ABSTRACT
Background: e-Health has played a crucial role during the COVID-19 pandemic in primary health care. e-Health is the cost-effective and secure use of Information and Communication Technologies (ICT) to support health and health-related fields. As a result of ICTs, the healthcare sector is undergoing a new revolution and societal governance is becoming more sustainable. As a result of the COVID-19 pandemic, information, and communication technology (ICT) has improved the quality of healthcare and the exchange of information, trained healthcare professionals and patients, and facilitated the relationship between patients and their healthcare providers. Various stakeholders worldwide use ICTs, including individuals, non-profit organizations, health practitioners, and governments. This study systematically reviews the literature on ICT-based automatic and remote monitoring methods and different ICT techniques used in the care of COVID-19-infected patients. Objective: The purpose of this systematic review is to identify the e-Health methods, associated information and communication technologies, implementation strategies, information collection techniques, advantages, and disadvantages of remote and automatic patient monitoring and care in COVID-19. Methods: The search included primary studies that were published between January 2020 and June 2022 in scientific and electronic databases, such as EBSCOhost, Scopus, ACM, Nature, SpringerLink, IEEE Xplore, MEDLINE, Google Scholar, JMIR, Web of Science, and PubMed. In this review, the findings from the included publications are presented and elaborated according to the research questions identified. Evidence-based systematic reviews and meta-analyses were conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Additionally, we improved the review process using the Rayyan tool and the Scale for the Assessment of Narrative Review Articles (SANRA). Among the eligibility criteria were methodological rigor, conceptual clarity, and useful implementation of ICTs in e-Health for remote and automatic monitoring of COVID-19 patients. Results: Our initial search identified 664 potential studies; 102 were assessed for eligibility in the pre-final stage and 65 articles were used in the final review with inclusion and exclusion criteria. The review identified the following eHealth methods-Telemedicine, Mobile Health (mHealth), and Telehealth. The associated ICTs are Wearable Body Sensors, Artificial Intelligence (AI) algorithms, Internet-of-Things, or Internet-of-Medical-Things (IoT or IoMT), Biometric Monitoring Technologies (BioMeTs), and Bluetooth-enabled (BLE) home health monitoring devices. Spatial or positional data, personal and individual health, and wellness data, including vital signs, symptoms, biomedical images and signals, and lifestyle data are examples of information that is managed by ICTs. Different AI and IoT methods have opened new possibilities for automatic and remote patient monitoring with associated advantages and weaknesses. Our findings were represented in a structured manner using an ontology model. Conclusions: Various e-Health methods, associated remote monitoring technologies, approaches, information types, adoption of ICT tools for automatic remote patient monitoring (RPM), advantages and limitations of RMTs in the COVID-19 case are discussed in this systematic literature review. The use of e-Health during the COVID-19 pandemic illustrates the constraints and possibilities of using ICT. ICTs are not merely an external tool to achieve definite remote and automatic health monitoring goals; instead, they are embedded in contexts. Therefore, the importance of the mutual design process between ICT and society during the global health crisis has been observed from a social informatics perspective. A global health crisis can be observed as an information crisis (e.g., insufficient information, unreliable information, and inaccessible information); however, this review shows the influence of ICTs on COVID-19 patients' health monitoring and related information collection techniques.
Subject(s)
COVID-19ABSTRACT
There are no known cures or vaccines for COVID-19, the defining pandemic of this era. Animal models are essential to fast track new interventions and nonhuman primate (NHP) models of other infectious diseases have proven extremely valuable. Here we compare SARS-CoV-2 infection in three species of experimentally infected NHPs (rhesus macaques, baboons, and marmosets). During the first 3 days, macaques developed clinical signatures of viral infection and systemic inflammation, coupled with early evidence of viral replication and mild-to-moderate interstitial and alveolar pneumonitis, as well as extra-pulmonary pathologies. Cone-beam CT scans showed evidence of moderate pneumonia, which progressed over 3 days. Longitudinal studies showed that while both young and old macaques developed early signs of COVID-19, both groups recovered within a two-week period. Recovery was characterized by low-levels of viral persistence in the lung, suggesting mechanisms by which individuals with compromised immune systems may be susceptible to prolonged and progressive COVID-19. The lung compartment contained a complex early inflammatory milieu with an influx of innate and adaptive immune cells, particularly interstitial macrophages, neutrophils and plasmacytoid dendritic cells, and a prominent Type I-interferon response. While macaques developed moderate disease, baboons exhibited prolonged shedding of virus and extensive pathology following infection; and marmosets demonstrated a milder form of infection. These results showcase in critical detail, the robust early cellular immune responses to SARS-CoV-2 infection, which are not sterilizing and likely impact development of antibody responses. Thus, various NHP genera recapitulate heterogeneous progression of COVID-19. Rhesus macaques and baboons develop different, quantifiable disease attributes making them immediately available essential models to test new vaccines and therapies.