scholarly journals Modelling the impact of extended vaccination strategies on the epidemiology of pertussis

2011 ◽  
Vol 140 (8) ◽  
pp. 1503-1514 ◽  
Author(s):  
M. H. ROZENBAUM ◽  
R. De VRIES ◽  
H. H. LE ◽  
M. J. POSTMA
Keyword(s):  
Booster Dose ◽  
Deterministic Model ◽  
Natural Infection ◽  
Age Groups ◽  
Vaccination Strategy ◽  
Booster Vaccination ◽  
Sensitivity Analyses ◽  
Wide Range ◽  
Age Structured ◽  
The Impact

SUMMARYThe aim of this study was to investigate the optimal pertussis booster vaccination strategy for The Netherlands. A realistic age-structured deterministic model was designed. Assuming a steady-state situation and correcting for underreporting, the model was calibrated using notification data from the period 1996–2000. Several sensitivity analyses were performed to explore the impact of different assumptions for parameters surrounded by uncertainty (e.g. duration of protection after natural infection, underreporting factors, and transmission probabilities). The optimal age of an additional booster dose is in the range of 10–15 years, and implementation of this booster dose will reduce both symptomatic and asymptomatic infections, although the incidence of symptomatic infections in older age groups will increase. The impact of the different assumptions used in the model was in general limited. We conclude that over a wide range of assumptions, an additional booster dose can reduce the incidence of pertussis in the population.

scholarly journals Modelling pertussis transmission to evaluate the effectiveness of an adolescent booster in Argentina

2012 ◽  
Vol 141 (4) ◽  
pp. 718-734 ◽  
Author(s):  
G. FABRICIUS ◽  
P. E. BERGERO ◽  
M. E. ORMAZABAL ◽  
A. L. MALTZ ◽  
D. F. HOZBOR
Keyword(s):  
Booster Dose ◽  
Deterministic Model ◽  
Risk Group ◽  
Age Group ◽  
Vulnerable Group ◽  
Vaccination Strategies ◽  
Epidemiological Features ◽  
Age Structured ◽  
The Impact ◽  
Positive Effect

SUMMARYDue to the current epidemiological situation of pertussis, several countries have implemented vaccination strategies that include a booster dose for adolescents. Since there is still no evidence showing that the adolescent booster has a positive effect on the most vulnerable group represented by infants, it is difficult to universalize the recommendation to include such reinforcement. In this work we present an age-structured compartmental deterministic model that considers the outstanding epidemiological features of the disease in order to assess the impact of the booster dose at age 11 years (Tdap booster) to infants. To this end, we performed different parameterizations of the model that represent distinct possible epidemiological scenarios. The results obtained show that the inclusion of a single Tdap dose at age 11 years significantly reduces the incidence of the disease within this age group, but has a very low impact on the risk group (0–1 year). An effort to improve the coverage of the first dose would have a much greater impact on infants. These results hold in the 18 scenarios considered, which demonstrates the robustness of these conclusions.

THE IMPACT OF VACCINATION ON MALARIA PREVALENCE: A VACCINE-AGE-STRUCTURED MODELING APPROACH

2020 ◽  
Vol 28 (02) ◽  
pp. 475-513
Author(s):  
KATIA VOGT-GEISSE ◽  
CALISTUS N. NGONGHALA ◽  
ZHILAN FENG
Keyword(s):  
Booster Dose ◽  
Deterministic Model ◽  
Vaccine Dose ◽  
Threshold Value ◽  
Disease Prevalence ◽  
Control Measures ◽  
Disease Eradication ◽  
Vaccination Programs ◽  
Age Structured ◽  
The Impact

