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

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.

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

10.1101/2020.04.13.20063933 ◽

2020 ◽

Cited By ~ 29

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.

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Age-structured Impact of Mitigation Strategies on COVID-19 Severity and Deaths in Kenya

10.21203/rs.3.rs-105797/v1 ◽

2020 ◽

Author(s):

Samuel Mwalili ◽

Mark E. M. Kimathi ◽

Viona N. Ojiambo ◽

Duncan K. Gathungu ◽

Thomas N. O. Achia

Keyword(s):

School Closure ◽

Mitigation Strategies ◽

Global Perspective ◽

Cumulative Number ◽

Social Distancing ◽

First Case ◽

Age Structured ◽

October 17 ◽

Novel Coronavirus ◽

Age Structured Model

Abstract Introduction: COVID-19, a coronavirus disease 2019, is an ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There have been a lot of attempts to model this pandemic from a global perspective. The Novel Coronavirus is still spreading quickly in several countries and the peak has not yet been reached in many countries. We developed age-structured model for describing the COVID-19 pandemic in Kenya under different non-pharmaceutical interventions. The first case in Kenya was identified in March 13, 2020 with the pandemic increasing to 465 confirmed cases by end of 3rd May, 2020. We fitted an age-structured deterministic mathematical model in Kenyan context.Methods: We model the COVID-19 situation in Kenya using Age-structured Susceptible Exposed Infectious Recovered compartmental model. These compartments follow a cascade of the disease from the Susceptible to Exposed individuals who in return are either symptomatic or asymptomatic. The symptomatic depict mild signs, which can develop to severe symptoms warranting hospitalization or can otherwise recover. The severe cases can recover with some developing critical condition. The critical are admitted at intensive care units. The resulting age-dependent ordinary differential equations from the model are solved using fourth order Runge-Kutta methods. We controlled for school closure, social distancing and lockdown in terms of movement restrictionsResults: The model shows varying epidemic peak by age-structure and the mitigation scenarios. The peak dates for unmitigated (UM), the 45% NPI (M45) and School closure-curfew-partial lockdown NPI (SCL) are May 21st, October 17th and December 13th 2020, respectively. Their respective cumulative infections peaks are 43M, 24M and 25M. The daily reported severe cases, critical cases and death proportionately increased with age. Conclusions: The cumulative number of infections reduces greatly with introduction of school closure, social distancing and restricted movement in highly affected counties. The degree of COVID-19 severity increases with age. However, it is not immediately clear when these restrictions can be lifted.

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Addressing the COVID-19 transmission in inner Brazil by a mathematical model

Scientific Reports ◽

10.1038/s41598-021-90118-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

G. B. Almeida ◽

T. N. Vilches ◽

C. P. Ferreira ◽

C. M. C. B. Fortaleza

Keyword(s):

Mathematical Model ◽

Disease Transmission ◽

Abiotic Factors ◽

Severe Pneumonia ◽

Mitigation Strategies ◽

Social Distancing ◽

Control Disease ◽

Set Up ◽

Novel Coronavirus ◽

Public Health Strategies

AbstractIn 2020, the world experienced its very first pandemic of the globalized era. A novel coronavirus, SARS-CoV-2, is the causative agent of severe pneumonia and has rapidly spread through many nations, crashing health systems and leading a large number of people to death. In Brazil, the emergence of local epidemics in major metropolitan areas has always been a concern. In a vast and heterogeneous country, with regional disparities and climate diversity, several factors can modulate the dynamics of COVID-19. What should be the scenario for inner Brazil, and what can we do to control infection transmission in each of these locations? Here, a mathematical model is proposed to simulate disease transmission among individuals in several scenarios, differing by abiotic factors, social-economic factors, and effectiveness of mitigation strategies. The disease control relies on keeping all individuals’ social distancing and detecting, followed by isolating, infected ones. The model reinforces social distancing as the most efficient method to control disease transmission. Moreover, it also shows that improving the detection and isolation of infected individuals can loosen this mitigation strategy. Finally, the effectiveness of control may be different across the country, and understanding it can help set up public health strategies.

