A brief note on a multistrain SIR model with complete cross-protection and nonlinear force of infection

2021 ◽  
pp. 106001
Author(s):  
Hermann J Eberl ◽  
Harry J Gaebler ◽  
Yrjö T Gröhn
Keyword(s):  
Sir Model ◽  
Cross Protection ◽  
Force Of Infection ◽  
Nonlinear Force

scholarly journals The attainment of herd immunity with a reducing risk of contact infection in modelling 

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M Peariasamy ◽  
Hishamshah Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Herd Immunity ◽  
Sir Model ◽  
Mixed Population ◽  
Transmission Model ◽  
Force Of Infection ◽  
Initial Stage ◽  
And Control ◽  
Model Features

Abstract The risk of contact infection among susceptible individuals in a randomly mixed population can be reduced by the presence of immune individuals and this principle forms the fundamental of herd immunity. The conventional susceptible-infectious-recovered (SIR) model features an infection-induced herd immunity model, but does not include the reducing risk of contact infection among susceptible individuals in the transmission model, therefore tends to overestimate the transmission dynamics of infectious diseases. Here we show that the reducing risk of contact infection among susceptible individuals can be achieved by incorporating the proportion of susceptible individuals (model A) or the inverse of proportion of recovered individuals (model B) in the force of infection of the SIR model. We numerically simulated the conventional SIR model and both new SIR models A and B under the exact condition with a basic reproduction number of 3·0. Prior to the numerical simulation, the threshold for the eradication of infectious disease through herd immunity was expected to be 0·667 (66·7%) for all three models. All three models performed likewise at the initial stage of disease transmission. In the conventional SIR model, the infectious disease subsided when 94·0 % of the population had been infected and recovered, way above the expected threshold for eradication and control of the infectious disease. Both models A and B simulated the infectious disease to diminish when 66·7% and 75·6% of the population had been infected, showing herd immunity might protect more susceptible individuals from the infectious disease as compared to the projection generated by the conventional SIR. Our study shows that model A provides a better framework for modelling herd immunity through vaccination, while model B provides a better framework for modelling herd immunity through infection. Both models overcome the insufficiency of the conventional SIR model in attaining the effect of herd immunity in modelling outputs, which is important and relevant for modelling infectious disease, such as the COVID-19 in a randomly mixed population.

scholarly journals Predicting the early depleting transmission dynamics of COVID-19: A time-varying SIR model

2020 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M Peariasamy ◽  
Balvinder Singh Gill ◽  
Sarbhan Singh Lakha Singh ◽  
Bala Murali Sundram ◽  
...  
Keyword(s):  
Temporal Trends ◽  
Model Fitting ◽  
Sir Model ◽  
Transmission Dynamics ◽  
Time Varying ◽  
Force Of Infection ◽  
Planning And Control ◽  
The Mean ◽  
And Control ◽  
Absolute Percent Error

Abstract The susceptible-infectious-removed (SIR) model offers the simplest framework to study transmission dynamics of COVID-19, however, it does not factor in its early depleting trend observed during a lockdown. We modified the SIR model to specifically simulate the early depleting transmission dynamics of COVID-19 to better predict its temporal trend in Malaysia. The classical SIR model was fitted to observed total (I total), active (I), and removed (R) cases of COVID-19 before lockdown to estimate the basic reproduction number. Next, the model was modified with a partial time-varying force of infection, given by a proportionally depleting transmission coefficient, βt, and a fractional term, z. The modified SIR model was then fitted to observed data over 6 weeks during the lockdown. Model fitting and projection were validated using the mean absolute percent error (MAPE). The transmission dynamics of COVID-19 was interrupted immediately by the lockdown. The modified SIR model projected the depleting temporal trends with lowest MAPE for I total, followed by I, I daily, and R. During lockdown, the dynamics of COVID-19 depleted at a rate of 4·7% each day with a decreased capacity of 40%. For 7–day and 14–day projections, the modified SIR model accurately predicted I total, I, and R. The depleting transmission dynamics for COVID-19 during lockdown can be accurately captured by time-varying SIR model. Projection generated based on observed data is useful for future planning and control of COVID-19.

