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Stopping the COVID-19 Pandemic: A Review on the Advances of Diagnosis, Treatment, and Control Measures.

ABSTRACT: With the continued spread of COVID-19 across the world, rapid diagnostic tools, readily available respurposable drugs, and prompt containment measures to control the SARS-CoV-2 infection are of paramount importance. Examples of recent advances in diagnostic tests are CRISPR technology, IgG assay, spike protein detection, and use of artificial intelligence. The gold standard reverse transcription polymerase chain (RT-PCR) has also been upgraded with point-of-care rapid tests. Supportive treatment, mechanical ventilation, and extracorporeal membrane oxygenation (ECMO) remain the primary choice, while therapeutic options include antivirals, antiparasitics, anti-inflammatories, interferon, convalescent plasma, monoclonal antibody, hyperimmunoglobulin, RNAi, and mesenchymal stem cell therapy. Different types of vaccines such as RNA, DNA, and lentiviral, inactivated, and viral vector are in clinical trials. Moreover, rapidly deployable and easy-to-transport innovative vaccine delivery systems are also in development. As countries have started easing down on the lockdown measures, the chance for a second wave of infection demands strict and rational control policies to keep fatalities minimized. An improved understanding of the advances in diagnostic tools, treatments, vaccines, and control measures for COVID-19 can provide references for further research and aid better containment strategies.

SUBMITTER: Siam MHB

PROVIDER: S-EPMC7588828 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Stopping the COVID-19 Pandemic: A Review on the Advances of Diagnosis, Treatment, and Control Measures.

Siam Md Hasanul Banna MHB Nishat Nahida Hannan NH Ahmed Ahsan A Hossain Mohammad Sorowar MS

Journal of pathogens 20201018

With the continued spread of COVID-19 across the world, rapid diagnostic tools, readily available respurposable drugs, and prompt containment measures to control the SARS-CoV-2 infection are of paramount importance. Examples of recent advances in diagnostic tests are CRISPR technology, IgG assay, spike protein detection, and use of artificial intelligence. The gold standard reverse transcription polymerase chain (RT-PCR) has also been upgraded with point-of-care rapid tests. Supportive treatment ...[more]

PMID: 33133697

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Project description:BackgroundIn the modern world, mobile apps are essential for human advancement, and pandemic control is no exception. The use of mobile apps and technology for the detection and diagnosis of COVID-19 has been the subject of numerous investigations, although no thorough analysis of COVID-19 pandemic prevention has been conducted using mobile apps, creating a gap.ObjectiveWith the intention of helping software companies and clinical researchers, this study provides comprehensive information regarding the different fields in which mobile apps were used to diagnose COVID-19 during the pandemic.MethodsIn this systematic review, 535 studies were found after searching 5 major research databases (ScienceDirect, Scopus, PubMed, Web of Science, and IEEE). Of these, only 42 (7.9%) studies concerned with diagnosing and detecting COVID-19 were chosen after applying inclusion and exclusion criteria using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol.ResultsMobile apps were categorized into 6 areas based on the content of these 42 studies: contact tracing, data gathering, data visualization, artificial intelligence (AI)-based diagnosis, rule- and guideline-based diagnosis, and data transformation. Patients with COVID-19 were identified via mobile apps using a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. Most studies concentrated on using AI methods to identify people who might have COVID-19. Additionally, symptoms, cough sounds, and radiological images were used more frequently compared to other data types. Deep learning techniques, such as convolutional neural networks, performed comparatively better in the processing of health care data than other types of AI techniques, which improved the diagnosis of COVID-19.ConclusionsMobile apps could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and the early identification of suspected cases. These technologies can work with the internet of things, cloud storage, 5th-generation technology, and cloud computing. Processing pipelines can be moved to mobile device processing cores using new deep learning methods, such as lightweight neural networks. In the event of future pandemics, mobile apps will play a critical role in rapid diagnosis using various image data and clinical symptoms. Consequently, the rapid diagnosis of these diseases can improve the management of their effects and obtain excellent results in treating patients.

