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Update on Immunology of COVID-19 Disease and Potential Strategy for Controlling.

ABSTRACT: Coronavirus disease 2019 (COVID-19) is caused by a novel form of the coronavirus that caused severe acute respiratory syndrome (SARS). SARS-CoV-2 raised in China and has broadcast to 261 countries globally. SARS-CoV-2 a member of β-coronavirus family and has an almost matching genome sequence to a bat coronavirus, pointing to the bat as the natural host before it was transmitted to humans. SARS-CoV-2 uses the same receptor, angiotensin-converting enzyme 2 (ACE2) as that used by SARS-CoV and principally infects the respiratory tract. The clinical symptoms of COVID-19 patients include fever, cough and fatigue whilst small populations of patients have gastrointestinal symptoms. The old people and people with underlying metabolic and cardiovascular diseases are more affected to infection and have worse outcomes. These may be associated with acute respiratory distress syndrome (ARDS) and a cytokine storm. In this review, we discuss the pathogenesis and clinical characteristics of disease and the pharmacologic approaches that may control COVID-19.

SUBMITTER: Dezfuli NK

PROVIDER: S-EPMC8088154 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Update on Immunology of COVID-19 Disease and Potential Strategy for Controlling.

Dezfuli Neda K NK Adcock Ian M IM Montazami Nooshin N Mortaz Esmaeil E Velayati Aliakbar A

Tanaffos 20201201 4

Coronavirus disease 2019 (COVID-19) is caused by a novel form of the coronavirus that caused severe acute respiratory syndrome (SARS). SARS-CoV-2 raised in China and has broadcast to 261 countries globally. SARS-CoV-2 a member of β-coronavirus family and has an almost matching genome sequence to a bat coronavirus, pointing to the bat as the natural host before it was transmitted to humans. SARS-CoV-2 uses the same receptor, angiotensin-converting enzyme 2 (ACE2) as that used by SARS-CoV and prin ...[more]

PMID: 33959165

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Project description:BackgroundThe sustainability and generalizability of China's dynamic zero-COVID strategy on eliminating SARS-CoV-2 transmission has casted doubt globally, mainly because it has exacted high social and economic cost. This study aimed to estimate the disease burden during the first wave of Omicron in China and compared the cost-effectiveness of implementing a Real-world strategy (adjusted dynamic zero-COVID strategy) with two simulated strategies (routine and stricter dynamic zero-COVID strategy) to inform appropriate strategies for COVID-19 pandemic control.MethodsA dynamic state-transition simulation model was developed to compare the health and cost outcomes between different dynamic zero-COVID strategies. Omicron-related healthcare costs were estimated from the societal perspective. Epidemiological parameter values were derived from data of real-world or generated by model calibration; costs and effectiveness parameter values were informed either by local data or published literature. The primary outcomes were total social cost, disability adjusted life-years (DALYs) and net monetary benefit (NMB). Deterministic sensitivity analyses (DSA) and scenario analyses were performed to assess the model robustness.ResultsThe first wave of Omicron in Shanghai resulted in 47,646 DALYs lost and 415 billion RMB losses. At a willingness-to-pay threshold of 173,630 RMB (the GDP per capita of Shanghai in 2021) per DALY saved, the Real-world strategy was considered as the most cost-effective strategy due to its highest NMB (-407 billion). Results from DSA confirmed the robustness of our findings.ConclusionOur finding supported the Real-world strategy taken by the Shanghai Municipal Government between March 1 and May 21, 2022 to control the first wave of Omicron outbreak. Moreover, our results indicated that whether the Stricter dynamic zero-COVID strategy is worth implementing at the beginning of the COVID-19 outbreak mainly depended on the infection rate of COVID-19 among primary contacts. Our analysis provides important evidence to inform policy makers to make appropriate decisions regarding COVID-19 pandemic management.

Dataset Information

Update on Immunology of COVID-19 Disease and Potential Strategy for Controlling.

Publications

Update on Immunology of COVID-19 Disease and Potential Strategy for Controlling.

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