scholarly journals Tracking the early depleting transmission dynamics of COVID-19 with a time-varying SIR model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M. Peariasamy ◽  
Balvinder Singh Gill ◽  
Sarbhan Singh ◽  
Bala Murali Sundram ◽  
...  
Keyword(s):  
Temporal Trends ◽  
Model Fitting ◽  
Sir Model ◽  
Transmission Dynamics ◽  
Time Varying ◽  
Force Of Infection ◽  
Planning And Control ◽  
The Mean ◽  
And Control ◽  
Absolute Percent Error

AbstractThe susceptible-infectious-removed (SIR) model offers the simplest framework to study transmission dynamics of COVID-19, however, it does not factor in its early depleting trend observed during a lockdown. We modified the SIR model to specifically simulate the early depleting transmission dynamics of COVID-19 to better predict its temporal trend in Malaysia. The classical SIR model was fitted to observed total (I total), active (I) and removed (R) cases of COVID-19 before lockdown to estimate the basic reproduction number. Next, the model was modified with a partial time-varying force of infection, given by a proportionally depleting transmission coefficient, $$\beta_{t}$$ β t and a fractional term, z. The modified SIR model was then fitted to observed data over 6 weeks during the lockdown. Model fitting and projection were validated using the mean absolute percent error (MAPE). The transmission dynamics of COVID-19 was interrupted immediately by the lockdown. The modified SIR model projected the depleting temporal trends with lowest MAPE for I total, followed by I, I daily and R. During lockdown, the dynamics of COVID-19 depleted at a rate of 4.7% each day with a decreased capacity of 40%. For 7-day and 14-day projections, the modified SIR model accurately predicted I total, I and R. The depleting transmission dynamics for COVID-19 during lockdown can be accurately captured by time-varying SIR model. Projection generated based on observed data is useful for future planning and control of COVID-19.

scholarly journals Tracking the early depleting transmission dynamics of COVID-19 with a time-varying SIR model

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M Peariasamy ◽  
Balvinder Singh Gill ◽  
Sarbhan Singh Lakha Singh ◽  
Bala Murali Sundram ◽  
...  
Keyword(s):  
Temporal Trends ◽  
Model Fitting ◽  
Sir Model ◽  
Transmission Dynamics ◽  
Time Varying ◽  
Force Of Infection ◽  
Planning And Control ◽  
The Mean ◽  
And Control ◽  
Absolute Percent Error

Abstract The susceptible-infectious-removed (SIR) model offers the simplest framework to study transmission dynamics of COVID-19, however, it does not factor in its early depleting trend observed during a lockdown. We modified the SIR model to specifically simulate the early depleting transmission dynamics of COVID-19 to better predict its temporal trend in Malaysia. The classical SIR model was fitted to observed total (I total), active (I), and removed (R) cases of COVID-19 before lockdown to estimate the basic reproduction number. Next, the model was modified with a partial time-varying force of infection, given by a proportionally depleting transmission coefficient, βt, and a fractional term, z. The modified SIR model was then fitted to observed data over 6 weeks during the lockdown. Model fitting and projection were validated using the mean absolute percent error (MAPE). The transmission dynamics of COVID-19 was interrupted immediately by the lockdown. The modified SIR model projected the depleting temporal trends with lowest MAPE for I total, followed by I, I daily, and R. During lockdown, the dynamics of COVID-19 depleted at a rate of 4·7% each day with a decreased capacity of 40%. For 7–day and 14–day projections, the modified SIR model accurately predicted I total, I, and R. The depleting transmission dynamics for COVID-19 during lockdown can be accurately captured by time-varying SIR model. Projection generated based on observed data is useful for future planning and control of COVID-19.

