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Unim B, Zile-Velika I, Pavlovska Z, Lapao L, Peyroteo M, Misins J, Forjaz MJ, Nogueira P, Grisetti T, Palmieri L. The role of digital tools and emerging devices in COVID-19 contact tracing during the first 18 months of the pandemic: a systematic review. Eur J Public Health 2024; 34:i11-i28. [PMID: 38946444 PMCID: PMC11215323 DOI: 10.1093/eurpub/ckae039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2024] Open
Abstract
BACKGROUND Contact tracing is a public health intervention implemented in synergy with other preventive measures to curb epidemics, like the coronavirus pandemic. The development and use of digital devices have increased worldwide to enhance the contact tracing process. The aim of the study was to evaluate the effectiveness and impact of tracking coronavirus disease 2019 (COVID-19) patients using digital solutions. METHODS Observational studies on digital contact tracing (DCT), published 2020-21, in English were identified through a systematic literature review performed on nine online databases. An ad hoc form was used for data extraction of relevant information. Quality assessment of the included studies was performed with validated tools. A qualitative synthesis of the findings is reported. RESULTS Over 8000 records were identified and 37 were included in the study: 24 modelling and 13 population-based studies. DCT improved the identification of close contacts of COVID-19 cases and reduced the effective reproduction number of COVID-19-related infections and deaths by over 60%. It impacted positively on societal and economic costs, in terms of lockdowns and use of resources, including staffing. Privacy and security issues were reported in 27 studies. CONCLUSIONS DCT contributed to curbing the COVID-19 pandemic, especially with the high uptake rate of the devices and in combination with other public health measures, especially conventional contact tracing. The main barriers to the implementation of the devices are uptake rate, security and privacy issues. Public health digitalization and contact tracing are the keys to countries' emergency preparedness for future health crises.
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Affiliation(s)
- Brigid Unim
- Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy
| | | | - Zane Pavlovska
- Centre for Disease Prevention and Control of Latvia, Riga, Latvia
| | - Luis Lapao
- UNIDEMI, Department of Mechanical and Industrial Engineering, NOVA School of Science and Technology, Universidade Nova de Lisboa, Caparica, Portugal
- CHRC, Nova Medical School, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Mariana Peyroteo
- UNIDEMI, Department of Mechanical and Industrial Engineering, NOVA School of Science and Technology, Universidade Nova de Lisboa, Caparica, Portugal
- CHRC, Nova Medical School, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Janis Misins
- Centre for Disease Prevention and Control of Latvia, Riga, Latvia
| | - Maria João Forjaz
- National Center of Epidemiology, Health Institute Carlos III and RICAPPS, Madrid, Spain
| | - Paulo Nogueira
- CHRC, National School of Public Health, Nova de Lisboa University, Lisbon, Portugal
- Nursing Research, Innovation and Development Centre of Lisbon (CIDNUR), Nursing School of Lisbon, Lisbon, Portugal
- Instituto de Saúde Ambiental (ISAMB), Laboratório para a Sustentabilidade do Uso da Terra e dos Serviços dos Ecossistemas—TERRA, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
| | - Tiziana Grisetti
- Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy
| | - Luigi Palmieri
- Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy
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Yamamoto K, Sakaguchi M, Onishi A, Yokoyama S, Matsui Y, Yamamoto W, Onizawa H, Fujii T, Murata K, Tanaka M, Hashimoto M, Matsuda S, Morinobu A. Energy landscape analysis and time-series clustering analysis of patient state multistability related to rheumatoid arthritis drug treatment: The KURAMA cohort study. PLoS One 2024; 19:e0302308. [PMID: 38709812 PMCID: PMC11073743 DOI: 10.1371/journal.pone.0302308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 04/02/2024] [Indexed: 05/08/2024] Open
Abstract
Rheumatoid arthritis causes joint inflammation due to immune abnormalities, resulting in joint pain and swelling. In recent years, there have been considerable advancements in the treatment of this disease. However, only approximately 60% of patients achieve remission. Patients with multifactorial diseases shift between states from day to day. Patients may remain in a good or poor state with few or no transitions, or they may switch between states frequently. The visualization of time-dependent state transitions, based on the evaluation axis of stable/unstable states, may provide useful information for achieving rheumatoid arthritis treatment goals. Energy landscape analysis can be used to quantitatively determine the stability/instability of each state in terms of energy. Time-series clustering is another method used to classify transitions into different groups to identify potential patterns within a time-series dataset. The objective of this study was to utilize energy landscape analysis and time-series clustering to evaluate multidimensional time-series data in terms of multistability. We profiled each patient's state transitions during treatment using energy landscape analysis and time-series clustering. Energy landscape analysis divided state transitions into two patterns: "good stability leading to remission" and "poor stability leading to treatment dead-end." The number of patients whose disease status improved increased markedly until approximately 6 months after treatment initiation and then plateaued after 1 year. Time-series clustering grouped patients into three clusters: "toward good stability," "toward poor stability," and "unstable." Patients in the "unstable" cluster are considered to have clinical courses that are difficult to predict; therefore, these patients should be treated with more care. Early disease detection and treatment initiation are important. The evaluation of state multistability enables us to understand a patient's current state in the context of overall state transitions related to rheumatoid arthritis drug treatment and to predict future state transitions.
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Affiliation(s)
- Keiichi Yamamoto
- Division of Data Science, Center for Industrial Research and Innovation, Translational Research Institute for Medical Innovation, Osaka Dental University, Hirakata City, Osaka, Japan
| | - Masahiko Sakaguchi
- Department of Engineering Informatics, Faculty of Information and Communication Engineering, Osaka Electro-Communication University, Neyagawa City, Osaka, Japan
| | - Akira Onishi
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
| | | | | | - Wataru Yamamoto
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
- Department of Health Information Management, Kurashiki Sweet Hospital, Nakasho, Kurashiki, Kurashiki City, Okayama Prefecture, Japan
| | - Hideo Onizawa
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
| | - Takayuki Fujii
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
| | - Koichi Murata
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
| | - Masao Tanaka
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
| | - Motomu Hashimoto
- Department of Clinical Immunology, Osaka Metropolitan University Graduate School of Medicine, Osaka City, Japan
| | - Shuichi Matsuda
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
| | - Akio Morinobu
- Department of Advanced Medicine for Rheumatic Diseases, Kyoto University Graduate School of Medicine, Sakyo, Kyoto, Japan
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Song S, Park J, Rho MJ. Effectiveness and intention to use a COVID-19 self-management app for epidemiological investigation: a web-based survey study. Front Public Health 2024; 12:1343734. [PMID: 38601508 PMCID: PMC11004299 DOI: 10.3389/fpubh.2024.1343734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 03/11/2024] [Indexed: 04/12/2024] Open
Abstract
Introduction Numerous COVID-19-related apps were widely used during the COVID-19 pandemic. Among them, those supporting epidemiological investigations were particularly useful. This study explored the effectiveness of apps that support epidemiological investigations, factors influencing users' intention to use them, and ways to encourage their use. Methods We developed and evaluated the KODARI app to demonstrate its importance in epidemiological investigations. After adapting a questionnaire based on an existing evaluation framework for COVID-19-related apps, we collected data from 276 participants through an online survey conducted between April 28 and May 25, 2023. We conducted two independent sample t-tests to determine the differences between each variable according to demographic characteristics and a multiple regression analysis to identify factors affecting intention to use. Results Users were generally satisfied with the KODARI. We observed differences in sex, age, marital status, occupational characteristics, and experience with epidemiological investigation. Females rated the app's information accuracy higher than males. Males had a higher intention to use than females. Participants aged under 35 years rated information accuracy and transparency highly, whereas single participants rated information accuracy higher than married participants. Occupational groups with frequent interactions with others evaluated their self-determination regarding the application. The app's self-determination was highly valued among participants with experience in epidemiological investigations. By investigating the factors affecting the intention to use the app, we confirmed that effectiveness, self-determination, and usability significantly affected the intention to use. Discussion This study demonstrated the effectiveness of app supporting epidemiological investigations, identified meaningful factors that influence intention to use, and confirmed the applicability of our new framework by considering the specificity of infectious disease situations such as COVID-19. This study provides a new basis for future epidemiological studies.
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Affiliation(s)
- Sihyun Song
- Department of Healthcare Service Management, Graduate School of Health and Welfare, Dankook University, Cheonan-si, Chungcheongnam-do, Republic of Korea
| | - Jihwan Park
- College of Liberal Arts, Dankook University, Cheonan-si, Chungcheongnam-do, Republic of Korea
| | - Mi Jung Rho
- College of Health Science, Dankook University, Cheonan-si, Chungcheongnam-do, Republic of Korea
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Helms YB, Stein ML, Hamdiui N, van der Meer A, Ferreira JA, Crutzen R, Timen A, Kretzschmar MEE. Determinants of Dutch public health professionals' intention to use digital contact tracing support tools: A cross-sectional online questionnaire study. PLOS DIGITAL HEALTH 2024; 3:e0000425. [PMID: 38354119 PMCID: PMC10866487 DOI: 10.1371/journal.pdig.0000425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/02/2023] [Indexed: 02/16/2024]
Abstract
Contact tracing (CT) can be a resource intensive task for public health services. To alleviate their workload and potentially accelerate the CT-process, public health professionals (PHPs) may transfer some tasks in the identification, notification, and monitoring of contacts to cases and their contacts themselves, using 'digital contact tracing support tools' (DCTS-tools). In this study, we aimed to identify determinants of PHPs' intention to use DCTS-tools. Between February and April 2022, we performed a cross-sectional online questionnaire study among PHPs involved in CT for COVID-19 in the Netherlands. We built three random forest models to identify determinants of PHPs' intention to use DCTS-tools for the identification, notification, and monitoring of contacts, respectively. The online questionnaire was completed by 641 PHPs. Most respondents had a positive intention towards using DCTS-tools for the identification (64.5%), notification (58%), and monitoring (55.2%) of contacts. Random forest models were able to correctly predict the intention of 81%, 80%, and 81% of respondents to use DCTS-tools for the identification, notification, and monitoring of contacts, respectively. Top-determinants of having a positive intention are the anticipated effect of DCTS-tools on the feasibility and efficiency of CT (speed, workload, difficulty), the degree to which PHPs anticipated that cases and contacts may find it pleasant and may be willing to participate in CT using DCTS-tools, and the degree to which PHPs anticipated that cases and contacts are sufficiently supported in CT when using DCTS-tools. Most PHPs have a positive intention to involve cases and their contacts in the identification, notification, and monitoring stages of the CT-process through DCTS-tools. The identified top-determinants should be prioritized in the (future) development and implementation of DCTS-tools in public health practice. Citizens' perspectives on the use of DCTS-tools should be investigated in future research.
