Modest effects of contact reduction measures on the reproduction number of SARS-CoV-2 in the most affected European countries and the US

AbstractPopulation density, behaviour and cultural habits strongly influence the spread of pathogens. Consequently, key epidemiological parameters may vary from country to country. Many estimates of SARS-CoV-2 and COVID-19 strongly depend on testing frequency and case definitions. The fatal cases due to SARS-CoV2 could be a more reliable parameter, since missing of deaths is less likely. We analysed the dynamics of new infection and death cases to estimate the daily reproduction numbers (Rt) and the effectiveness of control measures in the most affected European Countries and the US. In summary, calculating Rt based on the daily number of deaths as well as of new infections may lead to more reliable estimates than those based on infection cases alone, as death based Rt are expected to be less susceptible to testing bias or limited capacities.

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Determination of daily reproduction numbers of SARS-CoV2 based on death cases suggests more rapid initial spread in Italy and the United States

10.1101/2020.03.28.20046094 ◽

2020 ◽

Cited By ~ 1

Author(s):

Armin Ensser ◽

Klaus Überla

Keyword(s):

The United States ◽

Control Measures ◽

Virus Infections ◽

Case Definitions ◽

Lack Of Information ◽

Reproduction Numbers ◽

The Us ◽

Reliable Parameter ◽

Death Cases ◽

Epidemiological Parameters

Population density, behaviour and cultural habits strongly influence the spread of pathogens. Consequently, key epidemiological parameters may vary from country to country. Confirmed COVID-19 cases in in China have been used to estimate those parameters, that vary largely (reviewed in 1). The estimates also depend on testing frequency and case definitions that are prone to change during ongoing epidemics, providing additional uncertainties. The rise in fatal cases due to SARS-CoV2 could be a more reliable parameter, since missing of deaths is less likely. In the absence of changes in the management of severe COVID-19 cases, the rise in death cases should be proportional to the rise in virus infections. Although the fluctuating low numbers of fatal cases very early in the epidemic may lead to some uncertainty, more than 100 deaths per day are reported since 10.03.2020 in Italy and since 21.03.2020 in the US. Therefore, the dynamics of deaths were analysed to estimate the daily reproduction numbers (Rt) and the effectiveness of control measures.Thus, our analysis provides evidence that basic epidemiological parameters differ between countries to an extent compromising epidemiological predictions of the pandemic. It also suggests that suppression of spread in Italy and the US may be more difficult to achieve. Although we assume that variations in social behaviour are responsible for the different estimates of R0, selection of more rapidly spreading variants of SARS-CoV-2 cannot be excluded. Despite uncertainty in the reliability of the data used and lack of information on possible changes in the effectiveness of registration of COVID-19 deaths during the observation period, our findings should be considered as a working hypothesis demanding further investigations. As the number of deaths rapidly increases worldwide, we encourage more sophisticated modelling of the epidemic based on the dynamics of death cases by experts in the field.

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Is Nigeria really on top of COVID-19? Message from effective reproduction number

10.1101/2020.05.16.20104471 ◽

2020 ◽

Author(s):

Adeshina Israel Adekunle ◽

Oyelola Adegboye ◽

Ezra Gayawan ◽

Emma McBryde

Keyword(s):