A deterministic model for the effects on disease prevalence of the most advanced pre-erythrocytic vaccine against malaria is proposed and studied. The model includes two vaccinated classes that correspond to initially vaccinated and booster dose vaccinated individuals. These two classes are structured by time-since-initial-vaccination (vaccine-age). This structure is a novelty for vector–host models; it allows us to explore the effects of parameters that describe timed and delayed delivery of a booster dose, and immunity waning on disease prevalence. Incorporating two vaccinated classes can predict more accurately threshold vaccination coverages for disease eradication under multi-dose vaccination programs. We derive a vaccine-age-structured control reproduction number [Formula: see text] and establish conditions for the existence and stability of equilibria to the system. The model is bistable when [Formula: see text]. In particular, it exhibits a backward (sub-critical) bifurcation, indicating that [Formula: see text] is no longer the threshold value for disease eradication. Thus, to achieve eradication we must identify and implement control measures that will reduce [Formula: see text] to a value smaller than unity. Therefore, it is crucial to be cautious when using [Formula: see text] to guide public health policy, although it remains a key quantity for decision making. Our results show that if the booster vaccine dose is administered with delay, individuals may not acquire its full protective effect, and that incorporating waning efficacy into the system improves the accuracy of the model outcomes. This study suggests that it is critical to follow vaccination schedules closely, and anticipate the consequences of delays in those schedules.

scholarly journals Measuring the impact of COVID-19 vaccination and immunity waning: a modelling study for Portugal

2021 ◽  
Author(s):  
Constantino Caetano ◽  
Maria Luisa Morgado ◽  
Paula Patricio ◽  
Andreia Leite ◽  
Ausenda Machado ◽  
...  
Keyword(s):  
Deterministic Model ◽  
Vaccination Strategy ◽  
Booster Vaccination ◽  
Vaccine Effectiveness ◽  
Disease Spread ◽  
Peak Reduction ◽  
Substantial Impact ◽  
Control Disease ◽  
Lower Magnitude ◽  
The Impact

Vaccination strategies to control COVID-19 have been ongoing worldwide since the end of 2020. Understanding their possible effect is key to prevent future disease spread. Using a modelling approach, this study intends to measure the impact of the COVID-19 Portuguese vaccination strategy on the effective reproduction number and explore three scenarios for vaccine effectiveness waning. Namely, the no-immunity-loss, 1-year and 3-years of immunity duration scenarios. We adapted an age-structured SEIR deterministic model and used Portuguese hospitalisation data for the model calibration. Results show that, although the Portuguese vaccination plan had a substantial impact in reducing overall transmission, it might not be sufficient to control disease spread. A significant vaccination coverage of those above 5 years old, a vaccine effectiveness against disease of at least 80% and softer non-pharmaceutical interventions (NPIs), such as mask usage and social distancing, would be necessary to control disease spread in the worst scenario considered. The immunity duration scenario of 1-year displays a resurgence of COVID-19 hospitalisations by the end of 2021, the same is observed in 3-year scenario although with a lower magnitude. The no-immunity-loss scenario presents a low increase in hospitalisations. In both the 1-year and 3-year scenarios, a vaccination boost of those above 65 years old would result in a 53% and 38% peak reduction of non-ICU hospitalisations, respectively. These results suggest that NPIs should not be fully phased-out but instead be combined with a fast booster vaccination strategy to reduce healthcare burden.

scholarly journals Age-Structured Model for COVID-19: Effectiveness of Social Distancing and Contact Reduction

2020 ◽  
Author(s):  
Mark Kimathi ◽  
Samuel Mwalili ◽  
Viona Ojiambo ◽  
Duncan Gathungu
Keyword(s):  
Deterministic Model ◽  
Age Groups ◽  
School Closure ◽  
Model Parameters ◽  
Suitable Model ◽  
Age Group ◽  
Social Distancing ◽  
First Case ◽  
Age Structured ◽  
The Impact

Abstract Background: Coronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2. The disease has spread to almost every country in the world. Kenya reported its first case on 13th of March 2020. From 16th March 2020, the country instituted various social distancing strategies to reduce the transmission and flatten the epidemic curve. These strategies include school closure, dusk-to-dawn curfew, and travel restriction across counties, especially Nairobi, Mombasa and Kwale. An age-structured compartmental model was developed to assess the impact of non-pharmaceutical interventions on severity of infections, hospital demands and deaths. Methods: The population is divided into four age-groups and for each age-group there are seven compartments, namely: susceptible , exposed, asymptomatic, mild, severe, critical, death and recovered. The contact matrices between the different ages are integrated into an age-structured deterministic model via the force of infection. This model is represented by ordinary differential equations and solved using Runge–Kutta methods, with suitable model parameters. Simulation results for the unmitigated and mitigated scenarios were depicted, for the different age-groups. Results: The 45% reduction in contacts for 60-days period resulted to between 11.5-13% reduction of infections severity and deaths, while for the 190-days period yielded between 18.8-22.7% reduction. The peak of infections in the 60-days mitigation was higher and happened about 2 months after the relaxation of mitigation as compared to that of the 190-days mitigation, which happened just a month after mitigation were relaxed. Low numbers of cases in children under 15 years was attributed to low susceptibility of persons in this age-group. High numbers of cases are reported in the 15-29 years and 30-59 years age bands since these individuals have wider interaction spheres, and they form a significant percentage of Kenya population. Conclusion: Two mitigation periods, considered in the study, resulted to reductions in severe and critical cases, attack rates, hospital and ICU bed demands, as well as deaths, with the 190-days period giving higher reductions. The study revealed the age-dependency of the key health outputs.