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Affiliation(s)
- Yannick B. Helms
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Mart L. Stein
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Nora Hamdiui
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Akke van der Meer
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - José A. Ferreira
- Department of Statistics, Informatics and Modelling, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Rik Crutzen
- Department of Health Promotion, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Aura Timen
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Primary and Community Care, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mirjam E. E. Kretzschmar
- Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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Garavand A, Ameri F, Salehi F, Talebi AH, Karbasi Z, Sabahi A. A Systematic Review of Health Management Mobile Applications in COVID-19 Pandemic: Features, Advantages, and Disadvantages. BIOMED RESEARCH INTERNATIONAL 2024; 2024:8814869. [PMID: 38230030 PMCID: PMC10791194 DOI: 10.1155/2024/8814869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 12/01/2023] [Accepted: 12/28/2023] [Indexed: 01/18/2024]
Abstract
Introduction With the increasing accessibility of smartphones, their use has been considered in healthcare services. Mobile applications have played a pivotal role in providing health services during COVID-19. This study is aimed at identifying the features, advantages, and disadvantages of health management mobile applications during COVID-19. Methods This systematic review was conducted in PubMed, Scopus, and Web of Science using the related keywords up to November 2021. The original articles in English about the health management mobile applications in COVID-19 were selected. The study selection was done by two researchers independently according to inclusion and exclusion criteria. Data extraction was done using a data extraction form, and the results were summarized and reported in related tables and figures. Results Finally, 12 articles were included based on the criteria. The benefits of mobile health applications for health management during COVID-19 were in four themes and 19 subthemes, and the most advantages of the application were in disease management and the possibility of recording information by users, digital tracking of calls, and data confidentiality. Furthermore, the disadvantages of them have been presented in two themes and 14 subthemes. The most common disadvantages are reduced adherence to daily symptom reports, personal interpretation of questions, and result bias. Conclusion The study results showed that mobile applications have been effective in controlling the prevalence of COVID-19 by identifying virus-infested environments, identifying and monitoring infected people, controlling social distancing, and maintaining quarantine. It is suggested that usability, ethical and security considerations, protection of personal information, and privacy of users be considered in application design and development.
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Affiliation(s)
- Ali Garavand
- Health Information Management, Department of Health Information Technology, School of Allied Medical Sciences, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Fatemeh Ameri
- Health Information Technology, Student Research Committee, Department of Health Information Technology, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Fatemeh Salehi
- Health Information Management, Emam Reza Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Ali Hajipour Talebi
- Health Information Technology Expert, AJA University of Medical Sciences, Tehran, Iran
| | - Zahra Karbasi
- Health Information Management, School of Management and Medical Informatics, Kerman University of Medical Sciences, Kerman, Iran
| | - Azam Sabahi
- Health Information Management, Department of Health Information Technology, Ferdows School of Health and Allied Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran
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Alsahli S, Hor SY, Lam M. Factors Influencing the Acceptance and Adoption of Mobile Health Apps by Physicians During the COVID-19 Pandemic: Systematic Review. JMIR Mhealth Uhealth 2023; 11:e50419. [PMID: 37938873 PMCID: PMC10666016 DOI: 10.2196/50419] [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: 06/30/2023] [Revised: 09/13/2023] [Accepted: 10/04/2023] [Indexed: 11/10/2023] Open
Abstract
BACKGROUND During the COVID-19 pandemic, the provision of and access to health care have been uniquely challenging, particularly during lockdowns or when dealing with COVID-19 cases. Health care professionals have had to provide patients with the necessary health care. However, delivering health care services while reducing face-to-face interaction puts an immense strain on health systems that are already overburdened. Against this backdrop, it is now more critical than ever to ensure the accessibility of health care services. Such access has been made increasingly available through mobile health (mHealth) apps. These apps have the potential to significantly improve health care outcomes and expectations and address some of the challenges confronting health care systems worldwide. Despite the advantages of mHealth, its acceptance and adoption remain low. Hence, health care organizations must consider the perceptions and opinions of physicians if the technology is to be successfully implemented. OBJECTIVE The objective of this systematic review was to explore and synthesize the scientific literature on the factors influencing the acceptance and adoption of mHealth among physicians during the COVID-19 pandemic. METHODS A systematic review of the studies published between March 2020 and December 2022 was conducted using the MEDLINE, Scopus, Embase, and ProQuest databases. The database search yielded an initial sample of 455 potential publications for analysis, of which 9 (2%) met the inclusion criteria. The methodology of this review was based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). RESULTS The factors influencing mHealth acceptance and adoption by physicians were divided into perceived barriers and perceived facilitators, which were further grouped into the following 3 major thematic categories: technological, individual, and organizational barriers and facilitators, respectively. The technological barriers were accessibility, technical issues, usefulness, and data management; individual barriers were perceived patient barriers, time and workload pressure, technical literacy, knowledge of mHealth, and peer support; and organizational barriers were financial factors, management support and engagement, data security, telemonitoring policy, and collaboration. The technological facilitators of uptake were technical factors, clinical usefulness, and data management; individual facilitators were patient-related care, intrinsic motivation, collaboration, and data sharing (individual); and organizational facilitators were workflow-related determinants, organizational financial support, recommendation of mHealth services, and evidence-based guidelines. CONCLUSIONS This review summarized the evidence on the factors influencing mHealth acceptance and adoption by physicians during the COVID-19 pandemic. The main findings highlighted the importance of addressing organizational readiness to support physicians with adequate resources, shifting the focus from technological to patient-centered factors, and the seamless integration of mHealth into routine practice during and beyond the pandemic. TRIAL REGISTRATION PROSPERO CRD42022356125; https://tinyurl.com/2mmhn5yu.
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Affiliation(s)
- Sultan Alsahli
- School of Public Health, Faculty of Health, University of Technology Sydney, Sydney, Australia
- Department of Health Information Technology and Management, College of Public Health and Health Informatics, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Su-Yin Hor
- School of Public Health, Faculty of Health, University of Technology Sydney, Sydney, Australia
| | - Mary Lam
- Department of Health and Biomedical Sciences, STEM College, RMIT University, Melbourne, Australia
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Asadi F, Rahimi F, Ghaderkhany S, Almasi S. Self-care for coronavirus disease through electronic health technologies: A scoping review. Health Sci Rep 2023; 6:e1122. [PMID: 36824616 PMCID: PMC9941480 DOI: 10.1002/hsr2.1122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/06/2023] [Accepted: 02/07/2023] [Indexed: 02/25/2023] Open
Abstract
Background and Aims Considering the rapid spread and transmission of COVID-19 and its high mortality rate, self-care practices are of special importance during this pandemic to prevent and control the spread of the virus. In this regard, electronic health systems can play a major role in improving self-care practices related to coronavirus disease. This study aimed to review the electronic health technologies used in each of the constituent elements of the self-care (self-care maintenance, self-care monitoring, and self-care management) during the COVID-19 pandemic. Methods This scoping review was conducted based on Arksey and O'Malley's framework. In this study, the specific keywords related to "electronic health," "self-care," and "COVID-19" were searched on PubMed, Web of Science, Scopus, and Google. Results Of the 47 articles reviewed, most articles (27 articles) were about self-care monitoring and aimed to monitor the vital signs of patients. The results showed that the use of electronic health tools mainly focuses on training in the control and prevention of coronavirus disease during this pandemic, in the field of self-care maintenance, and medication management, communication, and consultation with healthcare providers, in the field of self-care management. Moreover, the most commonly used electronic health technologies were mobile web applications, smart vital signs monitoring devices, and social networks, respectively. Conclusion The study findings suggested that the use of electronic health technologies, such as mobile web applications and social networks, can effectively improve self-care practices for coronavirus disease. In addition, such technologies can be applied by health policymakers and disease control and prevention centers to better manage the COVID-19 pandemic.
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Affiliation(s)
- Farkhondeh Asadi
- Department of Health Information Technology and Management, School of Allied Medical SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Fatemeh Rahimi
- Department of Health Information Technology and Management, School of Allied Medical SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Shady Ghaderkhany
- Clinical Research Development Unit, Kowsar Medical, Educational and Therapeutic CenterKurdistan University of Medical SciencesSanandajIran
| | - Sohrab Almasi
- Department of Health Information Technology and Management, Health Information Management, School of Allied Medical SciencesShahid Beheshti University of Medical SciencesTehranIran
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Karthan M, Martin R, Holl F, Swoboda W, Kestler HA, Pryss R, Schobel J. Enhancing mHealth data collection applications with sensing capabilities. Front Public Health 2022; 10:926234. [PMID: 36187627 PMCID: PMC9521646 DOI: 10.3389/fpubh.2022.926234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/11/2022] [Indexed: 01/24/2023] Open
Abstract
Smart mobile devices such as smartphones or tablets have become an important factor for collecting data in complex health scenarios (e.g., psychological studies, medical trials), and are more and more replacing traditional pen-and-paper instruments. However, simply digitizing such instruments does not yet realize the full potential of mobile devices: most modern smartphones have a variety of different sensor technologies (e.g., microphone, GPS data, camera, ...) that can also provide valuable data and potentially valuable insights for the medical purpose or the researcher. In this context, a significant development effort is required to integrate sensing capabilities into (existing) data collection applications. Developers may have to deal with platform-specific peculiarities (e.g., Android vs. iOS) or proprietary sensor data formats, resulting in unnecessary development effort to support researchers with such digital solutions. Therefore, a cross-platform mobile data collection framework has been developed to extend existing data collection applications with sensor capabilities and address the aforementioned challenges in the process. This framework will enable researchers to collect additional information from participants and environment, increasing the amount of data collected and drawing new insights from existing data.
