scholarly journals COVID-19 Time-varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing

2021 ◽  
Author(s):  
Alexander Chudik ◽  
M. Hashem Pesaran ◽  
Alessandro Rebucci
Keyword(s):  
Reproduction Number ◽  
Transmission Rate ◽  
Economic Incentives ◽  
Moment Condition ◽  
Time Varying ◽  
Linear Interaction ◽  
Susceptible Population ◽  
Social Distancing ◽  
Transmission Rates ◽  
Reproduction Numbers

AbstractThis paper estimates time-varying COVID-19 reproduction numbers worldwide solely based on the number of reported infected cases, allowing for under-reporting. Estimation is based on a moment condition that can be derived from an agent-based stochastic network model of COVID-19 transmission. The outcomes in terms of the reproduction number and the trajectory of per-capita cases through the end of 2020 are very diverse. The reproduction number depends on the transmission rate and the proportion of susceptible population, or the herd immunity effect. Changes in the transmission rate depend on changes in the behavior of the virus, re-flecting mutations and vaccinations, and changes in people’s behavior, reflecting voluntary or government mandated isolation. Over our sample period, neither mutation nor vaccination are major factors, so one can attribute variation in the transmission rate to variations in behavior. Evidence based on panel data models explaining transmission rates for nine European countries indicates that the diversity of outcomes resulted from the non-linear interaction of mandatory containment measures, voluntary precautionary isolation, and the economic incentives that gov-ernments provided to support isolation. These effects are precisely estimated and robust to various assumptions. As a result, countries with seemingly different social distancing policies achieved quite similar outcomes in terms of the reproduction number. These results imply that ignoring the voluntary component of social distancing could introduce an upward bias in the estimates of the effects of lock-downs and support policies on the transmission rates.JEL ClassificationD0, F6, C4, I120, E7

scholarly journals COVID-19 Time-varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing

2021 ◽  
Vol 2021 (407) ◽  
Author(s):  
Alexander Chudik ◽  
◽  
M. Hashem Pesaran ◽  
Alessandro Rebucci ◽  
◽  
...  
Keyword(s):  
Empirical Analysis ◽  
Time Varying ◽  
Social Distancing ◽  
Reproduction Numbers

scholarly journals Estimation of the Time-Varying Reproduction Number of COVID-19 Outbreak in China

2020 ◽  
Author(s):  
Chong You ◽  
Yuhao Deng ◽  
Wenjie Hu ◽  
Jiarui Sun ◽  
Qiushi Lin ◽  
...  
Keyword(s):  
Standard Deviation ◽  
World Wide ◽  
Reproduction Number ◽  
Infectious Period ◽  
Time Varying ◽  
Exponential Growth Rate ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Controlled Reproduction ◽  
Novel Coronavirus

BackgroundThe 2019-nCoV outbreak in Wuhan, China has attracted world-wide attention. As of February 11, 2020, a total of 44730 cases of novel coronavirus-infected pneumonia associated with COVID-19 were confirmed by the National Health Commission of China.MethodsThree approaches, namely Poisson likelihood-based method (ML), exponential growth rate-based method (EGR) and stochastic Susceptible-Infected-Removed dynamic model-based method (SIR), were implemented to estimate the basic and controlled reproduction numbers.ResultsA total of 71 chains of transmission together with dates of symptoms onset and 67 dates of infections were identified among 5405 confirmed cases outside Hubei as reported by February 2, 2020. Based on this information, we find the serial interval having an average of 4.41 days with a standard deviation of 3.17 days and the infectious period having an average of 10.91 days with a standard deviation of 3.95 days.ConclusionsThe controlled reproduction number is declining. It is lower than one in most regions of China, but is still larger than one in Hubei Province. Sustained efforts are needed to further reduce the Rc to below one in order to end the current epidemic.

scholarly journals Estimation of COVID-19 transmission rates in California and the U.S. with reporting delays

