scholarly journals Expected impact of lockdown in Île-de-France and possible exit strategies

2020 ◽  
Author(s):  
Laura Di Domenico ◽  
Giulia Pullano ◽  
Chiara E. Sabbatini ◽  
Pierre-Yves Boëlle ◽  
Vittoria Colizza
Keyword(s):  
Substantial Reduction ◽  
Case Finding ◽  
System Capacity ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Reproductive Number ◽  
Health Crisis ◽  
Social Distancing ◽  
Response Planning ◽  
Exit Strategies

More than half of the global population is currently under strict forms of social distancing, with more than 90 countries in lockdown, including France. Estimating the expected impact of the lockdown, and the potential effectiveness of different exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis. We use a stochastic age-structured transmission model integrating data on age profile and social contacts in the Île-de-France region to (i) assess the current epidemic situation, (ii) evaluate the expected impact of the lockdown implemented in France on March 17, 2020, and (iii) estimate the effectiveness of possible exit strategies. The model is calibrated on hospital admission data of the region before lockdown and validated on syndromic and virological surveillance data. Different types and durations of social distancing interventions are simulated, including a progressive lifting of the lockdown targeted on specific classes of individuals (e.g. allowing a larger proportion of the population to go to work, while protecting the elderly), and large-scale testing. We estimate the basic reproductive number at 3.0 [2.8, 3.2] (95% confidence interval) prior to lockdown and the population infected by COVID-19 as of April 5 to be in the range 1% to 6%. The average number of contacts is predicted to be reduced by 80% during lockdown, leading to a substantial reduction of the reproductive number (RLD =0.68 [0.62-0.73]). Under these conditions, the epidemic curve reaches ICU system capacity and slowly decreases during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave largely overwhelming the healthcare system. Extensive case-finding, testing and isolation are required to envision social distancing strategies that gradually relax current constraints (larger fraction of individuals going back to work, progressive reopening of activities), while keeping schools closed and seniors isolated. As France faces the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case-finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.

scholarly journals Susceptible-Infected-Recovered model study using free particle dynamics

2021 ◽  
Vol 67 (4 Jul-Aug) ◽  
Author(s):  
Fernando Garzón ◽  
Olvera Orozco ◽  
Jorge Castro ◽  
Aldo Figueroa
Keyword(s):  
Particle Density ◽  
Transmission Rate ◽  
Free Particle ◽  
Sir Model ◽  
Particle Dynamics ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Closed Domain ◽  
Health Crisis ◽  
Social Distancing

A study on the epidemiologic Susceptible-Infected-Recovered (SIR) model is presented using free particle dynamics. The study is performed using a computational model consisting of randomly allocated particles in a closed domain which are free to move inrandom directions with the ability to collide into each other. The transmission rules for the particle–particle interactions are based on the main viral infection mechanisms, resulting in real–time results of the number of susceptible, infected, and recovered particles within a population of N= 200 particles. The results are qualitatively compared with a differential equation SIR model in terms of the transmission rate β, recovery rate γ, and the basic reproductive number R0, yielding overall good results. The effect of the particle density ρ on R0 is also studied to analyze how an infectious disease spreads over different types of populations. The versatility of the proposed free–particle–dynamics SIR model allows to simulate different scenarios, such as social distancing, commonly referredto as quarantine, no social distancing measures, and a mixture of the former and the latter. It is found that by implementing early relaxation of social distancing measures before the number of infected particles reaches zero, could lead to subsequent outbreaks such as the particular events observed in different countries due to the ongoing COVID–19 health crisis

scholarly journals Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hamid Khataee ◽  
Istvan Scheuring ◽  
Andras Czirok ◽  
Zoltan Neufeld
Keyword(s):  
Mobile Phone ◽  
Basic Reproductive Number ◽  
Mobile Phone Data ◽  
Reproductive Number ◽  
Expansion Phase ◽  
Social Distancing ◽  
Exponential Expansion ◽  
Total Death ◽  
Mobility Reduction ◽  
Epidemiological Parameters

AbstractA better understanding of how the COVID-19 pandemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number ($$R_0$$ R 0 ) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the pandemic.