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Affiliation(s)
- Maximilian Karthan
- DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany,Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany,*Correspondence: Maximilian Karthan
| | - Robin Martin
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
| | - Felix Holl
- DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany,Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilian University of Munich, Munich, Germany
| | - Walter Swoboda
- DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany
| | - Hans A. Kestler
- Institute of Medical Systems Biology, Ulm University, Ulm, Germany
| | - Rüdiger Pryss
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
| | - Johannes Schobel
- DigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany
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Wang Z, Xiong H, Tang M, Boukhechba M, Flickinger TE, Barnes LE. Mobile Sensing in the COVID-19 Era: A Review. HEALTH DATA SCIENCE 2022; 2022:9830476. [PMID: 36408201 PMCID: PMC9629686 DOI: 10.34133/2022/9830476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/18/2022] [Indexed: 12/03/2022]
Abstract
Background During the COVID-19 pandemic, mobile sensing and data analytics techniques have demonstrated their capabilities in monitoring the trajectories of the pandemic, by collecting behavioral, physiological, and mobility data on individual, neighborhood, city, and national scales. Notably, mobile sensing has become a promising way to detect individuals' infectious status, track the change in long-term health, trace the epidemics in communities, and monitor the evolution of viruses and subspecies. Methods We followed the PRISMA practice and reviewed 60 eligible papers on mobile sensing for monitoring COVID-19. We proposed a taxonomy system to summarize literature by the time duration and population scale under mobile sensing studies. Results We found that existing literature can be naturally grouped in four clusters, including remote detection, long-term tracking, contact tracing, and epidemiological study. We summarized each group and analyzed representative works with regard to the system design, health outcomes, and limitations on techniques and societal factors. We further discussed the implications and future directions of mobile sensing in communicable diseases from the perspectives of technology and applications. Conclusion Mobile sensing techniques are effective, efficient, and flexible to surveil COVID-19 in scales of time and populations. In the post-COVID era, technical and societal issues in mobile sensing are expected to be addressed to improve healthcare and social outcomes.
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Affiliation(s)
- Zhiyuan Wang
- School of Engineering and Applied Science, University of Virginia, Charlottesville, USA
| | - Haoyi Xiong
- Big Data Lab, Baidu Research, Baidu Inc., BeijingChina
| | - Mingyue Tang
- School of Engineering and Applied Science, University of Virginia, Charlottesville, USA
| | - Mehdi Boukhechba
- School of Engineering and Applied Science, University of Virginia, Charlottesville, USA
| | - Tabor E. Flickinger
- Department of Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - Laura E. Barnes
- School of Engineering and Applied Science, University of Virginia, Charlottesville, USA
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Shimizu N, Kotani K. Health information exchange in relation to point-of-care testing in home care: Issues in Japan. Clin Chim Acta 2022; 532:10-12. [PMID: 35594920 DOI: 10.1016/j.cca.2022.05.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/10/2022] [Accepted: 05/13/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Laboratory tests, especially point-of-care testing (POCT), and related health information exchange (HIE) are necessary for patient management in the home care setting, where clinic-hospital cooperation and interprofessional collaboration are important. METHODS We raised the issues ahead of HIE in relation to POCT in home care in Japan, including issues in electronic medical record use, localized interprofessional collaboration networks with information and communication technology, personal health record use and open connectivity. RESULTS HIE system may depend on the initiatives of expert communities with non-expert partnership, as well as national healthcare policies. CONCLUSION We promote future challenges in this growing area.
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Affiliation(s)
- Nayuta Shimizu
- Division of Community and Family Medicine, Center for Community Medicine, Jichi Medical University, Shimotsuke-City, Japan
| | - Kazuhiko Kotani
- Division of Community and Family Medicine, Center for Community Medicine, Jichi Medical University, Shimotsuke-City, Japan; Department of Clinical Laboratory Medicine, Faculty of Medicine, Jichi Medical University, Shimotsuke-City, Japan.
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Harahap NC, Handayani PW, Hidayanto AN. Barriers and facilitators of personal health record adoption in Indonesia: Health facilities' perspectives. Int J Med Inform 2022; 162:104750. [PMID: 35339888 DOI: 10.1016/j.ijmedinf.2022.104750] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 03/16/2022] [Accepted: 03/18/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Personal health record (PHR) has been extensively used in developed countries; however, it has been limitedly adopted in developing countries. This study was conducted in Indonesia: a developing country with the largest population in Southeast Asia. PHR that is integrated with health providers is needed to achieve a transformation from a health provider-centered to a patient-centered healthcare system. OBJECTIVE To qualitatively analyze barriers and facilitators of PHR adoption by health facilities in Indonesia from the technological, organizational, environmental, and individual factors. METHODS In this qualitative study, we used semi-structured interviews with three health facility directors, 17 IT heads, eight physicians, and three nurses from 10 primary healthcare facilities, nine government hospitals, and six private hospitals in Indonesia. Interview data were analyzed using thematic analysis in NVivo 12. The analysis stages involved familiarizing data, generating initial codes, searching themes, evaluating themes, defining and naming themes, and writing reports. RESULTS Regarding technological factors, the barriers to PHR adoption include security and privacy, interoperability, and infrastructure. Organizational support can facilitate PHR adoption in terms of organizational factors, while a lack of human resources is a barrier to PHR adoption. Regarding environmental factors, the lack of government regulations is the barrier to PHR adoption, while competition between health facilities and vendor support could facilitate PHR adoption. Finally, regarding individual factors, perceived usefulness and ease of use can be facilitators of PHR adoption, while user attitudes and e-health literacy can be barriers to PHR adoption. CONCLUSIONS This study is expected to comprehensively understand PHR adoption in Indonesia and could be applied to other developing countries with similar technological, legal, or cultural characteristics as Indonesia. This study also provides information that can guide health regulators, health facilities, or PHR vendors in planning the implementation of integrated PHR.
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Affiliation(s)
| | - Putu Wuri Handayani
- Faculty of Computer Science, University of Indonesia, Depok 16424, Indonesia.
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12
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The Impact of Using mHealth Apps on Improving Public Health Satisfaction during the COVID-19 Pandemic: A Digital Content Value Chain Perspective. Healthcare (Basel) 2022; 10:healthcare10030479. [PMID: 35326957 PMCID: PMC8954858 DOI: 10.3390/healthcare10030479] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 02/23/2022] [Accepted: 03/01/2022] [Indexed: 11/17/2022] Open
Abstract
The use of mobile technology and equipment has been found to be successful in the governance of public health. In the context of the coronavirus disease 2019 (COVID-19) pandemic, mobile health (mhealth) apps are expected to play an important role in the governance of public health. This study establishes a structural equation model based on the digital content value chain framework, identifies the main values created by mhealth apps in the prevention and control of COVID-19, and surveys 500 citizens of China. The data were analyzed using an independent t-test and partial least squares structural equations (PLS-SEM). The results showed that people who use mhealth apps are more satisfied with public health governance than those who do not; the healthcare assurance value of mhealth apps and healthcare confidence positively influence the interaction between users and mhealth app functions, the interaction with information, and the interaction with doctors to improve users’ satisfaction with public health governance; and the parasocial relationships between doctors and users of mhealth apps positively affect the interactions between users and doctors to improve users’ satisfaction with public health governance. This study confirms the potential of mhealth apps toward improving public health governance during the COVID-19 pandemic from a new perspective and provides a new theoretical basis whereby mobile technology can contribute toward improving public health governance.
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Mohammad H, Elham M, Mehraeen E, Aghamohammadi V, Seyedalinaghi S, Kalantari S, Nahid M, Nasiri K. Identifying data elements and key features of a mobile-based self-care application for patients with COVID-19 in Iran. Health Informatics J 2021; 27:14604582211065703. [PMID: 34936526 DOI: 10.1177/14604582211065703] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Mobile Health applications have shown different usages in the COVID-19 pandemic, which consisted of empowering patient's awareness, promoting patient's self-care, and self-monitor behaviors. The purpose of this study is to identify key features and capabilities of a mobile-based application for self-care and self-management of people with COVID-19 disease. This study was a descriptive-analytical study that was conducted in two main phases in 2020. In the first phase, a literature review study was performed. In the second phase, using the information obtained from the review of similar articles, a questionnaire was designed to validate identified requirements. Based on the results of the first phase, 53 data elements and technical key features for mobile-based self-care application for people with COVID-19 were identified. According to the statistical population, 11 data elements for demographic requirements, 11 data elements for clinical requirements, 15 data elements for self-care specifications, and 16 features for the technical capability of this app were determined. Most of the items were selected by infectious and internal medicine specialists (94%). This study supports that the use of mobile-based applications can play an important role in the management of this disease. Software design and development could help manage and improve patients' health status.
