scholarly journals Forecasting Transmission Dynamics of COVID-19 Epidemic in India under Various Containment Measures- A Time-Dependent State-Space SIR Approach

2020 ◽  
Author(s):  
Vishal Deo ◽  
Anuradha Rajkonwar Chetiya ◽  
Barnali Deka ◽  
Gurprit Grover
Keyword(s):  
State Space ◽  
Transmission Rate ◽  
Sir Model ◽  
Primary Objective ◽  
Time Dependent ◽  
Infectious Period ◽  
Total Incidence ◽  
Comparison Results ◽  
Containment Measures ◽  
The Impact

Objectives Our primary objective is to predict the dynamics of COVID-19 epidemic in India while adjusting for the effects of various progressively implemented containment measures. Apart from forecasting the major turning points and parameters associated with the epidemic, we intend to provide an epidemiological assessment of the impact of these containment measures in India. Methods We propose a method based on time-series SIR model to estimate time-dependent modifiers for transmission rate of the infection. These modifiers are used in state-space SIR model to estimate reproduction number R0, expected total incidence, and to forecast the daily prevalence till the end of the epidemic. We consider four different scenarios, two based on current developments and two based on hypothetical situations for the purpose of comparison. Results Assuming gradual relaxation in lockdown post 17 May 2020, we expect the prevalence of infecteds to cross 9 million, with at least 1 million severe cases, around the end of October 2020. For the same case, estimates of R0 for the phases no-intervention, partial-lockdown and lockdown are 4.46 (7.1), 1.47 (2.33), and 0.817 (1.29) respectively, assuming 14-day (24-day) infectious period. Conclusions Estimated modifiers give consistent estimates of unadjusted R0 across different scenarios, demonstrating precision. Results corroborate the effectiveness of lockdown measures in substantially reducing R0. Also, predictions are highly sensitive towards estimate of infectious period.

scholarly journals Predicting the propagation of COVID-19 at an international scale: extension of an SIR model

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e041472
Author(s):  
Marc Lavielle ◽  
Matthieu Faron ◽  
Jérémie H Lefevre ◽  
Jean-David Zeitoun
Keyword(s):  
Web Application ◽  
Compartmental Model ◽  
Transmission Rate ◽  
Sir Model ◽  
Time Dependent ◽  
Epidemiological Models ◽  
Containment Measures ◽  
Early Performance ◽  
High Level ◽  
Novel Model

ObjectivesSeveral epidemiological models have been published to forecast the spread of the COVID-19 pandemic, yet many of them have proven inaccurate for reasons that remain to be fully determined. We aimed to develop a novel model and implement it in a freely accessible web application.DesignWe built an SIR-type compartmental model with two additional compartments: D (deceased patients); L (individuals who will die but who will not infect anybody due to social or medical isolation) and integration of a time-dependent transmission rate and a periodical weekly component linked to the way in which cases and deaths are reported.ResultsThe model was implemented in a web application (as of 2 June 2020). It was shown to be able to accurately capture the changes in the dynamics of the pandemic for 20 countries whatever the type of pandemic spread or containment measures: for instance, the model explains 97% of the variance of US data (daily cases) and predicts the number of deaths at a 2-week horizon with an error of 1%.ConclusionsIn early performance evaluation, our model showed a high level of accuracy between prediction and observed data. Such a tool might be used by the global community to follow the spread of the pandemic.

scholarly journals Fractional SIR-Model for Estimating Transmission Dynamics of COVID-19 in India

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 86-100
Author(s):  
Nita H. Shah ◽  
Ankush H. Suthar ◽  
Ekta N. Jayswal ◽  
Ankit Sikarwar
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Sir Model ◽  
Time Dependent ◽  
Contact Rate ◽  
Distribution Maps ◽  
Fundamental Parameters ◽  
Different Order ◽  
The Basic Reproduction Number

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model's transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.

scholarly journals Modelling the time-dependent transmission rate for porcine circovirus type 2 (PCV2) in pigs using data from serial transmission experiments

