Role of asymptomatic and pre-symptomatic infections in covid-19 pandemic

Gao, Wenjing; Lv, Jun; Pang, Yuanjie; Li, Liming

doi:10.1136/bmj.n2342

Cited by 55 publications

(44 citation statements)

References 21 publications

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“…These were people who, due to persistent symptoms after contracting COVID-19, were seeking further diagnosis and treatment. According to this review results, over 99% of patients presented clinical symptoms, which obviously contradicts current medical evidence, which indicates that COVID-19 may be asymptomatic in even 8–30% of cases [ 41 ]. Due to the above, the results of this study should not be analyzed in relation to the entire population.…”

Section: Discussionmentioning

confidence: 95%

Do the Successive Waves of SARS-CoV-2, Vaccination Status and Place of Infection Influence the Clinical Picture and COVID-19 Severity among Patients with Persistent Clinical Symptoms? The Retrospective Study of Patients from the STOP-COVID Registry of the PoLoCOV-Study

Chudzik

Babicki

Kapusta

et al. 2022

JPM

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The severity of ailments caused by SARS-CoV-2 varies and the clinical picture has already evolved during the pandemic, complicating diagnostics. In Poland, no study has been performed to assess the clinical picture of patients across the successive pandemic waves. The aim of the study was to present the characteristics of patients who present to medical center because of persistent symptoms after COVID-19, and to study differences between hospitalized/non-hospitalized, vaccinated/non-vaccinated individuals and between different waves in Poland. This is a retrospective study evaluating the clinical presentation of COVID-19 patients from the STOP-COVID registry of the PoLoCOV-Study. This registry includes patients who present to the medical center because of persistent clinical symptoms after the isolation. The patients’ data were obtained from individuals who suffered from COVID-19 between September 2020 and December 2021.The patients were divided into groups according to the infection rate increase pattern (II/III/IV pandemic wave), status of vaccination and place of isolation. Regardless of the pandemic wave, the patients’ most commonly reported weaknesses were a cough and a headache. The arterial hypertension and hyperlipidemia were the most frequent concomitant chronic conditions. Hospitalized patients more often reported weakness or a cough while home-isolated patients were more likely to have rhinitis or a headache. Patients who completed the vaccination course showed a shorter duration of clinical symptoms and a lower mean number of symptoms. Additionally, vaccinated individuals reported less taste and/or olfactory dysfunction than unvaccinated individuals. To conclude, the persistence of the pandemic has resulted in significant changes observed in the clinical picture. Successive waves caused deterioration in the subjective assessment of the disease severity. A cough seemed to occur more frequently in the later pandemic waves.

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Section: Discussionmentioning

confidence: 95%

Do the Successive Waves of SARS-CoV-2, Vaccination Status and Place of Infection Influence the Clinical Picture and COVID-19 Severity among Patients with Persistent Clinical Symptoms? The Retrospective Study of Patients from the STOP-COVID Registry of the PoLoCOV-Study

Chudzik

Babicki

Kapusta

et al. 2022

JPM

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“…Since a transmission event is associated with a location linked to communities on the road network, over time, public health can use the PPT to predict/estimate the risk for the communities liked to the road network. Notably, we estimate that asymptomatic and presymptomatic cases will account for 15% and 52% of the notified positive cases, respectively, 25 which are associated with a lower secondary transmission risk. Such estimates will be contextualised using our empirical data and used to evaluate the tool’s effectiveness for contact tracing, that is, the sensitivity and proportion of expected false positive contact notification.…”

