scholarly journals How Much Testing and Social Distancing is Required to Control COVID-19? Some Insight Based on an Age-Differentiated Compartmental Model

2022 ◽  
pp. S145-S169
Author(s):  
Sara Grundel ◽  
Stefan Heyder ◽  
Thomas Hotz ◽  
Tobias K. S. Ritschel ◽  
Philipp Sauerteig ◽  
...  
Keyword(s):  
Compartmental Model ◽  
Social Distancing

scholarly journals Mathematical model of COVID-19 intervention scenarios for São Paulo—Brazil

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Osmar Pinto Neto ◽  
Deanna M. Kennedy ◽  
José Clark Reis ◽  
Yiyu Wang ◽  
Ana Carolina Brisola Brizzi ◽  
...  
Keyword(s):  
Compartmental Model ◽  
Time Window ◽  
Algorithm Design ◽  
Sao Paulo ◽  
Intervention Strategies ◽  
Transmission Dynamics ◽  
São Paulo ◽  
Protective Behavior ◽  
Social Distancing ◽  
Multi Objective Genetic Algorithm

AbstractWith COVID-19 surging across the world, understanding the effectiveness of intervention strategies on transmission dynamics is of primary global health importance. Here, we develop and analyze an epidemiological compartmental model using multi-objective genetic algorithm design optimization to compare scenarios related to strategy type, the extent of social distancing, time window, and personal protection levels on the transmission dynamics of COVID-19 in São Paulo, Brazil. The results indicate that the optimal strategy for São Paulo is to reduce social distancing over time with a stepping-down reduction in the magnitude of social distancing every 80-days. Our results also indicate that the ability to reduce social distancing depends on a 5–10% increase in the current percentage of people strictly following protective guidelines, highlighting the importance of protective behavior in controlling the pandemic. Our framework can be extended to model transmission dynamics for other countries, regions, states, cities, and organizations.

scholarly journals Mathematical model of COVID-19 intervention scenarios for São Paulo-Brazil

2020 ◽  
Author(s):  
Osmar Pinto Neto ◽  
José Clark Reis ◽  
Ana Carolina Brisola Brizzi ◽  
Gustavo José Zambrano ◽  
Joabe Marcos de Souza ◽  
...  
Keyword(s):  
Compartmental Model ◽  
Sao Paulo ◽  
São Paulo ◽  
Optimal Solutions ◽  
Personal Protection ◽  
Protective Behavior ◽  
Social Distancing ◽  
Second Wave ◽  
Oscillatory Level

AbstractAn epidemiological compartmental model was used to simulate social distancing strategies to contain the COVID-19 pandemic and prevent a second wave in São Paulo, Brazil. Optimization using genetic algorithm was used to determine the optimal solutions. Our results suggest the best-case strategy for São Paulo is to maintain or increase the current magnitude of social distancing for at least 60 more days and increase the current levels of personal protection behaviors by a minimum of 10% (e.g., wearing facemasks, proper hand hygiene and avoid agglomeration). Followed by a long-term oscillatory level of social distancing with a stepping-down approach every 80 days over a period of two years with continued protective behavior.

scholarly journals Describing the COVID-19 Outbreak Fitting Modified SIR models to Data

2020 ◽  
Author(s):  
Aldo Ianni ◽  
Nicola Rossi
Keyword(s):  
Time Evolution ◽  
Compartmental Model ◽  
Social Distancing ◽  
Future Evolution ◽  
The Social ◽  
Model Predictions ◽  
Official Sources ◽  
Far Future

AbstractIn this paper we fit simple modifications of the SIR compartmental model to the COVID-19 outbreak data, available from official sources for Italy and other countries. Even if the complexity of the pandemic can not be easily modelled, we show that our model, at present, describes the time evolution of the data in spite of the application of the social distancing and lock-down procedure. Finally, we discuss the reliability of the model predictions, under certain conditions, for estimating the near and far future evolution of the COVID-19 outbreak. The conditions for the applicability of the proposed models are discussed.

scholarly journals Possible fates of the dispersion of SARS-COV-2 in the Mexican context