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Affiliation(s)
- Heydari Mohammad
- Department of Health Information Technology, Khalkhal University of Medical Sciences, Khalkhal, Iran
| | - Monaghesh Elham
- Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Khalkhal, Iran
| | - Esmaeil Mehraeen
- Department of Health Information Technology, 48439Tehran University of Medical Sciences, Khalkhal, Iran
| | - Vahideh Aghamohammadi
- Department of Nutrition, 6339Khalkhal University of Medical Sciences, Khalkhal, Iran
| | - Seyedahmad Seyedalinaghi
- Iranian Research Center for HIV/AIDS, Iranian Institute for Reduction of High Risk Behaviors, 48439Tehran University of Medical Sciences, Tehran, Iran
| | - Saieed Kalantari
- Antimicrobial Resistance Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Mehrabi Nahid
- Assistant Professor of Health information management, Aja University of Medical Sciences (AUMS), Aja, Iran
| | - Khadije Nasiri
- Department of Medical- Surgical Nursing, Khalkhal University of Medical Sciences, Khalkhal, Iran
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14
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Thomas Craig KJ, Rizvi R, Willis VC, Kassler WJ, Jackson GP. Effectiveness of Contact Tracing for Viral Disease Mitigation and Suppression: Evidence-Based Review. JMIR Public Health Surveill 2021; 7:e32468. [PMID: 34612841 PMCID: PMC8496751 DOI: 10.2196/32468] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/02/2021] [Accepted: 09/07/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Contact tracing in association with quarantine and isolation is an important public health tool to control outbreaks of infectious diseases. This strategy has been widely implemented during the current COVID-19 pandemic. The effectiveness of this nonpharmaceutical intervention is largely dependent on social interactions within the population and its combination with other interventions. Given the high transmissibility of SARS-CoV-2, short serial intervals, and asymptomatic transmission patterns, the effectiveness of contact tracing for this novel viral agent is largely unknown. OBJECTIVE This study aims to identify and synthesize evidence regarding the effectiveness of contact tracing on infectious viral disease outcomes based on prior scientific literature. METHODS An evidence-based review was conducted to identify studies from the PubMed database, including preprint medRxiv server content, related to the effectiveness of contact tracing in viral outbreaks. The search dates were from database inception to July 24, 2020. Outcomes of interest included measures of incidence, transmission, hospitalization, and mortality. RESULTS Out of 159 unique records retrieved, 45 (28.3%) records were reviewed at the full-text level, and 24 (15.1%) records met all inclusion criteria. The studies included utilized mathematical modeling (n=14), observational (n=8), and systematic review (n=2) approaches. Only 2 studies considered digital contact tracing. Contact tracing was mostly evaluated in combination with other nonpharmaceutical interventions and/or pharmaceutical interventions. Although some degree of effectiveness in decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality was observed, these results were highly dependent on epidemic severity (R0 value), number of contacts traced (including presymptomatic and asymptomatic cases), timeliness, duration, and compliance with combined interventions (eg, isolation, quarantine, and treatment). Contact tracing effectiveness was particularly limited by logistical challenges associated with increased outbreak size and speed of infection spread. CONCLUSIONS Timely deployment of contact tracing strategically layered with other nonpharmaceutical interventions could be an effective public health tool for mitigating and suppressing infectious outbreaks by decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality.
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Affiliation(s)
- Kelly Jean Thomas Craig
- Center for AI, Research, and Evaluation, IBM Watson Health, IBM Corporation, Cambridge, MA, United States
| | - Rubina Rizvi
- Center for AI, Research, and Evaluation, IBM Watson Health, IBM Corporation, Cambridge, MA, United States
| | - Van C Willis
- Center for AI, Research, and Evaluation, IBM Watson Health, IBM Corporation, Cambridge, MA, United States
| | - William J Kassler
- Center for AI, Research, and Evaluation, IBM Watson Health, IBM Corporation, Cambridge, MA, United States
- Palantir Technologies, Denver, CO, United States
| | - Gretchen Purcell Jackson
- Center for AI, Research, and Evaluation, IBM Watson Health, IBM Corporation, Cambridge, MA, United States
- Vanderbilt University Medical Center, Nashville, TN, United States
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15
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Quiroz-Juárez MA, Torres-Gómez A, Hoyo-Ulloa I, León-Montiel RDJ, U’Ren AB. Identification of high-risk COVID-19 patients using machine learning. PLoS One 2021; 16:e0257234. [PMID: 34543294 PMCID: PMC8452016 DOI: 10.1371/journal.pone.0257234] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 08/26/2021] [Indexed: 12/21/2022] Open
Abstract
The current COVID-19 public health crisis, caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), has produced a devastating toll both in terms of human life loss and economic disruption. In this paper we present a machine-learning algorithm capable of identifying whether a given patient (actually infected or suspected to be infected) is more likely to survive than to die, or vice-versa. We train this algorithm with historical data, including medical history, demographic data, as well as COVID-19-related information. This is extracted from a database of confirmed and suspected COVID-19 infections in Mexico, constituting the official COVID-19 data compiled and made publicly available by the Mexican Federal Government. We demonstrate that the proposed method can detect high-risk patients with high accuracy, in each of four identified clinical stages, thus improving hospital capacity planning and timely treatment. Furthermore, we show that our method can be extended to provide optimal estimators for hypothesis-testing techniques commonly-used in biological and medical statistics. We believe that our work could be of use in the context of the current pandemic in assisting medical professionals with real-time assessments so as to determine health care priorities.
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Affiliation(s)
- Mario A. Quiroz-Juárez
- Departamento de Física, Universidad Autónoma Metropolitana Unidad Iztapalapa, Ciudad de México, México
- * E-mail:
| | | | | | | | - Alfred B. U’Ren
- Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Ciudad de México, México
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16
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Abd-Alrazaq A, Hassan A, Abuelezz I, Ahmed A, Alzubaidi MS, Shah U, Alhuwail D, Giannicchi A, Househ M. Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review. J Med Internet Res 2021; 23:e29136. [PMID: 34406962 PMCID: PMC8767979 DOI: 10.2196/29136] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 04/28/2021] [Accepted: 06/20/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Technologies have been extensively implemented to provide health care services for all types of clinical conditions during the COVID-19 pandemic. While several reviews have been conducted regarding technologies used during the COVID-19 pandemic, they were limited by focusing either on a specific technology (or features) or proposed rather than implemented technologies. OBJECTIVE This review aims to provide an overview of technologies, as reported in the literature, implemented during the first wave of the COVID-19 pandemic. METHODS We conducted a scoping review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Extension for Scoping Reviews. Studies were retrieved by searching 8 electronic databases, checking the reference lists of included studies and relevant reviews (backward reference list checking), and checking studies that cited included studies (forward reference list checking). The search terms were chosen based on the target intervention (ie, technologies) and the target disease (ie, COVID-19). We included English publications that focused on technologies or digital tools implemented during the COVID-19 pandemic to provide health-related services regardless of target health condition, user, or setting. Two reviewers independently assessed the eligibility of studies and extracted data from eligible papers. We used a narrative approach to synthesize extracted data. RESULTS Of 7374 retrieved papers, 126 were deemed eligible. Telemedicine was the most common type of technology (107/126, 84.9%) implemented in the first wave of the COVID-19 pandemic, and the most common mode of telemedicine was synchronous (100/108, 92.6%). The most common purpose of the technologies was providing consultation (75/126, 59.5%), followed by following up with patients (45/126, 35.7%), and monitoring their health status (22/126, 17.4%). Zoom (22/126, 17.5%) and WhatsApp (12/126, 9.5%) were the most commonly used videoconferencing and social media platforms, respectively. Both health care professionals and health consumers were the most common target users (103/126, 81.7%). The health condition most frequently targeted was COVID-19 (38/126, 30.2%), followed by any physical health conditions (21/126, 16.7%), and mental health conditions (13/126, 10.3%). Technologies were web-based in 84.1% of the studies (106/126). Technologies could be used through 11 modes, and the most common were mobile apps (86/126, 68.3%), desktop apps (73/126, 57.9%), telephone calls (49/126, 38.9%), and websites (45/126, 35.7%). CONCLUSIONS Technologies played a crucial role in mitigating the challenges faced during the COVID-19 pandemic. We did not find papers describing the implementation of other technologies (eg, contact-tracing apps, drones, blockchain) during the first wave. Furthermore, technologies in this review were used for other purposes (eg, drugs and vaccines discovery, social distancing, and immunity passport). Future research on studies on these technologies and purposes is recommended, and further reviews are required to investigate technologies implemented in subsequent waves of the pandemic.
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Affiliation(s)
- Alaa Abd-Alrazaq
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Asmaa Hassan
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Israa Abuelezz
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Arfan Ahmed
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Mahmood Saleh Alzubaidi
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Uzair Shah
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
| | - Dari Alhuwail
- Information Science Department, Kuwait University, Kuwait, Kuwait
- Health Informatics Unit, Dasman Diabetes Institute, Kuwait, Kuwait
| | - Anna Giannicchi
- School of Professional Studies, Berkeley College, New York, NY, United States
| | - Mowafa Househ
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar
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Xiao D, Song C, Nakamura N, Nakayama M. Development of an application concerning fast healthcare interoperability resources based on standardized structured medical information exchange version 2 data. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 208:106232. [PMID: 34174764 DOI: 10.1016/j.cmpb.2021.106232] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 06/02/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVE A mobile application for personal health records (PHR) would allow patients to access their clinical data easily. When PHR connects with multiple electronic health records (EHRs), doctors and patients can exchange large quantities of patient data from the EHR (e.g., medication list, diagnoses, allergies, and laboratory data). Furthermore, personal daily records can also be retrieved from PHR (e.g., blood pressure, pulse, dietary habits, and exercise). However, no standard interoperability between EHRs and PHR has been established. This study aims to convert clinical data in EHRs into the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) data format while developing a PHR application to present the FHIR data. METHODS In Japan, Standardized Structured Medical Information eXchange version 2 (SS-MIX2) is typically utilized as a health information exchange to preserve and elicit clinical data from EHRs. We converted clinical data in the SS-MIX2 storage at Tohoku University Hospital into the FHIR repository server using the R4 standard. Additionally, we used the Swift programming language to build a PHR application. RESULTS We converted patients' basic information, disease names, diagnostic reports, prescriptions, and injection data from the SS-MIX2 to the FHIR server. Besides, we launched a PHR application that could retrieve data from the FHIR server to display patients' clinical information. CONCLUSIONS Our work demonstrated the conversion of SS-MIX2 data into the FHIR and presented them with our PHR application. This mechanism may be useful to accelerate the sharing of clinical information among doctors and patients.
