scholarly journals Calibrating an SIR model for South Korea COVID-19 infections and predicting vaccination impact

2021 ◽  
Author(s):  
Brandon Pae
Keyword(s):  
South Korea ◽  
Vaccination Coverage ◽  
Herd Immunity ◽  
Sir Model ◽  
Transmission Dynamics ◽  
Effective Vaccine ◽  
Epidemiological Models ◽  
Policy Decisions

In the span of 1.5 years, COVID-19 has caused more than 4 million deaths worldwide. To prevent such a catastrophe from reoccurring, it is necessary to test and refine current epidemiological models that impact policy decisions. Thus, we developed a deterministic SIR model to examine the long-term transmission dynamics of COVID-19 in South Korea. Using this model, we analyzed how vaccines would affect the number of cases. We found that a 70% vaccination coverage with a 100% effective vaccine would effectively eliminate the number of cases and herd immunity would have been obtained approximately 85 days after February 15 had there not been a reintroduction of cases.

Calibrating an SIR model for South Korea COVID-19 infections and predicting vaccination impact (Preprint)

2021 ◽  
Author(s):  
Brandon Pae
Keyword(s):  
South Korea ◽  
Vaccination Coverage ◽  
Herd Immunity ◽  
Sir Model ◽  
Transmission Dynamics ◽  
Effective Vaccine ◽  
Epidemiological Models ◽  
Policy Decisions

UNSTRUCTURED In the span of 1.5 years, COVID-19 has caused more than 4 million deaths worldwide. To prevent such a catastrophe from reoccurring, it is necessary to test and refine current epidemiological models that impact policy decisions. Thus, we developed a deterministic SIR model to examine the long-term transmission dynamics of COVID-19 in South Korea. Using this model, we analyzed how vaccines would affect the number of cases. We found that a 70% vaccination coverage with a 100% effective vaccine would effectively eliminate the number of cases and herd immunity would have been obtained approximately 85 days after February 15 had there not been a reintroduction of cases.

scholarly journals Inducing Herd Immunity against Seasonal Influenza in Long-Term Care Facilities through Employee Vaccination Coverage: A Transmission Dynamics Model

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Aaron M. Wendelboe ◽  
Carl Grafe ◽  
Micah McCumber ◽  
Michael P. Anderson
Keyword(s):  
New Mexico ◽  
Vaccination Coverage ◽  
Long Term Care ◽  
Herd Immunity ◽  
Surveillance Data ◽  
Transmission Dynamics ◽  
Dynamics Model ◽  
Term Care ◽  
Care Facilities

Introduction. Vaccinating healthcare workers (HCWs) in long-term care facilities (LTCFs) may effectively induce herd immunity and protect residents against influenza-related morbidity and mortality. We used influenza surveillance data from all LTCFs in New Mexico to validate a transmission dynamics model developed to investigate herd immunity induction.Material and Methods. We adjusted a previously published transmission dynamics model and used surveillance data from an active system among 76 LTCFs in New Mexico during 2006-2007 for model validation. We used a deterministic compartmental model with a stochastic component for transmission between residents and HCWs in each facility in order to simulate the random variation expected in such populations.Results. When outbreaks were defined as a dichotomous variable, our model predicted that herd immunity could be induced. When defined as an attack rate, the model demonstrated a curvilinear trend, but insufficiently strong to induce herd immunity. The model was sensitive to changes in the contact parameterβbut was robust to changes in the visitor contact probability.Conclusions. These results further elucidate previous studies’ findings that herd immunity may not be induced by vaccinating HCWs in LTCFs; however, increased influenza vaccination coverage among HCWs reduces the probability of influenza infection among residents.

scholarly journals Long-term and herd immunity against SARS-CoV-2: implications from current and past knowledge

2020 ◽  
Vol 78 (3) ◽  
Author(s):  
Eleni Papachristodoulou ◽  
Loukas Kakoullis ◽  
Konstantinos Parperis ◽  
George Panos
Keyword(s):  
Immune Response ◽  
Herd Immunity ◽  
Effective Vaccine ◽  
Natural Immunity ◽  
Infection Rates ◽  
Mutant Strains ◽  
Current Infection ◽  
The Stability ◽  
Urgent Necessity