Modeling and stability analysis of the spread of novel coronavirus disease COVID-19

2021 ◽  
pp. 2150035
Author(s):  
A. George Maria Selvam ◽  
Jehad Alzabut ◽  
D. Abraham Vianny ◽  
Mary Jacintha ◽  
Fatma Bozkurt Yousef
Keyword(s):  
Fractional Order ◽  
Disease Transmission ◽  
Equilibrium Points ◽  
Sufficient Conditions ◽  
Basic Reproductive Number ◽  
Phase Portraits ◽  
Transmission Model ◽  
Reproductive Number ◽  
Discrete Version ◽  
Novel Coronavirus

Towards the end of 2019, the world witnessed the outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (COVID-19), a new strain of coronavirus that was unidentified in humans previously. In this paper, a new fractional-order Susceptible–Exposed–Infected–Hospitalized–Recovered (SEIHR) model is formulated for COVID-19, where the population is infected due to human transmission. The fractional-order discrete version of the model is obtained by the process of discretization and the basic reproductive number is calculated with the next-generation matrix approach. All equilibrium points related to the disease transmission model are then computed. Further, sufficient conditions to investigate all possible equilibria of the model are established in terms of the basic reproduction number (local stability) and are supported with time series, phase portraits and bifurcation diagrams. Finally, numerical simulations are provided to demonstrate the theoretical findings.

scholarly journals Differential effects of intervention timing on COVID-19 spread in the United States

2020 ◽  
Vol 6 (49) ◽  
pp. eabd6370 ◽  
Author(s):  
Sen Pei ◽  
Sasikiran Kandula ◽  
Jeffrey Shaman
Keyword(s):  
United States ◽  
Disease Transmission ◽  
Human Mobility ◽  
The United States ◽  
Control Measures ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Reproductive Number ◽  
Mobility Data ◽  
Nonpharmaceutical Interventions

Assessing the effects of early nonpharmaceutical interventions on coronavirus disease 2019 (COVID-19) spread is crucial for understanding and planning future control measures to combat the pandemic. We use observations of reported infections and deaths, human mobility data, and a metapopulation transmission model to quantify changes in disease transmission rates in U.S. counties from 15 March to 3 May 2020. We find that marked, asynchronous reductions of the basic reproductive number occurred throughout the United States in association with social distancing and other control measures. Counterfactual simulations indicate that, had these same measures been implemented 1 to 2 weeks earlier, substantial cases and deaths could have been averted and that delayed responses to future increased incidence will facilitate a stronger rebound of infections and death. Our findings underscore the importance of early intervention and aggressive control in combatting the COVID-19 pandemic.

scholarly journals Evaluation of Different Types of Face Masks to Limit the Spread of SARS-CoV-2 – A Modeling Study

2021 ◽  
Author(s):  
Brian M. Gurbaxani ◽  
Andrew N. Hill ◽  
Prabasaj Paul ◽  
Pragati V. Prasad ◽  
Rachel B. Slayton
Keyword(s):  
The United States ◽  
Basic Reproductive Number ◽  
Transmission Model ◽  
Source Control ◽  
Reproductive Number ◽  
Medical Procedure ◽  
Different Types ◽  
Protection Efficacy ◽  
N95 Respirators ◽  
Related Mortality

AbstractWe updated a published mathematical model of SARS-CoV-2 transmission with laboratory-derived source and wearer protection efficacy estimates for a variety of face masks to estimate their impact on COVID-19 incidence and related mortality in the United States. When used at already-observed population rates of 80% for those ≥65 years and 60% for those <65 years, face masks are associated with 69% (cloth) to 78% (medical procedure mask) reductions in cumulative COVID-19 infections and 82% (cloth) to 87% (medical procedure mask) reductions in related deaths over a 6-month timeline in the model. If cloth or medical procedure masks’ source control and wearer protection efficacies are boosted about 30% each to 84% and 60% by cloth over medical procedure masking, fitters, or braces, the COVID-19 basic reproductive number of 2.5 could decrease to an effective reproductive number ≤ 1.0, and from 4.0 to ≈ 1.6 for the B.1.1.7 variant.Article Summary LineAdapting a published SARS-CoV-2 transmission model together with updated, laboratory-derived source control and wearer protection efficacy estimates for a variety of face coverings as well as N95 respirators, we demonstrate that community masking as currently practiced has likely reduced cases and deaths and that this benefit can be increased with wider adoption of better performing masks.