scholarly journals Evaluating COVID-19 booster vaccination strategies in a partially vaccinated population: a modeling study.

2021 ◽  
Author(s):  
Clement R Massonnaud ◽  
Jonathan Roux ◽  
Vittoria Colizza ◽  
Pascal Crepey
Keyword(s):  
Age Groups ◽  
Booster Vaccination ◽  
Primary Vaccination ◽  
Morbidity And Mortality ◽  
Vaccination Strategies ◽  
Admission Data ◽  
Younger Age ◽  
Age Structured ◽  
Vaccination Campaigns ◽  
The Impact

Background. As evidence shows that vaccine immunity to COVID-19 wanes with time and decreases due to variants, several countries are implementing booster vaccination campaigns. The objective of this study was to analyze the morbidity and mortality burdens of different primary and booster vaccination strategies against COVID-19, using France as a case study. Methods. We used a deterministic, age-structured, compartmental model fitted to hospital admission data and validated against sero-prevalence data in France to analyze the impact of primary and booster vaccination strategies on morbidity and mortality assuming waning of immunity and increased virus transmissibility during winter. Findings. Strategies prioritizing primary vaccinations were systematically more effective than strategies prioritizing boosters. Regarding booster strategies targeting different age groups, their effectiveness varied with the levels of virus transmissibility, and according to the assumed loss of immunity for each age group. If the immunity reduction affects all age groups, people aged 30 to 49 years should be boosted in priority, even for low transmissibility levels. If the immunity reduction is restricted to people older than 65 years, boosting younger people becomes effective only above certain levels of transmissibility. Interpretation. Increasing the primary vaccination coverage should remain a priority to reduce morbidity and mortality due to COVID-19. If a plateau of primary vaccination has been reached, boosting immunity in younger age-groups could prevent more hospitalizations and deaths than boosting the immunity of older people, especially under conditions increasing SARS-CoV-2 transmissibility, or when facing new variants. Funding. The study was partially funded by the French national research agency through project SPHINX-17-CE36-0008-0.

scholarly journals Estimating the mortality caused by great cormorant predation on fish stocks: pikeperch in the Archipelago Sea, northern Baltic Sea, as an example

2016 ◽  
Vol 73 (1) ◽  
pp. 84-93 ◽  
Author(s):  
Outi Heikinheimo ◽  
Pekka Rusanen ◽  
Katja Korhonen
Keyword(s):  
Age Groups ◽  
Total Mortality ◽  
Sensitivity Analyses ◽  
Fish Stock ◽  
Great Cormorant ◽  
Phalacrocorax Carbo ◽  
Fish Stocks ◽  
Archipelago Sea ◽  
Phalacrocorax Carbo Sinensis ◽  
The Impact

Estimates of the mortality rates caused by cormorants are needed to assess the impact on fish stock dynamics and fisheries. In this study, we calculated the annual instantaneous mortality caused by great cormorants (Phalacrocorax carbo sinensis) on young pikeperch (Sander lucioperca), using data from Archipelago Sea, southwestern coast of Finland. The pikeperch are vulnerable to cormorant predation mainly at the ages 2–4. The annual instantaneous mortality caused by cormorants was between 0.04 and 0.13, and the estimated effect on the pikeperch stock size at recruitment to the fishery ranged from 4% to 23%, respectively. The average annual cormorant-induced mortality accounted for 5%–34% of the total mortality in these age groups. The sensitivity analyses proved that the rates of mortality from other sources largely affect the estimated mortality from cormorant predation. In cases with strong fluctuations in the abundance of the prey fish stocks, ignoring the size and density dependence of the natural mortality may lead to overestimation of the importance of cormorants as competitors of fisheries.