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Affiliation(s)
- Dingding Xiao
- Department of Medical Informatics, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan
| | - Chong Song
- Department of Medical Informatics, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan; Medical Information Technology Center, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan
| | - Naoki Nakamura
- Medical Information Technology Center, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan
| | - Masaharu Nakayama
- Department of Medical Informatics, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan; Medical Information Technology Center, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8574, Japan.
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18
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Park J, Han J, Kim Y, Rho MJ. Development, Acceptance, and Concerns Surrounding App-Based Services to Overcome the COVID-19 Outbreak in South Korea: Web-Based Survey Study. JMIR Med Inform 2021; 9:e29315. [PMID: 34137726 PMCID: PMC8330629 DOI: 10.2196/29315] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 05/16/2021] [Accepted: 06/17/2021] [Indexed: 02/06/2023] Open
Abstract
Background Since the COVID-19 outbreak, South Korea has been engaged in various efforts to overcome the pandemic. One of them is to provide app-based COVID-19–related services to the public. As the pandemic continues, a need for various apps has emerged, including COVID-19 apps that can support activities aimed at overcoming the COVID-19 pandemic. Objective We aimed to determine which apps were considered the most necessary according to users and evaluate the current status of the development of COVID-19–related apps in South Korea. We also aimed to determine users’ acceptance and concerns related to using apps to support activities to combat COVID-19. Methods We collected data from 1148 users from a web-based survey conducted between November 11 and December 6, 2020. Basic statistical analysis, multiple response analysis, and the Wilcoxon rank sum test were performed using R software. We then manually classified the current status of the development of COVID-19–related apps. Results In total, 68.4% (785/1148) of the respondents showed high willingness to protect themselves from COVID-19 by using related apps. Users considered the epidemiological investigation app to be the most necessary app (709/1148, 61.8%) overall, followed by the self-management app for self-isolation (613/1148, 53.4%), self-route management app (605/1148, 52.7%), COVID-19 symptom management app (483/1148, 42.1%), COVID-19–related information provision app (339/1148, 29.5%), and mental health management app (270/1148, 23.5%). Despite the high intention to use these apps, users were also concerned about privacy issues and media exposure. Those who had an underlying disease and had experience using COVID-19–related apps showed significantly higher intentions to use those apps (P=.05 and P=.01, respectively). Conclusions Targeting users is very important in order to design and develop the most necessary apps. Furthermore, to gain the public’s trust and make the apps available to as many people as possible, it is vital to develop diverse apps in which privacy protection is maximized.
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Affiliation(s)
- Jihwan Park
- School of Software Convergence, College of Software Convergence, Dankook University, Yongin-si, Republic of Korea
| | - Jinhyun Han
- Department of Urology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yerin Kim
- Department of Korean Language and Literature, The Anyang University of Korea, Anyang-si, Republic of Korea
| | - Mi Jung Rho
- Department of Urology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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19
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Harahap NC, Handayani PW, Hidayanto AN. Functionalities and Issues in the Implementation of Personal Health Records: Systematic Review. J Med Internet Res 2021; 23:e26236. [PMID: 34287210 PMCID: PMC8339989 DOI: 10.2196/26236] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 03/07/2021] [Accepted: 05/24/2021] [Indexed: 12/28/2022] Open
Abstract
Background Functionalities of personal health record (PHR) are evolving, and continued discussions about PHR functionalities need to be performed to keep it up-to-date. Technological issues such as nonfunctional requirements should also be discussed in the implementation of PHR. Objective This study systematically reviewed the main functionalities and issues in implementing the PHR. Methods This systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The search is performed using the online databases Scopus, ScienceDirect, IEEE, MEDLINE, CINAHL, and PubMed for English journal articles and conference proceedings published between 2015 and 2020. Results A total of 105 articles were selected in the review. Seven function categories were identified in this review, which is grouped into basic and advanced functions. Health records and administrative records were grouped into basic functions. Medication management, communication, appointment management, education, and self-health monitoring were grouped into advanced functions. The issues found in this study include interoperability, security and privacy, usability, data quality, and personalization. Conclusions In addition to PHR basic and advanced functions, other supporting functionalities may also need to be developed based on the issues identified in this study. This paper provides an integrated PHR architectural model that describes the functional requirements and data sources of PHRs.
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Khoshrounejad F, Hamednia M, Mehrjerd A, Pichaghsaz S, Jamalirad H, Sargolzaei M, Hoseini B, Aalaei S. Telehealth-Based Services During the COVID-19 Pandemic: A Systematic Review of Features and Challenges. Front Public Health 2021; 9:711762. [PMID: 34350154 PMCID: PMC8326459 DOI: 10.3389/fpubh.2021.711762] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 06/21/2021] [Indexed: 01/11/2023] Open
Abstract
Background: As an ever-growing popular service, telehealth catered for better access to high-quality healthcare services. It is more valuable and cost-effective, particularly in the middle of the current COVID-19 pandemic. Accordingly, this study aimed to systematically review the features and challenges of telehealth-based services developed to support COVID-19 patients and healthcare providers. Methods: A comprehensive search was done for the English language and peer-reviewed articles published until November 2020 using PubMed and Scopus electronic databases. In this review paper, only studies focusing on the telehealth-based service to support COVID-19 patients and healthcare providers were included. The first author's name, publication year, country of the research, study objectives, outcomes, function type including screening, triage, prevention, diagnosis, treatment or follow-up, target population, media, communication type, guideline-based design, main findings, and challenges were extracted, classified, and tabulated. Results: Of the 5,005 studies identified initially, 64 met the eligibility criteria. The studies came from 18 countries. Most of them were conducted in the United States and China. Phone calls, mobile applications, videoconferencing or video calls, emails, websites, text messages, mixed-reality, and teleradiology software were used as the media for communication. The majority of studies used a synchronous communication. The articles addressed the prevention, screening, triage, diagnosis, treatment, and follow-up aspects of COVID-19 which the most common purpose was the patients' follow-up (34/64, 53%). Thirteen group barriers were identified in the literature, which technology acceptance and user adoption, concerns about the adequacy and accuracy of subjective patient assessment, and technical issues were the most frequent ones. Conclusion: This review revealed the usefulness of telehealth-based services during the COVID-19 outbreak and beyond. The features and challenges identified through the literature can be helpful for a better understanding of current telehealth approaches and pointed out the need for clear guidelines, scientific evidence, and innovative policies to implement successful telehealth projects.
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Affiliation(s)
- Farnaz Khoshrounejad
- Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mahsa Hamednia
- Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Ameneh Mehrjerd
- Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Shima Pichaghsaz
- Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hossein Jamalirad
- Department of Computer Engineering, Ayatollah Amoli University, Science and Research Branch, Amol, Iran
| | - Mahdi Sargolzaei
- Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Benyamin Hoseini
- Pharmaceutical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Shokoufeh Aalaei
- Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
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21
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Hogan K, Macedo B, Macha V, Barman A, Jiang X. Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation. JMIR Med Inform 2021; 9:e27449. [PMID: 34254937 PMCID: PMC8291141 DOI: 10.2196/27449] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 04/03/2021] [Accepted: 04/14/2021] [Indexed: 02/06/2023] Open
Abstract
The global and national response to the COVID-19 pandemic has been inadequate due to a collective lack of preparation and a shortage of available tools for responding to a large-scale pandemic. By applying lessons learned to create better preventative methods and speedier interventions, the harm of a future pandemic may be dramatically reduced. One potential measure is the widespread use of contact tracing apps. While such apps were designed to combat the COVID-19 pandemic, the time scale in which these apps were deployed proved a significant barrier to efficacy. Many companies and governments sprinted to deploy contact tracing apps that were not properly vetted for performance, privacy, or security issues. The hasty development of incomplete contact tracing apps undermined public trust and negatively influenced perceptions of app efficacy. As a result, many of these apps had poor voluntary public uptake, which greatly decreased the apps' efficacy. Now, with lessons learned from this pandemic, groups can better design and test apps in preparation for the future. In this viewpoint, we outline common strategies employed for contact tracing apps, detail the successes and shortcomings of several prominent apps, and describe lessons learned that may be used to shape effective contact tracing apps for the present and future. Future app designers can keep these lessons in mind to create a version that is suitable for their local culture, especially with regard to local attitudes toward privacy-utility tradeoffs during public health crises.