Public Health ◽

Compartmental Model ◽

Reproduction Number ◽

Transmission Rate ◽

Credible Interval ◽

Control Measures ◽

Maximum Value ◽

Intervention Measures ◽

Death Cases ◽

Epidemiological Parameters

Following the importation of Covid-19 into Nigeria on the 27 February 2020 and then the outbreak, the question is: how do we anticipate the progression of the ongoing epidemics following all the intervention measures put in place? This kind of question is appropriate for public health responses and it will depend on the early estimates of the key epidemiological parameters of the virus in a defined population. In this study, we combined a likelihood-based method using a Bayesian framework and compartmental model of the epidemic of Covid-19 in Nigeria to estimate the effective reproduction number (R(t)) and basic reproduction number (R_0). This also enables us to estimate the daily transmission rate (β) that determines the effect of social distancing. We further estimate the reported fraction of symptomatic cases. The models are applied to the NCDC data on Covid-19 symptomatic and death cases from 27 February 2020 and 7 May 2020. In this period, the effective reproduction number is estimated with a minimum value of 0.18 and a maximum value of 1.78. Most importantly, the R(t) is strictly greater than one from April 13 till 7 May 2020. The R_0 is estimated to be 2.42 with credible interval: (2.37, 2.47). Comparing this with the R(t) shows that control measures are working but not effective enough to keep R(t) below one. Also, the estimated fractional reported symptomatic cases are between 10 to 50%. Our analysis has shown evidence that the existing control measures are not enough to end the epidemic and more stringent measures are needed.

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Is Nigeria really on top of COVID-19? Message from effective reproduction number

Epidemiology and Infection ◽

10.1017/s0950268820001740 ◽

2020 ◽

Vol 148 ◽

Cited By ~ 3

Author(s):

A. I. Adekunle ◽

O. A. Adegboye ◽

E. Gayawan ◽

E. S. McBryde

Keyword(s):

Public Health ◽

Compartmental Model ◽

Reproduction Number ◽

Transmission Rate ◽

Credible Interval ◽

Control Measures ◽

Maximum Value ◽

Intervention Measures ◽

Death Cases ◽

Epidemiological Parameters

Abstract Following the importation of coronavirus disease (COVID-19) into Nigeria on 27 February 2020 and then the outbreak, the question is: How do we anticipate the progression of the ongoing epidemic following all the intervention measures put in place? This kind of question is appropriate for public health responses and it will depend on the early estimates of the key epidemiological parameters of the virus in a defined population. In this study, we combined a likelihood-based method using a Bayesian framework and compartmental model of the epidemic of COVID-19 in Nigeria to estimate the effective reproduction number (R(t)) and basic reproduction number (R0) – this also enables us to estimate the initial daily transmission rate (β0). We further estimate the reported fraction of symptomatic cases. The models are applied to the NCDC data on COVID-19 symptomatic and death cases from 27 February 2020 and 7 May 2020. In this period, the effective reproduction number is estimated with a minimum value of 0.18 and a maximum value of 2.29. Most importantly, the R(t) is strictly greater than one from 13 April till 7 May 2020. The R0 is estimated to be 2.42 with credible interval: (2.37–2.47). Comparing this with the R(t) shows that control measures are working but not effective enough to keep R(t) below 1. Also, the estimated fraction of reported symptomatic cases is between 10 and 50%. Our analysis has shown evidence that the existing control measures are not enough to end the epidemic and more stringent measures are needed.

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Modelling the Evolution of COVID-19 in High-Incidence European Countries and Regions: Estimated Number of Infections and Impact of Past and Future Intervention Measures

Journal of Clinical Medicine ◽

10.3390/jcm9061825 ◽

2020 ◽

Vol 9 (6) ◽

pp. 1825 ◽

Cited By ~ 3

Author(s):

Juan Fernández-Recio

Keyword(s):

Reproduction Number ◽

Mechanistic Model ◽

Control Measures ◽

European Countries ◽

Intervention Measures ◽

High Incidence ◽

Future Outcomes ◽

Long Term Impact ◽

The Impact

A previously developed mechanistic model of COVID-19 transmission has been adapted and applied here to study the evolution of the disease and the effect of intervention measures in some European countries and territories where the disease has had a major impact. A clear impact of the major intervention measures on the reproduction number (Rt) has been found in all studied countries and territories, as already suggested by the drop in the number of deaths over time. Interestingly, the impact of such major intervention measures seems to be the same in most of these countries. The model has also provided realistic estimates of the total number of infections, active cases and future outcomes. While the predictive capabilities of the model are much more uncertain before the peak of the outbreak, we could still reliably predict the evolution of the disease after a major intervention by assuming the subsequent reproduction number from the current study. A greater challenge is to foresee the long-term impact of softer intervention measures, but this model can estimate the outcome of different scenarios and help to plan changes for the implementation of control measures in a given country or region.

