scholarly journals On the Transmission Dynamics of SARS-CoV-2 in a Temperate Climate

2021 ◽  
Vol 18 (4) ◽  
pp. 1660
Author(s):  
Ioannis Kioutsioukis ◽  
Nikolaos I. Stilianakis
Keyword(s):  
Dynamic Change ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Temperate Climate ◽  
Model Parameters ◽  
Forecast Horizon ◽  
Public Health Decision ◽  
Epidemic Dynamics ◽  
Positive Effects ◽  
Household Crowding

An epidemiological model, which describes the transmission dynamics of SARS-CoV-2 under specific consideration of the incubation period including the population with subclinical infections and being infective is presented. The COVID-19 epidemic in Greece was explored through a Monte Carlo uncertainty analysis framework, and the optimal values for the parameters that determined the transmission dynamics could be obtained before, during, and after the interventions to control the epidemic. The dynamic change of the fraction of asymptomatic individuals was shown. The analysis of the modelling results at the intra-annual climatic scale allowed for in depth investigation of the transmission dynamics of SARS-CoV-2 and the significance and relative importance of the model parameters. Moreover, the analysis at this scale incorporated the exploration of the forecast horizon and its variability. Three discrete peaks were found in the transmission rates throughout the investigated period (15 February–15 December 2020). Two of them corresponded to the timing of the spring and autumn epidemic waves while the third one occurred in mid-summer, implying that relaxation of social distancing and increased mobility may have a strong effect on rekindling the epidemic dynamics offsetting positive effects from factors such as decreased household crowding and increased environmental ultraviolet radiation. In addition, the epidemiological state was found to constitute a significant indicator of the forecast reliability horizon, spanning from as low as few days to more than four weeks. Embedding the model in an ensemble framework may extend the predictability horizon. Therefore, it may contribute to the accuracy of health risk assessment and inform public health decision making of more efficient control measures.

scholarly journals Model-free estimation of COVID-19 transmission dynamics from a complete outbreak

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0238800
Author(s):  
Alex James ◽  
Michael J. Plank ◽  
Shaun Hendy ◽  
Rachelle N. Binny ◽  
Audrey Lustig ◽  
...  
Keyword(s):  
The Elderly ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Lower Probability ◽  
Epidemic Dynamics ◽  
Model Free ◽  
Construction Techniques ◽  
Imported Cases ◽  
Border Controls ◽  
Case Data

New Zealand had 1499 cases of COVID-19 before eliminating transmission of the virus. Extensive contract tracing during the outbreak has resulted in a dataset of epidemiologically linked cases. This data contains useful information about the transmission dynamics of the virus, its dependence on factors such as age, and its response to different control measures. We use Monte-Carlo network construction techniques to provide an estimate of the number of secondary cases for every individual infected during the outbreak. We then apply standard statistical techniques to quantify differences between groups of individuals. Children under 10 years old are significantly under-represented in the case data. Children infected fewer people on average and had a lower probability of transmitting the disease in comparison to adults and the elderly. Imported cases infected fewer people on average and also had a lower probability of transmitting than domestically acquired cases. Superspreading is a significant contributor to the epidemic dynamics, with 20% of cases among adults responsible for 65–85% of transmission. Subclinical cases infected fewer individuals than clinical cases. After controlling for outliers serial intervals were approximated with a normal distribution (μ = 4.4 days, σ = 4.7 days). Border controls and strong social distancing measures, particularly when targeted at superspreading, play a significant role in reducing the spread of COVID-19.

TRANSMISSION DYNAMICS AND CONTROL STRATEGIES OF COVID-19 IN WUHAN, CHINA

2020 ◽  
Vol 28 (03) ◽  
pp. 543-560 ◽  
Author(s):  
LIUYONG PANG ◽  
SANHONG LIU ◽  
XINAN ZHANG ◽  
TIANHAI TIAN ◽  
ZHONG ZHAO
Keyword(s):  
Reproduction Number ◽  
Control Strategies ◽  
Public Awareness ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Published Data ◽  
Model Parameters ◽  
Strict Control ◽  
Dynamics And Control ◽  
Numerical Calculation Method

