scholarly journals A diffusive SEIR model for community transmission of Covid-19 epidemics: application to Brazil

2021 ◽  
Author(s):  
William E. Fitzgibbon ◽  
Jeffrey J. Morgan ◽  
Glenn F. Webb ◽  
Yixiang Wu
Keyword(s):  
Mathematical Model ◽  
Seir Model ◽  
Spatial Spread ◽  
Geographical Regions ◽  
Community Transmission

A mathematical model incorporating  diffusion is developed to describe the spatial spread of COVID-19 epidemics in geographical regions. The dynamics of the spatial spread are based on community transmission of the virus. The model is applied to the outbreak of the COVID-19 epidemic in Brazil.

Forecast of COVID-19 Trend Following Countrywide Movement Control Order in Malaysia: SEIR Model Approach (Preprint)

2020 ◽  
Author(s):  
Aidalina Mahmud ◽  
Poh Ying Lim ◽  
Hayati Kadir Shahar
Keyword(s):  
Mathematical Model ◽  
Incidence Rate ◽  
Movement Control ◽  
Seir Model ◽  
Infection Incidence ◽  
Contact Rates ◽  
Exposed Population ◽  
Control Order ◽  
Future Work ◽  
Model Approach

BACKGROUND On March 18, 2020, the Malaysian government implemented Movement Control Order (MCO) to limit the contact rates among the population and infected individuals. OBJECTIVE The objective of this study was to forecast the trend of the COVID-19 epidemic in Malaysia in terms of its magnitude and duration. METHODS Data for this analysis was obtained from publicly available databases, from March 17 until March 27, 2020. By applying the Susceptible, Exposed, Infectious and Removed (SEIR) mathematical model and several predetermined assumptions, two analyses were carried out: without and with MCO implementation. RESULTS Without MCO, it is forecasted that it would take 18 days to reach the peak of infection incidence. The incidence rate would plateau at day 80 and end by day 94, with 43% of the exposed population infected. With the implementation of the MCO, it is forecasted that new cases of infection would peak at day 25, plateau at day 90 and end by day 100. At its peak, the infection could affect up to about 40% of the exposed population. CONCLUSIONS It is forecasted that the COVID-19 epidemic in Malaysia will subside soon after the mid-year of 2020. Although the implementation of MCO can flatten the epidemiological curve, it also prolongs the duration of the epidemic. The MCO can result in several unfavorable consequences in economic and psychosocial aspects. A future work of an exit plan for the MCO should also be devised and implemented gradually. The exit plan raises several timely issues of re-infection resurgence after MCO are lifted.

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

2020 ◽  
Vol 17 (15) ◽  
pp. 5509 ◽  
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.

scholarly journals Mathematical model of transmission dynamics with mitigation and health measures for SARS-CoV-2 infection in European countries

2020 ◽  
Author(s):  
Shweta Sankhwar ◽  
Narender Kumar ◽  
Ravins Dohare
Keyword(s):  
Mathematical Model ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
European Countries ◽  
Transmission Dynamics ◽  
Second Phase ◽  
Geographical Regions ◽  
Two Phases ◽  
Spread Of Infection ◽  
And Control

Abstract The pandemic of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) continue to pose a serious threat to global health resulting in disease COVID-19. No specific drug or vaccine is available against this infection. Therefore, the prevention is only way to reduce the spread of infection. The pandemic needs an enhanced mathematical model, therefore, we propose a SEIAJR compartmental mathematical model to estimate the basic reproduction number (R0 ) and the transmission dynamics of four European countries (Germany, United Kingdom, Switzerland and Spain). The proposed mathematical model incorporates mitigation and healthcare measures as recommended by ECDC (European Centre for Disease Prevention and Control). The simulation of proposed model is done in two phases. First-phase simulation estimates basic reproduction number and mitigation rate according to active infected cases in all four European countries. R0 estimate 2.82 - 3.3 for considered European countries. Second-phase simulation predicts the dynamics of infection on the estimated R0 with varying mitigation rate and constant healthcare rate. This study predicts that no more mitigation is required to invade the infection. The current mitigation and healthcare measures are enough to stop the propogation of infection, however, infection would last by end of July 2020. The developed mathematical model would also be applicable to portray the infection trasmission dynamics for other geographical regions with varying parameters.

scholarly journals Impact of non-pharmaceutical interventions on the control of COVID-19 in Iran: A mathematical modeling study

2020 ◽  
Author(s):  
Mehran Nakhaeizadeh ◽  
Sana Eybpoosh ◽  
Yunes Jahani ◽  
Milad Ahmadi Gohari ◽  
Ali Akbar Haghdoost ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Reproductive Number ◽  
Cumulative Number ◽  
Seir Model ◽  
Control Programs ◽  
East Region ◽  
The Impact ◽  
Middle East Region ◽  
Pharmaceutical Interventions

