scholarly journals An SEIR Model with Contact Tracing and Age-Structured Social Mixing for COVID-19 outbreak

2020 ◽  
Author(s):  
Ali Teimouri
Keyword(s):  
Reproduction Number ◽  
Contact Tracing ◽  
Seir Model ◽  
Expectation Value ◽  
Proposed Model ◽  
Social Mixing ◽  
The World ◽  
Age Structured ◽  
And Control ◽  
Explicit Relation

AbstractIn December 2019 a severe acute respiratory syndrome now known as SARS-CoV-2 began to surge in Wuhan, China. The virus soon spread throughout the world to become a pandemic. Since the outbreak various measures were put in place to contain and control the spread, these interventions were mostly based on compartmental models in epidemiology with the main goal of controlling and monitoring the rate of the basic and effective reproduction number. In this paper, we propose an SEIR model where we incorporate contact tracing and age-structured social mixing. We show the explicit relation between contact tracing and social mixing and other relevant parameters of the proposed model. We derive a formula for the effective reproduction number which is expressed in terms of reported cases, tracing quantities and social mixing. We use this formula to determine the expectation value of the effective reproduction number in London, UK.

scholarly journals Exploring the role and mechanism of COVID-19 apps in fighting the current pandemic

2020 ◽  
Vol 0 ◽  
pp. 1-6
Author(s):  
Karthikeyan P. Iyengar ◽  
Rachit Jain ◽  
David Ananth Samy ◽  
Vijay Kumar Jain ◽  
Raju Vaishya ◽  
...  
Keyword(s):  
Data Privacy ◽  
Viral Transmission ◽  
Contact Tracing ◽  
The Novel ◽  
Test Track ◽  
The World ◽  
Novel Coronavirus ◽  
And Control ◽  
Second Wave ◽  
Transmission Test

As COVID-19 pandemic spread worldwide, policies have been developed to contain the disease and prevent viral transmission. One of the key strategies has been the principle of “‘test, track, and trace” to minimize spread of the virus. Numerous COVID-19 contact tracing applications have been rolled around the world to monitor and control the spread of the disease. We explore the characteristics of various COVID-19 applications and especially the Aarogya Setu COVID-19 app from India in its role in fighting the current pandemic. We assessed the current literature available to us using conventional search engines, including but not limited to PubMed, Google Scholar, and Research Gate in May 2020 till the time of submission of this article. The search criteria used MeSH keywords such as “COVID-19,” “pandemics,” “contact tracing,” and “mobile applications.” A variable uptake of different COVID-19 applications has been noted with increasing enrolment around the world. Security concerns about data privacy remain. The various COVID-19 applications will complement manual contact tracing system to assess and prevent viral transmission. Test, track, trace, and support policy will play a key role in avoidance of a “second wave” of the novel coronavirus severe acute respiratory syndrome coronavirus 2 outbreak.

scholarly journals Reducing contacts to stop SARS-CoV-2 transmission during the second pandemic wave in Brussels, Belgium

2020 ◽  
Author(s):  
Brecht Ingelbeen ◽  
Laurène Peckeu ◽  
Marie Laga ◽  
Ilona Hendrix ◽  
Inge Neven ◽  
...  
Keyword(s):  
European Commission ◽  
Risk Ratio ◽  
Reproduction Number ◽  
Case Reports ◽  
Contact Tracing ◽  
Social Mixing ◽  
Before School ◽  
Specific Number ◽  
Pandemic Wave ◽  
Close Contacts