In December 2019, a novel coronavirus, SARS-COV-2, was identified among patients in Wuhan, China. Two strict control measures, i.e., putting Wuhan on lockdown and taking strict quarantine rule, were carried out to contain the spread of COVID-19. Based on the different control measures, we divided the transmission process of COVID-19 into three stages. An SEIHR model was established to describe the transmission dynamics and was applied to fit the published data on the confirmed cases of Wuhan city from December 31, 2019 to March 25, 2020 to deduce the time when the first patient with COVID-19 appeared. The basic reproduction number was estimated in the first stage to demonstrate the number of secondary infectious cases generated by an average infectious case in the absence of policy intervention. The effective reproduction numbers in second and third stages were estimated to evaluate the effects of the two strict control measures. In addition, sensitivity analysis of the reproduction number according to model parameters was executed to demonstrate the effect of the control measures for containing the spread of COVID-19. Finally, the numerical calculation method was applied to investigate the influence of the different control measures on the spread of COVID-19. The results indicated that following the strict quarantine rule was very effective, and reducing the effective contact rates and improving the diagnosis rate were crucial in reducing the effective reproduction number, and taking control measures as soon as possible can effectively contain a larger outbreak of COVID-19. But a bigger challenge for us to contain the spread of COVID-19 was the transmission from the asymptomatic carriers, which required to raising the public awareness of self-protection and keeping a good physical protection.

scholarly journals A simple transmission dynamics model for predicting the evolution of COVID-19 under control measures in China

2020 ◽  
Author(s):  
Chenjing Shang ◽  
Yang Yang ◽  
Gui-Ying Chen ◽  
Xiao-Dong Shang
Keyword(s):  
Growth Rate ◽  
Prediction Models ◽  
Mainland China ◽  
Health Sector ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Disease Spread ◽  
Chinese Government ◽  
Model Parameters ◽  
Estimation Of Model Parameters

Abstract Epidemic forecasting provides an opportunity to predict geographic disease spread and counts when an outbreak occurs and plays a key role in preventing or controlling their adverse impact. However, conventional prediction models based on complex mathematical modeling rely on the estimation of model parameters, which yields unreliable and unsustainable results. Herein, we proposed a simple model for predicting the epidemic transmission dynamics based on nonlinear regression of the epidemic growth rate and iterative methods, which is applicable to the progression of the COVID-19 outbreak under the strict control measures of the Chinese government. Our model yields reliable and accurate results as confirmed by the available data: we predicted that the total number of infections in mainland China would be 91,253, and the maximum number of beds required for hospitalized patients would be 62,794. We inferred that the inflection point (when the growth rate turns from positive to negative) of the epidemic across China would be mid-February, and the end of the epidemic would be in late March. This model is expected to contribute to resourceallocation and planning in the health sector while providing a theoretical basis forgovernments to respond to future global health crises or epidemics.

scholarly journals Model-free estimation of COVID-19 transmission dynamics from a complete outbreak

2020 ◽  
Author(s):  
Alex James ◽  
Michael J Plank ◽  
Shaun Hendy ◽  
Rachelle N Binny ◽  
Audrey Lustig ◽  
...  
Keyword(s):  
New Zealand ◽  
Attack Rate ◽  
The Elderly ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Epidemic Dynamics ◽  
Model Free ◽  
Construction Techniques ◽  
Imported Cases ◽  
Border Controls

Background New Zealand had 1499 cases of COVID-19 before eliminating transmission of the virus. Extensive contract tracing during the outbreak has resulted in a dataset of epidemiologically linked cases. This data contains useful information about the transmission dynamics of the virus, its dependence on factors such as age, and its response to different control measures. Method We use Monte-Carlo network construction techniques to provide an estimate of the number of secondary cases for every individual infected during the outbreak. We then apply standard statistical techniques to quantify differences between groups of individuals. Findings Children under 10 years old are significantly under-represented in the case data. Children infected fewer people on average and had a lower secondary attack rate in comparison to adults and the elderly. Imported cases infected fewer people on average and had a lower secondary attack rate than domestically acquired cases. Superspreading is a significant contributor to the epidemic dynamics, with 20% of cases among adults responsible for 65-85% of transmission. Asymptomatic cases infected fewer individuals than clinical cases. Serial intervals are approximately normally distributed (μ=5.0 days, σ=5.7 days). Early isolation and quarantine of cases reduced secondary transmission rates. Interpretation Border controls and strong social distancing measures, particularly when targeted at superspreading, play a significant role in reducing the spread of COVID-19. Funding Te Pūnaha Matatini, the New Zealand Centre of Research Excellence in complex systems. New Zealand Ministry of Business, Innovation and Employment.

scholarly journals Assessing the effects of time-dependent restrictions and control actions to flatten the curve of COVID-19 in Kazakhstan

