The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using ...publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2-14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3-4 days without truncation and at 5-9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.
Abstract
Background
Coronavirus disease 2019 (COVID-19) has rapidly evolved to become a global pandemic, largely owing to the transmission of its causative virus through asymptomatic carriers. ...Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in asymptomatic people is an urgent priority for the prevention and containment of disease outbreaks in communities. However, few data are available in asymptomatic persons regarding the accuracy of polymerase chain reaction testing. In addition, although self-collected saliva samples have significant logistical advantages in mass screening, their utility as an alternative specimen in asymptomatic persons is yet to be determined.
Methods
We conducted a mass screening study to compare the utility of nucleic acid amplification, such as reverse-transcription polymerase chain reaction testing, using nasopharyngeal swab (NPS) and saliva samples from each individual in 2 cohorts of asymptomatic persons: the contact-tracing cohort and the airport quarantine cohort.
Results
In this mass screening study including 1924 individuals, the sensitivities of nucleic acid amplification testing with NPS and saliva specimens were 86% (90% credible interval, 77%–93%) and 92% (83%–97%), respectively, with specificities >99.9%. The true concordance probability between the NPS and saliva tests was estimated at 0.998 (90% credible interval, .996–.999) given the recent airport prevalence of 0.3%. In individuals testing positive, viral load was highly correlated between NPS and saliva specimens.
Conclusion
Both NPS and saliva specimens had high sensitivity and specificity. Self-collected saliva specimens are valuable for detecting SARS-CoV-2 in mass screening of asymptomatic persons.
The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) ...in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number-the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval CI: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.
A cluster of pneumonia cases linked to a novel coronavirus (2019-nCoV) was reported by China in late December 2019. Reported case incidence has now reached the hundreds, but this is likely an ...underestimate. As of 24 January 2020, with reports of thirteen exportation events, we estimate the cumulative incidence in China at 5502 cases (95% confidence interval: 3027, 9057). The most plausible number of infections is in the order of thousands, rather than hundreds, and there is a strong indication that untraced exposures other than the one in the epidemiologically linked seafood market in Wuhan have occurred.
•An epidemiological model with a stratified immunity level was constructed.•Without imposing a cut-off value for immune response, titer distributions were analysed.•The basic reproduction number was ...greater than the estimate with the cut-off value.
Seroepidemiological surveillance data has been demonstrated to be useful for estimating the cumulative incidence of influenza, and measures the difference between pre- and post-epidemic seropositive fractions. Despite this, such studies relied on a chosen cut-off value for seropositivity. The aim of the present study is to develop a method to analyze distributions of serial cross-sectional seroepidemiological surveillance datasets using an epidemiological model so that the transmission potential can be estimated without imposing a cut-off value.
A mathematical model of influenza transmission with a discrete antibody titer level was constructed. The final size equation for pre- and post-epidemic titer levels was derived. Subsequently, using the estimated distribution of the dilution increase caused by infection and the measurement error distribution, the model parameters were optimized using the maximum likelihood method. A bootstrap-based confidence interval calculation and sensitivity analysis were also performed.
Without imposing a cut-off value, the cumulative incidence was quantified, thereby yielding an estimate of the basic reproduction number. For the purpose of exposition, the proposed method was applied to influenza A/Victoria/3/75(H3N2) data, and serological data between 1975 and 1976 were compared. The estimated reproduction number was greater than that using the cut-off value of the hemagglutination inhibition level with titer level 20 (dilution 1:20) or above to define positives.
The proposed method without a cut-off value offers an unbiased approach to estimating the cumulative incidence along with the reproduction number. If a cut-off value is required, the results imply that titer level 20 or above may better represent a reasonable cut-off value for calculating the incidence, but it could underestimate the basic reproduction number.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
From 29 to 31 January 2020, a total of 565 Japanese citizens were evacuated from Wuhan, China on three chartered flights. All passengers were screened upon arrival in Japan for symptoms consistent ...with novel coronavirus (2019-nCoV) infection and tested for presence of the virus. Assuming that the mean detection window of the virus can be informed by the mean serial interval (estimated at 7.5 days), the ascertainment rate of infection was estimated at 9.2% (95% confidence interval: 5.0, 20.0). This indicates that the incidence of infection in Wuhan can be estimated at 20,767 infected individuals, including those with asymptomatic and mildly symptomatic infections. The infection fatality risk (IFR)-the actual risk of death among all infected individuals-is therefore 0.3% to 0.6%, which may be comparable to Asian influenza pandemic of 1957-1958.
The impact of the drastic reduction in travel volume within mainland China in January and February 2020 was quantified with respect to reports of novel coronavirus (COVID-19) infections outside ...China. Data on confirmed cases diagnosed outside China were analyzed using statistical models to estimate the impact of travel reduction on three epidemiological outcome measures: (i) the number of exported cases, (ii) the probability of a major epidemic, and (iii) the time delay to a major epidemic. From 28 January to 7 February 2020, we estimated that 226 exported cases (95% confidence interval: 86,449) were prevented, corresponding to a 70.4% reduction in incidence compared to the counterfactual scenario. The reduced probability of a major epidemic ranged from 7% to 20% in Japan, which resulted in a median time delay to a major epidemic of two days. Depending on the scenario, the estimated delay may be less than one day. As the delay is small, the decision to control travel volume through restrictions on freedom of movement should be balanced between the resulting estimated epidemiological impact and predicted economic fallout.
To understand the severity of infection for a given disease, it is common epidemiological practice to estimate the case fatality risk, defined as the risk of death among cases. However, there are ...three technical obstacles that should be addressed to appropriately measure this risk. First, division of the cumulative number of deaths by that of cases tends to underestimate the actual risk because deaths that will occur have not yet observed, and so the delay in time from illness onset to death must be addressed. Second, the observed dataset of reported cases represents only a proportion of all infected individuals and there can be a substantial number of asymptomatic and mildly infected individuals who are never diagnosed. Third, ascertainment bias and risk of death among all those infected would be smaller when estimated using shorter virus detection windows and less sensitive diagnostic laboratory tests. In the ongoing COVID-19 epidemic, health authorities must cope with the uncertainty in the risk of death from COVID-19, and high-risk individuals should be identified using approaches that can address the abovementioned three problems. Although COVID-19 involves mostly mild infections among the majority of the general population, the risk of death among young adults is higher than that of seasonal influenza, and elderly with underlying comorbidities require additional care.
Vehicular edge computing (VEC) is essential in vehicle applications such as traffic control and in-vehicle services. In the task offloading process of VEC, predictive-mode transmission based on deep ...learning is constrained by limited computational resources. Furthermore, the accuracy of deep learning algorithms in VEC is compromised due to the lack of edge computing features in algorithms. To solve these problems, this paper proposes a task offloading optimization approach that enables edge servers to store deep learning models. Moreover, this paper proposes the LTransformer, a transformer-based framework that incorporates edge computing features. The framework consists of pre-training, an input module, an encoding–decoding module, and an output module. Compared with four sequential deep learning methods, namely a Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), a Gated Recurrent Unit (GRU), and the Transformer, the LTransformer achieves the highest accuracy, reaching 80.1% on the real dataset. In addition, the LTransformer achieves 0.008 s when predicting a single trajectory, fully satisfying the fundamental requirements of real-time prediction and enabling task offloading optimization.
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