ABSTRACT Effective herd immunity against SARS-CoV-2 will be determined on many factors: the percentage of the immune population, the length and effectiveness of the immune response and the stability of the viral epitopes. The required percentage of immune individuals has been estimated to be 50–66% of the population which, given the current infection rates, will take long to be achieved. Furthermore, data from SARS-CoV suggest that the duration of immunity may not be sufficiently significant, while the immunity response against SARS-CoV-2 may not be efficiently effective in all patients, as relapses have already been reported. In addition, the development of mutant strains, which has already been documented, can cause the reemergence of the epidemic. In conclusion, the development of an effective vaccine is an urgent necessity, as long-term natural immunity to SARS-CoV-2 may not be sufficient for the control of the current and future outbreaks.

scholarly journals Modelling infectious diseases with herd immunity in a randomly mixed population

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M. Peariasamy ◽  
Hishamshah Mohd. Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Transmission Rate ◽  
Herd Immunity ◽  
Sir Model ◽  
Mixed Population ◽  
Transmission Dynamics ◽  
Transmission Model ◽  
Infection Model ◽  
Vaccination Rates

Abstract Background The conventional susceptible-infectious-recovered (SIR) model tends to overestimate the transmission dynamics of infectious diseases and ends up with total infections and total immunized population exceeding the threshold required for control and eradication of infectious diseases. The study aims to overcome the limitation by allowing the transmission rate of infectious disease to decline along with the reducing risk of contact infection. Methods Two new SIR models were developed to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A mimicked the declining transmission rate along with the reducing risk of transmission following infection, while Model B mimicked the declining transmission rate following recovery. Then, the conventional SIR model, Model A and Model B were used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. The infectious disease was expected to be controlled or eradicated when the total immunized population either through infection or vaccination reached the level predicted by the HIT. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations. Findings All three models performed likewise at the beginning of the transmission when sizes of infectious and recovered were relatively small as compared with the population size. The infectious disease modelled using the conventional SIR model appeared completely out of control even when the HIT was achieved in all scenarios with and without vaccination. The infectious disease modelled using Model A appeared to be controlled at the level predicted by the HIT in all scenarios with and without vaccination. Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. At lower vaccination rates or without vaccination, the level at which the infectious disease was controlled cannot be accurately predicted by the HIT. Conclusion Transmission dynamics of infectious diseases with herd immunity can accurately be modelled by allowing the transmission rate of infectious disease to decline along with the combined risk of contact infection. Model B provides a more credible framework for modelling infectious diseases with herd immunity in a randomly mixed population.

scholarly journals Modelling infectious diseases with herd immunity in a randomly mixed population

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M Peariasamy ◽  
Hishamshah Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Transmission Rate ◽  
Herd Immunity ◽  
Sir Model ◽  
Mixed Population ◽  
Transmission Dynamics ◽  
Transmission Model ◽  
Infection Model ◽  
Vaccination Rates

Abstract Background The conventional susceptible-infectious-recovered (SIR) model tends to overestimate transmission dynamics of infectious diseases and ends up with total infections exceeding the threshold required for control and eradication of infectious diseases. The study aims to overcome the limitation by allowing the transmission rate of infectious disease to decline along with the reducing risk of contact infection. MethodsTwo new SIR models were developed to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A mimicked the declining transmission rate along with the reducing risk of transmission following infection, while Model B mimicked the declining transmission rate following recovery. Then, the conventional SIR model, Model A and Model B were used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. The infectious disease was expected to be controlled or eradicated when the total immunized population either through infection or vaccination reached the level predicted by the HIT. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations.Findings All three models performed likewise at the beginning of transmission when sizes of infectious and recovered were relatively small as compared with the population size. The infectious disease modelled using the conventional SIR model appeared completely out of control even when the HIT was achieved in all scenarios with and without vaccination. The infectious disease modelled using Model A appeared to be controlled at the level predicted by the HIT in all scenarios with and without vaccination. Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. At lower vaccination rates or without vaccination, the level at which the infectious disease was controlled cannot be accurately predicted by the HIT. ConclusionTransmission dynamics of infectious diseases with herd immunity can accurately be modelled by allowing the transmission rate of infectious disease to decline along with the combined risk of contact infection. Model B provides a more realistic framework for modelling infectious diseases with herd immunity in a randomly mixed population.

scholarly journals National interest may require distributing COVID-19 vaccines to other countries

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tiziano Rotesi ◽  
Paolo Pin ◽  
Maria Cucciniello ◽  
Amyn A. Malik ◽  
Elliott E. Paintsil ◽  
...  
Keyword(s):  
United States ◽  
Quantitative Analysis ◽  
Vaccination Coverage ◽  
Herd Immunity ◽  
The United States ◽  
Sir Model ◽  
Sharp Reduction ◽  
Trade Offs ◽  
Self Interest ◽  
The Us

