scholarly journals An exploratory study on the correlation of population SARS-CoV-2 cycle threshold values to local disease dynamics

2021 ◽  
Author(s):  
Chak Foon Tso ◽  
Anurag Garikipati ◽  
Abigail Green-Saxena ◽  
Qingqing Mao ◽  
Ritankar Das
Keyword(s):  
Time Delay ◽  
Transmission Rate ◽  
El Paso ◽  
Geographical Area ◽  
Disease Dynamics ◽  
Cycle Threshold ◽  
Ct Value ◽  
Population Distributions ◽  
Percent Positivity ◽  
Daily Change

ABSTRACTIntroductionDespite limitations on the use of cycle threshold (CT) values for individual patient care, population distributions of CT values may be useful indicators of local outbreaks.MethodsSpecimens from the greater El Paso area were processed in the Dascena COVID-19 Laboratory. Daily median CT value, daily transmission rate R(t), daily count of COVID-19 hospitalizations, daily change in percent positivity, and rolling averages of these features were plotted over time. Two-way scatterplots and linear regression evaluated possible associations between daily median CT and outbreak measures. Cross-correlation plots determined whether a time delay existed between changes in the daily median CT value and measure of community disease dynamics.ResultsDaily median CT was negatively correlated with the daily R(t), the daily COVID-19 hospitalization count (with a time delay), and the daily change in percent positivity among testing samples. Despite visual trends suggesting time delays in the plots for median CT and outbreak measures, a statistically significant delay was only detected between changes in median CT and COVID-19 hospitalization count.ConclusionsThis study adds to the literature by analyzing samples collected from an entire geographical area, and contextualizing the results with other research investigating population CT values.

scholarly journals Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study (Preprint)

2021 ◽  
Author(s):  
Chak Foon Tso ◽  
Anurag Garikipati ◽  
Abigail Green-Saxena ◽  
Qingqing Mao ◽  
Ritankar Das
Keyword(s):  
Time Delay ◽  
Population Distribution ◽  
Transmission Rate ◽  
El Paso ◽  
Geographical Area ◽  
Disease Dynamics ◽  
Cycle Threshold ◽  
Population Distributions ◽  
Percent Positivity ◽  
Daily Changes

BACKGROUND Despite the limitations in the use of cycle threshold (CT) values for individual patient care, population distributions of CT values may be useful indicators of local outbreaks. OBJECTIVE We aimed to conduct an exploratory analysis of potential correlations between the population distribution of cycle threshold (CT) values and COVID-19 dynamics, which were operationalized as percent positivity, transmission rate (R<sub>t</sub>), and COVID-19 hospitalization count. METHODS In total, 148,410 specimens collected between September 15, 2020, and January 11, 2021, from the greater El Paso area were processed in the Dascena COVID-19 Laboratory. The daily median CT value, daily R<sub>t</sub>, daily count of COVID-19 hospitalizations, daily change in percent positivity, and rolling averages of these features were plotted over time. Two-way scatterplots and linear regression were used to evaluate possible associations between daily median CT values and outbreak measures. Cross-correlation plots were used to determine whether a time delay existed between changes in daily median CT values and measures of community disease dynamics. RESULTS Daily median CT values negatively correlated with the daily R<sub>t</sub> values (<i>P</i>&lt;.001), the daily COVID-19 hospitalization counts (with a 33-day time delay; <i>P</i>&lt;.001), and the daily changes in percent positivity among testing samples (<i>P</i>&lt;.001). Despite visual trends suggesting time delays in the plots for median CT values and outbreak measures, a statistically significant delay was only detected between changes in median CT values and COVID-19 hospitalization counts (<i>P</i>&lt;.001). CONCLUSIONS This study adds to the literature by analyzing samples collected from an entire geographical area and contextualizing the results with other research investigating population CT values.

scholarly journals 414. Association of SARS-CoV-2 Genomic Load Trends with Clinical Status in COVID-19:A Retrospective Analysis from an Academic Hospital Center in New York City

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S275-S275
Author(s):  
Ioannis Zacharioudakis ◽  
Fainareti Zervou ◽  
Prithiv Prasad ◽  
Yongzhao Shao ◽  
Atreyee Basu ◽  
...  
Keyword(s):  
New York ◽  
Sofa Score ◽  
Research Question ◽  
Clinical Status ◽  
Inverse Correlation ◽  
Duration Of Symptoms ◽  
Cycle Threshold ◽  
Ct Value ◽  
Failure Assessment ◽  
Polymerase Chain

