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Bouyer F, Thiongane O, Hobeika A, Arsevska E, Binot A, Corrèges D, Dub T, Mäkelä H, van Kleef E, Jori F, Lancelot R, Mercier A, Fagandini F, Valentin S, Van Bortel W, Ruault C. Epidemic intelligence in Europe: a user needs perspective to foster innovation in digital health surveillance. BMC Public Health 2024; 24:973. [PMID: 38582850 PMCID: PMC10999084 DOI: 10.1186/s12889-024-18466-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 03/27/2024] [Indexed: 04/08/2024] Open
Abstract
BACKGROUND European epidemic intelligence (EI) systems receive vast amounts of information and data on disease outbreaks and potential health threats. The quantity and variety of available data sources for EI, as well as the available methods to manage and analyse these data sources, are constantly increasing. Our aim was to identify the difficulties encountered in this context and which innovations, according to EI practitioners, could improve the detection, monitoring and analysis of disease outbreaks and the emergence of new pathogens. METHODS We conducted a qualitative study to identify the need for innovation expressed by 33 EI practitioners of national public health and animal health agencies in five European countries and at the European Centre for Disease Prevention and Control (ECDC). We adopted a stepwise approach to identify the EI stakeholders, to understand the problems they faced concerning their EI activities, and to validate and further define with practitioners the problems to address and the most adapted solutions to their work conditions. We characterized their EI activities, professional logics, and desired changes in their activities using NvivoⓇ software. RESULTS Our analysis highlights that EI practitioners wished to collectively review their EI strategy to enhance their preparedness for emerging infectious diseases, adapt their routines to manage an increasing amount of data and have methodological support for cross-sectoral analysis. Practitioners were in demand of timely, validated and standardized data acquisition processes by text mining of various sources; better validated dataflows respecting the data protection rules; and more interoperable data with homogeneous quality levels and standardized covariate sets for epidemiological assessments of national EI. The set of solutions identified to facilitate risk detection and risk assessment included visualization, text mining, and predefined analytical tools combined with methodological guidance. Practitioners also highlighted their preference for partial rather than full automation of analyses to maintain control over the data and inputs and to adapt parameters to versatile objectives and characteristics. CONCLUSIONS The study showed that the set of solutions needed by practitioners had to be based on holistic and integrated approaches for monitoring zoonosis and antimicrobial resistance and on harmonization between agencies and sectors while maintaining flexibility in the choice of tools and methods. The technical requirements should be defined in detail by iterative exchanges with EI practitioners and decision-makers.
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Affiliation(s)
- Fanny Bouyer
- Groupe d'Expérimentation et de Recherche: Développement et Actions Locales (GERDAL), Angers, France.
| | - Oumy Thiongane
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Alexandre Hobeika
- UMR MOISA, French Agricultural Research Centre for International Development (CIRAD), 34398, Montpellier, France
- MOISA, University Montpellier, CIHEAM-IAMM, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Elena Arsevska
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Aurélie Binot
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Déborah Corrèges
- Joint Research Unit EPIdemiological On Animal and Zoonotic Diseases (UMR EPIA), National School of Veterinary Services (VetAgro Sup), National Research Institute for Agriculture, Food and Environment (INRAE), Marcy L'Etoile, France
| | - Timothée Dub
- Department of Health Security, Finish Institute for Health and Welfare, Helsinki, Finland
| | - Henna Mäkelä
- Department of Health Security, Finish Institute for Health and Welfare, Helsinki, Finland
| | - Esther van Kleef
- Institute of Tropical Medicine, Department of Biomedical Sciences, Outbreak Research Team, Antwerp, Belgium
| | - Ferran Jori
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Renaud Lancelot
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Alize Mercier
- Joint Research Unit Animal, Health, Territories, Risks, Ecosystems (UMR ASTRE), French Agricultural Research Centre for International Development (CIRAD), National Research Institute for Agriculture, Food and Environment (INRAE), Montpellier, France
| | - Francesca Fagandini
- Joint Research Unit Land, Remote Sensing and Spatial Information (UMR TETIS), French Agricultural Research Centre for International Development (CIRAD), Montpellier, France
| | - Sarah Valentin
- Joint Research Unit Land, Remote Sensing and Spatial Information (UMR TETIS), French Agricultural Research Centre for International Development (CIRAD), Montpellier, France
| | - Wim Van Bortel
- Institute of Tropical Medicine, Department of Biomedical Sciences, Outbreak Research Team, Antwerp, Belgium
- Institute of Tropical Medicine, Department of Biomedical Sciences, Unit of Entomology, Antwerp, Belgium
| | - Claire Ruault
- Groupe d'Expérimentation et de Recherche: Développement et Actions Locales (GERDAL), Angers, France