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A versatile web app for identifying the drivers of COVID-19 epidemics

Journal of Translational Medicine ◽

10.1186/s12967-021-02736-2 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Wayne M. Getz ◽

Richard Salter ◽

Ludovica Luisa Vissat ◽

Nir Horvitz

Keyword(s):

Model Fitting ◽

Likelihood Estimation ◽

Stochastic Simulations ◽

Social Distancing ◽

Epidemic Curve ◽

Policies And Measures ◽

Incidence And Mortality ◽

Credible Intervals ◽

Web App ◽

Second Wave

Abstract Background No versatile web app exists that allows epidemiologists and managers around the world to comprehensively analyze the impacts of COVID-19 mitigation. The http://covid-webapp.numerusinc.com/ web app presented here fills this gap. Methods Our web app uses a model that explicitly identifies susceptible, contact, latent, asymptomatic, symptomatic and recovered classes of individuals, and a parallel set of response classes, subject to lower pathogen-contact rates. The user inputs a CSV file of incidence and, if of interest, mortality rate data. A default set of parameters is available that can be overwritten through input or online entry, and a user-selected subset of these can be fitted to the model using maximum-likelihood estimation (MLE). Model fitting and forecasting intervals are specifiable and changes to parameters allow counterfactual and forecasting scenarios. Confidence or credible intervals can be generated using stochastic simulations, based on MLE values, or on an inputted CSV file containing Markov chain Monte Carlo (MCMC) estimates of one or more parameters. Results We illustrate the use of our web app in extracting social distancing, social relaxation, surveillance or virulence switching functions (i.e., time varying drivers) from the incidence and mortality rates of COVID-19 epidemics in Israel, South Africa, and England. The Israeli outbreak exhibits four distinct phases: initial outbreak, social distancing, social relaxation, and a second wave mitigation phase. An MCMC projection of this latter phase suggests the Israeli epidemic will continue to produce into late November an average of around 1500 new case per day, unless the population practices social-relaxation measures at least 5-fold below the level in August, which itself is 4-fold below the level at the start of July. Our analysis of the relatively late South African outbreak that became the world’s fifth largest COVID-19 epidemic in July revealed that the decline through late July and early August was characterised by a social distancing driver operating at more than twice the per-capita applicable-disease-class (pc-adc) rate of the social relaxation driver. Our analysis of the relatively early English outbreak, identified a more than 2-fold improvement in surveillance over the course of the epidemic. It also identified a pc-adc social distancing rate in early August that, though nearly four times the pc-adc social relaxation rate, appeared to barely contain a second wave that would break out if social distancing was further relaxed. Conclusion Our web app provides policy makers and health officers who have no epidemiological modelling or computer coding expertise with an invaluable tool for assessing the impacts of different outbreak mitigation policies and measures. This includes an ability to generate an epidemic-suppression or curve-flattening index that measures the intensity with which behavioural responses suppress or flatten the epidemic curve in the region under consideration.

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Disparity and Dynamics of Social Distancing Behaviors in Japan: An Investigation of mobile phone mobility data (Preprint)

10.2196/preprints.31557 ◽

2021 ◽

Author(s):

Zeyu Lyu ◽

Hiroki Takikawa

Keyword(s):

Large Scale ◽

Age Groups ◽

Mitigation Strategies ◽

Social Distancing ◽

Demographic Groups ◽

Fine Grained ◽

Mobility Data ◽

The Social ◽

The Government ◽

Over Time

BACKGROUND The availability of large-scale and fine-grained aggregated mobility data has allowed researchers to observe the dynamic of social distancing behaviors at high spatial and temporal resolutions. Despite the increasing attentions paid to this research agenda, limited studies have focused on the demographic factors related to mobility and the dynamics of social distancing behaviors has not been fully investigated. OBJECTIVE This study aims to assist in the design and implementation of public health policies by exploring the social distancing behaviors among various demographic groups over time. METHODS We combined several data sources, including mobile tracking data and geographical statistics, to estimate visiting population of entertainment venues across demographic groups, which can be considered as the proxy of social distancing behaviors. Then, we employed time series analyze methods to investigate how voluntary and policy-induced social distancing behaviors shift over time across demographic groups. RESULTS Our findings demonstrate distinct patterns of social distancing behaviors and their dynamics across age groups. The population in the entertainment venues comprised mainly of individuals aged 20–40 years, while according to the dynamics of the mobility index and the policy-induced behavior, among the age groups, the extent of reduction of the frequency of visiting entertainment venues during the pandemic was generally the highest among younger individuals. Also, our results indicate the importance of implementing the social distancing policy promptly to limit the spread of the COVID-19 infection. However, it should be noticed that although the policy intervention during the second wave in Japan appeared to increase the awareness of the severity of the pandemic and concerns regarding COVID-19, its direct impact has been largely decreased could only last for a short time. CONCLUSIONS At the time we wrote this paper, in Japan, the number of daily confirmed cases was continuously increasing. Thus, this study provides a timely reference for decision makers about the current situation of policy-induced compliance behaviors. On the one hand, age-dependent disparity requires target mitigation strategies to increase the intention of elderly individuals to adopt mobility restriction behaviors. On the other hand, considering the decreasing impact of self-restriction recommendations, the government should employ policy interventions that limit the resurgence of cases, especially by imposing stronger, stricter social distancing interventions, as they are necessary to promote social distancing behaviors and mitigate the transmission of COVID-19. CLINICALTRIAL None

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High national acceptance for COVID-19 contact tracing technologies in Taiwan (Preprint)

10.2196/preprints.31522 ◽

2021 ◽

Author(s):

Paul M. Garrett ◽

Yuwen Wang ◽

Joshua P. White ◽

Yoshihisa Kashima ◽

Simon Dennis ◽

...

