Machine learning algorithms can reveal patterns in the data and enable faster anomaly detection. Furthermore, machine learning models can be trained on data to create predictive models.IoTUrban IoT systems can monitor environmental indices including water and air quality, energy consumption, waste management, and traffic congestion in smart cities.3 The data collected from such systems can be incorporated into more comprehensive disease surveillance systems and assist epidemiologists in better understanding populations and environmental risk factors.We will analyze and discuss such prospective applications with public health professionals to determine their potential impact on public health processes and practices in the next one, five, and ten years.ConclusionsBlockchain, AI, IoT and other emerging technologies have applications in public health surveillance and impact the field to varying degrees. In addition to technological advances, there will be barriers to adoption that must be overcome before the value provided by the technologies can be realized. Many new technologies will require significant collaboration between public health departments, healthcare providers, and other partners to successfully incorporate the technologies into epidemiological processes. These collaborations include forming consortiums to exchange data in a blockchain and working with IoT providers for data access. Some technologies will require public health professionals to obtain additional training before they can take full advantage of the capabilities provided, while other technologies may be implemented by external partners allowing epidemiologists to utilize the new capabilities without the need to completely understand the underlying concepts. As emerging technologies are introduced into the public health field, a strong understanding of their capabilities and suitable applications will allow public health professionals to fully capture the benefits provided by the new technologies.References1. Ekblaw A, Azaria A, Halamka JD, Lippman A. A Case Study for Blockchain in Healthcare:“MedRec” prototype for electronic health records and medical research data. InProceedings of IEEE open & big data conference 2016 Aug 22 (Vol. 13, p. 13).2. Yiannas F. A New Era of Food Transparency Powered by Blockchain. Innovations: Technology, Governance, Globalization. 2018 Jul;12(1-2):46-56.3. Zanella A, Bui N, Castellani A, Vangelista L, Zorzi M. Internet of things for smart cities. IEEE Internet of Things Journal. 2014 Feb 14;1(1):22-32.

scholarly journals Evaluation of Measles Surveillance Systems in Ginnir District, Bale Zone, Southeast Ethiopia: A Concurrent Embedded Mixed Quantitative/Qualitative Study 

2020 ◽  
Author(s):  
Falaho Sani ◽  
Mohammed Hasen ◽  
Mohammed Seid ◽  
Nuriya Umer
Keyword(s):  
Public Health ◽  
Qualitative Study ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Health Facilities ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Southeast Ethiopia ◽  
Bale Zone

Abstract Background: Public health surveillance systems should be evaluated periodically to ensure that the problems of public health importance are being monitored efficiently and effectively. Despite the widespread measles outbreak in Ginnir district of Bale zone in 2019, evaluation of measles surveillance system has not been conducted. Therefore, we evaluated the performance of measles surveillance system and its key attributes in Ginnir district, Southeast Ethiopia.Methods: We conducted a concurrent embedded mixed quantitative/qualitative study in August 2019 among 15 health facilities/study units in Ginnir district. Health facilities are selected using lottery method. The qualitative study involved purposively selected 15 key informants. Data were collected using semi-structured questionnaire adapted from Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems through face-to-face interview and record review. The quantitative findings were analyzed using Microsoft Excel 2016 and summarized by frequency and proportion. The qualitative findings were narrated and summarized based on thematic areas to supplement the quantitative findings.Results: The structure of surveillance data flow was from the community to the respective upper level. Emergency preparedness and response plan was available only at the district level. Completeness of weekly report was 95%, while timeliness was 87%. No regular analysis and interpretations of surveillance data, and the supportive supervision and feedback system was weak. The participation and willingness of surveillance stakeholders in implementation of the system was good. The surveillance system was found to be useful, easy to implement, representative and can accommodate and adapt to changing conditions. Report documentation and quality of data was poor at lower level health facilities. Stability of the system has been challenged by shortage of budget and logistics, staff turnover and lack of update trainings.Conclusions: The surveillance system was acceptable, useful, simple, flexible and representative. Data quality, timeliness and stability of the system were attributes that require improvement. The overall performance of measles surveillance system in the district was poor. Hence, regular analysis of data, preparation and dissemination of epidemiological bulletin, capacity building and regular supervision and feedback are recommended to enhance performance of the system.

scholarly journals Public Health Surveillance: Electronic Reporting as a Point of Reference

2019 ◽  
Vol 47 (S2) ◽  
pp. 19-22 ◽  
Author(s):  
Jennifer Black ◽  
Rachel Hulkower ◽  
Walter Suarez ◽  
Shreya Patel ◽  
Brandon Elliott
Keyword(s):  
Public Health ◽  
Health Information ◽  
Health Professionals ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Federal State ◽  
Electronic Reporting ◽  
Reporting Systems ◽  
State And Local ◽  
Point Of Reference

Federal, state, and local laws shape the use of health information for public health purposes, such as the mandated collection of data through electronic disease reporting systems. Health professionals can leverage these data to better anticipate and plan for the needs of communities, which is seen in the use of electronic case reporting.

scholarly journals Use of Severity Indicators in a Public Health Surveillance System

2014 ◽  
Vol 6 (1) ◽  
Author(s):  
Rhonda A. Lizewski ◽  
Howard Burkom ◽  
Joseph Lombardo ◽  
Christopher Cuellar ◽  
Yevgeniy Elbert ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Additional Data ◽  
Outpatient Setting ◽  
Health Surveillance ◽  
Surveillance Systems ◽  
Fusion Model ◽  
Community Based ◽  
Public Health Surveillance System

While other surveillance systems may only use death and admissions as severity indicators, these serious events may overshadow the more subtle severity signals based on appointment type, disposition from an outpatient setting, and whether that patient had to return for care if they their condition has not improved.  This abstract discusses how these additional data fields were utilized in a fusion model to improve the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE).

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