scholarly journals Effects of Demographic and Weather Parameters on COVID-19 Basic Reproduction Number

2021 ◽  
Vol 8 ◽  
Author(s):  
Igor Salom ◽  
Andjela Rodic ◽  
Ognjen Milicevic ◽  
Dusan Zigic ◽  
Magdalena Djordjevic ◽  
...  
Keyword(s):  
Negative Correlation ◽  
Blood Type ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Strong Positive Correlation ◽  
Related Factors ◽  
Positive Correlation ◽  
Social Distancing ◽  
Pollution Levels ◽  
Weather Parameters

It is hard to overstate the importance of a timely prediction of the COVID-19 pandemic progression. Yet, this is not possible without a comprehensive understanding of environmental factors that may affect the infection transmissibility. Studies addressing parameters that may influence COVID-19 progression relied on either the total numbers of detected cases and similar proxies (which are highly sensitive to the testing capacity, levels of introduced social distancing measures, etc.), and/or a small number of analyzed factors, including analysis of regions that display a narrow range of these parameters. We here apply a novel approach, exploiting widespread growth regimes in COVID-19 detected case counts. By applying nonlinear dynamics methods to the exponential regime, we extract basic reproductive number R0 (i.e., the measure of COVID-19 inherent biological transmissibility), applying to the completely naïve population in the absence of social distancing, for 118 different countries. We then use bioinformatics methods to systematically collect data on a large number of potentially interesting demographics and weather parameters for these countries (where data was available), and seek their correlations with the rate of COVID-19 spread. While some of the already reported or assumed tendencies (e.g., negative correlation of transmissibility with temperature and humidity, significant correlation with UV, generally positive correlation with pollution levels) are also confirmed by our analysis, we report a number of both novel results and those that help settle existing disputes: the absence of dependence on wind speed and air pressure, negative correlation with precipitation; significant positive correlation with society development level (human development index) irrespective of testing policies, and percent of the urban population, but absence of correlation with population density per se. We find a strong positive correlation of transmissibility on alcohol consumption, and the absence of correlation on refugee numbers, contrary to some widespread beliefs. Significant tendencies with health-related factors are reported, including a detailed analysis of the blood type group showing consistent tendencies on Rh factor, and a strong positive correlation of transmissibility with cholesterol levels. Detailed comparisons of obtained results with previous findings, and limitations of our approach, are also provided.

scholarly journals Significant Relaxation of SARS-CoV-2-Targeted Non-Pharmaceutical Interventions Will Result in Profound Mortality: A New York State Modelling Study

2020 ◽  
Author(s):  
Benjamin U. Hoffman
Keyword(s):  
New York ◽  
Severe Acute Respiratory Syndrome ◽  
Global Health ◽  
New York State ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Effective Vaccine ◽  
Health Crisis ◽  
York State ◽  
Pharmaceutical Interventions

AbstractSevere acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is the most significant global health crisis of the 21st century. The aim of this study was to develop a model to estimate the effect of undocumented infections, seasonal infectivity, immunity, and non-pharmaceutical interventions (NPIs), such as social distancing, on the transmission, morbidity, and mortality of SARS-CoV-2 in New York State (NYS). Simulations revealed dramatic infectivity driven by undocumented infections, and a peak basic reproductive number in NYS of 5.7. NPIs have been effective, and relaxation >50% will result in tens-of-thousands more deaths. Endemic infection is likely to occur in the absence of profound sustained immunity. As a result, until an effective vaccine or other effective pharmaceutical intervention is developed, it will be critical to not reduce NPIs >50% below current levels. This study establishes fundamental characteristics of SARS-CoV-2 transmission, which can help policymakers navigate combating this virus in the coming years.