Keyword(s):

Technology Acceptance ◽

Contact Tracing ◽

Virus Spread ◽

Security Measures ◽

Contributing Factors ◽

Privacy And Security ◽

Social Distancing ◽

The Public ◽

Privacy Measures ◽

Credible Intervals

BACKGROUND Governments worldwide have introduced COVID-19 tracing technologies. Taiwan, a world leader in controlling the virus’ spread, has introduced the Taiwan ‘Social Distancing App’ to facilitate COVID-19 contact tracing. However, for these technologies to be effective, they must be accepted and used by the public. OBJECTIVE Our study aimed to determine public acceptance for three hypothetical tracing technologies: a centralized Government App, a decentralized Bluetooth App (e.g., Taiwan’s Social Distancing App), and a Telecommunication tracing technology; and model what factors contributed to their acceptance. METHODS Four nationally representative surveys were conducted in April 2020 sampling 6,000 Taiwanese residents. Perceptions and impacts of COVID-19, government effectiveness, worldviews, and attitudes towards and acceptance of one-of-three hypothetical tracing technologies were assessed. RESULTS Technology acceptance was high across all hypothetical technologies (67% - 73%) and improved with additional privacy measures (82% - 88%). Bayesian modelling (using 95% highest density credible intervals) showed data sensitivity and perceived poor COVID-19 policy compliance inhibited technology acceptance. By contrast, technology benefits (e.g., returning to activities, reducing virus spread, lowering the likelihood of infection), higher education, and perceived technology privacy, security, and trust, were all contributing factors to overall acceptance. Bayesian ordinal probit models revealed higher COVID-19 concern for other people than for one’s self. CONCLUSIONS Taiwan is currently using a range of technologies to minimize the spread of COVID-19 as the country returns to normal economic and social activities. We observed high acceptance for COVID-19 tracing technologies among the Taiwanese public, a promising and necessary finding for the successful introduction of Taiwan’s new ‘Social Distancing App’. Policy makers may capitalize on this acceptance by focusing attention towards the App’s benefits, privacy and security measures, making the App’s privacy measures transparent to the public, and emphasizing App uptake and compliance among the public. CLINICALTRIAL Not applicable.

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The Potential for Transmission of Coronaviruses via Sports Equipment; A Cricket Case Study

International Journal of Sports Medicine ◽

10.1055/a-1500-4620 ◽

2021 ◽

Author(s):

Rory England ◽

Nicholas Peirce ◽

Joseph Torresi ◽

Sean Mitchell ◽

Andy Harland

Keyword(s):

Viral Load ◽

Mitigation Strategies ◽

Infected Person ◽

Review Of Literature ◽

Airborne Transmission ◽

Social Distancing ◽

Transmission Pathways ◽

Respiratory Droplets

AbstractA review of literature on the role of fomites in transmission of coronaviruses informed the development of a framework which was used to qualitatively analyse a cricket case study, where equipment is shared and passed around, and identify potential mitigation strategies. A range of pathways were identified that might in theory allow coronavirus transmission from an infected person to a non-infected person via communal or personal equipment fomites or both. Eighteen percent of potential fomite based interactions were found to be non-essential to play including all contact with another persons equipment. Six opportunities to interrupt the transmission pathway were identified, including the recommendation to screen participants for symptoms prior to play. Social distancing between participants and avoiding unnecessary surface contact provides two opportunities; firstly to avoid equipment exposure to infected respiratory droplets and secondly to avoid uninfected participants touching potential fomites. Hand sanitisation and equipment sanitisation provide two further opportunities by directly inactivating coronavirus. Preventing players from touching their mucosal membranes with their hands represents the sixth potential interruption. Whilst potential fomite transmission pathways were identified, evidence suggests that viral load will be substantially reduced during surface transfer. Mitigation strategies could further reduce potential fomites, suggesting that by comparison, direct airborne transmission presents the greater risk in cricket.

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A Conceptual Approach to Eliminate Bypass Release of Fission Products by In-Containment Relief Valve under SGTR Accident

Science and Technology of Nuclear Installations ◽

10.1155/2018/5936214 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12

Author(s):

Taeseok Kim ◽

Wonjun Choi ◽

Joongoo Jeon ◽

Nam Kyung Kim ◽

Hoichul Jung ◽

...