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Affiliation(s)
- Katie Hogan
- Department of Bioengineering, Rice University, Houston, TX, United States
| | - Briana Macedo
- School of Engineering, Princeton University, Princeton, NJ, United States
| | - Venkata Macha
- School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Arko Barman
- Department of Electrical & Computer Engineering, Rice University, Houston, TX, United States
- Data to Knowledge Lab, Rice University, Houston, TX, United States
| | - Xiaoqian Jiang
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States
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22
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Dixon BE, Mukherjee S, Wiensch A, Gray ML, Ferres JML, Grannis SJ. Capturing COVID-19-Like Symptoms at Scale Using Banner Ads on an Online News Platform: Pilot Survey Study. J Med Internet Res 2021; 23:e24742. [PMID: 33872190 PMCID: PMC8139394 DOI: 10.2196/24742] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/14/2020] [Accepted: 04/14/2021] [Indexed: 01/05/2023] Open
Abstract
Background Identifying new COVID-19 cases is challenging. Not every suspected case undergoes testing, because testing kits and other equipment are limited in many parts of the world. Yet populations increasingly use the internet to manage both home and work life during the pandemic, giving researchers mediated connections to millions of people sheltering in place. Objective The goal of this study was to assess the feasibility of using an online news platform to recruit volunteers willing to report COVID-19like symptoms and behaviors. Methods An online epidemiologic survey captured COVID-19related symptoms and behaviors from individuals recruited through banner ads offered through Microsoft News. Respondents indicated whether they were experiencing symptoms, whether they received COVID-19 testing, and whether they traveled outside of their local area. Results A total of 87,322 respondents completed the survey across a 3-week span at the end of April 2020, with 54.3% of the responses from the United States and 32.0% from Japan. Of the total respondents, 19,631 (22.3%) reported at least one symptom associated with COVID-19. Nearly two-fifths of these respondents (39.1%) reported more than one COVID-19like symptom. Individuals who reported being tested for COVID-19 were significantly more likely to report symptoms (47.7% vs 21.5%; P<.001). Symptom reporting rates positively correlated with per capita COVID-19 testing rates (R2=0.26; P<.001). Respondents were geographically diverse, with all states and most ZIP Codes represented. More than half of the respondents from both countries were older than 50 years of age. Conclusions News platforms can be used to quickly recruit study participants, enabling collection of infectious disease symptoms at scale and with populations that are older than those found through social media platforms. Such platforms could enable epidemiologists and researchers to quickly assess trends in emerging infections potentially before at-risk populations present to clinics and hospitals for testing and/or treatment.
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Affiliation(s)
- Brian E Dixon
- Department of Epidemiology, Richard M Fairbanks School of Public Health, Indiana University, Indianapolis, IN, United States.,Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States
| | - Sumit Mukherjee
- AI for Good Research Lab, Microsoft Corporation, Redmond, WA, United States
| | - Ashley Wiensch
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States
| | - Mary L Gray
- New England Lab, Microsoft Research, Cambridge, MA, United States.,Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States
| | | | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.,Department of Family Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
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23
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Raposo A, Marques L, Correia R, Melo F, Valente J, Pereira T, Rosário LB, Froes F, Sanches J, da Silva HP. e-CoVig: A Novel mHealth System for Remote Monitoring of Symptoms in COVID-19. SENSORS 2021; 21:s21103397. [PMID: 34068131 PMCID: PMC8152780 DOI: 10.3390/s21103397] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 05/03/2021] [Accepted: 05/08/2021] [Indexed: 12/15/2022]
Abstract
In 2019, a new virus, SARS-CoV-2, responsible for the COVID-19 disease, was discovered. Asymptomatic and mildly symptomatic patients were forced to quarantine and closely monitor their symptoms and vital signs, most of the time at home. This paper describes e-CoVig, a novel mHealth application, developed as an alternative to the current monitoring paradigm, where the patients are followed up by direct phone contact. The e-CoVig provides a set of functionalities for remote reporting of symptoms, vital signs, and other clinical information to the health services taking care of these patients. The application is designed to register and transmit the heart rate, blood oxygen saturation (SpO2), body temperature, respiration, and cough. The system features a mobile application, a web/cloud platform, and a low-cost specific device to acquire the temperature and SpO2. The architecture of the system is flexible and can be configured for different operation conditions. Current commercial devices, such as oximeters and thermometers, can also be used and read using the optical character recognition (OCR) functionality of the system. The data acquired at the mobile application are sent automatically to the web/cloud application and made available in real-time to the medical staff, enabling the follow-up of several users simultaneously without the need for time consuming phone call interactions. The system was already tested for its feasibility and a preliminary deployment was performed on a nursing home showing promising results.
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Affiliation(s)
- Afonso Raposo
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal; (R.C.); (F.M.)
- Instituto de Sistemas e Robótica (ISR), Av. Rovisco Pais n. 1, Torre Norte—Piso 6, 1049-001 Lisboa, Portugal
- Correspondence: (A.R.); (J.S.); (H.P.d.S.)
| | - Luis Marques
- BrainAnswer, Lda., Rua Engenheiro Pires Marques, Lote 61, n. 5—Dto, 6000-406 Castelo Branco, Portugal; (L.M.); (J.V.)
| | - Rafael Correia
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal; (R.C.); (F.M.)
| | - Francisco Melo
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal; (R.C.); (F.M.)
| | - João Valente
- BrainAnswer, Lda., Rua Engenheiro Pires Marques, Lote 61, n. 5—Dto, 6000-406 Castelo Branco, Portugal; (L.M.); (J.V.)
- Escola Superior de Saúde Dr. Lopes Dias—Instituto Politécnico de Castelo Branco, Av. Pedro Alvares Cabral 12, 6000-084 Castelo Branco, Portugal
| | - Telmo Pereira
- Laboratory for Applied Health Research (LabinSaúde), Polytechnic Institute of Coimbra, Coimbra Health School, Rua 5 de Outubro—SM Bispo, Apartado 7006, 3046-854 Coimbra, Portugal;
| | - Luis Brás Rosário
- Centro Cardiovascular da Universidade de Lisboa (CCUL), Faculdade de Medicina da Universidade de Lisboa (FMUL), Av. Prof. Egas Moniz MB, 1649-028 Lisboa, Portugal;
| | - Filipe Froes
- Hospital Pulido Valente Intensive Care Unit, Alameda das Linhas de Torres, 117, 1769-001 Lisboa, Portugal;
| | - João Sanches
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal; (R.C.); (F.M.)
- Instituto de Sistemas e Robótica (ISR), Av. Rovisco Pais n. 1, Torre Norte—Piso 6, 1049-001 Lisboa, Portugal
- Correspondence: (A.R.); (J.S.); (H.P.d.S.)
| | - Hugo Plácido da Silva
- Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal; (R.C.); (F.M.)
- Instituto de Telecomunicações (IT), Av. Rovisco Pais n. 1, Torre Norte—Piso 10, 1049-001 Lisboa, Portugal
- Correspondence: (A.R.); (J.S.); (H.P.d.S.)
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24
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Runkle JD, Sugg MM, Graham G, Hodge B, March T, Mullendore J, Tove F, Salyers M, Valeika S, Vaughan E. Participatory COVID-19 Surveillance Tool in Rural Appalachia : Real-Time Disease Monitoring and Regional Response. Public Health Rep 2021; 136:327-337. [PMID: 33601984 PMCID: PMC8580398 DOI: 10.1177/0033354921990372] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/06/2021] [Indexed: 01/19/2023] Open
Abstract
INTRODUCTION Few US studies have examined the usefulness of participatory surveillance during the coronavirus disease 2019 (COVID-19) pandemic for enhancing local health response efforts, particularly in rural settings. We report on the development and implementation of an internet-based COVID-19 participatory surveillance tool in rural Appalachia. METHODS A regional collaboration among public health partners culminated in the design and implementation of the COVID-19 Self-Checker, a local online symptom tracker. The tool collected data on participant demographic characteristics and health history. County residents were then invited to take part in an automated daily electronic follow-up to monitor symptom progression, assess barriers to care and testing, and collect data on COVID-19 test results and symptom resolution. RESULTS Nearly 6500 county residents visited and 1755 residents completed the COVID-19 Self-Checker from April 30 through June 9, 2020. Of the 579 residents who reported severe or mild COVID-19 symptoms, COVID-19 symptoms were primarily reported among women (n = 408, 70.5%), adults with preexisting health conditions (n = 246, 70.5%), adults aged 18-44 (n = 301, 52.0%), and users who reported not having a health care provider (n = 131, 22.6%). Initial findings showed underrepresentation of some racial/ethnic and non-English-speaking groups. PRACTICAL IMPLICATIONS This low-cost internet-based platform provided a flexible means to collect participatory surveillance data on local changes in COVID-19 symptoms and adapt to guidance. Data from this tool can be used to monitor the efficacy of public health response measures at the local level in rural Appalachia.
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Affiliation(s)
- Jennifer D. Runkle
- North Carolina Institute for Climate Studies, North Carolina State University, Asheville, NC, USA
| | - Maggie M. Sugg
- Department of Geography and Planning, Appalachian State University, Boone, NC, USA
| | - Garrett Graham
- North Carolina Institute for Climate Studies, North Carolina State University, Asheville, NC, USA
| | - Bryan Hodge
- Mountain Area Health Education, Asheville, NC, USA
| | - Terri March
- Hendersonville Family Medicine Residency, Mountain Area Health Education, Asheville, NC, USA
| | | | - Fletcher Tove
- Buncombe County Health and Human Services, Asheville, NC, USA
| | - Martha Salyers
- Public Health and Human Services Division, Eastern Band of the Cherokee Indians, Cherokee, NC, USA
| | - Steve Valeika
- Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ellis Vaughan
- Buncombe County Health and Human Services, Asheville, NC, USA
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Abd-alrazaq A, Hassan A, Abuelezz I, Ahmed A, Alzubaidi MS, Shah U, Alhuwail D, Giannicchi A, Househ M. Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review (Preprint).. [DOI: 10.2196/preprints.29136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
BACKGROUND
Technologies have been extensively implemented to provide health care services for all types of clinical conditions during the COVID-19 pandemic. While several reviews have been conducted regarding technologies used during the COVID-19 pandemic, they were limited by focusing either on a specific technology (or features) or proposed rather than implemented technologies.