Abstract Background The Infectious Diseases Society of America has identified the potential use of SARS-CoV-2 genomic load for prognostication purposes as a key research question. Methods We designed a retrospective cohort study that included adult patients with COVID-19 pneumonia who had at least 2 positive nasopharyngeal tests at least 24 hours apart to study the correlation between the change in the genomic load of SARS-CoV-2 in nasopharyngeal samples, as reflected by the Cycle threshold (Ct) value of the real-time Polymerase Chain Reaction (PCR) assay, with change in clinical status. The Sequential Organ Failure Assessment (SOFA) score was used as a surrogate for patients’ clinical status. A linear mixed-effects regression analysis was performed. Results Among 457 patients who presented to the emergency department between 3/31/2020- 4/10/2020, we identified 42 patients who met the inclusion criteria. The median initial SOFA score was 2 (IQR 2–3). 20 out of 42 patients had a lower SOFA score on their subsequent tests. We identified a statistically significant inverse correlation between the change in SOFA score and change in the Ct value with a decrease in SOFA score by 0.05 (SE 0.02; p &lt; 0.05) for an increase in Ct values by 1. This correlation was independent of the duration of symptoms. Flow chart A graph of the Cycle Threshold (Ct) values of the of Cepheid Xpert® Xpress SARS-CoV-2 assay measured on repeat screening of the 42 included patients. Graph of the fitted SOFA scores based on the Cycle Threshold values per patient. Conclusion Our findings suggest that an increasing Ct value in sequential tests may be of prognostic value for patients diagnosed with COVID-19 pneumonia. Before repeat testing can be recommended routinely in clinical practice as a predictor of disease outcomes, prospective studies with a standardized interval between repeat tests should confirm our findings. Disclosures All Authors: No reported disclosures

scholarly journals Hopf Bifurcation of a Delayed Ecoepidemic Model with Ratio-Dependent Transmission Rate

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Wanjun Xia ◽  
Soumen Kundu ◽  
Sarit Maitra
Keyword(s):  
Hopf Bifurcation ◽  
Time Delay ◽  
Center Manifold ◽  
Transmission Rate ◽  
Sufficient Conditions ◽  
Normal Form Theory ◽  
Center Manifold Theorem ◽  
Form Theory ◽  
Ratio Dependent ◽  
Theoretical Results

A delayed ecoepidemic model with ratio-dependent transmission rate has been proposed in this paper. Effects of the time delay due to the gestation of the predator are the main focus of our work. Sufficient conditions for local stability and existence of a Hopf bifurcation of the model are derived by regarding the time delay as the bifurcation parameter. Furthermore, properties of the Hopf bifurcation are investigated by using the normal form theory and the center manifold theorem. Finally, numerical simulations are carried out in order to validate our obtained theoretical results.

scholarly journals 147. Defining the Optimal Serial Testing Interval and Features for Identifying Patients with Early SARS-CoV-2 Infection

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S88-S89
Author(s):  
Sanjat Kanjilal
Keyword(s):  
Panel Member ◽  
Early Infection ◽  
Test Pair ◽  
Positive Test ◽  
Time Interval ◽  
Body Site ◽  
Time Intervals ◽  
Ct Value ◽  
Serial Testing ◽  
Percent Positivity

Abstract Background Serial testing for SARS-CoV-2 is necessary to prevent spread from patients early in infection. Testing intervals are largely derived from viral kinetic studies performed early in the COVID-19 pandemic. Laboratory and epidemiologic data accrued over the past year present an opportunity to use empiric models to define optimal serial testing intervals and features predictive of early infection. Methods Retrospective analysis of 15,314 inpatients within the Mass General Brigham healthcare system who had two tests within a 36-hour period between May 1 2020 and May 29 2021. Early infection was defined as having a negative test followed by a positive test. Patients with prior positive tests were excluded. The primary outcome was the proportion of patients in early infection over the total number tested serially, stratified by 4-hour testing intervals from the timestamp of the first test. Multivariate modeling was used to identify features predictive of early infection. Covariates included demographics, body site, PCR assay, location, community incidence, percent positivity, and median / skew of Ct value distributions. Results Of 19,971 test pairs, 193 (0.97%) were characterized as a negative followed by a positive within 36 hours. Bivariate analysis showed a close association between negative to positive test pairs during the first surge in spring 2020 that was not present during the winter surge. Negative to positive test pairs were most common in the 12 to 16 hour time interval (51/193, 26%, Figure 1). After controlling for covariates, the Roche cobas assay was more likely to identify patients with a negative to positive test pair relative to the Cepheid Xpert, Hologic Panther Fusion and Roche Liat assays. A second specimen from the lower respiratory tract was more likely to lead to a positive relative to other body sites. Community incidence and Ct value distributions were not predictive and there were no differences between nasal and nasopharyngeal swabs. All 4-hour time intervals from 16 to 36 hours were significant for predicting a negative to positive test pair (Table 1). Figure 1. Distribution of negative to positive test pairs by 4 hour time intervals Table 1. Multivariate regression predicting a negative to positive test pair Conclusion The likelihood of detecting early infection is dependent on PCR platform and body site of sampling. A range of time intervals between 16 to 36 hours after the initial test were likely to identify positive cases. Disclosures Sanjat Kanjilal, MD, MPH, GlaskoSmithKline (Advisor or Review Panel member)