Keyword(s):

Steam Generator ◽

Nuclear Power ◽

Power Plants ◽

Fission Products ◽

Mitigation Strategies ◽

Severe Accident ◽

Base Case ◽

Conceptual Approach ◽

Relief Valve ◽

Radioactive Nuclides

During a hypothesized severe accident, a containment building is designed to act as a final barrier to prevent release of fission products to the environment in nuclear power plants. However, in a bypass scenario of steam generator tube rupture (SGTR), radioactive nuclides can be released to environment even if the containment is not ruptured. Thus, thorough mitigation strategies are needed to prevent such unfiltered release of the radioactive nuclides during SGTR accidents. To mitigate the consequence of the SGTR accident, this study was conducted to devise a conceptual approach of installing In-Containment Relief Valve (ICRV) from steam generator (SG) to the free space in the containment building and it was simulated by MELCOR code for numerical analysis. Simulation results show that the radioactive nuclides were not released to the environment in the ICRV case. However, the containment pressure increased more than the base case, which is a disadvantage of the ICRV. To minimize the negative effects of the ICRV, the ICRV linked to Reactor Drain Tank (RDT) and cavity flooding was performed. Because the overpressurization of containment is due to heat of ex-vessel corium, only cavity flooding was effective for depressurization. The conceptual design of the ICRV is effective in mitigating the SGTR accident.

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Sensitivity Analyses for a PWR SCC Case Using the Probabilistic Loss-of-Coolant-Accident (Pro-LOCA) Software

Volume 6A: Materials and Fabrication ◽

10.1115/pvp2016-63085 ◽

2016 ◽

Author(s):

Bruce A. Young ◽

Sang-Min Lee ◽

Paul M. Scott

Keyword(s):

Nuclear Power ◽

Power Plants ◽

The United States ◽

Design Criterion ◽

Mitigation Strategies ◽

Sensitivity Analyses ◽

Base Case ◽

Piping System ◽

Loss Of Coolant Accident ◽

Piping Systems

As a means of demonstrating compliance with the United States Code of Federal Regulations 10CFR50 Appendix A, General Design Criterion 4 (GDC-4) requirement that primary piping systems for nuclear power plants exhibit an extremely low probability of rupture, probabilistic fracture mechanics (PFM) software has become increasingly popular. One of these PFM codes for nuclear piping is Pro-LOCA which has been under development over the last decade. Currently, Pro-LOCA is being enhanced under an international cooperative program entitled PARTRIDGE-II (Probabilistic Analysis as a Regulatory Tool for Risk-Informed Decision GuidancE - Phase II). This paper focuses on the use of a pre-defined set of base-case inputs along with prescribed variation in some of those inputs to determine a comparative set of sensitivity analyses results. The benchmarking case was a circumferential Primary Water Stress Corrosion Crack (PWSCC) in a typical PWR primary piping system. The effects of normal operating loads, temperature, leak detection, inspection frequency and quality, and mitigation strategies on the rupture probability were studied. The results of this study will be compared to the results of other PFM codes using the same base-case and variations in inputs. This study was conducted using Pro-LOCA version 4.1.9.

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strandCet: R package for estimating natural and non-natural mortality-at-age of cetaceans from age-structured strandings

PeerJ ◽

10.7717/peerj.5768 ◽

2018 ◽

Vol 6 ◽

pp. e5768 ◽

Cited By ~ 1

Author(s):

Camilo Saavedra

Keyword(s):

Total Mortality ◽

R Package ◽

Analytical Framework ◽

Population Projections ◽

Sources Of Information ◽

Mortality Models ◽

Credible Intervals ◽

Leslie Matrices ◽

Age Structured ◽

Derived Data

Mortality is one of the most important parameters for the study of population dynamics. One of the main sources of information to calculate the mortality of cetaceans arises from the observed age-structure of stranded animals. A method based on an adaptation of a Heligman-Pollard model is proposed. A freely accessible package of functions (strandCet) has been created to apply this method in the statistical software R. Total, natural, and anthropogenic mortality-at-age is estimated using only data of stranded cetaceans whose age is known. Bayesian melding estimation with Incremental Mixture Importance Sampling is used for fitting this model. This characteristic, which accounts for uncertainty, further eases the estimation of credible intervals. The package also includes functions to perform life tables, Siler mortality models to calculate total mortality-at-age and Leslie matrices to derive population projections. Estimated mortalities can be tested under different scenarios. Population parameters as population growth, net production or generation time can be derived from population projections. The strandCet R package provides a new analytical framework to assess mortality in cetacean populations and to explore the consequences of management decisions using only stranding-derived data.

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