scholarly journals THE OUTBREAK’S MODELING OF CORONAVIRUS (COVID-19) USING THE MODIFIED SEIR MODEL IN INDONESIA

2020 ◽  
Vol 5 (1) ◽  
pp. 61-68
Author(s):  
Rustan Rustan ◽  
Linda Handayani

Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by a new type of virus called SARS-CoV-2, and by the beginning of 2020 had spread throughout the world, including Indonesia. A high rate of spread of COVID-19 causes the number of patients that infected increase significantly. In this study, mathematical modeling was carried out to predict the number of COVID-19 patients and the duration of the COVID-19 pandemic in Indonesia. The model used is a modified SEIR model (Susceptible, Exposed, Infected, Recovered) with several assumptions such as a constant and homogeneous population, patients who have recovered can not be infected, and the spread only occurs from human to human. In addition,  it is assumed that there are individuals who carry out quarantine and isolation. Modeling is done using the help of MATLAB R2015a. The modeling results show that the peak of the COVID-19 pandemic in Indonesia will occur in the middle of May 2020, and the number of infected patients will be about 15000 people. This amount can be reduced if the quarantine and self-isolation process is carried out optimally.

Introduction: COVID-19 appeared in China at the end of 2019. It then spread all over the world very quickly. The new type of corona virus COVID-19, which causes respiratory tract infection, is destructive with its high rate of transmission and mortality rate. Materials and Methods: In this study, determining the course of the COVID-19 pandemic for next 4 months in Afghanistan with the help of a specially modified mathematical modeling is intended to reveal. Results: results of our study show that the COVID-19 pandemic can affect a large population in Afghanistan in a short time. However, it is possible to reduce the number of cases and deaths very effectively with easy measures. Keywords: COVID-19, precautions, pandemic, logistic mathematical model, Afghanistan.


Author(s):  
Nacima Moussouni ◽  
Mohamed Aliane

Coronavirus disease of 2019 or COVID-19 (acronym for coronavirus disease 2019) is an emerging infectious disease caused by a strain of coronavirus called SARS-CoV-22, contagious with human-to-human transmission via respiratory droplets or by touching contaminated surfaces then touching them face. Faced with what the world lives, to define this problem, we have modeled it as an optimal control problem based on the models of William Ogilvy Kermack et Anderson Gray McKendrick, called SEIR model, modified by adding compartments suitable for our study. Our objective in this work is to maximize the number of recovered people while minimizing the number of infected. We solved the problem theoretically using the Pontryagin maximum principle, numerically we used and compared results of two methods namely the indirect method (shooting method) and the Euler discretization method, implemented in MATLAB.


2020 ◽  
Vol 2 (3) ◽  
pp. 172-177
Author(s):  
Shawni Dutta ◽  
◽  
Samir Kumar Bandyopadhyay ◽  

Introduction: Corona Virus Infectious Disease (COVID-19) is the infectious disease. The COVID-19 disease came to earth in early 2019. It is expanding exponentially throughout the world and affected an enormous number of human beings starting from the last month. The World Health Organization (WHO) on March 11, 2020 declared COVID-19 was characterized as “Pandemic”. This paper proposed approach for confirmation of COVID-19 cases after the diagnosis of doctors. The objective of this study uses machine learning method to evaluate how much predicted results are close to original data related to Confirmed-Negative-Released-Death cases of COVID-19. Materials and methods: For this purpose, a verification method is proposed in this paper that uses the concept of Deep-learning Neural Network. In this framework, Long shrt-term memory (LSTM) and Gated Recurrent Unit (GRU) are also assimilated finally for training the dataset. The prediction results are tally with the results predicted by clinical doctors. Results: The results are obtained from the proposed method with accuracy 87 % for the “confirmed Cases”, 67.8 % for “Negative Cases”, 62% for “Deceased Case” and 40.5 % for “Released Case”. Another important parameter i.e. RMSE shows 30.15% for Confirmed Case, 49.4 % for Negative Cases, 4.16 % for Deceased Case and 13.72 % for Released Case. Conclusions: The outbreak of Coronavirus has the nature of exponential growth and so it is difficult to control with limited clinical persons for handling a huge number of patients within a reasonable time. So it is necessary to build an automated model, based on machine learning approach, for corrective measure after the decision of clinical doctors.


