scholarly journals Estimation of the test to test distribution as a proxy for generation interval distribution for the Omicron variant in England

2022 ◽  
Author(s):  
Sam Abbott ◽  
Katharine Sherratt ◽  
Moritz Gerstung ◽  
Sebastian Funk
Keyword(s):  
South Africa ◽  
Standard Deviation ◽  
Generation Time ◽  
Time Distribution ◽  
Immune Escape ◽  
Credible Interval ◽  
Contact Tracing ◽  
Time Varying ◽  
Daily Growth ◽  
Gene Target

Background Early estimates from South Africa indicated that the Omicron COVID-19 variant may be both more transmissible and have greater immune escape than the previously dominant Delta variant. The rapid turnover of the latest epidemic wave in South Africa as well as initial evidence from contact tracing and household infection studies has prompted speculation that the generation time of the Omicron variant may be shorter in comparable settings than the generation time of the Delta variant. Methods We estimated daily growth rates for the Omicron and Delta variants in each UKHSA region from the 23rd of November to the 23rd of December 2021 using surveillance case counts by date of specimen and S-gene target failure status with an autoregressive model that allowed for time-varying differences in the transmission advantage of the Delta variant where the evidence supported this. By assuming a gamma distributed generation distribution we then estimated the generation time distribution and transmission advantage of the Omicron variant that would be required to explain this time varying advantage. We repeated this estimation process using two different prior estimates for the generation time of the Delta variant first based on household transmission and then based on its intrinsic generation time. Results Visualising our growth rate estimates provided initial evidence for a difference in generation time distributions. Assuming a generation time distribution for Delta with a mean of 2.5-4 days (90% credible interval) and a standard deviation of 1.9-3 days we estimated a shorter generation time distribution for Omicron with a mean of 1.5-3.2 days and a standard deviation of 1.3-4.6 days. This implied a transmission advantage for Omicron in this setting of 160%-210% compared to Delta. We found similar relative results using an estimate of the intrinsic generation time for Delta though all estimates increased in magnitude due to the longer assumed generation time. Conclusions We found that a reduction in the generation time of Omicron compared to Delta was able to explain the observed variation over time in the transmission advantage of the Omicron variant. However, this analysis cannot rule out the role of other factors such as differences in the populations the variants were mixing in, differences in immune escape between variants or bias due to using the test to test distribution as a proxy for the generation time distribution.

scholarly journals On the relationship between serial interval, infectiousness profile and generation time

2021 ◽  
Vol 18 (174) ◽  
pp. 20200756
Author(s):  
Sonja Lehtinen ◽  
Peter Ashcroft ◽  
Sebastian Bonhoeffer
Keyword(s):  
Symptom Onset ◽  
Generation Time ◽  
Time Distribution ◽  
Contact Tracing ◽  
Time Interval ◽  
Single Individual ◽  
Generation Times ◽  
Serial Interval ◽  
The Impact ◽  
The Relationship

The timing of transmission plays a key role in the dynamics and controllability of an epidemic. However, observing generation times—the time interval between the infection of an infector and an infectee in a transmission pair—requires data on infection times, which are generally unknown. The timing of symptom onset is more easily observed; generation times are therefore often estimated based on serial intervals—the time interval between symptom onset of an infector and an infectee. This estimation follows one of two approaches: (i) approximating the generation time distribution by the serial interval distribution or (ii) deriving the generation time distribution from the serial interval and incubation period—the time interval between infection and symptom onset in a single individual—distributions. These two approaches make different—and not always explicitly stated—assumptions about the relationship between infectiousness and symptoms, resulting in different generation time distributions with the same mean but unequal variances. Here, we clarify the assumptions that each approach makes and show that neither set of assumptions is plausible for most pathogens. However, the variances of the generation time distribution derived under each assumption can reasonably be considered as upper (approximation with serial interval) and lower (derivation from serial interval) bounds. Thus, we suggest a pragmatic solution is to use both approaches and treat these as edge cases in downstream analysis. We discuss the impact of the variance of the generation time distribution on the controllability of an epidemic through strategies based on contact tracing, and we show that underestimating this variance is likely to overestimate controllability.

scholarly journals On the relationship between serial interval, infectiousness profile and generation time

2020 ◽  
Author(s):  
Sonja Lehtinen ◽  
Peter Ashcroft ◽  
Sebastian Bonhoeffer
Keyword(s):  
Symptom Onset ◽  
Generation Time ◽  
Time Distribution ◽  
Contact Tracing ◽  
Time Interval ◽  
Single Individual ◽  
Serial Interval ◽  
The Impact ◽  
The Relationship ◽  
Interval Distribution