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Bolt K, Gil-González D, Oliver N. Unconventional data, unprecedented insights: leveraging non-traditional data during a pandemic. Front Public Health 2024; 12:1350743. [PMID: 38566798 PMCID: PMC10986850 DOI: 10.3389/fpubh.2024.1350743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/20/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction The COVID-19 pandemic prompted new interest in non-traditional data sources to inform response efforts and mitigate knowledge gaps. While non-traditional data offers some advantages over traditional data, it also raises concerns related to biases, representativity, informed consent and security vulnerabilities. This study focuses on three specific types of non-traditional data: mobility, social media, and participatory surveillance platform data. Qualitative results are presented on the successes, challenges, and recommendations of key informants who used these non-traditional data sources during the COVID-19 pandemic in Spain and Italy. Methods A qualitative semi-structured methodology was conducted through interviews with experts in artificial intelligence, data science, epidemiology, and/or policy making who utilized non-traditional data in Spain or Italy during the pandemic. Questions focused on barriers and facilitators to data use, as well as opportunities for improving utility and uptake within public health. Interviews were transcribed, coded, and analyzed using the framework analysis method. Results Non-traditional data proved valuable in providing rapid results and filling data gaps, especially when traditional data faced delays. Increased data access and innovative collaborative efforts across sectors facilitated its use. Challenges included unreliable access and data quality concerns, particularly the lack of comprehensive demographic and geographic information. To further leverage non-traditional data, participants recommended prioritizing data governance, establishing data brokers, and sustaining multi-institutional collaborations. The value of non-traditional data was perceived as underutilized in public health surveillance, program evaluation and policymaking. Participants saw opportunities to integrate them into public health systems with the necessary investments in data pipelines, infrastructure, and technical capacity. Discussion While the utility of non-traditional data was demonstrated during the pandemic, opportunities exist to enhance its impact. Challenges reveal a need for data governance frameworks to guide practices and policies of use. Despite the perceived benefit of collaborations and improved data infrastructure, efforts are needed to strengthen and sustain them beyond the pandemic. Lessons from these findings can guide research institutions, multilateral organizations, governments, and public health authorities in optimizing the use of non-traditional data.
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Affiliation(s)
- Kaylin Bolt
- Health Sciences Division (Assessment, Policy Development, and Evaluation Unit), Public Health - Seattle & King County, Seattle, WA, United States
| | - Diana Gil-González
- Department of Community Nursing, Preventive Medicine and Public Health and History of Science, University of Alicante, Alicante, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Nuria Oliver
- European Laboratory for Learning and Intelligent Systems (ELLIS) Alicante, Alicante, Spain
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3
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Martani A, Geneviève LD, Wangmo T, Maurer J, Crameri K, Erard F, Spoendlin J, Pauli-Magnus C, Pittet V, Sengstag T, Soldini E, Hirschel B, Borisch B, Kruschel Weber C, Zwahlen M, Elger BS. Sensing the (digital) pulse. Future steps for improving the secondary use of data for research in Switzerland. Digit Health 2023; 9:20552076231169826. [PMID: 37113255 PMCID: PMC10126638 DOI: 10.1177/20552076231169826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 03/29/2023] [Indexed: 04/29/2023] Open
Abstract
Introduction Ensuring that the health data infrastructure and governance permits an efficient secondary use of data for research is a policy priority for many countries. Switzerland is no exception and many initiatives have been launched to improve its health data landscape. The country now stands at an important crossroad, debating the right way forward. We aimed to explore which specific elements of data governance can facilitate - from ethico-legal and socio-cultural perspectives - the sharing and reuse of data for research purposes in Switzerland. Methods A modified Delphi methodology was used to collect and structure input from a panel of experts via successive rounds of mediated interaction on the topic of health data governance in Switzerland. Results First, we suggested techniques to facilitate data sharing practices, especially when data are shared between researchers or from healthcare institutions to researchers. Second, we identified ways to improve the interaction between data protection law and the reuse of data for research, and the ways of implementing informed consent in this context. Third, we put forth ideas on policy changes, such as the steps necessary to improve coordination between different actors of the data landscape and to win the defensive and risk-adverse attitudes widespread when it comes to health data. Conclusions After having engaged with these topics, we highlighted the importance of focusing on non-technical aspects to improve the data-readiness of a country (e.g., attitudes of stakeholders involved) and of having a pro-active debate between the different institutional actors, ethico-legal experts and society at large.