AbstractBackgroundReducing contacts is a cornerstone of containing SARS-CoV-2. We evaluated the effect of physical distancing measures and of school reopening on contacts and consequently on SARS-CoV-2 transmission in Brussels, a hotspot during the second European wave.MethodsUsing SARS-CoV-2 case reports and contact tracing data during August-November 2020, we estimated changes in the age-specific number of reported contacts. We associated these trends with changes in the instantaneous reproduction number Rt and in age-specific transmission-events during distinct intervention periods in the Brussels region. Furthermore, we analysed trends in age-specific case numbers, pre- and post-school opening.FindingsWhen schools reopened and physical distancing measures relaxed, the weekly mean number of reported contacts surged from 2.01 (95%CI 1.73-2.29) to 3.04 (95%CI 2.93-3.15), increasing across all ages. The fraction of cases aged 10-19 years started increasing before school reopening, with no further increase following school reopening (risk ratio 1.23, 95%CI 0.79-1.94). During the subsequent month, 8.9% (67/755) of infections identified were from teenagers to other ages, while 17.0% (131/755) from other ages to teenagers. Rt peaked mid-September at 1.48 (95%CI 1.35-1.63). Reintroduction of physical distancing measures reduced reported contacts to 1.85 (95%CI 1.78-1.91), resulting in Rt dropping below 1 within 3 weeks.InterpretationThe second pandemic wave in Brussels was the result of increased contacts across all ages following school reopening. Stringent physical distancing measures, including closure of bars and limiting close contacts while schools remain open, reduced social mixing, in turn controlling SARS-CoV-2 transmission.FundingEuropean Commission H2020. GGC Brussel.

scholarly journals Control of COVID-19 outbreak using an extended SEIR model

2021 ◽  
pp. 1-26
Author(s):  
Sean T. McQuade ◽  
Ryan Weightman ◽  
Nathaniel J. Merrill ◽  
Aayush Yadav ◽  
Emmanuel Trélat ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Optimal Strategies ◽  
Economic Cost ◽  
Contact Tracing ◽  
Economic Activities ◽  
Seir Model ◽  
Proposed Model ◽  
High Death ◽  
Containment Measures ◽  
The Cost

The outbreak of COVID-19 resulted in high death tolls all over the world. The aim of this paper is to show how a simple SEIR model was used to make quick predictions for New Jersey in early March 2020 and call for action based on data from China and Italy. A more refined model, which accounts for social distancing, testing, contact tracing and quarantining, is then proposed to identify containment measures to minimize the economic cost of the pandemic. The latter is obtained taking into account all the involved costs including reduced economic activities due to lockdown and quarantining as well as the cost for hospitalization and deaths. The proposed model allows one to find optimal strategies as combinations of implementing various non-pharmaceutical interventions and study different scenarios and likely initial conditions.

scholarly journals Determination of critical decision points for COVID-19 measures in Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Junu Kim ◽  
Kensaku Matsunami ◽  
Kozue Okamura ◽  
Sara Badr ◽  
Hirokazu Sugiyama
Keyword(s):  
Time Delay ◽  
Infection Rate ◽  
Reproduction Number ◽  
Sir Model ◽  
Infection Rates ◽  
Seir Model ◽  
Decision Points ◽  
Medical Institutions ◽  
The World

AbstractCoronavirus disease 2019 (COVID-19) has spread throughout the world. The prediction of the number of cases has become essential to governments’ ability to define policies and take countermeasures in advance. The numbers of cases have been estimated using compartment models of infectious diseases such as the susceptible-infected-removed (SIR) model and its derived models. However, the required use of hypothetical future values for parameters, such as the effective reproduction number or infection rate, increases the uncertainty of the prediction results. Here, we describe our model for forecasting future COVID-19 cases based on observed data by considering the time delay (tdelay). We used machine learning to estimate the future infection rate based on real-time mobility, temperature, and relative humidity. We then used this calculation with the susceptible-exposed-infectious-removed (SEIR) model to forecast future cases with less uncertainty. The results suggest that changes in mobility affect observed infection rates with 5–10 days of time delay. This window should be accounted for in the decision-making phase especially during periods with predicted infection surges. Our prediction model helps governments and medical institutions to take targeted early countermeasures at critical decision points regarding mobility to avoid significant levels of infection rise.

scholarly journals Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions

2020 ◽  
Vol 9 (2) ◽  
pp. 462 ◽  
Author(s):  
Biao Tang ◽  
Xia Wang ◽  
Qian Li ◽  
Nicola Luigi Bragazzi ◽  
Sanyi Tang ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Transmission Risk ◽  
Sensitivity Analyses ◽  
Contact Tracing ◽  
The Novel ◽  
Intervention Measures ◽  
Novel Coronavirus ◽  
Restrictive Measures ◽  
And Control ◽  
Travel Restriction