2019 ◽  
Vol 16 (1) ◽  
pp. 107
Author(s):  
Willyam Daniel Sihotang ◽  
Ceria Clara Simbolon ◽  
July Hartiny ◽  
Desrinawati Tindaon ◽  
Lasker Pangarapan Sinaga

Measles is a contagious infectious disease caused by a virus and has the potential to cause an outbreak. Immunization and vaccination are carried out as an effort to prevent the spread of measles. This study aims to analyze and determine the stability of the SEIR model on the spread of measles with the influence of immunization and MR vaccines. The results obtained from model analysis, namely there are two disease free and endemic equilibrium points. If the conditions are met, the measles-free equilibrium point will be asymptotically stable and the measles endemic equilibrium point will be stable. Numerical solutions show a decrease in the rate of spread of measles due to the effect of immunization and the addition of MR vaccines.


2020 ◽  
Author(s):  
Altahir A. Altahir ◽  
Nirbhay Mathur ◽  
Loshini Thiruchelvam ◽  
Ghulam E. Mustafa Abro ◽  
Syaimaa’ S. M. Radzi ◽  
...  

AbstractAfter a breakdown notified in Wuhan, China in December 2019, COVID-19 is declared as pandemic diseases. To the date more than 13 million confirmed cases and more than half a million are dead around the world. This virus also attached Malaysia in its immature stage where 8718 cases were confirmed and 122 were declared as death. Malaysia responsibly controlled the spread by enforcing MCO. Hence, it is required to visualize the pattern of Covid-19 spread. Also, it is necessary to estimate the impact of the enforced prevention measures. In this paper, an infectious disease dynamic modeling (SEIR) is used to estimate the epidemic spread in Malaysia. The main assumption is to update the reproduction number Rt with respect to the implemented prevention measures. For a time-frame of five month, the Rt was assumed to vary between 2.9 and 0.3. Moreover, the manuscript includes two possible scenarios: the first will be the extension of the stricter measures all over the country, and the second will be the gradual lift of the lock-down. After implementing several stages of lock-down we have found that the estimated values of the Rt with respect to the strictness degree varies between 0.2 to 1.1. A continuous strict lock-down may reduce the Rt to 0.2 and accordingly the estimated active cases will be reduced to 20 by the beginning of September 2020. In contrast, the second scenario considers a gradual lift of the enforced prevention measures by the end of June 2020, here we have considered three possible outcomes according to the MCO relaxation. Thus, the estimated values of Rt = 0.7, 0.9, 1.1, which shows a rapid increase in the number of active cases. The implemented SEIR model shows a close resemblance with the actual data recorded from 10, March till 7, July 2020.Author summaryConceptualization, A.A.A; methodology, A.A.A, N.M; validation, A.A.A, N.M; formal analysis, A.A.A; investigation, N.M, A.A.A; resources, G.E.M.A, L.T; data collection, L.T, N.M; writing—original draft preparation, A.A.A, L.T, G.E.M.A, N.M; writing—review and editing, V.S.A, S.C.D, B.S.G, P.S, S.A.B.M.Z, N.M; visualization, N.M; supervision, V.S.A; project administration, V.S.A. All authors have read and agreed to the published version of the manuscript


2020 ◽  
Vol 9 (2) ◽  
pp. 141-147
Author(s):  
Israfil Israfil ◽  
Pipit Festi Wiliyanarti ◽  
Pius Selasa