OBJECTIVE
This review aims to provide an overview of technologies, as reported in the literature, implemented during the first wave of the COVID-19 pandemic.
METHODS
We conducted a scoping review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Extension for Scoping Reviews. Studies were retrieved by searching 8 electronic databases, checking the reference lists of included studies and relevant reviews (backward reference list checking), and checking studies that cited included studies (forward reference list checking). The search terms were chosen based on the target intervention (ie, technologies) and the target disease (ie, COVID-19). We included English publications that focused on technologies or digital tools implemented during the COVID-19 pandemic to provide health-related services regardless of target health condition, user, or setting. Two reviewers independently assessed the eligibility of studies and extracted data from eligible papers. We used a narrative approach to synthesize extracted data.
RESULTS
Of 7374 retrieved papers, 126 were deemed eligible. Telemedicine was the most common type of technology (107/126, 84.9%) implemented in the first wave of the COVID-19 pandemic, and the most common mode of telemedicine was synchronous (100/108, 92.6%). The most common purpose of the technologies was providing consultation (75/126, 59.5%), followed by following up with patients (45/126, 35.7%), and monitoring their health status (22/126, 17.4%). Zoom (22/126, 17.5%) and WhatsApp (12/126, 9.5%) were the most commonly used videoconferencing and social media platforms, respectively. Both health care professionals and health consumers were the most common target users (103/126, 81.7%). The health condition most frequently targeted was COVID-19 (38/126, 30.2%), followed by any physical health conditions (21/126, 16.7%), and mental health conditions (13/126, 10.3%). Technologies were web-based in 84.1% of the studies (106/126). Technologies could be used through 11 modes, and the most common were mobile apps (86/126, 68.3%), desktop apps (73/126, 57.9%), telephone calls (49/126, 38.9%), and websites (45/126, 35.7%).
CONCLUSIONS
Technologies played a crucial role in mitigating the challenges faced during the COVID-19 pandemic. We did not find papers describing the implementation of other technologies (eg, contact-tracing apps, drones, blockchain) during the first wave. Furthermore, technologies in this review were used for other purposes (eg, drugs and vaccines discovery, social distancing, and immunity passport). Future research on studies on these technologies and purposes is recommended, and further reviews are required to investigate technologies implemented in subsequent waves of the pandemic.
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Dixon BE, Wools-Kaloustian KK, Fadel WF, Duszynski TJ, Yiannoutsos C, Halverson PK, Menachemi N. Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study. PLoS One 2021; 16:e0241875. [PMID: 33760821 PMCID: PMC7990210 DOI: 10.1371/journal.pone.0241875] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 02/26/2021] [Indexed: 01/16/2023] Open
Abstract
Background Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods. Methods We pooled community-based cohorts of individuals aged 12 and older screened for SARS-CoV-2 infection in April and June 2020 for a statewide prevalence study. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection. Results Among 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV <50.0%. The individual symptoms most greatly associated with SARS-CoV-2 positivity were fever (OR = 5.34, p<0.001), anosmia (OR = 4.08, p<0.001), ageusia (OR = 2.38, p = 0.006), and cough (OR = 2.86, p<0.001). Results from EFA identified two primary symptom clusters most associated with SARS-CoV-2 infection: (1) ageusia, anosmia, and fever; and (2) shortness of breath, cough, and chest pain. Moreover, being non-white (13.6% vs. 2.3%, p<0.001), Hispanic (27.9% vs. 2.5%, p<0.001), or living in an Urban area (5.4% vs. 3.8%, p<0.001) was associated with infection. Conclusions Symptoms can help distinguish SARS-CoV-2 infection from other respiratory viruses, especially in community or urgent care settings where rapid testing may be limited. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease spread by public health. These symptoms, derived from asymptomatic as well as mildly infected individuals, can also inform vaccine and therapeutic clinical trials.
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Affiliation(s)
- Brian E. Dixon
- Department of Epidemiology, IU Fairbanks School of Public Health, Indianapolis, Indiana, United States of America
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, United States of America
- * E-mail:
| | - Kara K. Wools-Kaloustian
- Department of Medicine, IU School of Medicine, Indianapolis, Indiana, United States of America
- Center for Global Health, Indiana University, Indianapolis, Indiana, United States of America
| | - William F. Fadel
- Department of Biostatistics, IU Fairbanks School of Public Health, Indianapolis, Indiana, United States of America
| | - Thomas J. Duszynski
- Department of Epidemiology, IU Fairbanks School of Public Health, Indianapolis, Indiana, United States of America
| | - Constantin Yiannoutsos
- Department of Biostatistics, IU Fairbanks School of Public Health, Indianapolis, Indiana, United States of America
| | - Paul K. Halverson
- Department of Health Policy and Management, IU Fairbanks School of Public Health, Indianapolis, Indiana, United States of America
- Department of Family Medicine, IU School of Medicine, Indianapolis, Indiana, United States of America
| | - Nir Menachemi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, United States of America
- Department of Health Policy and Management, IU Fairbanks School of Public Health, Indianapolis, Indiana, United States of America
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Watanabe O, Narita N, Katsuki M, Ishida N, Cai S, Otomo H, Yokota K. Prediction Model of Deep Learning for Ambulance Transports in Kesennuma City by Meteorological Data. Open Access Emerg Med 2021; 13:23-32. [PMID: 33536798 PMCID: PMC7850460 DOI: 10.2147/oaem.s293551] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 01/14/2021] [Indexed: 12/15/2022] Open
Abstract
PURPOSE With the aging population in Japan, the prediction of ambulance transports is needed to save the limited medical resources. Some meteorological factors were risks of ambulance transports, but it is difficult to predict in a classically statistical way because Japan has 4 seasons. We tried to make prediction models for ambulance transports using the deep learning (DL) framework, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with the meteorological and calendarial variables. MATERIALS AND METHODS We retrospectively investigated the daily ambulance transports and meteorological data between 2017 and 2019. First, to confirm their association, we performed classically statistical analysis. Second, to test the DL framework's utility for ambulance transports prediction, we made 3 prediction models for daily ambulance transports (total daily ambulance transports more than 5 or not, cardiopulmonary arrest (CPA), and trauma) using meteorological and calendarial factors and evaluated their accuracies by internal cross-validation. RESULTS During the 1095 days of 3 years, the total ambulance transports were 5948, including 240 CPAs and 337 traumas. Cardiogenic CPA accounted for 72.3%, according to the Utstein classification. The relation between ambulance transports and meteorological parameters by polynomial curves were statistically obtained, but their r2s were small. On the other hand, all DL-based prediction models obtained satisfactory accuracies in the internal cross-validation. The areas under the curves obtained from each model were all over 0.947. CONCLUSION We could statistically make polynomial curves between the meteorological variables and the number of ambulance transport. We also preliminarily made DL-based prediction models. The DL-based prediction for daily ambulance transports would be used in the future, leading to solving the lack of medical resources in Japan.
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Affiliation(s)
- Ohmi Watanabe
- Kesennuma City Hospital, Kesennuma, Miyagi988-0181, Japan
| | - Norio Narita
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi988-0181, Japan
| | - Masahito Katsuki
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi988-0181, Japan
| | - Naoya Ishida
- Kesennuma City Hospital, Kesennuma, Miyagi988-0181, Japan
| | - Siqi Cai
- Kesennuma City Hospital, Kesennuma, Miyagi988-0181, Japan
| | - Hiroshi Otomo
- Department of Surgery, Kesennuma City Hospital, Kesennuma, Miyagi988-0181, Japan
| | - Kenichi Yokota
- Department of Surgery, Kesennuma City Hospital, Kesennuma, Miyagi988-0181, Japan
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Katsuki M, Narita N, Ishida N, Watanabe O, Cai S, Ozaki D, Sato Y, Kato Y, Jia W, Nishizawa T, Kochi R, Sato K, Tominaga T. Preliminary development of a prediction model for daily stroke occurrences based on meteorological and calendar information using deep learning framework (Prediction One; Sony Network Communications Inc., Japan). Surg Neurol Int 2021; 12:31. [PMID: 33598347 PMCID: PMC7881509 DOI: 10.25259/sni_774_2020] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 01/07/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Chronologically meteorological and calendar factors were risks of stroke occurrence. However, the prediction of stroke occurrences is difficult depending on only meteorological and calendar factors. We tried to make prediction models for stroke occurrences using deep learning (DL) software, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with those variables. METHODS We retrospectively investigated the daily stroke occurrences between 2017 and 2019. We used Prediction One software to make the prediction models for daily stroke occurrences (present or absent) using 221 chronologically meteorological and calendar factors. We made a prediction models from the 3-year dataset and evaluated their accuracies using the internal cross-validation. Areas under the curves (AUCs) of receiver operating characteristic curves were used as accuracies. RESULTS The 371 cerebral infarction (CI), 184 intracerebral hemorrhage (ICH), and 53 subarachnoid hemorrhage patients were included in the study. The AUCs of the several DL-based prediction models for all stroke occurrences were 0.532-0.757. Those for CI were 0.600-0.782. Those for ICH were 0.714-0.988. CONCLUSION Our preliminary results suggested a probability of the DL-based prediction models for stroke occurrence only by meteorological and calendar factors. In the future, by synchronizing a variety of medical information among the electronic medical records and personal smartphones as well as integrating the physical activities or meteorological conditions in real time, the prediction of stroke occurrence could be performed with high accuracy, to save medical resources, to have patients care for themselves, and to perform efficient medicine.