AbstractAs immunization campaigns are accelerating, understanding how to distribute the scarce doses of vaccines is of paramount importance and a quantitative analysis of the trade-offs involved in domestic-only versus cooperative distribution is still missing. In this study we use a network Susceptible-Infected-Removed (SIR) model to show circumstances under which it is in a country’s self-interest to ensure other countries can obtain COVID-19 vaccines rather than focusing only on vaccination of their own residents. In particular, we focus our analysis on the United States and estimate the internal burden of COVID-19 disease under different scenarios about vaccine cooperation. We show that in scenarios in which the US has reached the threshold for domestic herd immunity, the US may find it optimal to donate doses to other countries with lower vaccination coverage, as this would allow for a sharp reduction in the inflow of infected individuals from abroad.

scholarly journals Steep decline of HPV 6 and genital warts despite low HPV vaccination coverage in young women in Germany: a long-term, population-based cohort study

2019 ◽  
Author(s):  
Agnieszka Denecke ◽  
Thomas Iftner ◽  
Angelika Iftner ◽  
Sebastian Riedle ◽  
Marion Ocak ◽  
...  
Keyword(s):  
Protective Effect ◽  
Young Women ◽  
Vaccination Coverage ◽  
Hpv Vaccination ◽  
Herd Immunity ◽  
Life Time ◽  
Genital Warts ◽  
Quadrivalent Vaccine ◽  
Vaccination Rates

Abstract Background: The introduction of human papilloma virus (HPV) vaccination has resulted in a remarkable decline of genital warts in women and men, but in Germany historical rates of vaccination are relatively low. We report long-term surveillance data on changes in HPV 6 and 11 infection and the prevalence of genital warts in young women in the Wolfsburg HPV epidemiological study (WOLVES).Methods: Women born in 1983/84, 1988/89, and 1993/94 participated in four cohorts between 2009/10 and 2014/15. Vaccination coverage and prevalence of HPV 6/11 and genital warts are reported for participants aged 19−22 years and 24−27 years at the time of analysis. Statistical analyses were done to compare similarly aged participants using 2 x 2 contingency tables (Röhmel-Mansmann unconditional exact test; two-side alpha of 0.05).Results: A total of 2,456 women were recruited. In 2010, vaccination rates were 40/659 (6.1%) in women aged 24−27 years and 142/600 (23.7%) in those aged 19−22 years; 5 years later, vaccination rates had increased to 135/733 (18.4%) and 177/368 (48.1%), respectively. Between 2010 and 2015, there was a statistically significant decrease in the prevalence of HPV 6 among women aged 24−27 years (2.12% versus 0%; P<0.0001) and women aged 19−22 years (2.0% versus 0%; P=0.0056). In total, 52 of 2341 participants were diagnosed with genital warts. There was a statistically significant decrease in the life-time risk of developing genital warts in women aged 24−27 years between 2010 and 2015 (4.7% versus 1.68%, respectively; P=0.0018). The overall life-time risk of developing genital warts in women aged 19−27 years decreased from 3.1% in 2010 to 1.2% in 2015 (P=0.0022).Conclusions: An increase in vaccination coverage was associated with a decreased prevalence of genital warts in young women. A protective effect greater than herd immunity alone was seen despite low vaccination rates. Quadrivalent vaccine had a protective effect on genital HPV 6 positivity and a fully protective effect on the development of genital warts in the youngest population.

scholarly journals Counting the Costs of COVID-19: Why Future Treatment Option Values Matter

2020 ◽  
Vol 7 (6) ◽  
pp. 36
Author(s):  
Adrian Kent
Keyword(s):  
Herd Immunity ◽  
Life Quality ◽  
Quality Adjusted Life Year ◽  
Recent Analysis ◽  
Effective Vaccine ◽  
Medical Interventions ◽  
Social Interventions ◽  
The United Kingdom ◽  
Cast Doubt

