Hamiltonian dynamics of the SIS epidemic model with stochastic fluctuations

Nakamura, Gilberto M.; Martinêz, Alexandre Souto

doi:10.1038/s41598-019-52351-x

Cited by 39 publications

(49 citation statements)

References 56 publications

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“…The review on epidemic processes have been done in [4]- [6] (see also references therein). Description of the balance between the susceptible and infected individuals in population under the various conditions of infection transfer, stochastic approaches and fluctuations influence have been developed in [7]- [9]. Kinetic approach can be applied based on [10].…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Epidemic Big Bang: development and quarantine measures for Covid-19

Trigger

Czerniawski

2020

Preprint

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New discrete approximation for the infection spread is constructed based on COVID-19 epidemic data. We consider the epidemic as dependent upon four key parameters: the size of population involved, the mean number of dangerous contacts of one infected person per day, the probability to transmit infection due to such contact and the mean duration of disease. In the simplest case of free epidemic in an infinite population, the number of infected rises exponentially day by day. Here we show the model for epidemic process in a closed population, constrained by isolation, treatment and so on. The four parameters introduced here have the clear sense and are in association with the well-known concept of reproduction number in the continuous susceptible-infected-susceptible model. We derive these parameters from the adequate statistical data. On this basis, we also found the corresponding basic reproduction number mentioned above. Our approach allows evaluating the influence of quarantine measures on free pandemic process. We found a good correspondence of the theory and reliable statistical data. The model is quite flexible and it can be expanded for situations that are more complex.

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Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Epidemic Big Bang: development and quarantine measures for Covid-19

Trigger

Czerniawski

2020

Preprint

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“…The SIS model is used for a given closed population that is susceptible to a particular disease, is prone to be infected, and communicate the infection within the community [ 21 ]. It is a time dynamic model with the numbers of susceptible and infected people changing with time according to two different compartments which are characterized by two differential equations:…”

Section: Susceptible Infectious Susceptible (Sis) Modelmentioning

confidence: 99%

COVID-19 in India: State-wise Analysis and Prediction

Ghosh

Chakraborty

2020

Preprint

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Coronavirus disease 2019 (COVID-19), a highly infectious disease, was first detected in Wuhan, China, in December 2019. The disease has spread to 212 countries and territories around the world and infected (confirmed) more than three million people. In India, the disease was first detected on 30 January 2020 in Kerala in a student who returned from Wuhan. The total (cumulative) number of confirmed infected people is more than 37000 till now across India (3 May 2020). Most of the research and newspaper articles focus on the number of infected people in the entire country. However, given the size and diversity of India, it may be a good idea to look at the spread of the disease in each state separately, along with the entire country. For example, currently, Maharashtra has more than 10000 confirmed cumulative infected cases, whereas West Bengal has less than 800 confirmed infected cases (1 May 2020). The approaches to address the pandemic in the two states must be different due to limited resources. In this article, we will focus the infected people in each state (restricting to only those states with enough data for prediction) and build three growth models to predict infected people for that state in the next 30 days. The impact of preventive measures on daily infected-rate is discussed for each state.

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“…The SEIR ideal model that assumes people convey lifetime immunity to an ailment even after recovery, but in case of some viral transmission the resistance after infection declines in a short time. The SEIRS model is an alternative model that allows the immunity waned over time to reappear as a susceptible state, Nakamura et al [34], He S. et al [35], Bjørnstad et al [36]. The other SIR manages the susceptible, infectious and then immediately removed and isolated.…”

Section: Mathematical Pandemic Modelsmentioning

confidence: 99%

Micro Level Search for COVID-19, Bhubaneswar: Odisha, India

Mishra

Sethi

2020

CJAST

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Outlines: Severe acute respiratory syndrome; coronavirus 2 (SARS-CoV-2) is an emerging virus from 16th Dec 2019, has created virulent pandemic situation over 217 major countries and territories including USA, India, and Brazil etc. There are multiple pharmaceuticals available for treatment. Although no vaccine yet available in the world but few Indian and Russian vaccine results are promising. The treatment procedure is compelling for lock downs and confinements. The COVID-19 is still on the trot from March 24th, 2020 in India so also Odisha and its capital Bhubaneswar killing 87 people and suffering 33454 people and accompanied by ill health, job losses, domestic violence, poverty, food scarcity and loss of mobility. Scope: To manage the pandemic need good governance, leadership and health-care upgrading, public private partnership, public awareness, risk communication with improvising continuous supply of foods, goods, service systems. Many dynamic epidemic models i.e. SIR and SIS and SEIR and SEIRS are suggested, but the Ganjam practical field model has been observed successful in Odisha like Kerala, Bhilwara (Rajasthan) and Dharabi (Mumbai) models are popular in India. However the present focused areas is Bhubaneswar Municipal Corporation which is worst affected hotspot areas for COVID19 in Odisha. Methodology: The search envisages collection of data of Ganjam, Bhubaneswar, Odisha and India day wise and analyzing the data statistically. The work includes preparing the adoptive model for Ganjam district and age wise. The age group and gender wise analysis of the COVID19 data of Bhubaneswar has been done along with finding the peaks of the outbreak curve in Odisha and the districts. Results: The micro level investigation revealed that male female confirmed case has a ratio of 67%:33%. The number cases is observed higher from age group is 15 to 41 years. Still the virus has proved causing more mortality to age group >60 in Odisha including Bhubaneswar. The children and women are the least prey to COVID19. The ACE 2 receptors are responsible for infection from SARSCoV2 virus. Ganjam model is one among the successful model to combat against COVID19 for the people of Odisha.

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Hamiltonian dynamics of the SIS epidemic model with stochastic fluctuations

Cited by 39 publications

References 56 publications

WITHDRAWN: Epidemic Big Bang: development and quarantine measures for Covid-19

WITHDRAWN: Epidemic Big Bang: development and quarantine measures for Covid-19

COVID-19 in India: State-wise Analysis and Prediction

Micro Level Search for COVID-19, Bhubaneswar: Odisha, India

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