scholarly journals Change points in the spread of COVID-19 question the effectiveness of nonpharmaceutical interventions in Germany

2020 ◽  
Author(s):  
Thomas Wieland
Keyword(s):  
Growth Models ◽  
Change Points ◽  
Test Volume ◽  
Child Day Care ◽  
Reproduction Numbers ◽  
Care Facilities ◽  
True Infection ◽  
Nonpharmaceutical Interventions ◽  
Case Data ◽  
Reporting Delay

AbstractAimsNonpharmaceutical interventions against the spread of SARS-CoV-2 in Germany included the cancellation of mass events (from March 8), closures of schools and child day care facilities (from March 16) as well as a “lockdown” (from March 23). This study attempts to assess the effectiveness of these interventions in terms of revealing their impact on infections over time.MethodsDates of infections were estimated from official German case data by incorporating the incubation period and an empirical reporting delay. Exponential growth models for infections and reproduction numbers were estimated and investigated with respect to change points in the time series.ResultsA significant decline of daily and cumulative infections as well as reproduction numbers is found at March 8 (CI [7, 9]), March 10 (CI [9, 11] and March 3 (CI [2, 4]), respectively. Further declines and stabilizations are found in the end of March. There is also a change point in new infections at April 19 (CI [18, 20]), but daily infections still show a negative growth. From March 19 (CI [18, 20]), the reproduction numbers fluctuate on a level below one.ConclusionsThe decline of infections in early March 2020 can be attributed to relatively small interventions and voluntary behavioural changes. Additional effects of later interventions cannot be detected clearly. Liberalizations of measures did not induce a re-increase of infections. Thus, the effectiveness of most German interventions remains questionable. Moreover, assessing of interventions is impeded by the estimation of true infection dates and the influence of test volume.

Optimal number and allocation of data collection points for linear spline growth curve modeling

2016 ◽  
Vol 41 (4) ◽  
pp. 550-558 ◽  
Author(s):  
Wei Wu ◽  
Fan Jia ◽  
Richard Kinai ◽  
Todd D. Little
Keyword(s):  
Data Collection ◽  
Change Point ◽  
Growth Models ◽  
Optimal Number ◽  
Change Points ◽  
Change Processes ◽  
Linear Spline ◽  
Curve Modeling ◽  
Data Points ◽  
Two Phases

Spline growth modelling is a popular tool to model change processes with distinct phases and change points in longitudinal studies. Focusing on linear spline growth models with two phases and a fixed change point (the transition point from one phase to the other), we detail how to find optimal data collection designs that maximize the efficiency of detecting key parameters in the spline models, holding the total number of data points or sample size constant. We identify efficient designs for the cases where (a) the exact location of the change point is known (complete certainty), (b) only the interval that contains the change point is known (partial certainty), and (c) no prior knowledge on the location of the change point is available (zero certainty). We conclude with recommendations for optimal number and allocation of data collection points.

Zoning for Child Day Care Facilities

1985 ◽  
Vol 37 (2) ◽  
pp. 5-9
Author(s):  
Martin Jaffe ◽  
Edith Netter
Keyword(s):  
Day Care ◽  
Child Day Care ◽  
Care Facilities

scholarly journals Analysis of the early Covid-19 epidemic curve in Germany by regression models with change points

2020 ◽  
Author(s):  
Helmut Küchenhoff ◽  
Felix Günther ◽  
Michael Höhle ◽  
Andreas Bender
Keyword(s):  
Time Series ◽  
Disease Onset ◽  
Major Change ◽  
Change Points ◽  
Federal State ◽  
Strong Increase ◽  
Robert Koch Institute ◽  
Epidemic Curve ◽  
Projection Techniques ◽  
Reporting Delay