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Affiliation(s)
- Andrea Martani
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
- Andrea Martani, Institute of Biomedical
Ethics, University of Basel, Bernoullistrasse 28, Basel, Kanton Basel-Stadt,
4056, Schweiz.
| | | | - Tenzin Wangmo
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
| | - Julia Maurer
- Personalized Health Informatics Group, SIB Swiss Institute of
Bioinformatics, Basel, Switzerland
| | - Katrin Crameri
- Personalized Health Informatics Group, SIB Swiss Institute of
Bioinformatics, Basel, Switzerland
| | - Frédéric Erard
- Legal & Technology Transfer, Swiss Institute of Bioinformatics
(SIB), Lausanne, Switzerland
| | - Julia Spoendlin
- Basel Pharmacoepidemiology Unit,
Division of Clinical Pharmacy and Epidemiology, Department of Pharmaceutical
Sciences, University of Basel, Basel, Switzerland
- Hospital Pharmacy, University Hospital Basel, Basel, Switzerland
| | - Christiane Pauli-Magnus
- Clinical Trial Unit, Department of
Clinical Research, University of Basel and University Hospital Basel, Basel,
Switzerland
| | - Valerie Pittet
- Center for Primary Care and Public
Health, Department of Epidemiology and Health Systems, University of Lausanne, Lausanne, Switzerland
| | | | - Emiliano Soldini
- Competence Centre for Healthcare
Practices and Policies, Department of Business Economics, Health and Social Care,
University of Applied Sciences and Arts of Southern Switzerland, Manno,
Switzerland
| | - Bernard Hirschel
- Cantonal Ethics Commission for
Research on Human Beings, Geneva, Switzerland
| | - Bettina Borisch
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | | | - Marcel Zwahlen
- Institute of Social and Preventive
Medicine, University of Bern, Bern, Switzerland
| | - Bernice Simone Elger
- Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
- University Center of Legal Medicine, University of Geneva, Geneva, Switzerland
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Kerr JI, Naegelin M, Benk M, V Wangenheim F, Meins E, Viganò E, Ferrario A. Investigating Employees’ Concerns and Wishes for Digital Stress Management Interventions with Value Sensitive Design: Mixed Methods Study (Preprint). J Med Internet Res 2022; 25:e44131. [PMID: 37052996 PMCID: PMC10141316 DOI: 10.2196/44131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/21/2023] [Accepted: 03/12/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND Work stress places a heavy economic and disease burden on society. Recent technological advances include digital health interventions for helping employees prevent and manage their stress at work effectively. Although such digital solutions come with an array of ethical risks, especially if they involve biomedical big data, the incorporation of employees' values in their design and deployment has been widely overlooked. OBJECTIVE To bridge this gap, we used the value sensitive design (VSD) framework to identify relevant values concerning a digital stress management intervention (dSMI) at the workplace, assess how users comprehend these values, and derive specific requirements for an ethics-informed design of dSMIs. VSD is a theoretically grounded framework that front-loads ethics by accounting for values throughout the design process of a technology. METHODS We conducted a literature search to identify relevant values of dSMIs at the workplace. To understand how potential users comprehend these values and derive design requirements, we conducted a web-based study that contained closed and open questions with employees of a Swiss company, allowing both quantitative and qualitative analyses. RESULTS The values health and well-being, privacy, autonomy, accountability, and identity were identified through our literature search. Statistical analysis of 170 responses from the web-based study revealed that the intention to use and perceived usefulness of a dSMI were moderate to high. Employees' moderate to high health and well-being concerns included worries that a dSMI would not be effective or would even amplify their stress levels. Privacy concerns were also rated on the higher end of the score range, whereas concerns regarding autonomy, accountability, and identity were rated lower. Moreover, a personalized dSMI with a monitoring system involving a machine learning-based analysis of data led to significantly higher privacy (P=.009) and accountability concerns (P=.04) than a dSMI without a monitoring system. In addition, integrability, user-friendliness, and digital independence emerged as novel values from the qualitative analysis of 85 text responses. CONCLUSIONS Although most surveyed employees were willing to use a dSMI at the workplace, there were considerable health and well-being concerns with regard to effectiveness and problem perpetuation. For a minority of employees who value digital independence, a nondigital offer might be more suitable. In terms of the type of dSMI, privacy and accountability concerns must be particularly well addressed if a machine learning-based monitoring component is included. To help mitigate these concerns, we propose specific requirements to support the VSD of a dSMI at the workplace. The results of this work and our research protocol will inform future research on VSD-based interventions and further advance the integration of ethics in digital health.
