Outbreak dynamics of COVID-19 in China and the United States

Peirlinck, Mathias; Linka, Kevin; Costabal, Francisco Sahli; Kuhl, Ellen

doi:10.1101/2020.04.06.20055863

Cited by 69 publications

(107 citation statements)

References 25 publications

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“…Altogether we identify three parameters for 27 countries, the basic reproduction number R 0 = C/B, the initial community spread ρ = E 0 /I 0 , and the affected population η = N * /N using the Levenberg-Marquardt method of least squares. For the indentified parameters, we compare two COVID-19 outbreak scenarios: outbreak dynamics with the current travel restrictions, a mobility coefficient of ϑ = 0.00, and a country-specific outbreak on day d 0 , the day at which 0.001% of the population is reported as infected; and outbreak dynamics without travel restrictions, with a mobility coefficient of ϑ = 0.43 (Peirlinck et al 2020), and a European outbreak on day d 0 in Italy, the first country in which 0.001% of the population is reported as infected (Johns Hopkins University 2020). Figure 1 shows the basic reproduction number R 0 = C/B, the initial community spread ρ = E 0 /I 0 , and the affected population η = N * /N across all 27 countries of the European Union.…”

Section: Parameter Identificationmentioning

confidence: 99%

Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions

Linka¹,

Peirlinck²,

Costabal

et al. 2020

Preprint

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107

142

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For the first time in history, on March 17,2020, the European Union closed all its external borders to contain the spreading of the coronavirus 2019, COVID-19. Throughout two past months, governments around the world have implemented massive travel restrictions and border control to mitigate the outbreak of this global pandemic. However, the precise effects of travel restrictions on the outbreak dynamics of COVID-19 remain unknown. Here we combine a global network mobility model with a local epidemiology model to simulate and predict the outbreak dynamics and outbreak control of COVID-19 across Europe. We correlate our mobility model to passenger air travel statistics and calibrate our epidemiology model using the number of reported COVID-19 cases for each country. Our simulations show that mobility networks of air travel can predict the emerging global diffusion pattern of a pandemic at the early stages of the outbreak. Our results suggest that an unconstrained mobility would have significantly accelerated the spreading of COVID-19, especially in Central Europe, Spain, and France. Ultimately, our network epidemiology model can inform political decision making and help identify exit strategies from current travel restrictions and total lockdown.

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Section: Parameter Identificationmentioning

confidence: 99%

Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions

Linka¹,

Peirlinck²,

Costabal

et al. 2020

Preprint

Self Cite

107

142

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“…Mondal and Ghosh (2020) studied the scenarios of the exponential and sigmoid growth of COVID-19 total cases data for 15 states of India considering a initial exponential growth and a extrapolation with a sigmoid-type profile. Peirlinck et al (2020) estimated to the United States the nationwide peak of the outbreak on May 10, 2020 with 3 million infections across the United States.…”

Section: Introductionmentioning

confidence: 99%

Non-Linear Fitting of Sigmoidal Growth Curves to predict a maximum limit to the total number of COVID-19 cases in the United States

Dutra

2020

Preprint

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In the present work is used non-linear fitting of the "Gompert" and "Logistic" growth models to the number of total COVID-19 cases from the United States as a country and individually by states. The methodology allowed us to estimate that the maximum limit for the total number of cases of COVID-19 patients such as those registered with the World Health Organization will be approximately one million and one hundred thousand cases to the United States. Up to 04/19/20 the models indicate that United States reached 70% of this maximum number of "total cases" and the United States will reach 95% of this limit by 05/14/2020. The application of the nonlinear fitting of growth curves to the individual data of each American state showed that only 25% of them did not reach, on 04/19/20, the percentage of 59% of the maximum limit of "total cases" and that 17 of the 50 states still will not have reached 95% of that limit on 05/14/20.

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“…In our study, we utilized their work and conducted our model in a worldwide scale. On April, 2020, Mathias Peirlinck et al [11], used the global network model with the local SEIR model to estimate the outbreak dynamics both in China and the United States, the prior distributions in China, including latent period, contact period and infectious period were used to generate posterior distributions in the United States. The precise timelines and reproductive number were estimated based on these mentioned distributions in areas of China and the United States.…”

Section: Related Workmentioning

confidence: 99%

Transmission in Latent Period Causes A Large Number of Infected People in the United States

Liu

Zhu

Liu

et al. 2020

Preprint

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The cumulative number of confirmed cases in the United States exceeded one million on 29 April 2020, becoming the country of the most serious pandemic in the world. We proposed a model to analyze the real situation and follow-up trend of the epidemic in the US.The proposed model divides the epidemic period into two phases, and includes three different categories of transmitters: the latent population, the documented infectious population, and the undocumented infectious population. We use metapopulation network to simulate the spread of the COVID-19 in the US, and apply the Bayesian inference to estimate the key parameters of the model. We also perform component analysis and sensitivity analysis, researching the compositions of the people with COVID-19.The results show that the basic reproduction number in the early period of propagation is 4.06. As of April 13, 2020, only 45% (95% CI: 35% -73%) of symptom onset cases in the United States were documented. The incubation period of COVID-19 is 10.69 days (95% CI: 10.02 -11.74). If the current level of interventions is continued, the cumulative number of confirmed cases is expected to reach more than 1.7 million in July and continue to grow.

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Outbreak dynamics of COVID-19 in China and the United States

Cited by 69 publications

References 25 publications

Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions

Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions

Non-Linear Fitting of Sigmoidal Growth Curves to predict a maximum limit to the total number of COVID-19 cases in the United States

Transmission in Latent Period Causes A Large Number of Infected People in the United States

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