2020 ◽  
Author(s):  
Lee Worden ◽  
Rae Wannier ◽  
Micaela Neus ◽  
Jennifer C. Kwan ◽  
Alex Y. Ge ◽  
...  
Keyword(s):  
United States ◽  
Symptom Onset ◽  
The United States ◽  
Time Varying ◽  
Transmission Rates ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Reporting Delays ◽  
Interval Distribution ◽  
The U.S

We estimated time-varying reproduction numbers of COVID-19 transmission in counties and regions of California and in states of the United States, using the Wallinga-Teunis method of estimations applied to publicly available data. The serial interval distribution assumed incorporates wide uncertainty in delays from symptom onset to case reporting. This assumption contributes smoothing and a small but meaningful increase in numerical estimates of reproduction numbers due to the likely existence of secondary cases not yet reported. Transmission in many areas of the U.S. may not yet be controlled, including areas in which case counts appear to be stable or slowly declining.

scholarly journals Decline in global transmission rates of COVID-19

2020 ◽  
Author(s):  
Ethan Romero-Severson ◽  
Nick Hengartner ◽  
Grant Meadors ◽  
Ruian Ke
Keyword(s):  
Particle Filtering ◽  
Transmission Rate ◽  
Global Scale ◽  
Initial Growth ◽  
Social Distancing ◽  
Transmission Rates ◽  
Case Count ◽  
Slow Decline ◽  
Detection Probabilities ◽  
Variable Transmission

AbstractOur method uses a hybrid deterministic and stochastic formalism that allows for time variable transmission rates and detection probabilities. The model was fit using iterated particle filtering to case count and death count time series from 51 countries. We found evidence for a declining transmission rate in 42 of the 51 examined countries. Of those 42 countries 34 have significant evidence for subcritical transmission rates, although the decline in new cases are relatively slow compared to the initial growth rates. This suggests that global scale social distancing efforts to slow the spread of COVID-19 are effective although they need to be strengthened in many regions and maintained in others to avoid further resurgence of COVID-19. The slow decline also suggests alternative strategies to control the virus are needed before social distancing efforts are partially relaxed.

scholarly journals Qualitative analysis and optimal control of an SIR model with logistic growth, non-monotonic incidence and saturated treatment

2021 ◽  
Author(s):  
Jayanta Kumar Ghosh ◽  
Prahlad Majumdar ◽  
Uttam Ghosh
Keyword(s):  
Optimal Control ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Sir Model ◽  
Logistic Growth ◽  
Treatment Rate ◽  
Globally Asymptotically Stable ◽  
Susceptible Population ◽  
Saturated Treatment

This paper describes an SIR model with logistic growth rate of susceptible population, non-monotonic incidence rate and saturated treatment rate. The existence and stability analysis of equilibria have been investigated. It has been shown that the disease free equilibrium point ( DFE ) is globally asymptotically stable if the basic reproduction number is less than unity and the transmission rate of infection less than some threshold. The system exhibits the transcritical bifurcation at DFE with respect to the cure rate. We have also found the condition for occurring the backward bifurcation, which implies the value of basic reproduction number less than unity is not enough to eradicate the disease. Stability or instability of different endemic equilibria has been shown analytically. The system also experiences the saddle-node and Hopf bifurcation. The existence of Bogdanov - Takens bifurcation ( BT ) of co-dimension 2 has been investigated which has also been shown through numerical simulations. Here we have used two control functions, one is vaccination control and other is treatment control. We have solved the optimal control problem both analytically and numerically. Finally, the efficiency analysis has been used to determine the best control strategy among vaccination and treatment.

scholarly journals COVID-19 transmission in the U.S. before vs. after relaxation of state social distancing measures

2020 ◽  
Author(s):  
Alexander C Tsai ◽  
Guy Harling ◽  
Zahra C Reynolds ◽  
Rebecca F Gilbert ◽  
Mark J Siedner
Keyword(s):  
State Government ◽  
Reproduction Number ◽  
District Of Columbia ◽  
Third Party ◽  
Time Varying ◽  
Control Methods ◽  
Epidemic Control ◽  
Social Distancing ◽  
Significant Reversal ◽  
The U.S