Since the emergence of the first cases in Wuhan, China, the novel coronavirus (2019-nCoV) infection has been quickly spreading out to other provinces and neighboring countries. Estimation of the basic reproduction number by means of mathematical modeling can be helpful for determining the potential and severity of an outbreak and providing critical information for identifying the type of disease interventions and intensity. A deterministic compartmental model was devised based on the clinical progression of the disease, epidemiological status of the individuals, and intervention measures. The estimations based on likelihood and model analysis show that the control reproduction number may be as high as 6.47 (95% CI 5.71–7.23). Sensitivity analyses show that interventions, such as intensive contact tracing followed by quarantine and isolation, can effectively reduce the control reproduction number and transmission risk, with the effect of travel restriction adopted by Wuhan on 2019-nCoV infection in Beijing being almost equivalent to increasing quarantine by a 100 thousand baseline value. It is essential to assess how the expensive, resource-intensive measures implemented by the Chinese authorities can contribute to the prevention and control of the 2019-nCoV infection, and how long they should be maintained. Under the most restrictive measures, the outbreak is expected to peak within two weeks (since 23 January 2020) with a significant low peak value. With travel restriction (no imported exposed individuals to Beijing), the number of infected individuals in seven days will decrease by 91.14% in Beijing, compared with the scenario of no travel restriction.

scholarly journals COVID-19 outbreak and control in Kenya- Insights from a mathematical model

2021 ◽  
Author(s):  
Rachel Waema Mbogo ◽  
Titus Okello Orwa
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Capital City ◽  
World Health ◽  
Transmission Model ◽  
Global Public Health ◽  
The World ◽  
Rate Of Recovery ◽  
Health Organization ◽  
And Control

Abstract The coronavirus disease 2019 (COVID-19) pandemic reached Kenya in March 2020 with the initial cases reported in the capital city Nairobi and in the coastal area Mombasa. As reported by the World Health Organization, the outbreak of COVID-19 has spread across the world, killed many, collapsed economies and changed the way people live since it was first reported in Wuhan, China, in the end of 2019. As of May 25,2020 It had led to over 100,000 confirmed cases in Africa with over 3000 deaths. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.We employed a SEIHCRD mathematical transmission model with reported Kenyan data on cases of COVID-19 to estimate how transmission varies over time. The model is concise in structure, and successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak. The next generation matrix approach was adopted to calculate the basic reproduction number (R0) from the model to assess the factors driving the infection . The results from the model analysis shows that non-pharmaceutical interventions over a relatively long period is needed to effectively get rid of the COVID-19 epidemic otherwise the rate of infection will continue to increase despite the increased rate of recovery.

scholarly journals Potential reduction in transmission of COVID-19 by digital contact tracing systems

2020 ◽  
Author(s):  
Michael J Plank ◽  
Alex James ◽  
Audrey Lustig ◽  
Nicholas Steyn ◽  
Rachelle N Binny ◽  
...  
Keyword(s):  
Uptake Rate ◽  
Process Model ◽  
Reproduction Number ◽  
Contact Tracing ◽  
Location Tracking ◽  
Public Health Agencies ◽  
Proximity Detection ◽  
Health Agencies ◽  
Alternative Approaches ◽  
Age Structured

Digital tools are being developed to support contact tracing as part of the global effort to control the spread of COVID-19. These include smartphone apps, Bluetooth-based proximity detection, location tracking, and automatic exposure notification features. Evidence on the effectiveness of alternative approaches to digital contact tracing is so far limited. We use an age-structured branching process model of the transmission of COVID-19 in different settings to estimate the potential of manual contact tracing and digital tracing systems to help control the epidemic. We investigate the effect of the uptake rate and proportion of contacts recorded by the digital system on key model outputs: the effective reproduction number, the mean outbreak size after 30 days, and the probability of elimination. We show that effective manual contact tracing can reduce the effective reproduction number from 2.4 to around 1.5. The addition of a digital tracing system with a high uptake rate over 75% could further reduce the effective reproduction number to around 1.1. Fully automated digital tracing without manual contact tracing is predicted to be much less effective. We conclude that, for digital tracing systems to make a significant contribution to the control of COVID-19, they need be designed in close conjunction with public health agencies to support and complement manual contact tracing by trained professionals.