Abstract Background During the first months of the COVID-19 pandemic, Iran reported high numbers of infections and deaths in the Middle East region. In the following months, the burden of this infection decreased significantly, possibly due to the impact of a package of interventions. We modeled the dynamics of COVID-19 infection in Iran to quantify the impacts of these interventions. Methods We used a modified susceptible–exposed–infected–recovered (SEIR) model to model the COVID-19 epidemic in Iran, from 21 January to 21 September 2020, using Markov chain Monte Carlo simulation to calculate 95% uncertainty intervals (UI). We used the model to assess the effectiveness of physical distancing measures and self-isolation under different scenarios. We also estimated the control reproductive number (Rc), using our mathematical model and epidemiologic data. Results If no non-pharmaceutical interventions (NPIs) were applied, there could have been a cumulative number of 51,800,000 (95% UI: 19,100,000–77,600,000) COVID-19 infections and 266,000 (95% UI: 119,000–476,000) deaths by September 21 2020. If physical distancing interventions, such as school/border closures and self-isolation interventions, had been introduced a week earlier than they were actually launched, a 30% reduction in the number of infections and deaths could have been achieved by September 21 2020. The observed daily number of deaths showed that the Rc was one or more than one almost every day during the analysis period. Conclusions Our models suggest that the NPIs implemented in Iran between 21 January and 21 September 2020 had significant effects on the spread of the COVID-19 epidemic. Therefore, we recommend that these interventions are considered when designing future control programs, while simultaneously considering innovative approaches that can minimize harmful economic impacts on the community and the state. Our study also showed that the timely implementation of NPIs showed a profound effect on further reductions in the numbers of infections and deaths. This highlights the importance of forecasting and early detection of future waves of infection and of the need for effective preparedness and response capabilities.

Campaign Optimization through Mobility Network Analysis

2015 ◽  
pp. 33-75 ◽  
Author(s):  
Yaniv Altshuler ◽  
Erez Shmueli ◽  
Guy Zyskind ◽  
Oren Lederman ◽  
Nuria Oliver ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Network Analysis ◽  
Real World ◽  
Service Provision ◽  
Political Campaigns ◽  
Mobility Data ◽  
Proposed Model ◽  
Geographical Regions ◽  
Marketing Service ◽  
The Cost

Optimizing the use of available resources is one of the key challenges in activities that consist of interactions with a large number of “target individuals”, with the ultimate goal of affecting as many of them as possible, such as in marketing, service provision and political campaigns. Typically, the cost of interactions is monotonically increasing such that a method for maximizing the performance of these campaigns is required. This chapter proposes a mathematical model to compute an optimized campaign by automatically determining the number of interacting units and their type, and how they should be allocated to different geographical regions in order to maximize the campaign's performance. The proposed model is validated using real world mobility data.

scholarly journals Prediction of the Epidemic of COVID-19 Based on Quarantined Surveillance in China

2020 ◽  
Author(s):  
Rui Li ◽  
Wenliang Lu ◽  
Xifei Yang ◽  
Peihua Feng ◽  
Ozarina Muqimova ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Incubation Period ◽  
Real World ◽  
Epidemiological Data ◽  
Hubei Province ◽  
Chinese Government ◽  
Peak Time ◽  
Newly Diagnosed ◽  
Seir Model ◽  
Design And Methods

AbstractBackgroud and ObjectiveTo predict the epidemic of COVID-19 based on quarantined surveillance from real world in China by modified SEIR model different from the previous simply mathematical model.Design and MethodsWe forecasted the epidemic of COVID-19 based on current clinical and epidemiological data and built a modified SEIR model to consider both the infectivity during incubation period and the influence on the epidemic from strict quarantined measures.ResultsThe peak time of the curve for the infected newly diagnosed as COVID-19 should substantially present on Feb. 5, 2020 (in non-Hubei areas) and Feb. 19, 2020 (in Hubei). It is estimated that the peak of the curve of the cumulative confirmed cases will appear in non-Hubei areas on Mar. 3, 2020 and in Hubei province on Mar. 10, 2020, and the total number of the patients diagnosed as COVID-19 is 18,000 in non-Hubei areas and 78,000-96,000 in Hubei. The Chinese COVID-19 epidemic can be completetly controlled in May, 2020.ConclusionsCOVID-19 is only a local outbreak in Hubei Province, China. It can be probably avoided the pandemic of global SARS-CoV-2 cases rise with the great efforts by Chinese government and its people.

scholarly journals A Spatial SEIR Model for COVID-19 in South Africa

2021 ◽  
Author(s):  
Inger Fabris-Rotelli ◽  
Jenny Holloway ◽  
Zaid Kimmie ◽  
Sally Archibald ◽  
Pravesh Debba ◽  
...  
Keyword(s):  
South Africa ◽  
South African ◽  
Transmission Rate ◽  
Vulnerability Index ◽  
Relevant Factor ◽  
The South ◽  
Seir Model ◽  
Spatial Spread ◽  
African Setting ◽  
Modelling Approaches

The virus SARS-CoV-2 has resulted in numerous modelling approaches arising rapidly to understand the spread of the disease COVID-19 and to plan for future interventions. Herein, we present an SEIR model with a spatial spread component as well as four infectious compartments to account for the variety of symptom levels and transmission rate. The model takes into account the pattern of spatial vulnerability in South Africa through a vulnerability index that is based on socioeconomic and health susceptibility characteristics. Another spatially relevant factor in this context is level of mobility throughout. The thesis of this study is that without the contextual spatial spread modelling, the heterogeneity in COVID-19 prevalence in the South African setting would not be captured. The model is illustrated on South African COVID-19 case counts and hospitalisations.

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