AbstractWe analyze the Covid-19 epidemic curve from March to end of April 2020 in Germany. We use statistical models to estimate the number of cases with disease onset on a given day and use back-projection techniques to obtain the number of new infections per day. The respective time series are analyzed by a Poisson trend regression model with change points. The change points are estimated directly from the data without further assumptions. We carry out the analysis for the whole of Germany and the federal state of Bavaria, where we have more detailed data. Both analyses show a major change between March 9th and 13th for the time series of infections: from a strong increase to a stagnation or a slight decrease. Another change was found between March 24th and March 31st, where the decline intensified. These two major changes can be related to different governmental measures. On March, 11th, Chancellor Merkel appealed for social distancing in a press conference with the Robert Koch Institute (RKI) and a ban on major events with more than 1000 visitors (March 10th) was issued. The other change point at the end of March could be related to the shutdown in Germany.Our results differ from those by other authors as we take into account the reporting delay, which turned out to be time dependent and therefore changes the structure of the epidemic curve compared to the curve of newly reported cases.

Infectious Diseases and Child Day Care

PEDIATRICS ◽  
1984 ◽  
Vol 74 (1) ◽  
pp. 134-139
Author(s):  
Richard A. Goodman ◽  
Michael T. Osterholm ◽  
Dan M. Granoff ◽  
Larry K. Pickering
Keyword(s):  
United States ◽  
Infectious Diseases ◽  
Day Care ◽  
The United States ◽  
Infectious Agents ◽  
Day Care Centers ◽  
Child Day Care ◽  
Recent Interest ◽  
Care Facilities ◽  
Control And Prevention

The number of day care centers and home care facilities has steadily increased in the United States. Recent interest has focused on the possible relationship between attendance at child day care facilities and the occurrence of certain infectious diseases. A variety of infectious agents have been reported as causes of illness among children and staff in day care programs. In general, however, concurrent risks for these infections among children attending and those not attending day care programs have not been established by prospective studies. A review is made of the pathogens that have been associated with infections in day care settings, patterns of occurrence of infectious diseases in day care facilities, aspects of control and prevention of these diseases, and controversies related to infectious diseases in child day care facilities. Aspects of this problem that warrant further research are outlined.

scholarly journals Flatten the Curve!

REGION ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 43-83
Author(s):  
Thomas Wieland
Keyword(s):  
Growth Rates ◽  
Growth Models ◽  
Regional Growth ◽  
Logistic Growth ◽  
School Closures ◽  
Epidemic Curve ◽  
Child Day Care ◽  
Voluntary Behavior ◽  
Before School ◽  
Novel Coronavirus

Since the emerging of the "novel coronavirus" SARS-CoV-2 and the corresponding respiratory disease COVID-19, the virus has spread all over the world. Being one of the most affected countries in Europe, in March 2020, Germany established several nonpharmaceutical interventions to contain the virus spread, including the closure of schools and child day care facilities (March 16-18, 2020) as well as a full "lockdown" with forced social distancing and closures of "nonessential" services (March 23, 2020). The present study attempts to analyze whether these governmental interventions had an impact on the declared aim of "flattening the curve", referring to the epidemic curve of new infections. This analysis is conducted from a regional perspective. On the level of the 412 German counties, logistic growth models were estimated based on daily infections (estimated from reported cases), aiming at determining the regional growth rate of infections and the point of inflection where infection rates begin to decrease and the curve flattens. All German counties exceeded the peak of new infections between the beginning of March and the middle of April. In a large majority of German counties, the epidemic curve has flattened before the "lockdown" was established. In a minority of counties, the peak was already exceeded before school closures. The growth rates of infections vary spatially depending on the time the virus emerged. Counties belonging to states which established an additional curfew show no significant improvement with respect to growth rates and mortality. Furthermore, mortality varies strongly across German counties, which can be attributed to infections of people belonging to the "risk group", especially residents of retirement homes. The decline of infections in absence of the "lockdown" measures could be explained by 1) earlier governmental interventions (e.g., cancellation of mass events, domestic quarantine), 2) voluntary behavior changes (e.g., physical distancing and hygiene), 3) seasonality of the virus, and 4) a rising but undiscovered level of immunity within the population. The results raise the question whether formal contact bans and curfews really contribute to curve flattening within a pandemic.

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 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))

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