2020 ◽  
Author(s):  
Ivan Santamaria-Holek ◽  
Victor Castano
Keyword(s):  
Time Evolution ◽  
Compartmental Model ◽  
Social Policies ◽  
Infection Rates ◽  
Conceptual Tool ◽  
Epidemiological Research ◽  
Social Distancing ◽  
The Impact

The determination of the adequate time for house confinement and when social distancing restrictions should end are now two of the main challenges that any country has to face in an effective battle against. The possibility of a new outbreak of the pandemic and how to avoid it is, nowadays, one of the primary objectives of epidemiological research. In this work, we go deep in this subject by presenting an innovative compartmental model, that explicitly introduces the number of active cases, and employing it as a conceptual tool to explore the possible fates of the dispersion of SARS-COV-2 in the Mexican context. We incorporated the impact of starting, inattention, and end of restrictive social policies on the time evolution of the pandemics via time-in-run corrections to the infection rates. The magnitude and impact on the epidemic due to post-social restrictive policies are also studied. The scenarios generated by the model can help authorities to determine an adequate time and population load that may be allowed to reassume normal activities.

scholarly journals Mitigation of COVID-19 using social distancing of the elderly in Brazil: The vertical quarantine effects in hospitalizations and deaths

2021 ◽  
Author(s):  
Vito Ribeiro Venturieri ◽  
Matheus Silva Gonçalves ◽  
Vinícius Rios Fuck
Keyword(s):  
Elderly Population ◽  
Compartmental Model ◽  
The Elderly ◽  
Mitigation Strategies ◽  
Social Distancing ◽  
System Collapse ◽  
The Social ◽  
Hospital Beds ◽  
Intervention Scenario ◽  
Pharmaceutical Interventions

SummaryGovernments and epidemiologists have been proposing several mitigation strategies based on non-pharmaceutical interventions to reduce COVID-19 cases, hospitalizations, and deaths. In this work, we quantitatively compare the effects of elderly population (60 years old or more) selective isolation with a no isolation scenario using an adapted Susceptible - Exposed - Infectious - Removed (SEIR) compartmental model. For these simulated scenarios, we estimate the number of hospitalizations and deaths for different Brazilian cities, including those due to the lack of hospital beds. Our simulations show that, for São Paulo City, the isolation of the elderly would reduce demand for hospital beds by 9% and deaths by 16% compared to the no intervention scenario. Other Brazilian cities follow the same pattern, with median reductions of deaths ranging from 12-18%. We conclude that the social distancing of the elderly would be marginally effective and would not avoid health system collapse in several Brazilian cities.

scholarly journals Prediction of the Peak, Effect of Intervention and Total Infected by the Coronavirus Disease in India

2020 ◽  
Author(s):  
Parth Vipul Shah
Keyword(s):  
Infection Rate ◽  
Compartmental Model ◽  
Total Population ◽  
Reproduction Number ◽  
Least Square Method ◽  
Peak Effect ◽  
Poisson Noise ◽  
Least Square ◽  
Intervention Period ◽  
Social Distancing

AbstractWe study the effect of the coronavirus disease 2019 (COVID-19) in India using the SEIR compartmental model. After it’s outbreak in Wuhan, China, it has been imported to India which is a densely populated country. India is fighting against this disease by ensuring nationwide social distancing. We estimate the infection rate to be 0.258 using a least square method with Poisson noise and estimate the reproduction number to be 2.58. We approximate the peak of the epidemic to be August 11, 2020. We estimate that a 25% drop in infection rate will delay the peak by 38 days for a 1 month intervention period. We estimate that the total individuals infected in India will be approximately 9% of the total population.

scholarly journals A model for COVID-19 with isolation, quarantine and testing as control measures

2020 ◽  
Author(s):  
M.S. Aronna ◽  
R. Guglielmi ◽  
L.M. Moschen
Keyword(s):  
Compartmental Model ◽  
Reproduction Number ◽  
Risk Groups ◽  
Control Measures ◽  
Contact Rate ◽  
Control Parameters ◽  
Social Distancing ◽  
Proposed Model ◽  
Asymptomatic Infections ◽  
The Basic Reproduction Number