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10806
Author(s):  
Ton Duc Do ◽  
Meei Mei Gui ◽  
Kok Yew Ng
Keyword(s):  
Ad Hoc ◽  
Reproduction Number ◽  
National Level ◽  
Control Measures ◽  
Time Dependent ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
Real World Data ◽  
Control Actions ◽  
And Control

This article presents the assessment of time-dependent national-level restrictions and control actions and their effects in fighting the COVID-19 pandemic. By analysing the transmission dynamics during the first wave of COVID-19 in the country, the effectiveness of the various levels of control actions taken to flatten the curve can be better quantified and understood. This in turn can help the relevant authorities to better plan for and control the subsequent waves of the pandemic. To achieve this, a deterministic population model for the pandemic is firstly developed to take into consideration the time-dependent characteristics of the model parameters, especially on the ever-evolving value of the reproduction number, which is one of the critical measures used to describe the transmission dynamics of this pandemic. The reproduction number alongside other key parameters of the model can then be estimated by fitting the model to real-world data using numerical optimisation techniques or by inducing ad-hoc control actions as recorded in the news platforms. In this article, the model is verified using a case study based on the data from the first wave of COVID-19 in the Republic of Kazakhstan. The model is fitted to provide estimates for two settings in simulations; time-invariant and time-varying (with bounded constraints) parameters. Finally, some forecasts are made using four scenarios with time-dependent control measures so as to determine which would reflect on the actual situations better.

scholarly journals The Role of Control Measures and the Environment in the Transmission Dynamics of Cholera

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Nicholas Kwasi-Do Ohene Opoku ◽  
Cecilia Afriyie
Keyword(s):  
Basic Education ◽  
Least Square Method ◽  
Least Square ◽  
Control Measures ◽  
Water Bodies ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
Severe Diarrhea ◽  
Educational Campaign

Cholera is an infectious intestinal disease which occurs as a result of poor sanitation and lack of basic education in its transmission. It is characterized by profuse vomiting and severe diarrhea when an individual eats food or drinks water contaminated with the Vibrio cholerae. A dynamic mathematical model that explicitly simulates the transmission mechanism of cholera by taking into account the role of control measures and the environment in the transmission of the disease is developed. The model comprises two populations: the human population and bacteria population. The next-generation method is used to compute the basic reproduction number, R0. Both the disease-free and endemic equilibria are shown to be locally and globally stable for R0 values less than unity and unstable otherwise. Necessary conditions of the optimal control problem were analyzed using Pontryagin’s maximum principle with control measures such as educational campaign and treatment of water bodies used to optimize the objective function. Numerical values of model parameters were estimated using the nonlinear least square method. The model simulations confirm the significant role played by control measures (education and treatment of water bodies) and the bacteria in the environment in the transmission dynamics as well as reducing the spread of cholera.

scholarly journals A simple transmission dynamics model for predicting the evolution of COVID-19 under control measures in China

2021 ◽  
Vol 149 ◽  
Author(s):  
Chenjing Shang ◽  
Yang Yang ◽  
Gui-Ying Chen ◽  
Xiao-Dong Shang
Keyword(s):  
Growth Rate ◽  
Prediction Models ◽  
Mainland China ◽  
Health Sector ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Disease Spread ◽  
Chinese Government ◽  
Model Parameters ◽  
Hospitalised Patients

Abstract Epidemic forecasting provides an opportunity to predict geographic disease spread and counts when an outbreak occurs and plays a key role in preventing or controlling their adverse impact. However, conventional prediction models based on complex mathematical modelling rely on the estimation of model parameters, which yields unreliable and unsustainable results. Herein, we proposed a simple model for predicting the epidemic transmission dynamics based on nonlinear regression of the epidemic growth rate and iterative methods, which is applicable to the progression of the COVID-19 outbreak under the strict control measures of the Chinese government. Our model yields reliable and accurate results as confirmed by the available data: we predicted that the total number of infections in mainland China would be 91 253, and the maximum number of beds required for hospitalised patients would be 62 794. We inferred that the inflection point (when the growth rate turns from positive to negative) of the epidemic across China would be mid-February, and the end of the epidemic would be in late March. This model is expected to contribute to resource allocation and planning in the health sector while providing a theoretical basis for governments to respond to future global health crises or epidemics.

scholarly journals Parameter-dependent transmission dynamics and optimal control of foot and mouth disease in a contaminated environment