scholarly journals High amounts of SARS-CoV-2 precede sickness among asymptomatic healthcare workers

2021 ◽  
Author(s):  
Joakim Dillner ◽  
K Miriam Elfström ◽  
Jonas Blomqvist ◽  
Lars Engstrand ◽  
Mathias Uhlén ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Sick Leave ◽  
Healthcare Workers ◽  
Multinomial Logistic Regression ◽  
Excess Risk ◽  
University Hospital ◽  
Cycle Threshold ◽  
The Past ◽  
Ct Value

Abstract Background Whether SARS-CoV-2 positivity among symptomatic subjects reflects past or future disease may be difficult to ascertain. Methods We tested a cohort of 9449 employees at work at the Karolinska University Hospital, Stockholm, Sweden for SARS-CoV-2 RNA and antibodies, linked the testing results to sick leave records and determined associations with past or future sick leave using multinomial logistic regression. ClinicalTrials.gov NCT04411576. Results Subjects with high amounts of SARS-CoV-2 virus, as indicated by the Cycle threshold (Ct) value in the PCR, had the highest risk for sick leave in the two weeks after testing (OR 11.97 (CI 95% 6.29-22.80)) whereas subjects with low amounts of virus had the highest risk for sick leave in the past three weeks before testing (OR 6.31 (4.38-9.08)). Only 2.5% of employees were SARS-CoV-2 positive while 10.5% were positive by serology and 1.2% were positive in both tests. Serology-positive subjects were not at excess risk for future sick leave (OR 1.06 (95% CI, 0.71-1.57)). Conclusions High amounts of SARS-CoV-2 virus, as determined using PCR Ct values, associates with development of sickness in the next few weeks. The results support the concept that PCR Ct may be informative when testing for SARS-CoV-2 is performed.

scholarly journals Intelligent Transport System Using Time Delay-Based Multipath Routing Protocol for Vehicular Ad Hoc Networks

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7706
Author(s):  
Yashar Ghaemi ◽  
Hosam El-Ocla ◽  
Nitin Ramesh Yadav ◽  
Manisha Reddy Madana ◽  
Dheeraj Kurugod Raju ◽  
...  
Keyword(s):  
Time Delay ◽  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Transmission Rate ◽  
Multipath Routing ◽  
Real Life ◽  
The Other ◽  
Traffic Load ◽  
Intelligent Transport System ◽  
Hoc Networks

During the last decade, the research on Intelligent Transportation System (ITS) has improved exponentially in real-life scenarios to provide optimized transport network performance. It is a matter of importance that alert messages are delivered promptly to prevent vehicular traffic problems. The fact is an ITS system per se could be a part of a vehicular ad hoc network (VANET) which is an extension of a wireless network. In all sorts of wireless ad hoc networks, the network topology is subjected to change due to the mobility of network nodes; therefore, an existing explored route between two nodes could be demolished in a minor fraction of time. When it comes to the VANETs, the topology likely changes due to the high velocity of nodes. On the other hand, time is a crucial factor playing an important role in message handling between the network’s nodes. In this paper, we propose Time delay-based Multipath Routing (TMR) protocol that effectively identifies an optimized path for packet delivery to the destination vehicle with a minimal time delay. Our algorithm gives a higher priority to alert messages compared to normal messages. It also selects the routes with the short round-trip time (RTT) within the RTT threshold. As a result, our algorithm would realize two goals. Firstly, it would speed up the data transmission rate and deliver data packets, particularly warning messages, to the destination vehicle promptly and therefore avoid vehicular problems such as car accidents. Secondly, the TMR algorithm reduces the data traffic load, particularly of the normal messages, to alleviate the pressure on the network and therefore avoids network congestion and data collisions. This, in turn, lessens the packets’ retransmissions. To demonstrate the effectiveness of the proposed protocol, the TMR has been compared with the other protocols such as AOMDV, FF-AOMDV, EGSR, QMR, and ISR. Simulation results demonstrate that our proposed protocol proves its excellent performance compared to other protocols.