AbstractIn this article we propose a compartmental model for the dynamics of Coronavirus Disease 2019 (COVID-19). We take into account the presence of asymptomatic infections and the main policies that have been adopted so far to contain the epidemic: isolation (or social distancing) of a portion of the population, quarantine for confirmed cases and testing. We model isolation by separating the population in two groups: one composed by key-workers that keep working during the pandemic and have a usual contact rate, and a second group consisting of people that are enforced/recommended to stay at home. We refer to quarantine as strict isolation, and it is applied to confirmed infected cases.In the proposed model, the proportion of people in isolation, the level of contact reduction and the testing rate are control parameters that can vary in time, representing policies that evolve in different stages. We obtain an explicit expression for the basic reproduction number in terms of the parameters of the disease and of the control policies. In this way we can quantify the effect that isolation and testing have in the evolution of the epidemic. We present a series of simulations to illustrate different realistic scenarios. From the expression of and the simulations we conclude that isolation (social distancing) and testing among asymptomatic cases are fundamental actions to control the epidemic, and the stricter these measures are and the sooner they are implemented, the more lives can be saved. Additionally, we show that people that remain in isolation significantly reduce their probability of contagion, so risk groups should be recommended to maintain a low contact rate during the course of the epidemic.

scholarly journals State-specific projection of COVID-19 infection in the United States and evaluation of three major control measures

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Shi Chen ◽  
Qin Li ◽  
Song Gao ◽  
Yuhao Kang ◽  
Xun Shi
Keyword(s):  
United States ◽  
New York ◽  
Compartmental Model ◽  
Spatial Interaction ◽  
The United States ◽  
State Policies ◽  
Control Measures ◽  
Specific Information ◽  
Social Distancing ◽  
Infected People

AbstractMost models of the COVID-19 pandemic in the United States do not consider geographic variation and spatial interaction. In this research, we developed a travel-network-based susceptible-exposed-infectious-removed (SEIR) mathematical compartmental model system that characterizes infections by state and incorporates inflows and outflows of interstate travelers. Modeling reveals that curbing interstate travel when the disease is already widespread will make little difference. Meanwhile, increased testing capacity (facilitating early identification of infected people and quick isolation) and strict social-distancing and self-quarantine rules are most effective in abating the outbreak. The modeling has also produced state-specific information. For example, for New York and Michigan, isolation of persons exposed to the virus needs to be imposed within 2 days to prevent a broad outbreak, whereas for other states this period can be 3.6 days. This model could be used to determine resources needed before safely lifting state policies on social distancing.

Optimal Control of Fractional Order COVID-19 Epidemic Spreading in Japan and India 2020

2020 ◽  
Vol 15 (04) ◽  
pp. 207-236 ◽  
Author(s):  
Meghadri Das ◽  
G. P. Samanta
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Incomplete Information ◽  
Fractional Order ◽  
Compartmental Model ◽  
Transmission Dynamics ◽  
Epidemic Spreading ◽  
Social Distancing ◽  
First Case

In Japan, the first case of Coronavirus disease 2019 (COVID-19) was reported on 15th January 2020. In India, on 30th January 2020, the first case of COVID-19 in India was reported in Kerala and the number of reported cases has increased rapidly. The main purpose of this work is to study numerically the epidemic peak for COVID-19 disease along with transmission dynamics of COVID-19 in Japan and India 2020. Taking into account the uncertainty due to the incomplete information about the coronavirus (COVID-19), we have taken the Susceptible-Asymptomatic-Infectious-Recovered (SAIR) compartmental model under fractional order framework for our study. We have also studied the effects of fractional order along with other parameters in transfer dynamics and epidemic peak control for both the countries. An optimal control problem has been studied by controlling social distancing parameter.

scholarly journals Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model

2020 ◽  
Vol 9 (5) ◽  
pp. 1492 ◽  
Author(s):  
Chiara Reno ◽  
Jacopo Lenzi ◽  
Antonio Navarra ◽  
Eleonora Barelli ◽  
Davide Gori ◽  
...  
Keyword(s):  
Hospital Care ◽  
Compartmental Model ◽  
Deterministic Model ◽  
Northern Italy ◽  
Health Interventions ◽  
Contact Rate ◽  
Public Health Interventions ◽  
Social Distancing ◽  
Containment Measures ◽  
Different Levels

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world’s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

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