2019 ◽  
Vol 27 (1) ◽  
Author(s):  
Francis Mugabi ◽  
Joseph Mugisha ◽  
Betty Nannyonga ◽  
Henry Kasumba ◽  
Margaret Tusiime
Keyword(s):  
Optimal Control ◽  
Deterministic Model ◽  
Foot And Mouth Disease ◽  
Decay Rates ◽  
Mouth Disease ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Optimality System ◽  
Foot And Mouth ◽  
Environmental Decontamination

AbstractThe problem of foot and mouth disease (FMD) is of serious concern to the livestock sector in most nations, especially in developing countries. This paper presents the formulation and analysis of a deterministic model for the transmission dynamics of FMD through a contaminated environment. It is shown that the key parameters that drive the transmission of FMD in a contaminated environment are the shedding, transmission, and decay rates of the virus. Using numerical results, it is depicted that the host-to-host route is more severe than the environmental-to-host route. The model is then transformed into an optimal control problem. Using the Pontryagin’s Maximum Principle, the optimality system is determined. Utilizing a gradient type algorithm with projection, the optimality system is solved for three control strategies: optimal use of vaccination, environmental decontamination, and a combination of vaccination and environmental decontamination. Results show that a combination of vaccination and environmental decontamination is the most optimal strategy. These results indicate that if vaccination and environmental decontamination are used optimally during an outbreak, then FMD transmission can be controlled. Future studies focusing on the control measures for the transmission of FMD in a contaminated environment should aim at reducing the transmission and the shedding rates, while increasing the decay rate.

scholarly journals High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ellen Brooks-Pollock ◽  
Hannah Christensen ◽  
Adam Trickey ◽  
Gibran Hemani ◽  
Emily Nixon ◽  
...  
Keyword(s):  
Prediction Interval ◽  
Mitigation Strategies ◽  
Control Measures ◽  
Transmission Model ◽  
Model Parameters ◽  
Infection Rates ◽  
First Year Students ◽  
Transmission Potential ◽  
Plausible Model ◽  
Effective Option

AbstractControlling COVID-19 transmission in universities poses challenges due to the complex social networks and potential for asymptomatic spread. We developed a stochastic transmission model based on realistic mixing patterns and evaluated alternative mitigation strategies. We predict, for plausible model parameters, that if asymptomatic cases are half as infectious as symptomatic cases, then 15% (98% Prediction Interval: 6–35%) of students could be infected during the first term without additional control measures. First year students are the main drivers of transmission with the highest infection rates, largely due to communal residences. In isolation, reducing face-to-face teaching is the most effective intervention considered, however layering multiple interventions could reduce infection rates by 75%. Fortnightly or more frequent mass testing is required to impact transmission and was not the most effective option considered. Our findings suggest that additional outbreak control measures should be considered for university settings.

Kinetic Model of Adiabatic Temperature Rise of Mass Concrete

2021 ◽  
Vol 13 (5) ◽  
pp. 771-780
Author(s):  
Shou-Kai Chen ◽  
Bo-Wen Xu
Keyword(s):  
Temperature Field ◽  
Temperature Rise ◽  
Initial Conditions ◽  
Dynamic Change ◽  
Adiabatic Temperature ◽  
Model Parameters ◽  
Hydration Reaction ◽  
Mass Concrete ◽  
Adiabatic Temperature Rise ◽  
Proposed Model

The adiabatic temperature rise model of mass concrete is very important for temperature field simulation, same to crack resistance capacity and temperature control of concrete structures. In this research, a thermal kinetics analysis was performed to study the exothermic hydration reaction process of concrete, and an adiabatic temperature rise model was proposed. The proposed model considers influencing factors, including initial temperature, temperature history, activation energy, and the completion degree of adiabatic temperature rise and is theoretically mature and definitive in physical meaning. It was performed on different initial temperatures for adiabatic temperature rise test; the data were employed in a regression analysis of the model parameters and initial conditions. The same function was applied to describe the dynamic change of the adiabatic temperature rise rates for different initial temperatures and different temperature changing processes and subsequently employed in a finite element analysis of the concrete temperature field. The test results indicated that the proposed model adequately fits the data of the adiabatic temperature rise test, which included different initial temperatures, and accurately predicts the changing pattern of adiabatic temperature rise of concrete at different initial temperatures. Compared with the results using the traditional age-based adiabatic temperature rise model, the results of a calculation example revealed that the simulated calculation results using the proposed model can accurately reflect the temperature change pattern of concrete in heat dissipation conditions.

Sign in / Sign up

Export Citation Format

Share Document