Background: Weeks after issuing social distancing orders, all U.S. states and the District of Columbia at least partially relaxed these measures. Critical unanswered questions remain about the timing of relaxation, and if and how unregulated social distancing measures can be sustained while effectively maintaining epidemic control. Methods: We identified all statewide social distancing measures that were implemented and/or relaxed in the U.S. between March 10-July 15, 2020, triangulating data from state government and third-party sources. Using segmented linear regression, we evaluated the extent to which social distancing measure relaxation affected epidemic control, as indicated by the time-varying, state-specific effective reproduction number (R[t]). Results: In the eight weeks prior to relaxation, mean R[t] declined by 0.012 units per day (95% CI, -0.013 to -0.012), and 46/51 jurisdictions achieved R[t] < 1.0 by the date of relaxation. After relaxation of social distancing, R[t] reversed course and began increasing by 0.007 units per day (95% CI, 0.006-0.007), reaching a mean R[t] of 1.16 eight weeks later, with only 9/51 jurisdictions maintaining R[t] <1.0. Indicators often used to motivate relaxation at the time of relaxation (e.g. test positivity rate <5%) predicted greater post-relaxation epidemic growth. Conclusions: We detected an immediate and significant reversal in epidemic growth gains after relaxation of social distancing measures across the U.S. These results illustrate the potential pitfalls of premature relaxation of social distancing measures in the U.S.

scholarly journals SARS-CoV-2 variant dynamics across US states show consistent differences in effective reproduction numbers

2021 ◽  
Author(s):  
Marlin D. Figgins ◽  
Trevor Bedford
Keyword(s):  
Reproduction Number ◽  
Sequence Data ◽  
The United States ◽  
Transmission Rates ◽  
Reproduction Numbers ◽  
The Us ◽  
Relative Transmission ◽  
Variant Frequency ◽  
The Rich ◽  
Case Data

AbstractAccurately estimating relative transmission rates of SARS-CoV-2 Variant of Concern and Variant of Interest viruses remains a scientific and public health priority. Recent studies have used the sample proportions of different variants from sequence data to describe variant frequency dynamics and relative transmission rates, but frequencies alone cannot capture the rich epidemiological behavior of SARS-CoV-2. Here, we extend methods for inferring the effective reproduction number of an epidemic using confirmed case data to jointly estimate variant-specific effective reproduction numbers and frequencies of co-circulating variants using case data and genetic sequences across states in the US from January to October 2021. Our method can be used to infer structured relationships between effective reproduction numbers across time series allowing us to estimate fixed variant-specific growth advantages. We use this model to estimate the effective reproduction number of SARS-CoV-2 Variants of Concern and Variants of Interest in the United States and estimate consistent growth advantages of particular variants across different locations.

scholarly journals A mechanistic and data-driven reconstruction of the time-varying reproduction number: Application to the COVID-19 epidemic

2021 ◽  
Vol 17 (7) ◽  
pp. e1009211
Author(s):  
Bernard Cazelles ◽  
Clara Champagne ◽  
Benjamin Nguyen-Van-Yen ◽  
Catherine Comiskey ◽  
Elisabeta Vergu ◽  
...  
Keyword(s):  
Temporal Evolution ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Specific Model ◽  
Mechanistic Modeling ◽  
Mitigation Strategies ◽  
Brownian Diffusion ◽  
Third Wave ◽  
Time Varying ◽  
Modeling Framework

The effective reproduction number Reff is a critical epidemiological parameter that characterizes the transmissibility of a pathogen. However, this parameter is difficult to estimate in the presence of silent transmission and/or significant temporal variation in case reporting. This variation can occur due to the lack of timely or appropriate testing, public health interventions and/or changes in human behavior during an epidemic. This is exactly the situation we are confronted with during this COVID-19 pandemic. In this work, we propose to estimate Reff for the SARS-CoV-2 (the etiological agent of the COVID-19), based on a model of its propagation considering a time-varying transmission rate. This rate is modeled by a Brownian diffusion process embedded in a stochastic model. The model is then fitted by Bayesian inference (particle Markov Chain Monte Carlo method) using multiple well-documented hospital datasets from several regions in France and in Ireland. This mechanistic modeling framework enables us to reconstruct the temporal evolution of the transmission rate of the COVID-19 based only on the available data. Except for the specific model structure, it is non-specifically assumed that the transmission rate follows a basic stochastic process constrained by the observations. This approach allows us to follow both the course of the COVID-19 epidemic and the temporal evolution of its Reff(t). Besides, it allows to assess and to interpret the evolution of transmission with respect to the mitigation strategies implemented to control the epidemic waves in France and in Ireland. We can thus estimate a reduction of more than 80% for the first wave in all the studied regions but a smaller reduction for the second wave when the epidemic was less active, around 45% in France but just 20% in Ireland. For the third wave in Ireland the reduction was again significant (>70%).