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Affiliation(s)
- Jasmine I Kerr
- Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland
- Chair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Mara Naegelin
- Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland
- Chair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Michaela Benk
- Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland
- Chair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Florian V Wangenheim
- Chair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
| | - Erika Meins
- Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland
| | - Eleonora Viganò
- Institute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland
| | - Andrea Ferrario
- Mobiliar Lab for Analytics at ETH Zurich, Department of Management, Technology, and Economics, ETH Zurich, Zürich, Switzerland
- Chair of Technology Marketing, Department of Management, Technology, and Economics, ETH Zurich, Zurich, Switzerland
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5
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Smartphone apps in the COVID-19 pandemic. Nat Biotechnol 2022; 40:1013-1022. [PMID: 35726090 DOI: 10.1038/s41587-022-01350-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 05/04/2022] [Indexed: 01/08/2023]
Abstract
At the beginning of the COVID-19 pandemic, analog tools such as nasopharyngeal swabs for PCR tests were center stage and the major prevention tactics of masking and physical distancing were a throwback to the 1918 influenza pandemic. Overall, there has been scant regard for digital tools, particularly those based on smartphone apps, which is surprising given the ubiquity of smartphones across the globe. Smartphone apps, given accessibility in the time of physical distancing, were widely used for tracking, tracing and educating the public about COVID-19. Despite limitations, such as concerns around data privacy, data security, digital health illiteracy and structural inequities, there is ample evidence that apps are beneficial for understanding outbreak epidemiology, individual screening and contact tracing. While there were successes and failures in each category, outbreak epidemiology and individual screening were substantially enhanced by the reach of smartphone apps and accessory wearables. Continued use of apps within the digital infrastructure promises to provide an important tool for rigorous investigation of outcomes both in the ongoing outbreak and in future epidemics.
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Viberg Johansson J, Bentzen HB, Mascalzoni D. What ethical approaches are used by scientists when sharing health data? An interview study. BMC Med Ethics 2022; 23:41. [PMID: 35410285 PMCID: PMC9004072 DOI: 10.1186/s12910-022-00779-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 04/01/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Health data-driven activities have become central in diverse fields (research, AI development, wearables, etc.), and new ethical challenges have arisen with regards to privacy, integrity, and appropriateness of use. To ensure the protection of individuals' fundamental rights and freedoms in a changing environment, including their right to the protection of personal data, we aim to identify the ethical approaches adopted by scientists during intensive data exploitation when collecting, using, or sharing peoples' health data. METHODS Twelve scientists who were collecting, using, or sharing health data in different contexts in Sweden, were interviewed. We used systematic expert interviews to access these scientists' specialist knowledge, and analysed the interviews with thematic analysis. Phrases, sentences, or paragraphs through which ethical values and norms were expressed, were identified and coded. Codes that reflected similar concepts were grouped, subcategories were formulated, and categories were connected to traditional ethical approaches. RESULTS Through several examples, the respondents expressed four different ethical approaches, which formed the main conceptual categories: consideration of consequences, respect for rights, procedural compliance, and being professional. CONCLUSIONS To a large extent, the scientists' ethical approaches were consistent with ethical and legal principles. Data sharing was considered important and worth pursuing, even though it is difficult. An awareness of the complex issues involved in data sharing was reflected from different perspectives, and the respondents commonly perceived a general lack of practical procedures that would by default ensure ethical and legally compliant data collection and sharing. We suggest that it is an opportune time to move on from policy discussions to practical technological ethics-by-design solutions that integrate these principles into practice.
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Affiliation(s)
- Jennifer Viberg Johansson
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, Box 564, 751 22, Uppsala, Sweden.