scholarly journals Association between household exposure and cycle threshold in COVID-19 infected health care workers

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ai Chien ◽  
Sandra Domeracki ◽  
Sandeep Guntur ◽  
Kristopher Taylor ◽  
Chuanyi M. Lu ◽  
...  
Keyword(s):  
Health Care ◽  
Viral Load ◽  
Health Care Workers ◽  
Bivariate Model ◽  
Cycle Threshold ◽  
Ct Value ◽  
Care Workers ◽  
Polymerase Chain ◽  
Ct Data ◽  
Multivariable Modelling

Abstract Objective Household SARS-COV-2 contact constitutes a high-risk exposure for health care workers (HCWs). Cycle threshold (Ct) of reverse transcriptase–polymerase chain reaction testing provides an estimate of COVID-19 viral load, which can inform clinical and workplace management. We assessed whether Ct values differed between HCWs with COVID-19 with and without household exposure. Methods We analyzed HCW COVID-19 cases whose Ct data could be compared. We defined low Ct at a cut-point approximating a viral load of 4.6 × 106 copies per ml. Logistic regression tested the association of household exposure and symptoms at diagnosis with a low Ct value. Results Of 77 HCWs with COVID-19, 20 were household exposures cases and 34 were symptomatic at testing (7 were both household-exposed and symptomatic at testing). Among household exposures, 9 of 20 (45%) manifested lower Ct values compared to 14 of 57 (25%) for all others. In a bivariate model, household exposure was not statistically associated with lower Ct (Odds Ratio [OR] 1.20; 95% Confidence Interval [CI] 0.97–1.51). In multivariable modelling both household exposure (OR] 1.3; 95% CI 1.03–1.6) and symptoms at diagnosis (OR 1.4; 95% CI 1.15–1.7) were associated with a low Ct value. Discussion Household exposure in HCWs with newly diagnosed COVID-19 was associated with lower Ct values, consistent with a higher viral load, supporting the hypothesis that contracting COVID-19 in that manner leads to a greater viral inoculum.

scholarly journals #27: Comparison of RT-PCR Cycle Threshold Values from Respiratory Specimens in Symptomatic and Asymptomatic Children with SARS CoV-2 Infection

2021 ◽  
Vol 10 (Supplement_2) ◽  
pp. S10-S11
Author(s):  
John Strutner ◽  
Nanda Ramchandar ◽  
Shruti Dubey ◽  
Mary Gamboa ◽  
Michelle K Vanderpool ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Tertiary Care ◽  
Severe Illness ◽  
Rt Pcr ◽  
Respiratory Specimen ◽  
Cycle Threshold ◽  
Ct Value ◽  
Asymptomatic Children ◽  
The Mean

Abstract Background Understanding viral kinetics of SARS-CoV-2 is important to assess risk of transmission, manage treatment, and determine the need for isolation and protective equipment. Children have been noted to have less severe illness than adults and may have less transmission potential. We sought to determine whether children deemed to be asymptomatic had a difference in the PCR cycle threshold (Ct) value of respiratory samples from symptomatic children with SARS CoV-2 infection. Methods This was a retrospective cross-sectional study to compare PCR Ct values of 728 children who tested positive for SARS-CoV-2 by respiratory samples collected over a 4-month period. The study was a single center review of patients who tested positive for SARS-CoV-2 by RT-PCR from a respiratory specimen at a large tertiary care children’s hospital. Inclusion criteria included children 0–18 years of age who tested positive for SARS-CoV-2 by RT-PCR from a respiratory specimen for whom clinical information was available in the electronic medical record. Results We analyzed 728 children who tested positive for SARS-CoV-2 by RT-PCR from a respiratory sample over a 4-month period and for whom data was available in the electronic medical record. Overall, 71.2% of infected children were symptomatic. The mean Ct value for symptomatic patients (Ct mean 19.9, SD 6.3) was significantly lower than asymptomatic patients (Ct mean 23.5, SD 6.5) (P value &lt; 0.001, CI95th 2.6 - 4.6). The mean PCR Ct value was lowest in children less than 5 years of age. Conclusions and Relevance In this retrospective review of children who tested positive by RT-PCR for SARS CoV-2, the mean Ct was significantly lower in symptomatic children and was lowest in children under 5 years of age.

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