scholarly journals IMPULSIVE CONTROL OF AN INTEGRATED PEST MANAGEMENT MODEL WITH DISPERSAL BETWEEN PATCHES

2010 ◽  
Vol 18 (03) ◽  
pp. 535-569 ◽  
Author(s):  
PAUL GEORGESCU ◽  
GABRIEL DIMITRIU ◽  
ROBERT SINCLAIR
Keyword(s):  
Biological Control ◽  
Integrated Pest Management ◽  
Pest Management ◽  
Floquet Theory ◽  
Impulsive Control ◽  
Abstract Form ◽  
Pest Population ◽  
Force Of Infection ◽  
Nonlinear Force ◽  
Si Model

We consider a two-patch SI model of integrated pest management with dispersal of both susceptible and infective pests between patches. A biological control, consisting of the periodic release of infective pests and a chemical control, consisting of periodic and impulsive pesticide spraying, are employed in order to maintain the size of the pest population below an economically acceptable level. It is assumed that the spread of the disease which is inflicted on the pest population through the use of the biological control is characterized by a nonlinear force of infection expressed in an abstract form. A sufficient condition for the local stability of the susceptible pest-eradication periodic solution is found using Floquet theory for periodic systems of ordinary differential equations, an analysis of the influence of dispersal between patches being performed for several particular cases. Our numerical simulations indicate that an increase in the amount but not in the frequency of pesticide use may not result in control. We also show that patches which are stable in isolation can be destabilized by dispersal between patches.

scholarly journals The attainment of herd immunity with reduced risk of contact infection in modelling

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M Peariasamy ◽  
Hishamshah Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Herd Immunity ◽  
Sir Model ◽  
Mixed Population ◽  
Reproduction Ratio ◽  
Force Of Infection ◽  
Population Immunity ◽  
Modelling Framework ◽  
And Control ◽  
Reduced Risk

Abstract The risk of contact infection among susceptible individuals in a randomly mixed population can be reduced by the presence of immune individuals and this concept is referred to as herd immunity1–3. The conventional susceptible-infectious-recovered (SIR) model does not feature a reduced risk of susceptible individuals in the transmission dynamics of infectious disease, therefore violates the fundamental of herd immunity4. Here we show that the reduced risk of contact infection among susceptible individuals in the SIR model can be attained by incorporating the proportion of susceptible individuals (model A) or the inverse of proportion of recovered individuals (model B) in the force of infection of the SIR model. We simulated the conventional SIR model and both new SIR models under the exact condition with a basic reproduction ratio of 3.0 and an expected herd immunity threshold of 0.667 (66.7%). All three models performed likewise at the initial stage of an epidemic. In the conventional SIR model, the epidemic continued until 94.0 % of the population had been infected and recovered, way above the threshold for eradication and control of the epidemic. Both models A and B simulated the epidemic waning when 66.7% and 75.6% of the population had been infected, as a result of the herd effect. As a result, model A provides a better framework for modelling vaccine-induced herd or population immunity, while model B provides a better framework for modelling infection-induced herd or population immunity. Our results demonstrate how the new modelling framework overcomes the drawback of the conventional SIR model and attain the effect of herd immunity in modelling outputs, which is important for modelling infectious disease in a randomly mixed population, especially for the COVID-19 pandemic.

scholarly journals The attainment of herd immunity with a restructured risk of contact infection in compartmental models

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M Peariasamy ◽  
Hishamshah Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Herd Immunity ◽  
Approximate Solutions ◽  
Sir Model ◽  
Compartmental Models ◽  
Mixed Population ◽  
Reproduction Ratio ◽  
Force Of Infection ◽  
Infection Dynamics ◽  
The Difference