- Institute for Futures Studies, Stockholm, Sweden.
| | - Heidi Beate Bentzen
- Norwegian Research Center for Computers and Law, Faculty of Law, University of Oslo, Oslo, Norway
| | - Deborah Mascalzoni
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, Box 564, 751 22, Uppsala, Sweden
- Institute of Biomedicine, Eurac Research, Bolzano, Italy
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Sood SK, Rawat KS, Kumar D. Analytical mapping of information and communication technology in emerging infectious diseases using CiteSpace. TELEMATICS AND INFORMATICS 2022; 69:101796. [PMID: 35282387 PMCID: PMC8901238 DOI: 10.1016/j.tele.2022.101796] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 01/24/2022] [Accepted: 02/28/2022] [Indexed: 11/05/2022]
Abstract
The prevalence of severe infectious diseases has become a major global health concern. Currently, the COVID-19 outbreak has spread across the world and has created an unprecedented humanitarian crisis. The proliferation of novel viruses has put traditional health systems under immense pressure and posed several serious issues. Henceforth, early detection, identification, rapid testing, and advanced surveillance systems are required to address public health emergencies. However, Information and Communication Technology (ICT) tackles several issues raised by this pandemic and significantly improves the quality of services in the health care sector. This paper presents an ICT-assisted scientometric analysis of infectious diseases, namely, airborne, food & waterborne, fomite-borne, sexually transmitted illnesses, and vector-borne illnesses. It assesses the international research status of this field in terms of citation structure, prolific journals, and country contributions. It has used the CiteSpace tool to address the visualization needs and in-depth insights of scientific literature to pinpoint core hotspots, research frontiers, emerging research areas, and ICT trends. The research finding reveals that mobile apps, telemedicine, and artificial intelligence technologies have greater scope to reduce the threats of infectious diseases. COVID-19, influenza, HIV, and malaria viruses have been identified as research hotspots whereas COVID-19, contact tracing applications, security and privacy concerns about users' data are the recent challenges in this field that need to address. The United States has produced higher research output in all domains of infectious diseases. Furthermore, it explores the co-occurrence network analysis and intellectual landscape of each domain of infectious diseases. It provides potential research directions and insightful clues to researchers and the academic fraternity for further research.
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Affiliation(s)
- Sandeep Kumar Sood
- Department of Computer Aplications, National Institute of Technology, Kurukshetra, Haryana 136119, India
| | - Keshav Singh Rawat
- Department of Computer Science and Informatics, Central University of Himachal Pradesh, Dharmashala, Himachal Pradesh 176215, India
| | - Dheeraj Kumar
- Department of Computer Science and Informatics, Central University of Himachal Pradesh, Dharmashala, Himachal Pradesh 176215, India,Corresponding author
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Geneviève LD, Martani A, Wangmo T, Elger BS. Precision Public Health and Structural Racism in the United States: promoting health equity in the COVID-19 pandemic response. JMIR Public Health Surveill 2022; 8:e33277. [PMID: 35089868 PMCID: PMC8900917 DOI: 10.2196/33277] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 12/31/2021] [Accepted: 01/27/2022] [Indexed: 11/13/2022] Open
Abstract
UNSTRUCTURED The COVID-19 pandemic has revealed deeply entrenched structural inequalities that resulted in an excess of mortality and morbidity in certain racial and ethnic groups in the US. Therefore, this paper examines from the US perspective how structural racism and defective data collections on racial and ethnic minorities can negatively influence the development of precision public health approaches to tackle the ongoing COVID-19 pandemic. Importantly, the effects of structural and data racism on the elaboration of fair and inclusive data-driven components of precision public health interventions are discussed, such as with the use of machine learning algorithms to predict public health risks. The objective of this viewpoint is thus to inform public health policy-making with regard to the development of ethically sound precision public health interventions against COVID-19. Particular attention is given to components of structural racism (e.g. hospital segregation, implicit and organizational bias, digital divide and sociopolitical influences) that are likely to hinder such approaches from achieving their social justice and health equity goals.