Covid-19 is a contagious pulmonary infectious disease caused by a new type of coronavirus (SARS-COV-2). Covid-19 is a global pandemic that has infected millions of people and killed thousands of people in the world. Cases of death in Covid-19 patients were first discovered in China in December 2019. In Indonesia, since it was first discovered, cases of death of Covid-19 patients continue to increase and has become one of the countries with the highest fatality rate in the world reaching 9.11 percent. The purpose of this study is to determine risk factors for death in covid-19 patients in China in order to get guidance in preventing death in Covid-19 patients in Indonesia. This type of research is a literature review. The results of the study found five risk factors for death in Covid-19 patients, namely age, Covid-19 complications, the immune system (immunity), concomitant diseases (cormobidity), and treatment facilities. Suggestions of various risk factors for death in Covid-19 patients in China are expected to be a guide in efforts to prevent death in Covid-19 patients that occur in Indonesia.


2020 ◽  
Vol 38 (3) ◽  
pp. 183-187
Author(s):  
Doo Hyuk Kwon ◽  
Ji Hye Hwang ◽  
Jeong-Ho Hong

Coronavirus disease 2019 (COVID-19) is a new type of epidemic infectious disease that threatens the world after it first broke out in Wuhan, China, in December 2019. By early March, Korea had the second largest number of confirmed cases of COVID-19 in the world after China, among which about 90% of patients reported in Daegu and Gyeongsangbuk-do province. As a neurologist, the author experienced various neurological diseases while working at hub-hospitals for COVID-19 in Daegu. I would like to describe the role of a neurologist in the emerging outbreak of infectious diseases, along with my experience working at the hub-hospital for Middle East Respiratory Syndrome (MERS) in 2015.


2021 ◽  
Vol 328 ◽  
pp. 06002
Author(s):  
Dayat Hidayat ◽  
Edwin Setiawan Nugraha

Covid-19 is a very extraordinary case not only in one country but all countries in the world. The number of deaths caused by Covid-19 is very large and the rate of spread of this disease is very high and fast. In this paper, we perform an analysis of a covid-19 epidemic model. This model is a development of the SEIR model in general which is equipped with a Quarantine (Q), Fatality (F) compartment, and there is a separation between detected and undetected infected people (I). Our analysis shows that there are two equilibria, namely, disease free equilibrium and endemic equilibrium. by using, Lyapunov function, we demonstrated that disease free is globally asymptotically stable if R0 < 1, and disease-free becomes unstable if R0 > 1. This result reveal that the intervention of infection rate and quarantine process are important to control and achieve global stability of disease-free equilibrium


2021 ◽  
Vol 162 (4) ◽  
pp. 123-134
Author(s):  
Blanka Emődy-Kiss ◽  
Ágnes Pataki ◽  
Gábor Deli ◽  
Sándor Papp ◽  
Mária Mátyus ◽  
...  