The timing of transmission plays a key role in the dynamics and controllability of an epidemic. However, observing the distribution of generation times (time interval between the points of infection of an infector and infectee in a transmission pair) requires data on infection times, which are generally unknown. The timing of symptom onset is more easily observed; the generation time distribution is therefore often estimated based on the serial interval distribution (distribution of time intervals between symptom onset of an infector and an infectee). This estimation follows one of two approaches: i) approximating the generation time distribution by the serial interval distribution; or ii) deriving the generation time distribution from the serial interval and incubation period (time interval between infection and symptom onset in a single individual) distributions. These two approaches make different -- and not always explicitly stated -- assumptions about the relationship between infectiousness and symptoms, resulting in different generation time distributions with the same mean but unequal variances. Here, we clarify the assumptions that each approach makes and show that neither set of assumptions is plausible for most pathogens. However, the variances of the generation time distribution derived under each assumption can reasonably be considered as upper (approximation with serial interval) and lower (derivation from serial interval) bounds. Thus, we suggest a pragmatic solution is to use both approaches and treat these as edge cases in downstream analysis. We discuss the impact of the variance of the generation time distribution on the controllability of an epidemic through strategies based on contact tracing, and we show that underestimating this variance is likely to overestimate controllability.

scholarly journals Preliminary modeling estimates of the relative transmissibility and immune escape of the Omicron SARS-CoV-2 variant of concern in South Africa

2022 ◽  
Author(s):  
Nicolò Gozzi ◽  
Matteo Chinazzi ◽  
Jessica T. Davis ◽  
Kunpeng Mu ◽  
Ana Pastore y Piontti ◽  
...  
Keyword(s):  
South Africa ◽  
Parameter Space ◽  
Generation Time ◽  
Immune Escape ◽  
Current Knowledge ◽  
Unknown Origin ◽  
Epidemiological Data ◽  
Initial Seeding ◽  
Epidemic Wave ◽  
Pharmaceutical Interventions

We develop a stochastic, multi-strain, compartmental epidemic model to estimate the relative transmissibility and immune escape of the Omicron variant of concern (VOC) in South Africa. The model integrates population, non-pharmaceutical interventions, vaccines, and epidemiological data and it is calibrated in the period May 1st, 2021 - November 23rd, 2021. We explore a parameter space of relative transmissibility with respect to the Delta variant and immune escape for Omicron by assuming an initial seeding, from unknown origin, in the first week of October 2021. We identify a region of the parameter space where combinations of relative transmissibility and immune escape are compatible with the growth of the epidemic wave. We also find that changes in the generation time associated with Omicron infections strongly affect the results concerning its relative transmissibility. The presented results are informed by current knowledge of Omicron and subject to changes.

scholarly journals Challenges in Contact Tracing by Mining Mobile Phone Location Data for COVID-19: Implications for Public Governance in South Africa

10.28945/4736 ◽  
2021 ◽  
Vol 16 ◽  
pp. 101-124
Author(s):  
Paul Kariuki ◽  
Lizzy O Ofusori ◽  
Prabhakar Rontala Subramanniam ◽  
Moses Okpeku ◽  
Maria L Goyayi
Keyword(s):  
Public Health ◽  
South Africa ◽  
Mobile Phone ◽  
Contact Tracing ◽  
Future Research ◽  
Public Governance ◽  
The Public ◽  
Location Data ◽  
Pertinent Data ◽  
Privacy And Confidentiality

Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving.

scholarly journals Transmission dynamics of the delta variant of SARS-CoV-2 infections in Daejeon, South Korea

2021 ◽  
Author(s):  
Hari Hwang ◽  
Jun-Sik Lim ◽  
Sun-Ah Song ◽  
Chiara Achangwa ◽  
Woobeom Sim ◽  
...  
Keyword(s):  
South Korea ◽  
Symptom Onset ◽  
Credible Interval ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Nasopharyngeal Swab ◽  
Strict Adherence ◽  
Virus Shedding ◽  
Viral Shedding ◽  
Asymptomatic Patients