2008 ◽  
Vol 6 (30) ◽  
pp. 39-50 ◽  
Author(s):  
M Andraud ◽  
B Grasland ◽  
B Durand ◽  
R Cariolet ◽  
A Jestin ◽  
...  
Keyword(s):  
Transmission Rate ◽  
Transmission Function ◽  
Latency Period ◽  
Porcine Circovirus Type ◽  
Time Dependent ◽  
Porcine Circovirus ◽  
Infectious Period ◽  
Post Inoculation ◽  
Unimodal Function ◽  
Reproduction Ratio

Six successive transmission trials were carried out from 4 to 39 days post inoculation (DPI) to determine the features of the infectious period for PCV2-infected pigs. The infectiousness of inoculated pigs, assessed from the frequency of occurrence of infected pigs in susceptible groups in each contact trial, increased from 4 to 18 DPI (0, 7 and 8 infected pigs at 4, 11 and 18 DPI, respectively) and then decreased slowly until 39 days post infection (4, 2 and 1 pigs infected at 25, 32 and 39 DPI, respectively). The estimated time-dependent infectiousness was fitted to three unimodal function shapes (gamma, Weibull and lognormal) for comparison. The absence of infected pigs at 4 DPI revealed a latency period between 4 and 10 DPI. A sensitivity analysis was performed to test whether the parametric shape of the transmission function influenced the estimations. The estimated time-dependent transmission rate was implemented in a deterministic SEIR model and validated by comparing the model prediction with external data. The lognormal-like function shape evidenced the best quality of fit, leading to a latency period of 8 days, an estimated basic reproduction ratio of 5.9 [1.8,10.1] and a mean disease generation time of 18.4 days [18.2, 18.5].

scholarly journals Assessment of Vaccination and Underreporting on COVID-19 Infections in Turkey Based On Effective Reproduction Number

2021 ◽  
Author(s):  
Tuğba Akman Yıldız ◽  
Emek Köse ◽  
Necibe Tuncer
Keyword(s):  
Critical Parameter ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Vaccination Rate ◽  
Future Trend ◽  
Time Dependent ◽  
Modified Model ◽  
Department Of Health ◽  
Number Of Patients ◽  
The Impact

AbstractIn this paper, we introduce a SEIR type COVID-19 model where the infected class is further divided into individuals in intensive care (ICUs) and ventilation units. The model is validated with the COVID-19 cases, deaths, and the number of patients in ICUs and ventilation units as reported by Turkey Department of Health for the period March 11 through May 30 when the nationwide lockdown is in order. COVID-19 interventions in Turkey are incorporated into the model to detect the future trend of the outbreak accurately. The lockdown is lifted on June 1, and the model is modified to include a time dependent transmission rate which is linked to the effective reproduction number ℛt through basic reproduction number ℛ0. The modified model captures the changing dynamics and peaks of the outbreak successfully. With the onset of vaccination on 13 January 2021, we augment the model with the vaccination class to investigate the impact of vaccination rate and efficacy. We observe that vaccination rate is a more critical parameter than the vaccine efficacy to eliminate the disease successfully.

scholarly journals Evolution of disease transmission rate during the course of SARS-COV-2: Patterns and determinants

2020 ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Region Of Interest ◽  
Health Interventions ◽  
Transmission Model ◽  
Public Health Interventions ◽  
Containment Measures ◽  
The Impact

Abstract To date, many studies have argued the potential impact of public health interventions on flattening the epidemic curve of SARS-CoV-2. Most of them have focused on simulating the impact of interventions in a region of interest by manipulating contact patterns and key transmission parameters to reflect different scenarios. Our study looks into the evolution of the daily effective reproduction number during the epidemic via a stochastic transmission model. We found this measure (although model-dependent) provides an early signal of the efficacy of containment measures. This epidemiological parameter when updated in real-time can also provide better predictions of future outbreaks. Our results found a substantial variation in the effect of public health interventions on the dynamic of SARS-CoV-2 transmission over time and across countries, that could not be explained solely by the timing and number of the adopted interventions. This suggests that further knowledge about the idiosyncrasy of their implementation and effectiveness is required. Although sustained containment measures have successfully lowered growth in disease transmission, more than half of the 101 studied countries failed to maintain the effective reproduction number close to or below 1. This resulted in continued growth in reported cases. Finally, we were able to predict with reasonable accuracy which countries would experience outbreaks in the next 30 days.

scholarly journals Extension of a SIR model for modelling the propagation of Covid-19 in several countries.