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Modelling the Effectiveness of Epidemic Control Measures in Preventing the Transmission of COVID-19 in Malaysia

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17155509 ◽

2020 ◽

Vol 17 (15) ◽

pp. 5509 ◽

Cited By ~ 1

Author(s):

Balvinder Singh Gill ◽

Vivek Jason Jayaraj ◽

Sarbhan Singh ◽

Sumarni Mohd Ghazali ◽

Yoon Ling Cheong ◽

...

Keyword(s):

Mathematical Model ◽

Model Calibration ◽

Reproduction Number ◽

Close Contact ◽

Movement Control ◽

Control Measures ◽

Seir Model ◽

Epidemic Curve ◽

Reproduction Numbers ◽

Control Order

Malaysia is currently facing an outbreak of COVID-19. We aim to present the first study in Malaysia to report the reproduction numbers and develop a mathematical model forecasting COVID-19 transmission by including isolation, quarantine, and movement control measures. We utilized a susceptible, exposed, infectious, and recovered (SEIR) model by incorporating isolation, quarantine, and movement control order (MCO) taken in Malaysia. The simulations were fitted into the Malaysian COVID-19 active case numbers, allowing approximation of parameters consisting of probability of transmission per contact (β), average number of contacts per day per case (ζ), and proportion of close-contact traced per day (q). The effective reproduction number (Rt) was also determined through this model. Our model calibration estimated that (β), (ζ), and (q) were 0.052, 25 persons, and 0.23, respectively. The (Rt) was estimated to be 1.68. MCO measures reduce the peak number of active COVID-19 cases by 99.1% and reduce (ζ) from 25 (pre-MCO) to 7 (during MCO). The flattening of the epidemic curve was also observed with the implementation of these control measures. We conclude that isolation, quarantine, and MCO measures are essential to break the transmission of COVID-19 in Malaysia.

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Modelling the evolution of COVID-19 in high-incidence European countries and regions: estimated number of infections and impact of past and future intervention measures

10.1101/2020.05.09.20096735 ◽

2020 ◽

Author(s):

Juan Fernandez-Recio

Keyword(s):

Reproduction Number ◽

Mechanistic Model ◽

Control Measures ◽

European Countries ◽

Intervention Measures ◽

High Incidence ◽

Long Term Impact ◽

The Impact ◽

Over Time

A previously developed mechanistic model of COVID-19 transmission has been adapted and applied here to study the evolution of the disease and the effect of intervention measures in some European countries and territories where the disease had major impact. A clear impact of the major intervention measures on the reproduction number (Rt) has been found in all studied countries and territories, as already suggested by the drop in the number of deaths over time. Interestingly, the impact of such major intervention measures seems to be the same in most of these countries. The model has also provided realistic estimates of the total number of infections, active cases and future outcome. While the predictive capabilities of the model are much more uncertain before the peak of the outbreak, we could still reliably predict the evolution of the disease after a major intervention by assuming the afterwards reproduction number from current study. More challenging is to foresee the long-term impact of softer intervention measures, but this model can estimate the outcome of different scenarios and help planning changes in the implementation of control measures in a given country or region.

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The long-term dynamics of tuberculosis and other diseases with long serial intervals: implications of and for changing reproduction numbers

Epidemiology and Infection ◽

10.1017/s0950268898001113 ◽

1998 ◽

Vol 121 (2) ◽

pp. 309-324 ◽

Cited By ~ 36

Author(s):

E. VYNNYCKY ◽

P. E. M. FINE

Keyword(s):