Abstract Background The delta variant of SARS-CoV-2 is now the predominant variant worldwide. However, its transmission dynamics remain unclear. Methods We analyzed all case patients in local clusters and temporal patterns of viral shedding using contact tracing data from 405 cases associated with the delta variant of SARS-CoV-2 between 22 June and 31 July 2021 in Daejeon, South Korea. Results Overall, half of the cases were aged under 19 years, and 20% were asymptomatic at the time of epidemiological investigation. We estimated the mean serial interval as 3.26 days (95% credible interval 2.92, 3.60), and 12% of the transmission occurred before symptom onset of the infector. We identified six clustered outbreaks, and all were associated with indoor facilities. In 23 household contacts, the secondary attack rate was 63% (52/82). We estimated that 15% (95% confidence interval, 13–18%) of cases seeded 80% of all local transmission. Analysis of the nasopharyngeal swab samples identified virus shedding from asymptomatic patients, and the highest viral load was observed two days after symptom onset. The temporal pattern of viral shedding did not differ between children and adults (P = 0.48). Conclusions Our findings suggest that the delta variant is highly transmissible in indoor settings and households. Rapid contact tracing, isolation of the asymptomatic contacts, and strict adherence to public health measures are needed to mitigate the community transmission of the delta variant.

scholarly journals Household point of care CD4 testing and isoniazid preventive therapy initiation in a household TB contact tracing programme in two districts of South Africa

PLoS ONE ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. e0192089 ◽  
Author(s):  
Liesl Page-Shipp ◽  
James J. Lewis ◽  
Kavindhran Velen ◽  
Sedikanelo Senoge ◽  
Elizabeth Zishiri ◽  
...  
Keyword(s):  
South Africa ◽  
Point Of Care ◽  
Preventive Therapy ◽  
Isoniazid Preventive Therapy ◽  
Contact Tracing ◽  
Therapy Initiation ◽  
Cd4 Testing

scholarly journals Estimating Time-Varying Applied Current in the Hodgkin-Huxley Model

2020 ◽  
Vol 10 (2) ◽  
pp. 550
Author(s):  
Kayleigh Campbell ◽  
Laura Staugler ◽  
Andrea Arnold
Keyword(s):  
Kalman Filter ◽  
Standard Deviation ◽  
Ensemble Kalman Filter ◽  
Single Neuron ◽  
Constant Current ◽  
Time Varying ◽  
Applied Current ◽  
Parameter Tracking ◽  
Voltage Spike ◽  
Low Amplitude

The classic Hodgkin-Huxley model is widely used for understanding the electrophysiological dynamics of a single neuron. While applying a low-amplitude constant current to the system results in a single voltage spike, it is possible to produce multiple voltage spikes by applying time-varying currents, which may not be experimentally measurable. The aim of this work is to estimate time-varying applied currents of different deterministic forms given noisy voltage data. In particular, we utilize an augmented ensemble Kalman filter with parameter tracking to estimate four different time-varying applied current parameters and associated Hodgkin-Huxley model states, along with uncertainty bounds in each case. We test the efficiency of the parameter tracking algorithm in this setting by analyzing the effects of changing the standard deviation of the parameter drift and the frequency of data available on the resulting time-varying applied current estimates and related uncertainty.

scholarly journals Evaluation of Regional Climatic Model Simulated Aerosol Optical Properties over South Africa Using Ground-Based and Satellite Observations

2013 ◽  
Vol 2013 ◽  
pp. 1-17 ◽  
Author(s):  
M. Tesfaye ◽  
J. Botai ◽  
V. Sivakumar ◽  
G. Mengistu Tsidu
Keyword(s):  
South Africa ◽  
Standard Deviation ◽  
Climate Model ◽  
Regional Climate ◽  
Dust Emission ◽  
Aerosol Extinction ◽  
Aerosol Optical Property ◽  
Area Of Interest ◽  
Good Ability ◽  
Simulated Precipitation

The present study evaluates the aerosol optical property computing performance of the Regional Climate Model (RegCM4) which is interactively coupled with anthropogenic-desert dust schemes, in South Africa. The validation was carried out by comparing RegCM4 estimated: aerosol extinction coefficient profile, Aerosol Optical Depth (AOD), and Single Scattering Albedo (SSA) with AERONET, LIDAR, and MISR observations. The results showed that the magnitudes of simulated AOD at the Skukuza station (24°S, 31°E) are within the standard deviation of AERONET and ±25% of MISR observations. Within the latitudinal range of 26.5°S to 24.5°S, simulated AOD and SSA values are within the standard deviation of MISR retrievals. However, within the latitude range of 33.5°S to 27°S, the model exhibited enhanced AOD and SSA values when compared with MISR observations. This is primarily associated with the dry bias in simulated precipitation that leads to the overestimation of dust emission and underestimation of aerosol wet deposition. With respect to LIDAR, the model performed well in capturing the major aerosol extinction profiles. Overall, the results showed that RegCM4 has a good ability in reproducing the major observational features of aerosol optical fields over the area of interest.

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