I critique a recent analysis (Miles, Stedman & Heald, 2020) of COVID-19 lockdown costs and benefits, focussing on the United Kingdom (UK). Miles et al. (2020) argue that the March-June UK lockdown was more costly than the benefit of lives saved, evaluated using the NICE threshold of £30000 for a quality-adjusted life year (QALY) and that the costs of a lockdown for 13 weeks from mid-June would be vastly greater than any plausible estimate of the benefits, even if easing produced a second infection wave causing over 7000 deaths weekly by mid-September.   I note here two key problems that significantly affect their estimates and cast doubt on their conclusions. Firstly, their calculations arbitrarily cut off after 13 weeks, without costing the epidemic end state. That is, they assume indifference between mid-September states of 13 or 7500 weekly deaths and corresponding infection rates. This seems indefensible unless one assumes that (a) there is little chance of any effective vaccine or improved medical or social interventions for the foreseeable future, (b) notwithstanding temporary lockdowns, COVID-19 will very likely propagate until herd immunity. Even under these assumptions it is very questionable. Secondly, they ignore the costs of serious illness, possible long-term lowering of life quality and expectancy for survivors. These are uncertain, but plausibly at least as large as the costs in deaths.In summary, policy on tackling COVID-19 cannot be rationally made without estimating probabilities of future medical interventions and long-term illness costs. More work on modelling these uncertainties is urgently needed.

scholarly journals Modelling infectious diseases with herd immunity in a randomly mixed population

2021 ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M. Peariasamy ◽  
Hishamshah Mohd. Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Transmission Rate ◽  
Herd Immunity ◽  
Sir Model ◽  
Mixed Population ◽  
Transmission Dynamics ◽  
Transmission Model ◽  
Infection Model ◽  
Vaccination Rates

Abstract Background The conventional susceptible-infectious-recovered (SIR) model tends to overestimate the transmission dynamics of infectious diseases and ends up with total infections and total immunized population exceeding the threshold required for control and eradication of infectious diseases. The study aims to overcome the limitation by allowing the transmission rate of infectious disease to decline along with the reducing risk of contact infection. Methods Two new SIR models were developed to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A mimicked the declining transmission rate along with the reducing risk of transmission following infection, while Model B mimicked the declining transmission rate following recovery. Then, the conventional SIR model, Model A and Model B were used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. The infectious disease was expected to be controlled or eradicated when the total immunized population either through infection or vaccination reached the level predicted by the HIT. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations.Findings All three models performed likewise at the beginning of the transmission when sizes of infectious and recovered were relatively small as compared with the population size. The infectious disease modelled using the conventional SIR model appeared completely out of control even when the HIT was achieved in all scenarios with and without vaccination. The infectious disease modelled using Model A appeared to be controlled at the level predicted by the HIT in all scenarios with and without vaccination. Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. At lower vaccination rates or without vaccination, the level at which the infectious disease was controlled cannot be accurately predicted by the HIT. Conclusion Transmission dynamics of infectious diseases with herd immunity can accurately be modelled by allowing the transmission rate of infectious disease to decline along with the combined risk of contact infection. Model B provides a more credible framework for modelling infectious diseases with herd immunity in a randomly mixed population.

scholarly journals Modelling infectious diseases with herd immunity in a randomly mixed population

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kian Boon Law ◽  
Kalaiarasu M. Peariasamy ◽  
Hishamshah Mohd Ibrahim ◽  
Noor Hisham Abdullah
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Transmission Rate ◽  
Herd Immunity ◽  
The United States ◽  
Sir Model ◽  
Mixed Population ◽  
Transmission Dynamics ◽  
Vaccination Rates ◽  
Reduced Risk

AbstractThe conventional susceptible-infectious-recovered (SIR) model tends to magnify the transmission dynamics of infectious diseases, and thus the estimated total infections and immunized population may be higher than the threshold required for infection control and eradication. The study developed a new SIR framework that allows the transmission rate of infectious diseases to decline along with the reduced risk of contact infection to overcome the limitations of the conventional SIR model. Two new SIR models were formulated to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A utilized the declining transmission rate along with the reduced risk of contact infection following infection, while Model B incorporated the declining transmission rate following recovery. Both new models and the conventional SIR model were then used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations. Further, all three models were used to simulate the transmission dynamics of seasonal influenza in the United States and disease burdens were projected and compared with estimates from the Centers for Disease Control and Prevention. For the simulated infectious disease, in the initial phase of the outbreak, all three models performed expectedly when the sizes of infectious and recovered populations were relatively small. As the infectious population increased, the conventional SIR model appeared to overestimate the infections even when the HIT was achieved in all scenarios with and without vaccination. For the same scenario, Model A appeared to attain the level predicted by the HIT and in comparison, Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. For infectious diseases with high r0, and at low vaccination rates, the level at which the infectious disease was controlled cannot be accurately predicted by the current theorem. Transmission dynamics of infectious diseases with herd immunity can be accurately modelled by allowing the transmission rate of infectious diseases to decline along with the reduction of contact infection risk after recovery or vaccination. Model B provides a credible framework for modelling infectious diseases with herd immunity in a randomly mixed population.

Sign in / Sign up

Export Citation Format

Share Document