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Affiliation(s)
| | - Andrea Martani
- Institute for Biomedical Ethics, University of Basel, Bernoullistrasse 28, Basel, CH
| | - Tenzin Wangmo
- Institute for Biomedical Ethics, University of Basel, Bernoullistrasse 28, Basel, CH
| | - Bernice Simone Elger
- Institute for Biomedical Ethics, University of Basel, Bernoullistrasse 28, Basel, CH.,University Center of Legal Medicine, University of Geneva, Geneva, CH
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Adebisi YA, Rabe A, Lucero-Prisno III DE. COVID-19 surveillance systems in African countries. Health Promot Perspect 2021; 11:382-392. [PMID: 35079582 PMCID: PMC8767077 DOI: 10.34172/hpp.2021.49] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 08/08/2021] [Indexed: 12/29/2022] Open
Abstract
Background: Surveillance forms the basis for response to disease outbreaks, including COVID-19. Herein, we identified the COVID-19 surveillance systems and the associated challenges in 13 African countries. Methods: We conducted a comprehensive narrative review of peer-reviewed literature published between January 2020 and April 2021 in PubMed, Medline, PubMed Central, and Google Scholar using predetermined search terms. Relevant studies from the search and other data sources on COVID-19 surveillance strategies and associated challenges in 13 African countries (Mauritius, Algeria, Nigeria, Angola, Cote d'Ivoire, the Democratic Republic of the Congo, Ghana, Ethiopia, South Africa, Kenya, Zambia, Tanzania, and Uganda) were identified and reviewed. Results: Our findings revealed that the selected African countries have ramped up COVID-19 surveillance ranging from immediate case notification, virological surveillance, hospital-based surveillance to mortality surveillance among others. Despite this, there exist variations in the level of implementation of the surveillance systems across countries. Integrated Disease Surveillance and Response (IDSR) strategy is also being leveraged in some African countries, but the implementation across countries remains uneven. Our study also revealed various challenges facing surveillance which included shortage of skilled human resources resulting in poor data management, weak health systems, complexities of ethical considerations, diagnostic insufficiency, the burden of co-epidemic surveillance, and geographical barriers, among others. Conclusion: With the variations in the level of implementation of COVID-19 surveillance strategies seen across countries, it is pertinent to ensure proper coordination of the surveillance activities in the African countries and address all the challenges facing COVID-19 surveillance using tailored strategies.
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Affiliation(s)
- Yusuff Adebayo Adebisi
- Global Health Focus Africa, Nigeria
- African Young Leaders for Global Health, Abuja, Nigeria
- Faculty of Pharmacy, University of Ibadan, Ibadan, Nigeria
| | - Adrian Rabe
- Global Health Focus Africa, Nigeria
- Faculty of Medicine, School of Public Health, Imperial College London, UK
| | - Don Eliseo Lucero-Prisno III
- Global Health Focus Africa, Nigeria
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK
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Althobaiti K. Surveillance in Next-Generation Personalized Healthcare: Science and Ethics of Data Analytics in Healthcare. New Bioeth 2021; 27:295-319. [PMID: 34720071 DOI: 10.1080/20502877.2021.1993055] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Advances in science and technology have allowed for incredible improvements in healthcare. Additionally, the digital revolution in healthcare provides new ways of collecting and storing large volumes of patient data, referred to as big healthcare data. As a result, healthcare providers are now able to use data to gain a deeper understanding of how to treat an individual in what is referred to as personalized healthcare. Regardless, there are several ethical challenges associated with big healthcare data that affect how personalized healthcare is delivered. To highlight these issues, this article will review the role of big data in personalized healthcare while also discussing the ethical challenges associated with it. The article will also discuss public health surveillance, its implications, and the challenges associated with collecting participants' information. The article will proceed by highlighting next generation technologies, including robotics and 3D printing. The article will conclude by providing recommendations on how patient privacy can be protected in next-generation personalized healthcare.
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Affiliation(s)
- Kamal Althobaiti
- Centre for Global Health Ethics, Duquesne University, Pittsburgh, PA, USA
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Kostkova P, Saigí-Rubió F, Eguia H, Borbolla D, Verschuuren M, Hamilton C, Azzopardi-Muscat N, Novillo-Ortiz D. Data and Digital Solutions to Support Surveillance Strategies in the Context of the COVID-19 Pandemic. Front Digit Health 2021; 3:707902. [PMID: 34713179 PMCID: PMC8522016 DOI: 10.3389/fdgth.2021.707902] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 06/30/2021] [Indexed: 12/23/2022] Open
Abstract
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.