Project description:BackgroundIn the current COVID-19 pandemic, aggressive Infection Prevention and Control (IPC) measures have been adopted to prevent health care-associated transmission of COVID-19. We evaluated the impact of a multimodal IPC strategy originally designed for the containment of COVID-19 on the rates of other hospital-acquired-infections (HAIs).MethodologyFrom February-August 2020, a multimodal IPC strategy was implemented across a large health care campus in Singapore, comprising improved segregation of patients with respiratory symptoms, universal masking and heightened adherence to Standard Precautions. The following rates of HAI were compared pre- and postpandemic: health care-associated respiratory-viral-infection (HA-RVI), methicillin-resistant Staphylococcus aureus, and CP-CRE acquisition rates, health care-facility-associated C difficile infections and device-associated HAIs.ResultsEnhanced IPC measures introduced to contain COVID-19 had the unintended positive consequence of containing HA-RVI. The cumulative incidence of HA-RVI decreased from 9.69 cases per 10,000 patient-days to 0.83 cases per 10,000 patient-days (incidence-rate-ratio = 0.08; 95% confidence interval [CI] = 0.05-0.13, P< .05). Hospital-wide MRSA acquisition rates declined significantly during the pandemic (incidence-rate-ratio = 0.54, 95% CI = 0.46-0.64, P< .05), together with central-line-associated-bloodstream infection rates (incidence-rate-ratio = 0.24, 95% CI = 0.07-0.57, P< .05); likely due to increased compliance with Standard Precautions. Despite the disruption caused by the pandemic, there was no increase in CP-CRE acquisition, and rates of other HAIs remained stable.ConclusionsMultimodal IPC strategies can be implemented at scale to successfully mitigate health care-associated transmission of RVIs. Good adherence to personal-protective-equipment and hand hygiene kept other HAI rates stable even during an ongoing pandemic where respiratory infections were prioritized for interventions.

Project description:ObjectivesTo comprehensively map the existing evidence assessing the impact of travel-related control measures for containment of the SARS-CoV-2/COVID-19 pandemic.DesignRapid evidence map.Data sourcesMEDLINE, Embase and Web of Science, and COVID-19 specific databases offered by the US Centers for Disease Control and Prevention and the WHO.Eligibility criteriaWe included studies in human populations susceptible to SARS-CoV-2/COVID-19, SARS-CoV-1/severe acute respiratory syndrome, Middle East respiratory syndrome coronavirus/Middle East respiratory syndrome or influenza. Interventions of interest were travel-related control measures affecting travel across national or subnational borders. Outcomes of interest included infectious disease, screening, other health, economic and social outcomes. We considered all empirical studies that quantitatively evaluate impact available in Armenian, English, French, German, Italian and Russian based on the team's language capacities.Data extraction and synthesisWe extracted data from included studies in a standardised manner and mapped them to a priori and (one) post hoc defined categories.ResultsWe included 122 studies assessing travel-related control measures. These studies were undertaken across the globe, most in the Western Pacific region (n=71). A large proportion of studies focused on COVID-19 (n=59), but a number of studies also examined SARS, MERS and influenza. We identified studies on border closures (n=3), entry/exit screening (n=31), travel-related quarantine (n=6), travel bans (n=8) and travel restrictions (n=25). Many addressed a bundle of travel-related control measures (n=49). Most studies assessed infectious disease (n=98) and/or screening-related (n=25) outcomes; we found only limited evidence on economic and social outcomes. Studies applied numerous methods, both inferential and descriptive in nature, ranging from simple observational methods to complex modelling techniques.ConclusionsWe identified a heterogeneous and complex evidence base on travel-related control measures. While this map is not sufficient to assess the effectiveness of different measures, it outlines aspects regarding interventions and outcomes, as well as study methodology and reporting that could inform future research and evidence synthesis.

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Stopping the COVID-19 Pandemic: A Review on the Advances of Diagnosis, Treatment, and Control Measures.

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Stopping the COVID-19 Pandemic: A Review on the Advances of Diagnosis, Treatment, and Control Measures.

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