Asymptomatic infection by SARS-CoV-2 in healthcare workers: A study in a large teaching hospital in Wuhan, China

Zhao, Dong; Wang, Mengmei; Wang, Ming; Zhao, Yang; Zheng, Zhong; Li, Xiaochen; Zhang, Yunting; Wang, Tao; Zeng, Shaolin; Hu, Weihua; Yu, Wenzhen; Hu, Ke

doi:10.1016/j.ijid.2020.07.082

Cited by 41 publications

(36 citation statements)

References 28 publications

(47 reference statements)

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“…Of the 1021 COVID-19-positive cases in our study, 10.9% were asymptomatic, which is in accordance with the findings in South Korea and China [ 10 , 19 ]. Interestingly, our observation identified an upward trend for the increase in asymptomatic COVID-19 cases following April 2020 ( Fig.…”

Section: Discussionsupporting

confidence: 92%

A multi-centre, cross-sectional study on coronavirus disease 2019 in Bangladesh: clinical epidemiology and short-term outcomes in recovered individuals

Mannan¹,

Mehedi²,

Chy³

et al. 2021

New Microbes and New Infections

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Section: Discussionsupporting

confidence: 92%

A multi-centre, cross-sectional study on coronavirus disease 2019 in Bangladesh: clinical epidemiology and short-term outcomes in recovered individuals

Mannan¹,

Mehedi²,

Chy³

et al. 2021

New Microbes and New Infections

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“…Of the 1,021 COVID-19 positive cases in our sample, 10.9% were asymptomatic which is in accordance with the findings in South Korea and China. 9, 16 Interesting enough, our observation identified an upward trend for the increase in asymptomatic COVID-19 cases following April 2020 (Figure 1). Although no systematic assessment has been done on this aspect, our observation complies with the records and pronouncements of the health professionals and hospital registries in Bangladesh.…”

Section: Discussionsupporting

confidence: 51%

Epidemiology and clinical outcome of COVID-19: A multi-centre cross sectional study from Bangladesh

Mannan

Mehedi

Chy

et al. 2020

Preprint

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Objectives: To investigate SARS-CoV-2 associated epidemiology and clinical outcomes in Bangladesh to understand the course of COVID-19 pandemic and suggest prevention measures. Methods: A cross-sectional retrospective study was conducted among 1,021 RT-PCR confirmed but recovered COVID-19 cases from six participating hospitals in Bangladesh. Results: Of the total sample, 111 (10.9%) cases were asymptomatic while the number of symptomatic cases were 910 (89.1%). Higher prevalence of COVID-19 persisted in the male population (75%) and for the 31-40 age group. More than 85% of the samples reported BCG vaccination mark. Common symptoms observed in our study samples were fever (72.4%), cough (55.9%), loss of taste (40.7%) and body ache (40%); whereas for the biochemical parameters, Neutrophil (46.4%), D-dimer (46.1%), Ferritin (37.9%) and SGPT (36.8%) levels were found elevated. Post-COVID complications including pain (31.8%), loss of concentration (24.4%) and anxiety or depression (23.1%) were found significantly prevalent. Conclusion: Our study has shown that adult males aged between 31-40 in Bangladesh are more vulnerable to being infected with COVID-19. With an indication for the rising trend of the asymptomatic cases, deployment of interventions to curb further community spread is necessary to avoid the grave outcomes of COVID-19 in Bangladesh.

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“…This prompt us to use the threshold 0 = 0.63 to set apart patients which have mild infections (about 80% as in reality [52]- [54]) to those having severe disease (15% with dyspnoea, hypoxia, lung changes on images [55]) or critical illness (5%, respiratory failure, shock, multi organi dysfunction, cytokine storm syndrome [56]), that is, we label patients with ≥ 0 as symptomatic while those with < 0 asymptomatic.…”

Section: How the Model Explains Symptomsmentioning

confidence: 99%

From infection to immunity: understanding the response to SARS-CoV2 through in-silico modeling

Castiglione

Deb

Srivastava

et al. 2020

Preprint

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BackgroundImmune system conditions of the patient is a key factor in COVID-19 infection survival. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies.AimThe dynamics of the insurgence of immunity is at the core of the both SARS-CoV-2 vaccine development and therapies. This paper addresses a fundamental question in the management of the infection: can we describe the insurgence (and the span) of immunity in COVID-19? The in-silico model developed here answers this question at individual (personalized) and population levels.We simulate the immune response to SARS-CoV-2 and analyze the impact of infecting viral load, affinity to the ACE2 receptor and age in the artificially infected population on the course of the disease.MethodsWe use a stochastic agent-based immune simulation platform to construct a virtual cohort of infected individuals with age-dependent varying degree of immune competence. We use a parameter setting to reproduce known inter-patient variability and general epidemiological statistics.ResultsWe reproduce in-silico a number of clinical observations and we identify critical factors in the statistical evolution of the infection. In particular we evidence the importance of the humoral response over the cytotoxic response and find that the antibody titers measured after day 25 from the infection is a prognostic factor for determining the clinical outcome of the infection.Our modeling framework uses COVID-19 infection to demonstrate the actionable effectiveness of simulating the immune response at individual and population levels. The model developed is able to explain and interpret observed patterns of infection and makes verifiable temporal predictions.Within the limitations imposed by the simulated environment, this work proposes in a quantitative way that the great variability observed in the patient outcomes in real life can be the mere result of subtle variability in the infecting viral load and immune competence in the population.In this work we i) show the power of model predictions, ii) identify the clinical end points that could be more suitable for computational modeling of COVID-19 immune response, iii) define the resolution and amount of data required to empower this class of models for translational medicine purposes and, iv) we exemplify how computational modeling of immune response provides an important view to discuss hypothesis and design new experiments, in particular paving the way to further investigations about the duration of vaccine-elicited immunity especially in the view of the blundering effect of immunesenescence.

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Asymptomatic infection by SARS-CoV-2 in healthcare workers: A study in a large teaching hospital in Wuhan, China

Abstract: Highlights A high rate of asymptomatic SARS-CoV-2 carriers was found in healthcare workers. Asymptomatic individuals had lower antibody levels in the acute phase. Asymptomatic IgG titration reduced during the early convalescent phase.

Cited by 41 publications

References 28 publications

A multi-centre, cross-sectional study on coronavirus disease 2019 in Bangladesh: clinical epidemiology and short-term outcomes in recovered individuals

A multi-centre, cross-sectional study on coronavirus disease 2019 in Bangladesh: clinical epidemiology and short-term outcomes in recovered individuals

Epidemiology and clinical outcome of COVID-19: A multi-centre cross sectional study from Bangladesh

From infection to immunity: understanding the response to SARS-CoV2 through in-silico modeling

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