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Affiliation(s)
- Patty Kostkova
- UCL Centre for Digital Public Health in Emergencies (dPHE), Institute for Risk and Disaster Reduction, University College London, London, United Kingdom
| | - Francesc Saigí-Rubió
- Faculty of Health Sciences, Universitat Oberta de Catalunya, Barcelona, Spain
- Interdisciplinary Research Group on ICTs, Barcelona, Spain
| | - Hans Eguia
- Faculty of Health Sciences, Universitat Oberta de Catalunya, Barcelona, Spain
- SEMERGEN New Technologies Working Group, Madrid, Spain
| | - Damian Borbolla
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States
| | - Marieke Verschuuren
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
| | - Clayton Hamilton
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
| | - Natasha Azzopardi-Muscat
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
| | - David Novillo-Ortiz
- Division of Country Health Policies and Systems, Regional Office for Europe, World Health Organization, Copenhagen, Denmark
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12
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Leal-Neto OB, Santos FAS, Lee JY, Albuquerque JO, Souza WV. Prioritizing COVID-19 tests based on participatory surveillance and spatial scanning. Int J Med Inform 2020; 143:104263. [PMID: 32877853 PMCID: PMC7449898 DOI: 10.1016/j.ijmedinf.2020.104263] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 08/20/2020] [Accepted: 08/24/2020] [Indexed: 12/24/2022]
Abstract
OBJECTIVES This study aimed to identify, describe and analyze priority areas for COVID-19 testing combining participatory surveillance and traditional surveillance. DESIGN It was carried out a descriptive transversal study in the city of Caruaru, Pernambuco state, Brazil, within the period of 20/02/2020 to 05/05/2020. Data included all official reports for influenza-like illness notified by the municipality health department and the self-reports collected through the participatory surveillance platform Brasil Sem Corona. METHODS We used linear regression and loess regression to verify a correlation between Participatory Surveillance (PS) and Traditional Surveillance (TS). Also a spatial scanning approach was deployed in order to identify risk clusters for COVID-19. RESULTS In Caruaru, the PS had 861 active users, presenting an average of 1.2 reports per user per week. The platform Brasil Sem Corona started on March 20th and since then, has been officially used by the Caruaru health authority to improve the quality of information from the traditional surveillance system. Regarding the respiratory syndrome cases from TS, 1588 individuals were positive for this clinical outcome. The spatial scanning analysis detected 18 clusters and 6 of them presented statistical significance (p-value < 0.1). Clusters 3 and 4 presented an overlapping area that was chosen by the local authority to deploy the COVID-19 serology, where 50 individuals were tested. From there, 32 % (n = 16) presented reagent results for antibodies related to COVID-19. CONCLUSION Participatory surveillance is an effective epidemiological method to complement the traditional surveillance system in response to the COVID-19 pandemic by adding real-time spatial data to detect priority areas for COVID-19 testing.
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Affiliation(s)
- O B Leal-Neto
- Department of Economics, University of Zurich, Zurich, Switzerland; Epitrack, Recife, Brazil.
| | - F A S Santos
- Agreste Academic Center, Federal University of Pernambuco, Caruaru, Brazil
| | | | - J O Albuquerque
- Epitrack, Recife, Brazil; Immunopathology Laboratory Keizo Asami, Federal University of Pernambuco, Recife, Brazil
| | - W V Souza
- Aggeu Magalhães Research Center, Oswaldo Cruz Foundation, Recife, Brazil
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13
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Woldaregay AZ, Launonen IK, Årsand E, Albers D, Holubová A, Hartvigsen G. 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. J Med Internet Res 2020; 22:e18911. [PMID: 32784178 PMCID: PMC7450374 DOI: 10.2196/18911] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 06/06/2020] [Accepted: 06/11/2020] [Indexed: 01/23/2023] Open
Abstract
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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Affiliation(s)
| | | | - Eirik Årsand
- Department of Computer Science, University of Tromsø - The Arctic University of Norway, Tromsø, Norway
| | - David Albers
- Department of Pediatrics, Informatics and Data Science, University of Colorado, Aurora, CO, United States
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Anna Holubová
- Department of ICT in Medicine, Faculty of Biomedical Engineering, Czech Technical University, Prague, Czech Republic
- Spin-off Company and Research Results Commercialization Center of the First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Gunnar Hartvigsen
- Department of Computer Science, University of Tromsø - The Arctic University of Norway, Tromsø, Norway
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14
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Abstract
OBJECTIVE To summarize significant research contributions on ethics in medical informatics published in 2019. METHODS An extensive search using PubMed/Medline was conducted to identify the scientific contributions published in 2019 that address ethics issues in medical informatics. The selection process comprised three steps: 1) 15 candidate best papers were first selected by the two section editors; 2) external reviewers from internationally renowned research teams reviewed each candidate best paper; and 3) the final selection of three best papers was conducted by the editorial committee of the Yearbook. RESULTS The three selected best papers explore timely issues of concern to the community and demonstrate how ethics considerations influence applied informatics. CONCLUSION With regard to ethics in informatics, data sharing and privacy remain primary areas of concern. Ethics issues related to the development and implementation of artificial intelligence is an emerging topic of interest.