Abstract Introduction: The risk of contact infection among susceptible individuals in a randomly mixed population can be reduced by the presence of immune individuals and this concept is referred to as herd immunity. Although herd immunity is observed in vaccinated populations for some infectious diseases, it has never been truly attained in compartmental models such as the susceptible-infectious-recovered (SIR) model. This paper introduces a new SIR framework to overcome the limitation of the conventional SIR model in attaining herd immunity.Methods: Two SIR models were newly developed based on the reduced risk of contact infection. The first model A assumes that the risk of contact infection reduces as soon as susceptible individuals are infected and move from class S(t) to I(t), therefore incorporating prevalence of both infectious and susceptible individuals into its force of infection. The second model B assumes the risk of contact infection would reduce after infected individuals have recovered from infection and move from class I(t) to R(t), therefore incorporating the prevalence of infectious and the inverse of prevalence of recovered individuals into its force of infection. Then, numerical simulations were applied to obtain approximate solutions for all three conventional SIR model, new SIR model A and model B for comparison under exact and arbitrary conditions with β = 0.3 and σ = 0.1 to mimic the infection dynamics with basic reproduction ratio (r0) of 3.0 and herd immunity threshold (HIT) of 0.667 (66.7%).Results and discussion: All three models performed likewise at the initial stage of the epidemic. The conventional SIR model simulated the epidemic diminishing when 94.0% of the population had been infected and recovered, way above its HIT. Model A simulated the epidemic waning when 66.7% of the population had been infected and recovered, in line with its HIT. However, the model conceptualized herd immunity incorrectly. Model B simulated the epidemic waning at 75.6%, slightly above its HIT and was more in line with the fundamental of herd immunity. The difference between model A and model B can be attributed to the proportion of infectious individuals, and this would increase in infectious disease with high transmissibility. The threshold theorem derived based on r0 may not be sufficient for optimal control and eradication of infectious disease with high transmissibility like the COVID-19.Conclusion: The newly developed SIR model that includes the inverse of proportion of recovered individuals into its force of infection is more accurate and credible for modelling infection with high transmissibility or vaccine-induced herd immunity in a randomly mixed population, especially in COVID-19.

scholarly journals The attainment of herd immunity with a restructured risk of contact infection in compartmental models

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M Peariasamy ◽  
Hishamshah Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Herd Immunity ◽  
Approximate Solutions ◽  
Sir Model ◽  
Compartmental Models ◽  
Mixed Population ◽  
Reproduction Ratio ◽  
Force Of Infection ◽  
Infection Dynamics ◽  
The Difference

Abstract Introduction: The risk of contact infection among susceptible individuals in a randomly mixed population can be reduced by the presence of immune individuals and this concept is referred as herd immunity. Although herd immunity is observed in vaccinated population for some infectious diseases, it has never been truly attained in compartmental models such as the susceptible-infectious-recovered (SIR) model. This paper introduces a new SIR framework to overcome the limitation of the conventional SIR model in attaining herd immunity.Methods: Two SIR models were newly developed based on the reduced risk of contact infection. The first model A assumes that the risk of contact infection reduces as soon as susceptible individuals are infected and move from class S(t) to I(t), therefore incorporating prevalence of both infectious and susceptible individuals into its force of infection. The second model B assumes the risk of contact infection would reduce after infected individuals have recovered from infection and move from class I(t) to R(t), therefore incorporating the prevalence of infectious and the inverse of prevalence of recovered individuals into its force of infection. Then, numerical simulations were applied to obtain approximate solutions for all three conventional SIR model, new SIR model A and model B for comparison under exact and arbitrary conditions with β = 0.3 and σ = 0.1 to mimic the infection dynamics with basic reproduction ratio (r0) of 3.0 and herd immunity threshold (HIT) of 0.667 (66.7%).Results and discussion: All three models performed likewise at the initial stage of epidemic. The conventional SIR model simulated the epidemic diminishing when 94.0% of the population had been infected and recovered, way above its HIT. Model A simulated the epidemic waning when 66.7% of the population had been infected and recovered, in line with its HIT, however, the model conceptualized the herd immunity incorrectly. Model B simulated the epidemic waning at 75.6%, slightly above its HIT and was in line with the fundamental of herd immunity. The difference between model A and model B can be attributed to the proportion of infectious individuals, and this would increase in infectious disease with high transmissibility. The threshold theorem derived based on r0 may not be sufficient for optimal control and eradication of infectious disease with high transmissibility like the COVID-19.Conclusion: The newly developed SIR model that includes the inverse of proportion of recovered individuals into its force of infection is more accurate and credible for modelling infection with high transmissibility or vaccine-induced herd immunity in a randomly mixed population, especially in COVID-19.

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