scholarly journals What can we learn from COVID-19 data by using epidemic models with unidentified infectious cases?

2021 ◽  
Author(s):  
quentin Griette ◽  
Jacques Demongeot ◽  
pierre magal
Keyword(s):  
Social Interactions ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Social Effects ◽  
Time Dependent ◽  
Reproduction Numbers ◽  
The Social ◽  
The World ◽  
Early Beginning ◽  
Case Data

Background: The COVID-19 epidemic, which started in late December 2019 and rapidly spread throughout the world, was accompanied by an unprecedented release of reported case data. Our objective is to propose a fresh look at this data by coupling a phenomenological description to the epidemiological dynamics. Methods: We use a phenomenological model to describe and regularize the data. This model can be matched by a single mathematical model reproducing the epidemiological dynamics with a time-dependent transmission rate. We provide a method to compute this transmission rate and reconstruct the changes in the social interactions between people as well as changes in host-pathogen interactions. This method is applied to the cumulative case data of 8 different geographic areas. Findings: We reconstruct the transmission rate from the data, therefore we are in position to understand the contribution of the dynamical effects of social interactions (contacts between individuals) and the contribution of the dynamics of the epidemic. We deduce from the comparison of several instantaneous reproduction numbers that the social effects are the most important in the dynamic of COVID-19. We obtain an instantaneous reproduction number that stays below $3.5$ from early beginning of the epidemic. Conclusion: The instantaneous reproduction number staying below $3.5$ implies that it is sufficient to vaccinate $71\%$ of the population in each state or country considered in our study. Therefore assuming the vaccines will remain efficient against the new variants, and to be more confident it is sufficient to vaccinate $75-80\%$ to get rid of COVID-19 in each state or country. Funding: This research was funded by the Agence Nationale de la Recherche in France (Project name: MPCUII (PM) and (QG))

scholarly journals Inhomogeneous Transmission and Asynchronic Mixing in the Spread of COVID-19 Epidemics

2021 ◽  
Vol 9 ◽  
Author(s):  
Carlos I. Mendoza
Keyword(s):  
Reproduction Number ◽  
Transmission Rate ◽  
Real Data ◽  
Epidemiological Models ◽  
Subexponential Growth ◽  
The Public ◽  
Transmission Rates ◽  
Proposed Model ◽  
Containment Measures ◽  
Mitigation Policies

The ongoing epidemic of COVID-19 first found in China has reinforced the need to develop epidemiological models capable of describing the progression of the disease to be of use in the formulation of mitigation policies. Here, this problem is addressed using a metapopulation approach to consider the inhomogeneous transmission of the spread arising from a variety of reasons, like the distribution of local epidemic onset times or of the transmission rates. We show that these contributions can be incorporated into a susceptible-infected-recovered framework through a time-dependent transmission rate. Thus, the reproduction number decreases with time despite the population dynamics remaining uniform and the depletion of susceptible individuals is small. The obtained results are consistent with the early subexponential growth observed in the cumulated number of confirmed cases even in the absence of containment measures. We validate our model by describing the evolution of COVID-19 using real data from different countries, with an emphasis in the case of Mexico, and show that it also correctly describes the longtime dynamics of the spread. The proposed model yet simple is successful at describing the onset and progression of the outbreak, and considerably improves the accuracy of predictions over traditional compartmental models. The insights given here may prove to be useful to forecast the extent of the public health risks of the epidemics, thus improving public policy-making aimed at reducing such risks.

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