scholarly journals The basic reproduction number of COVID-19 across Africa

2021 ◽  
Author(s):  
Sarafa Adewale Iyaniwura ◽  
Muhammad Rabiu Musa ◽  
Jummy F. David ◽  
Jude Dzevela Kong
Keyword(s):  
Bayesian Inference ◽  
Severe Acute Respiratory Syndrome ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
Clear Understanding ◽  
Seir Model ◽  
The World ◽  
Bayesian Inference Framework ◽  
The Basic Reproduction Number

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31 - 4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions.

scholarly journals COVID-19 outbreak and control in Kenya- Insights from a mathematical model

2020 ◽  
Author(s):  
Rachel Waema Mbogo ◽  
Titus Okello Orwa
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Capital City ◽  
World Health ◽  
Transmission Model ◽  
Global Public Health ◽  
The World ◽  
Rate Of Recovery ◽  
Health Organization ◽  
And Control

Abstract The coronavirus disease 2019 ( COVID -19) pandemic reached Kenya in March 2020 with the initial cases reported in the capital city Nairobi and in the coastal area Mombasa. As reported by the World Health Organization, the outbreak of COVID -19 has spread across the world, killed many, collapsed economies and changed the way people live since it was first reported in Wuhan, China, in the end of 2019. As of May 25,2020 It had led to over 100,000 confirmed cases in Africa with over 3000 deaths. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. We employed a SEIHCRD mathematical transmission model with reported Kenyan data on cases of COVID -19 to estimate how transmission varies over time. The model is concise in structure, and successfully captures the course of the COVID -19 outbreak, and thus sheds light on understanding the trends of the outbreak. The next generation matrix approach was adopted to calculate the basic reproduction number ( $R_0$ ) from the model to assess the factors driving the infection . The results from the model analysis shows that non-pharmaceutical interventions over a relatively long period is needed to effectively get rid of the COVID -19 epidemic otherwise the rate of infection will continue to increase despite the increased rate of recovery.

scholarly journals On an SE(Is)(Ih)AR epidemic model with combined vaccination and antiviral controls for COVID-19 pandemic

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
M. De la Sen ◽  
A. Ibeas
Keyword(s):  
Equilibrium Point ◽  
Basic Reproduction Number ◽  
Epidemic Model ◽  
Reproduction Number ◽  
Antiviral Treatment ◽  
Stability Properties ◽  
Local Asymptotic Stability ◽  
Proposed Model ◽  
And Control ◽  
The Basic Reproduction Number

AbstractIn this paper, we study the nonnegativity and stability properties of the solutions of a newly proposed extended SEIR epidemic model, the so-called SE(Is)(Ih)AR epidemic model which might be of potential interest in the characterization and control of the COVID-19 pandemic evolution. The proposed model incorporates both asymptomatic infectious and hospitalized infectious subpopulations to the standard infectious subpopulation of the classical SEIR model. In parallel, it also incorporates feedback vaccination and antiviral treatment controls. The exposed subpopulation has three different transitions to the three kinds of infectious subpopulations under eventually different proportionality parameters. The existence of a unique disease-free equilibrium point and a unique endemic one is proved together with the calculation of their explicit components. Their local asymptotic stability properties and the attainability of the endemic equilibrium point are investigated based on the next generation matrix properties, the value of the basic reproduction number, and nonnegativity properties of the solution and its equilibrium states. The reproduction numbers in the presence of one or both controls is linked to the control-free reproduction number to emphasize that such a number decreases with the control gains. We also prove that, depending on the value of the basic reproduction number, only one of them is a global asymptotic attractor and that the solution has no limit cycles.

Sign in / Sign up

Export Citation Format

Share Document