2020 ◽  
Author(s):  
Marc Lavielle ◽  
Matthieu Faron ◽  
jeremie lefevre ◽  
Jean-David Zeitoun
Keyword(s):  
Compartmental Model ◽  
Transmission Rate ◽  
Sir Model ◽  
Decision Makers ◽  
Short Term ◽  
Early Evaluation ◽  
The Public ◽  
Containment Measures ◽  
High Level ◽  
Over Time

Background Several epidemiologic models have been published to forecast the spread of the COVID-19 pandemic yet there are still uncertainties regarding their accuracy. We report the main features of the development of a novel freely accessible model intended to urgently help researchers and decision makers to predict the evolution of the pandemic in their country. Methods and findings We built a SIR-type compartmental model with additional compartments and features. We made the hypothesis that the number of contagious individuals in the population was negligible as compared to the population size. We introduced a compartment D corresponding to the deceased patients and a compartment L representing the group of individuals who will die but who will not infect anybody (due to social or medical isolation). Our model integrated a time-dependent transmission rate, whose variations can be thought to be related to the public measures taken by each country and a cosine function to incorporate a periodic weekly component linked to the way in which numbers of cases and deaths are counted and reported, which can change from day to day. The model was able to accurately capture the different changes in the dynamics of the pandemic for nine different countries whatever the type of pandemic spread or containment measures. The model provided very accurate forecasts in the relatively short term (10 days). Conclusions In early evaluation of the performance of our model, we found a high level of accuracy between prediction and observed data, regardless of the country. The model should be used by the community to help public health decisions as we will refine it over time and further investigate its performance.

scholarly journals The nature of individual heterogeneity shape outbreak dynamics

2021 ◽  
Author(s):  
Baptiste Elie ◽  
Christian Selinger ◽  
Samuel Alizon
Keyword(s):  
Transmission Rate ◽  
Sir Model ◽  
Pathogen Transmission ◽  
Main Driver ◽  
Biological Sources ◽  
Stochastic Sir ◽  
Stochastic Sir Model ◽  
The Impact ◽  
Parasite Emergence

AbstractIt is now common-place that pathogen transmission during an outbreak can be more heterogeneous than what is commonly assumed, and that it can have major consequences on their dynamics. However, previous studies did not explore the impact of the different biological sources of heterogeneity while controlling for the resulting heterogeneity in the number of secondary cases. In this study, we explore the role of individual variation in infection duration and transmission rate on parasite emergence and spread in a population. We simulate outbreaks using a custom stochastic SIR model, with and without evolution of the parasite. We show that for a given mean, the variance in the number of secondary cases is the main driver of the outbreak probability, with or without evolution, while it does not play a role on the outbreak dynamic once it emerged. On the opposite, a smaller and more realistic variance in the infection duration causes a faster outbreak. It is therefore useful to take into consideration more realistic distributions when modelling infectious diseases outbreaks.

scholarly journals Toward the Impact of Non-pharmaceutical Interventions and Vaccination on the COVID-19 Pandemic With Time-Dependent SEIR Model

2021 ◽  
Vol 4 ◽  
Author(s):  
Yuexin Li ◽  
Linqiang Ge ◽  
Yang Zhou ◽  
Xuan Cao ◽  
Jingyi Zheng
Keyword(s):  
Dynamic Models ◽  
Transmission Rate ◽  
National Level ◽  
Time Dependent ◽  
World Health ◽  
Seir Model ◽  
Level Data ◽  
The World ◽  
The Impact ◽  
The U.S