Összefoglaló. Bevezetés: A COVID–19-járvány az egész világon elterjedt. A járvány Európában való első megjelenése során megfigyelhető volt, hogy a terjedés mértéke kisebb azokban az országokban, ahol a tuberkulózis elleni védekezésül kiterjedt BCG-vakcinációt végeznek. Célkitűzés: A jelen munkában olyan összefüggéseket igyekeztünk feltárni, amelyek befolyásolták a járványterjedés paramétereit, különös figyelemmel a BCG-vakcinációs gyakorlatra. Módszerek: A világ összes olyan országára vonatkozóan, ahol megfelelő minőségű statisztikai adatok álltak rendelkezésünkre, vizsgáltuk a járvány terjedésének első hullámát. A mozgóátlagolt járványgörbéken elemeztük a járvány időtartamát, a tetőzés mértékét, a fertőzöttek és a halálesetek egymillió lakosra vetített számát. Figyelembe vettük az országok gazdasági mutatóit (GDP, légi forgalom, a tengeri hajózás mértéke). Statisztikai analízis: A vizsgált paraméterek nem mutattak normális eloszlást, így nemparaméteres próbákkal (rangkorreláció, Kruskal–Wallis ANOVA) statisztikai kapcsolatot kerestünk a járványterjedés mértéke, a BCG-vakcináció és más paraméterek között. Eredmények: A járvány gyorsan elterjedt a világon, de mégis, február első három hetében a terjedésben egy szünet volt megfigyelhető. A járványhullám Európában nagyjából egyszerre ért véget. A járvány által leginkább azok az országok érintettek, ahol nem alkalmaztak rendszeres BCG-vakcinációt, bár a képet bonyolítja, hogy ezek az országok gazdaságilag többnyire fejlettek. A halálozási rátában nem mutatkozott ilyen különbség. Következtetés: Statisztikailag igazolható tény, hogy a vakcinációt végző országokból az első hullám alatt kevesebb fertőzöttet jelentettek; az ok-okozati összefüggés bizonytalan, hiszen az országok múltja, szokásai, társadalmi berendezkedése, gazdasági fejlettsége nem azonos. Eredményeink alátámasztják az összehasonlító kontaktkutatás fontosságát annak tisztázására, hogy a BCG-oltás hogyan befolyásolja az emberek vírussal szembeni érzékenységét, valamint a vírus terjesztésének, továbbadásának képességét. Orv Hetil. 2021; 162(4): 123–134. Summary. Introduction: The new type of coronavirus (SARS-CoV-2) epidemic is widespread throughout the world. During the outbreak of the pandemic in Europe it was revealed that the rate of spread was lower in countries where extensive BCG vaccination is used to protect against tuberculosis. Objective: In the present work, we sought to explore relationships that influenced epidemic spreading parameters, with particular reference to BCG vaccination practice. Methods: We examined the first wave of the spread of the epidemic for all countries in the world where adequate quality statistics were available. We analyzed the duration of the epidemic, the extent of the peak, the number of infected people, and the number of deaths per million inhabitants with the moving average of epidemic curves. We took into account the economic indicators of the countries (GDP, air traffic and extent of maritime shipping). Statistical analysis: The examined parameters did not show a normal distribution, so we looked for a statistical relationship with non-parametric tests (rank correlation, Kruskal–Wallis ANOVA) between the extents of epidemic spread, BCG vaccination and other parameters. Results: The epidemic spread rapidly around the world, but still, in the first three weeks of February, there was a pause in the spread. The first wave of epidemics ended roughly at the same time in Europe. Those countries are the most affected by the epidemic where regular BCG vaccination has not been used, although the picture is complicated by the fact that these countries are mostly economically developed. There was no such difference observable in the mortality rate. Conclusion: Although this work clearly demonstrates that during the first wave of the pandemic, fewer infections were reported worldwide in countries where BCG vaccination is obligatory, however, the causal relationship is uncertain, as the countries’ past, customs, social organization and economic development are different. Our results support the necessity of comparative contact tracing to clarify how BCG vaccination affects people’s susceptibility to this new type of coronavirus as well as their ability to spread and transmit the virus. Orv Hetil. 2021; 162(4): 123–134.


Author(s):  
Indri Seta Septadina

Viruses are one of the causes of infectious diseases that need to be watched out for. In the last 20 years, several viral diseases have caused epidemics such as severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002-2003, influenza H1N1 in 2009 and Middle East Respiratory syndrome (MERS-CoV) which was first identified in Saudi Arabia in year 2012. On December 31, 2019, China reported a case of mysterious pneumonia of unknown cause. Within 3 days, the number of patients with these cases was 44 patients and continues to increase until now there are millions of cases. Initially, the epidemiological data showed that 66% of patients were related to or exposed to a seafood market or live market in Wuhan, Hubei Province, China. Samples of isolates from patients were studied with the results showing the presence of coronavirus infection, a new type of betacoronavirus, named 2019 novel Coronavirus (2019-nCoV). On February 11, 2020, the World Health Organization named the new virus SARS-CoV-2 and the disease name as Coronavirus Disease 2019 (COVID-19). The corona virus is the main pathogen causing an outbreak of respiratory disease. On March 11, 2020, WHO announced that COVID-19 was becoming a pandemic in the world.


Sign in / Sign up

Export Citation Format

Share Document