Infectious Disease ◽

Basic Reproduction Number ◽

Reproduction Number ◽

England And Wales ◽

Transmission Potential ◽

Reproduction Numbers ◽

Serial Interval ◽

Net Reproduction ◽

Epidemiological Parameters ◽

The Basic Reproduction Number

The net and basic reproduction numbers are among the most widely-applied concepts in infectious disease epidemiology. A net reproduction number (the average number of secondary infectious cases resulting from each case in a given population) of above 1 is conventionally associated with an increase in incidence; the basic reproduction number (defined analogously for a ‘totally susceptible’ population) provides a standard measure of the ‘transmission potential’ of an infection. Using a model of the epidemiology of tuberculosis in England and Wales since 1900, we demonstrate that these measures are difficult to apply if disease can follow reinfection, and that they lose their conventional interpretations if important epidemiological parameters, such as the rate of contact between individuals, change over the time interval between successive cases in a chain of transmission (the serial interval).The net reproduction number for tuberculosis in England and Wales appears to have been approximately 1 from 1900 until 1950, despite concurrent declines in morbidity and mortality rates, and it declined rapidly in the second half of this century. The basic reproduction number declined from about 3 in 1900, reached 2 by 1950, and first fell below 1 in about 1960. Reductions in effective contact between individuals over this period, measured in terms of the average number of individuals to whom each case could transmit the infection, meant that the conventional basic reproduction number measure (which does not consider subsequent changes in epidemiological parameters) for a given year failed to reflect the ‘actual transmission potential’ of the infection. This latter property is better described by a variant of the conventional measure which takes secular trends in contact into account. These results are relevant for the interpretation of trends in any infectious disease for which epidemiological parameters change over time periods comparable to the infectious period, incubation period or serial interval.

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

10.1101/2021.12.09.21267544 ◽

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.

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Epidemiology of a bubonic plague outbreak in Glasgow, Scotland in 1900

Royal Society Open Science ◽

10.1098/rsos.181695 ◽

2019 ◽

Vol 6 (1) ◽

pp. 181695 ◽

Cited By ~ 8

Author(s):

Katharine R. Dean ◽

Fabienne Krauer ◽

Boris V. Schmid

Keyword(s):

Yersinia Pestis ◽

Reproduction Number ◽

Control Measures ◽

High Rate ◽

Bubonic Plague ◽

The Third ◽

Serial Interval ◽

The Mean ◽

First Time ◽

Epidemiological Parameters

On 3 August 1900, bubonic plague ( Yersinia pestis ) broke out in Glasgow for the first time during the Third Pandemic. The local sanitary authorities rigorously tracked the spread of the disease and they found that nearly all of the 35 cases could be linked by contact with a previous case. Despite trapping hundreds of rats in the area, there was no evidence of a rat epizootic and the investigators speculated that the outbreak could be due to human-to-human transmission of bubonic plague. Here we use a likelihood-based method to reconstruct transmission trees for the outbreak. From the description of the outbreak and the reconstructed trees, we infer several epidemiological parameters. We found that the estimated mean serial interval was 7.4–9.2 days and the mean effective reproduction number dropped below 1 after implementation of control measures. We also found a high rate of secondary transmissions within households and observations of transmissions from individuals who were not terminally septicaemic. Our results provide important insights into the epidemiology of a bubonic plague outbreak during the Third Pandemic in Europe.

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Evaluating the effect of Chinese control measures on COVID-19 via temporal reproduction number estimation

PLoS ONE ◽

10.1371/journal.pone.0246715 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0246715

Author(s):

Duanbing Chen ◽

Tao Zhou

Keyword(s):

Reproduction Number ◽

Early Stage ◽

Mainland China ◽

Complete Information ◽

Control Measures ◽

Research Needs ◽

Temporal Reproduction ◽

Reproduction Numbers ◽

Province Level ◽

Level Analysis

Control measures are necessary to contain the spread of serious infectious diseases such as COVID-19, especially in its early stage. We propose to use temporal reproduction number an extension of effective reproduction number, to evaluate the efficacy of control measures, and establish a Monte-Carlo method to estimate the temporal reproduction number without complete information about symptom onsets. The province-level analysis indicates that the effective reproduction numbers of the majority of provinces in mainland China got down to < 1 just by one week from the setting of control measures, and the temporal reproduction number of the week [15 Feb, 21 Feb] is only about 0.18. It is therefore likely that Chinese control measures on COVID-19 are effective and efficient, though more research needs to be performed.

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