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Affiliation(s)
- Masahito Katsuki
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Norio Narita
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Naoya Ishida
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Ohmi Watanabe
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Siqi Cai
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Dan Ozaki
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Yoshimichi Sato
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Yuya Kato
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Wenting Jia
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Taketo Nishizawa
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Ryuzaburo Kochi
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Kanako Sato
- Department of Neurosurgery, Kesennuma City Hospital, Kesennuma, Miyagi, Japan
| | - Teiji Tominaga
- Department of Neurosurgery, Tohoku University, Sendai, Miyagi, Japan
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Camacho-Rivera M, Islam JY, Rivera A, Vidot DC. Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey. JMIR Mhealth Uhealth 2020; 8:e24693. [PMID: 33301415 PMCID: PMC7748389 DOI: 10.2196/24693] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 11/16/2020] [Accepted: 11/20/2020] [Indexed: 02/07/2023] Open
Abstract
Background Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. Although COVID-19 mobile health (mHealth) apps have emerged, research on attitudes toward using COVID-19 mHealth tools among those with chronic conditions is scarce. Objective This study aimed to examine attitudes toward COVID-19, identify determinants of COVID-19 mHealth tool use across demographic and health-related characteristics, and evaluate associations between chronic health conditions and attitudes toward using COVID-19 mHealth tools (eg, mHealth or web-based methods for tracking COVID-19 exposures, symptoms, and recommendations). Methods We used nationally representative data from the COVID-19 Impact Survey collected from April to June 2020 (n=10,760). Primary exposure was a history of chronic conditions, which were defined as self-reported diagnoses of cardiometabolic, respiratory, immune-related, and mental health conditions and overweight/obesity. Primary outcomes were attitudes toward COVID-19 mHealth tools, including the likelihood of using (1) a mobile phone app to track COVID-19 symptoms and receive recommendations; (2) a website to track COVID-19 symptoms, track location, and receive recommendations; and (3) an app using location data to track potential COVID-19 exposure. Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression. Results Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very (conditional odds ratio 1.16, 95% CI 1.00-1.35) and moderately likely (conditional odds ratio 1.23, 95% CI 1.04-1.45) to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. Conclusions Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities (eg, web-based method vs app) and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions.
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Affiliation(s)
- Marlene Camacho-Rivera
- Department of Community Health Sciences, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States
| | - Jessica Yasmine Islam
- University of North Carolina, Lineberger Comprehensive Cancer Center, Chapel Hill, NC, United States
| | - Argelis Rivera
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Denise Christina Vidot
- University of Miami School of Nursing and Health Studies, Coral Gables, FL, United States
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30
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Kondylakis H, Katehakis DG, Kouroubali A, Logothetidis F, Triantafyllidis A, Kalamaras I, Votis K, Tzovaras D. COVID-19 Mobile Apps: A Systematic Review of the Literature. J Med Internet Res 2020; 22:e23170. [PMID: 33197234 PMCID: PMC7732358 DOI: 10.2196/23170] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 09/18/2020] [Accepted: 10/11/2020] [Indexed: 02/06/2023] Open
Abstract
Background A vast amount of mobile apps have been developed during the past few months in an attempt to “flatten the curve” of the increasing number of COVID-19 cases. Objective This systematic review aims to shed light into studies found in the scientific literature that have used and evaluated mobile apps for the prevention, management, treatment, or follow-up of COVID-19. Methods We searched the bibliographic databases Global Literature on Coronavirus Disease, PubMed, and Scopus to identify papers focusing on mobile apps for COVID-19 that show evidence of their real-life use and have been developed involving clinical professionals in their design or validation. Results Mobile apps have been implemented for training, information sharing, risk assessment, self-management of symptoms, contact tracing, home monitoring, and decision making, rapidly offering effective and usable tools for managing the COVID-19 pandemic. Conclusions Mobile apps are considered to be a valuable tool for citizens, health professionals, and decision makers in facing critical challenges imposed by the pandemic, such as reducing the burden on hospitals, providing access to credible information, tracking the symptoms and mental health of individuals, and discovering new predictors.
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Affiliation(s)
- Haridimos Kondylakis
- Computational Biomedicine Laboratory, Foundation for Research and Technology - Hellas-Institute of Computer Science, Heraklion, Greece
| | - Dimitrios G Katehakis
- Center for eHealth Applications and Services, Foundation for Research and Technology - Hellas, Institute of Computer Science, Heraklion, Greece
| | - Angelina Kouroubali
- Computational Biomedicine Laboratory, Foundation for Research and Technology - Hellas-Institute of Computer Science, Heraklion, Greece
| | - Fokion Logothetidis
- Center for eHealth Applications and Services, Foundation for Research and Technology - Hellas, Institute of Computer Science, Heraklion, Greece
| | - Andreas Triantafyllidis
- Information Technologies Institute, Centre for Research and Technology - Hellas, Thessaloniki, Greece
| | - Ilias Kalamaras
- Information Technologies Institute, Centre for Research and Technology - Hellas, Thessaloniki, Greece
| | - Konstantinos Votis
- Information Technologies Institute, Centre for Research and Technology - Hellas, Thessaloniki, Greece
| | - Dimitrios Tzovaras
- Information Technologies Institute, Centre for Research and Technology - Hellas, Thessaloniki, Greece
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Dixon BE, Wools-Kaloustian K, Fadel WF, Duszynski TJ, Yiannoutsos C, Halverson PK, Menachemi N. Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020. [PMID: 33106813 PMCID: PMC7587833 DOI: 10.1101/2020.10.11.20210922] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Background: Prior studies examining symptoms of COVID-19 are primarily descriptive and measured among hospitalized individuals. Understanding symptoms of SARS-CoV-2 infection in pre-clinical, community-based populations may improve clinical screening, particularly during flu season. We sought to identify key symptoms and symptom combinations in a community-based population using robust methods. Methods: We pooled community-based cohorts of individuals aged 12 and older screened for SARS-CoV-2 infection in April and June 2020 for a statewide seroprevalence study. Main outcome was SARS-CoV-2 positivity. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for individual symptoms as well as symptom combinations. We further employed multivariable logistic regression and exploratory factor analysis (EFA) to examine symptoms and combinations associated with SARS-CoV-2 infection. Results: Among 8214 individuals screened, 368 individuals (4.5%) were RT-PCR positive for SARS-CoV-2. Although two-thirds of symptoms were highly specific (>90.0%), most symptoms individually possessed a PPV <50.0%. The individual symptoms most greatly associated with SARS-CoV-2 positivity were fever (OR=5.34, p<0.001), anosmia (OR=4.08, p<0.001), ageusia (OR=2.38, p=0.006), and cough (OR=2.86, p<0.001). Results from EFA identified two primary symptom clusters most associated with SARS-CoV-2 infection: (1) ageusia, anosmia, and fever; and (2) shortness of breath, cough, and chest pain. Moreover, being non-white (13.6% vs. 2.3%, p<0.001), Hispanic (27.9% vs. 2.5%, p<0.001), or living in an Urban area (5.4% vs. 3.8%, p<0.001) was associated with infection. Conclusions: Symptoms can help distinguish SARS-CoV-2 infection from other respiratory viruses, especially in community or urgent care settings where rapid testing may be limited. Symptoms should further be structured in clinical documentation to support identification of new cases and mitigation of disease spread by public health. These symptoms, derived from asymptomatic as well as mildly infected individuals, can also inform vaccine and therapeutic clinical trials.
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Affiliation(s)
- Brian E Dixon
- Department of Epidemiology, IU Fairbanks School of Public Health, Center for Biomedical Informatics, Regenstrief Institute, Inc., 1101 W. 10th St., RF 336, Indianapolis, IN 46202
| | | | - William F Fadel
- Department of Biostatistics, IU Fairbanks School of Public Health
| | | | | | - Paul K Halverson
- Department of Health Policy and Management, IU Fairbanks School of Public Health
| | - Nir Menachemi
- Department of Health Policy & Management, IU Fairbanks School of Public Health
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Walrave M, Waeterloos C, Ponnet K. Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach. JMIR Public Health Surveill 2020; 6:e20572. [PMID: 32755882 PMCID: PMC7470174 DOI: 10.2196/20572] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 07/20/2020] [Accepted: 08/05/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND To track and reduce the spread of COVID-19, apps have been developed to identify contact with individuals infected with SARS-CoV-2 and warn those who are at risk of having contracted the virus. However, the effectiveness of these apps depends highly on their uptake by the general population. OBJECTIVE The present study investigated factors influencing app use intention, based on the health belief model. In addition, associations with respondents' level of news consumption and their health condition were investigated. METHODS A survey was administered in Flanders, Belgium, to 1500 respondents, aged 18 to 64 years. Structural equation modeling was used to investigate relationships across the model's constructs. RESULTS In total, 48.70% (n=730) of respondents indicated that they intend to use a COVID-19 tracing app. The most important predictor was the perceived benefits of the app, followed by self-efficacy and perceived barriers. Perceived severity and perceived susceptibility were not related to app uptake intention. Moreover, cues to action (ie, individuals' exposure to [digital] media content) were positively associated with app use intention. As the respondents' age increased, their perceived benefits and self-efficacy for app usage decreased. CONCLUSIONS Initiatives to stimulate the uptake of contact tracing apps should enhance perceived benefits and self-efficacy. A perceived barrier for some potential users is privacy concerns. Therefore, when developing and launching an app, clarification on how individuals' privacy will be protected is needed. To sustain perceived benefits in the long run, supplementary options could be integrated to inform and assist users.
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Affiliation(s)
- Michel Walrave
- Research Group MIOS, Department of Communication Studies, Faculty of Social Sciences, University of Antwerp, Antwerp, Belgium
| | - Cato Waeterloos
- Research Group IMEC-MICT, Department of Communication Sciences, Faculty of Political and Social Sciences, Ghent University, Ghent, Belgium
| | - Koen Ponnet
- Research Group IMEC-MICT, Department of Communication Sciences, Faculty of Political and Social Sciences, Ghent University, Ghent, Belgium
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