Section: Methodsmentioning

confidence: 92%

Developing digital contact tracing tailored to haulage in East Africa to support COVID-19 surveillance: a protocol

et al. 2022

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IntroductionAt the peak of Uganda’s first wave of SARS-CoV-2 in May 2020, one in three COVID-19 cases was linked to the haulage sector. This triggered a mandatory requirement for a negative PCR test result at all ports of entry and exit, resulting in significant delays as haulage drivers had to wait for 24–48 hours for results, which severely crippled the regional supply chain.To support public health and economic recovery, we aim to develop and test a mobile phone-based digital contact tracing (DCT) tool that both augments conventional contact tracing and also increases its speed and efficiency.Methods and analysisTo test the DCT tool, we will use a stratified sample of haulage driver journeys, stratified by route type (regional and local journeys).We will include at least 65% of the haulage driver journeys ~83 200 on the network through Uganda. This allows us to capture variations in user demographics and socioeconomic characteristics that could influence the use and adoption of the DCT tool. The developed DCT tool will include a mobile application and web interface to collate and intelligently process data, whose output will support decision-making, resource allocation and feed mathematical models that predict epidemic waves.The main expected result will be an open source-tested DCT tool tailored to haulage use in developing countries.This study will inform the safe deployment of DCT technologies needed for combatting pandemics in low-income countries.Ethics and disseminationThis work has received ethics approval from the School of Public Health Higher Degrees, Research and Ethics Committee at Makerere University and The Uganda National Council for Science and Technology. This work will be disseminated through peer-reviewed publications, our websites https://project-thea.org/ and Github for the open source code https://github.com/project-thea/.

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“…Then it is reasonable to assume that r I = 1/13.4 per day and r A = 1/8 per day. Gao et al (2021) discovered that 76% of seropositive infections were accompanied by no symptoms based on a study among 34857 participants in China. In addition, they found that the relative transmissibility varied from 0.35 to 0.58 for asymptomatic cases and was 0.63 for pre-symptomatic cases.…”

Section: Parameter Estimationmentioning

confidence: 99%

“…info/coronavirus/country/us/). We assume that A[1] = 0.76I [1]/0.24 according to Gao et al (2021). It follows that…”

Section: Parameter Estimationmentioning

confidence: 99%

From Policy to Prediction: Forecasting COVID-19 Dynamics Under Imperfect Vaccination

Wang

Ramazi

et al. 2022

Bull Math Biol

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Understanding the joint impact of vaccination and non-pharmaceutical interventions on COVID-19 development is important for making public health decisions that control the pandemic. Recently, we created a method in forecasting the daily number of confirmed cases of infectious diseases by combining a mechanistic ordinary differential equation (ODE) model for infectious classes and a generalized boosting machine learning model (GBM) for predicting how public health policies and mobility data affect the transmission rate in the ODE model (Wang et al. in Bull Math Biol 84:57, 2022). In this paper, we extend the method to the post-vaccination period, accordingly obtain a retrospective forecast of COVID-19 daily confirmed cases in the US, and identify the relative influence of the policies used as the predictor variables. In particular, our ODE model contains both partially and fully vaccinated compartments and accounts for the breakthrough cases, that is, vaccinated individuals can still get infected. Our results indicate that the inclusion of data on non-pharmaceutical interventions can significantly improve the accuracy of the predictions. With the use of policy data, the model predicts the number of daily infected cases up to 35 days in the future, with an average mean absolute percentage error of 20.15%, which is further improved to 14.88% if combined with human mobility data. Moreover, the most influential predictor variables are the policies of restrictions on gatherings, testing B Hao Wang

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Role of asymptomatic and pre-symptomatic infections in covid-19 pandemic

Cited by 55 publications

References 21 publications

Do the Successive Waves of SARS-CoV-2, Vaccination Status and Place of Infection Influence the Clinical Picture and COVID-19 Severity among Patients with Persistent Clinical Symptoms? The Retrospective Study of Patients from the STOP-COVID Registry of the PoLoCOV-Study

Do the Successive Waves of SARS-CoV-2, Vaccination Status and Place of Infection Influence the Clinical Picture and COVID-19 Severity among Patients with Persistent Clinical Symptoms? The Retrospective Study of Patients from the STOP-COVID Registry of the PoLoCOV-Study

Developing digital contact tracing tailored to haulage in East Africa to support COVID-19 surveillance: a protocol

From Policy to Prediction: Forecasting COVID-19 Dynamics Under Imperfect Vaccination

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