The outbreak of COVID-19, caused by the SARS-CoV-2 coronavirus, has been declared a pandemic by the World Health Organization (WHO) in March, 2020 and rapidly spread to over 210 countries and territories around the world. By December 24, there are over 77M cumulative confirmed cases with more than 1.72M deaths worldwide. To mathematically describe the dynamic of the COVID-19 pandemic, we propose a time-dependent SEIR model considering the incubation period. Furthermore, we take immunity, reinfection, and vaccination into account and propose the SEVIS model. Unlike the classic SIR based models with constant parameters, our dynamic models not only predicts the number of cases, but also monitors the trajectories of changing parameters, such as transmission rate, recovery rate, and the basic reproduction number. Tracking these parameters, we observe the significant decrease in the transmission rate in the U.S. after the authority announced a series of orders aiming to prevent the spread of the virus, such as closing non-essential businesses and lockdown restrictions. Months later, as restrictions being gradually lifted, we notice a new surge of infection emerges as the transmission rates show increasing trends in some states. Using our epidemiology models, people can track, timely monitor, and predict the COVID-19 pandemic with precision. To illustrate and validate our model, we use the national level data (the U.S.) and the state level data (New York and North Dakota), and the resulting relative prediction errors for the infected group and recovered group are mostly lower than 0.5%. We also simulate the long-term development of the pandemic based on our proposed models to explore when the crisis will end under certain conditions.

scholarly journals Flattening the Curve: The effects of intervention strategies during COVID-19

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Kelly Reagan ◽  
Rachel Pryor ◽  
Gonzalo Bearman ◽  
David Chan
Keyword(s):  
Personal Protective Equipment ◽  
Transmission Rate ◽  
State Level ◽  
Sir Model ◽  
Intervention Strategies ◽  
Time Dependent ◽  
Protective Equipment ◽  
Social Distancing ◽  
Peak Number ◽  
Number Of Individuals

COVID-19 has plagued countries worldwide due to its infectious nature. Social distancing and the use of personal protective equipment (PPE) are two main strategies employed to prevent its spread. A SIR model with a time-dependent transmission rate is implemented to examine the effect of social distancing and PPE use in hospitals. These strategies’ effect on the size and timing of the peak number of infectious individuals are examined as well as the total number of individuals infected by the epidemic. The effect on the epidemic of when social distancing is relaxed is also examined. Overall, social distancing was shown to cause the largest impact in the number of infections. Studying this interaction between social distancing and PPE use is novel and timely. We show that decisions made at the state level on implementing social distancing and acquiring adequate PPE have dramatic impact on the health of its citizens.

scholarly journals The impact of containment measures and air temperature on mitigating COVID-19 transmission: non-classical SEIR modeling and analysis

2020 ◽  
Author(s):  
Di Liu ◽  
Qidong Tai ◽  
Yaping Wang ◽  
Miao Pu ◽  
Sikai Ge ◽  
...  
Keyword(s):  
Air Temperature ◽  
Model Simulation ◽  
Transmission Rate ◽  
Mainland China ◽  
Contact Tracing ◽  
Modeling And Analysis ◽  
Optimal Temperature Range ◽  
Containment Measures ◽  
China Model ◽  
The Impact

Early non-pharmaceutical interventions (NPIs) are crucial to prevent and control of COVID-19 pandemic. We established a stochastic non-classical SEIR NPIs model (ScEIQRsh) which can quantify the three kinds of NPIs measures simultaneously to mimic the clustered intra-family or intra-acquaintance spreading pattern of COVID-19 under the effective integrated NPIs in Mainland China. Model simulation demonstrated that measures to diminish contactable susceptible (Sc), such as home confinement, travel constraint, social distancing etc. and measures to avoid delay of diagnosis and hospitalized isolation (η) were more effective but consumptive than contact tracing (κ, ρ). From fitted model by MCMC method, the proportion of asymptomatic infectors was 14.88% (IQR 8.17%, 25.37%). The association between air temperature and the fitted transmission rate (β) of COVID-19 suggests that COVID-19 pandemic would be seasonal with the optimal temperature range of 5℃-14℃ and peak of 10℃ for spreading, and vaccine is indispensable to ultimate prevention COVID-19.

Sign in / Sign up

Export Citation Format

Share Document