Parameters Estimation of Generalized Richards Model for COVID-19 Cases in Indonesia Using Genetic Algorithm (original) (raw)
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ABSTRACTThe Philippines has been under a series of different levels of community quarantine and this affected the dynamics of the COVID-19 spread in the country. Predicting the trajectory has been an interest of various research groups. To provide a more efficient method to estimate the parameters of the Age-Stratified, Quarantine-modified SEIR model with Nonlinear Incidence Rates (ASQ-SEIR-NLIR) other than the shooting method, a genetic algorithm approach is explored. By defining constraints for each parameter, the algorithm arrived at an acceptable optimal value for each parameter. The experiment is done on two regions of interest: the Philippines (country-level) and Quezon City, Metro Manila (city-level). The ASQ-SEIR-NLIR model, using the parameters generated by the genetic algorithm, is able to produce an average trajectory compared to the actual data, which may be deemed noisy. The dynamics of the COVID-19 spread between Quezon City and average country level is compared, showi...
Real-time Forecasting of the COVID-19 Epidemic using the Richards Model in South Sulawesi, Indonesia
2020
This paper discussed Real-time Forecasting of the COVID-19 Epidemic using daily cumulative cases of COVID-19 in South Sulawesi Our aim is to make model for the growth of COVID-19 cases in South Sulawesi in the top 5 provinces with the largest COVID-19 cases in Indonesia and predict when this pandemic reaches the peak of spread and when it ends This paper used the Richards model, which is an extension of a simple logistic growth model with additional scaling parameters Data used in the paper as of June 24, 2020 were taken from the official website of the Indonesian government Our results are that the maximum cumulative number of COVID-19 cases has reached 10,000 to 12,000 cases The peak of the pandemic is estimated to occur from June to July 2020 while continuing to impose social restrictions The condition in South Sulawesi shows a sloping curve around October 2020, which means that there are still additional cases but not significant When entering November, the curve starts to flat ...
Estimation of COVID-19 epidemic curves using genetic programming algorithm
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Predictive Mathematical Modelling of the Total Number of COVID-19 Cases for Indonesia
Journal of Environmental Microbiology and Toxicology, 2020
In the current article, we showcase various growth models like Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in the fitting and analysis of the COVID-19 epidemic trend as of 15 July 2020 in Indonesia in the form of the total number of SARS-CoV-2 infections. The MMF model was proved as the suitable model with the highest adjusted R2 value and lowest RMSE value. The Accuracy and Bias Factors values were near to unity (1.0). The parameters obtained from the MMF model consist of maximum growth rate (µm) (log) of 0.025 (95% CI from 0.020 to 0.028), curve constant (ï¤) that affects the inflection point of 0.770 (95% CI from 0.691 to 0.849), lower asymptote value (ï¢) of 0.297 (95% CI from 0.229 to 0.365) and maximal total number of cases (ymax) of 4,634,469 (95% CI from 1,967,886 to 15,417,005). The MMF forecast that the total number of cases in Indonesia on the coming 15th of August and 15th of Septembe...
Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm
International Journal of Environmental Research and Public Health
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Comparison of various epidemic models on the COVID-19 outbreak in Indonesia
Jurnal Teknologi dan Sistem Komputer
This paper compares four mathematical models to describe Indonesia's current coronavirus disease 2019 (COVID-19) pandemic. The daily confirmed case data are used to develop the four models: Logistic, Richards, SIR, and SEIR. A least-square fitting computes each parameter to the available confirmed cases data. We conducted parameterization and sensitivity experiments by varying the length of the data from 60 until 300 days of transmission. All models are susceptible to the epidemic data. Though the correlations between the models and the data are pretty good (>90%), all models still show a poor performance (RMSE>18%). In this study case, Richards model is superior to other models from the highest projection of the positive cases of COVID-19 in Indonesia. At the same time, others underestimate the outbreak and estimate too early decreasing phase. Richards model predicts that the pandemic remains high for a long time, while others project the pandemic will finish much earlier.
Predictive model for COVID 19 curve - An evolutionary approach
2020
In this manuscript we propose a novel method that models the evolution, spread and transmission of COVID 19 pandemic. The proposed model is inspired partly from the evolutionary based state of the art genetic algorithm. The rate of virus evolution, spread and transmission of the COVID 19 and its associated recovery and death rate are modeled using the principle inspired from evolutionary algorithm. Furthermore, the interaction within a community and interaction outside the community is modeled. Using this model, the maximum healthcare threshold is fixed as a constraint. Our evolutionary based model distinguishes between individuals in the population depending on the severity of their symptoms/infection based on the fitness value of the individuals. There is a need to differentiate between virus infected diagnosed (Self isolated) and virus infected non-diagnosed (Highly interacting) sub populations/group. In this study the model results does not compare the number outcomes with any a...
2020 International Conference on ICT for Smart Society (ICISS)
Coronavirus Disease 2019 or COVID-19 is a new disease that can cause respiratory and inflammatory disorders. As a new model virus the general public has difficulty finding its match and then consider it trivial. The spread of the disease caused by COVID virus 19 is set to become a pandemic by the WHO as of March 12, 2020. Development of covid-19 pandemic data in Indonesia, has claimed 1089 lives on May 17, 2020 (source: http: //covid19.bnpb.go.id/) and is a major threat to global public health especially Indonesia. The pandemic behavior in one area can be learned by comparing behavior in other regions. We propose SEIR epidemic models (S = Suspect, E = Expose, I = Infected, and R = Recovered) to predict the behavior of covid-19 transmission in Indonesia with parameters of distribution, cure rate, mortality rate, communication rate and movement. The appropriate parameters to predict the behavior of the Covid-19 virus spreading in Indonesia, firstly, the number of cases that occurred in Indonesia are compared with other countries that were first exposed to this pandemic. Several countries in Asia, Australia, Europe and America are chosen for comparison. Comparisons are performed by examining the maximum correlation values in each country. The pattern of the number of cases that occurred in Indonesia is very similar to the UK, Malaysia and Australia. The first prediction maximum number of new cases per daily is 1,343 people occurring on May 15, 2020. The end of the pandemic is predicted on August 8-10, 2020 (circumstance 1). The second prediction maximum number of new cases per daily is 1,034 people occurring on May 30, 2020. The end of the pandemic is predicted on September 9-10, 2020 (circumstance 2). The SEIR model for predicting the number of Covid-19 cases is sufficient when there is no further development of this pandemic.
Electronics, 2021
The global explosion of the COVID-19 pandemic has created worldwide unprecedented health and economic challenges which stimulated one of the biggest annual migrations globally. In the Indian context, even after proactive decisions taken by the Government, the continual growth of COVID-19 raises questions regarding its extent and severity. The present work utilizes the susceptible-infected-recovered-death (SIRD) compartment model for parameter estimation and fruitful prediction of COVID-19. Further, various optimization techniques such as particle swarm optimization (PSO), gradient (G), pattern search (PS) and their hybrid are employed to solve the considered model. The simulation study endorse the efficiency of PSO (with or without G) and G+PS+G over other techniques for ongoing pandemic assessment. The key parametric values including characteristic time of infection and death and reproduction number have been estimated as 60 days, 67 days and 4.78 respectively by utilizing the opti...