scholarly journals Microsimulation of SARS-CoV-2 Transmission in Society

2021 ◽  
Author(s):  
Anthony R Green ◽  
Daniel Keep ◽  
Ian Piper
Keyword(s):  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Infection Model ◽  
Infection Rates ◽  
Social Distancing ◽  
Source Of Infection ◽  
Population Sizes ◽  
Doubling Times ◽  
Good Agreement ◽  
Infection Spread

The outbreak of the pandemic disease, COVID-19, has shown that the approaches by different countries has resulted in a range of infection rates through their societies. This has arisen from the varying personal behaviour and tactical use of lockdown strategies within each country. We report the use of microsimulation of a simulated community in Australia, using a discrete infection model within a community of residences, places of work and recreation to demonstrate the applicability of this method to both the current pandemic and to infection more generally. Simulations without any societal intervention on infection spread provided base simulations that could be compared with social and societal controls in the future and which were compared with the initial doubling times of country outbreaks across the world. Different population sizes were represented in some simulations and in other simulations the effects of either social distancing or the use of facial masks as personal behaviours was investigated within the community. Good agreement is found between the initial doubling times for several countries and the simulations that suggests that modelling infection as a collection of individual infections provides an alternative to current epidemiological models. The variation of the basic reproductive number, R0, with time and population size, suggests that one of the fundamentals assumptions in SIR type models is wrong, but varies according to the properties of the population being modelled. Investigation of the infection spread shows that the number of super-spreaders varies with the size of the population and occurs through contacts in clubs, supermarkets, schools and theatres where the source of infection is an employee and where there are high numbers of contacts. The simulations of individual control show that the benefits of social distancing or wearing masks is only fully realised where there is considerable compliance within society to these measures.

scholarly journals Mathematical modeling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada

2020 ◽  
Author(s):  
Ashleigh R. Tuite ◽  
David N. Fisman ◽  
Amy L. Greer
Keyword(s):  
Median Number ◽  
Case Finding ◽  
Mitigation Strategies ◽  
System Capacity ◽  
Base Case ◽  
Social Distancing ◽  
Effective Dynamic ◽  
Credible Intervals ◽  
Age Structured ◽  
Limited Testing

AbstractBackgroundWe evaluated how non-pharmaceutical interventions could be used to control the COVID-19 pandemic and reduce the burden on the healthcare system.MethodsUsing an age-structured compartmental model of COVID-19 transmission in the population of Ontario, Canada, we compared a base case with limited testing, isolation, and quarantine to scenarios with: enhanced case finding; restrictive social distancing measures; or a combination of enhanced case finding and less restrictive social distancing. Interventions were either implemented for fixed durations or dynamically cycled on and off, based on projected ICU bed occupancy. We present median and credible intervals (CrI) from 100 replicates per scenario using a two-year time horizon.ResultsWe estimated that 56% (95% CrI: 42-63%) of the Ontario population would be infected over the course of the epidemic in the base case. At the epidemic peak, we projected 107,000 (95% CrI: 60,760-149,000) cases in hospital and 55,500 (95% CrI: 32,700-75,200) cases in ICU. For fixed duration scenarios, all interventions were projected to delay and reduce the height of the epidemic peak relative to the base case, with restrictive social distancing estimated to have the greatest effect. Longer duration interventions were more effective. Dynamic interventions were projected to reduce the proportion of the population infected at the end of the two-year period. Dynamic social distancing interventions could reduce the median number of cases in ICU below current estimates of Ontario’s ICU capacity.InterpretationWithout significant social distancing or a combination of moderate social distancing with enhanced case finding, we project that ICU resources would be overwhelmed. Dynamic social distancing could maintain health system capacity and also allow periodic psychological and economic respite for populations.

scholarly journals Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data

2020 ◽  
Author(s):  
Hamid Khataee ◽  
Istvan Scheuring ◽  
Andras Czirok ◽  
Zoltan Neufeld
Keyword(s):  
Mobile Phone ◽  
Basic Reproductive Number ◽  
Mobile Phone Data ◽  
Reproductive Number ◽  
Expansion Phase ◽  
Social Distancing ◽  
Exponential Expansion ◽  
Total Death ◽  
Mobility Reduction ◽  
Epidemiological Parameters

AbstractA better understanding of how the COVID-19 epidemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number (R0) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the epidemic.

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