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Affiliation(s)
- Carolyn Petersen
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | - Vignesh Subbian
- College of Engineering, The University of Arizona, Tucson, Arizona, USA
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15
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Garg S, Bhatnagar N, Gangadharan N. A Case for Participatory Disease Surveillance of the COVID-19 Pandemic in India. JMIR Public Health Surveill 2020; 6:e18795. [PMID: 32287038 PMCID: PMC7164788 DOI: 10.2196/18795] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 04/09/2020] [Accepted: 04/13/2020] [Indexed: 12/26/2022] Open
Abstract
The coronavirus disease pandemic requires the deployment of novel surveillance strategies to curtail further spread of the disease in the community. Participatory disease surveillance mechanisms have already been adopted in countries for the current pandemic. India, with scarce resources, good telecom support, and a not-so-robust heath care system, makes a strong case for introducing participatory disease surveillance for the prevention and control of the pandemic. India has just launched Aarogya Setu, which is a first-of-its-kind participatory disease surveillance initiative in India. This will supplement the existing Integrated Disease Surveillance Programme in India by finding missing cases and having faster aggregation, analysis of data, and prompt response measures. This newly created platform empowers communities with the right information and guidance, enabling protection from infection and reducing unnecessary contact with the overburdened health care system. However, caution needs to be exercised to address participation from digitally isolated populations, ensure the reliability of data, and consider ethical concerns such as maintaining individual privacy.
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Affiliation(s)
- Suneela Garg
- Maulana Azad Medical College, Delhi University, Delhi, India
| | - Nidhi Bhatnagar
- Maulana Azad Medical College, Delhi University, Delhi, India
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16
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Zeeb H, Pigeot I, Schüz B. [Digital public health-an overview]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2020; 63:137-144. [PMID: 31919531 DOI: 10.1007/s00103-019-03078-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The rapid development and proliferation of digital health technologies have not only changed the medical professions, but offer great potential for public health, particularly in health promotion and disease prevention.At the same time, this emerging field is also characterized by conceptual and terminological fuzziness, a marked lack of high-quality evidence, and an absence of an honest discussion of unintended consequences and side effects. Further challenges for digital public health lie in the fact that the development of new health technologies is mainly driven by technological progress and less by evidence-based needs and research in public health.In this overview paper, we aim at conceptually denoting the field of digital public health, using principal public health functions as guiding principles. We discuss some current applications of digital health technologies in fulfilling public health functions and propose a needs-based development of digital health technologies.We will further address specific challenges to digital public health, in particular socio-economic differences in the usage of and profiting from digital health technologies, data protection and privacy issues, as well as ethical issues.
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Affiliation(s)
- Hajo Zeeb
- Leibniz WissenschaftsCampus Digital Public Health Bremen, Bremen, Deutschland. .,Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Achterstr. 30, 28359, Bremen, Deutschland. .,Fachbereich Human- und Gesundheitswissenschaften, Universität Bremen, Bremen, Deutschland.
| | - Iris Pigeot
- Leibniz WissenschaftsCampus Digital Public Health Bremen, Bremen, Deutschland.,Leibniz-Institut für Präventionsforschung und Epidemiologie - BIPS, Achterstr. 30, 28359, Bremen, Deutschland.,Fachbereich Mathematik und Informatik, Universität Bremen, Bremen, Deutschland
| | - Benjamin Schüz
- Leibniz WissenschaftsCampus Digital Public Health Bremen, Bremen, Deutschland.,Fachbereich Human- und Gesundheitswissenschaften, Institut für Public Health und Pflegeforschung, Universität Bremen, Bremen, Deutschland
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17
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Aiello AE, Renson A, Zivich PN. Social Media- and Internet-Based Disease Surveillance for Public Health. Annu Rev Public Health 2020; 41:101-118. [PMID: 31905322 DOI: 10.1146/annurev-publhealth-040119-094402] [Citation(s) in RCA: 106] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.
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Affiliation(s)
- Allison E Aiello
- Department of Epidemiology, Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7435, USA; , ,
| | - Audrey Renson
- Department of Epidemiology, Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7435, USA; , ,
| | - Paul N Zivich
- Department of Epidemiology, Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7435, USA; , ,
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