scholarly journals Contact surveys reveal heterogeneities in age-group contributions to SARS-CoV-2 dynamics in the United States

2021 ◽  
Author(s):  
Taylor Chin ◽  
Dennis M. Feehan ◽  
Caroline O. Buckee ◽  
Ayesha S. Mahmud
Keyword(s):  
United States ◽  
Age Groups ◽  
The United States ◽  
Contact Rate ◽  
Age Group ◽  
Contact Rates ◽  
Contact Patterns ◽  
Age Structured ◽  
The Impact ◽  
Over Time

SARS-CoV-2 is spread primarily through person-to-person contacts. Quantifying population contact rates is important for understanding the impact of physical distancing policies and for modeling COVID-19, but contact patterns have changed substantially over time due to shifting policies and behaviors. There are surprisingly few empirical estimates of age-structured contact rates in the United States both before and throughout the COVID-19 pandemic that capture these changes. Here, we use data from six waves of the Berkeley Interpersonal Contact Survey (BICS), which collected detailed contact data between March 22, 2020 and February 15, 2021 across six metropolitan designated market areas (DMA) in the United States. Contact rates were low across all six DMAs at the start of the pandemic. We find steady increases in the mean and median number of contacts across these localities over time, as well as a greater proportion of respondents reporting a high number of contacts. We also find that young adults between ages 18 and 34 reported more contacts on average compared to other age groups. The 65 and older age group consistently reported low levels of contact throughout the study period. To understand the impact of these changing contact patterns, we simulate COVID-19 dynamics in each DMA using an age-structured mechanistic model. We compare results from models that use BICS contact rate estimates versus commonly used alternative contact rate sources. We find that simulations parameterized with BICS estimates give insight into time-varying changes in relative incidence by age group that are not captured in the absence of these frequently updated estimates. We also find that simulation results based on BICS estimates closely match observed data on the age distribution of cases, and changes in these distributions over time. Together these findings highlight the role of different age groups in driving and sustaining SARS-CoV-2 transmission in the U.S. We also show the utility of repeated contact surveys in revealing heterogeneities in the epidemiology of COVID-19 across localities in the United States.

scholarly journals Mathematical modeling of vaccination rollout and NPIs lifting on COVID-19 transmission with VOC: a case study in Toronto, Canada

2021 ◽  
Author(s):  
Elena Aruffo ◽  
Pei Yuan ◽  
Yi Tan ◽  
Evgenia Gatov ◽  
Iain Moyles ◽  
...  
Keyword(s):  
Vaccination Coverage ◽  
Age Groups ◽  
Vaccination Strategy ◽  
The Elderly ◽  
Public Health Agencies ◽  
Initial Strategy ◽  
Working Age ◽  
Waning Immunity ◽  
Nonpharmaceutical Interventions ◽  
The Impact

ABSTRACT Background: Since December 2020, public health agencies have implemented a variety of vaccination strategies to curb the spread of SARS-CoV-2, along with pre-existing Nonpharmaceutical Interventions (NPIs). Initial strategy focused on vaccinating the elderly to prevent hospitalizations and deaths. With vaccines becoming available to the broader population, we aimed to determine the optimal strategy to enable the safe lifting of NPIs while avoiding virus resurgence. Methods: We developed a compartmental deterministic SEIR model to simulate the lifting of NPIs under different vaccination rollout scenarios. Using case and vaccination data from Toronto, Canada between December 28, 2020 and May 19, 2021, we estimated transmission throughout past stages of NPI escalation/relaxation to compare the impact of lifting NPIs on different dates on cases, hospitalizations, and deaths, given varying degrees of vaccine coverages by 20-year age groups, accounting for waning immunity. Results: We found that, once coverage among the elderly is high enough (80% with at least one dose), the main age groups to target are 20-39 and 40-59 years, whereby first-dose coverage of at least 70% by mid-June 2021 is needed to minimize the possibility of resurgence if NPIs are to be lifted in the summer. While a resurgence was observed for every scenario of NPI lifting, we also found that under an optimistic vaccination coverage (70% by mid-June, postponing reopening from August 2021 to September 2021can reduce case counts and severe outcomes by roughly 80% by December 31, 2021. Conclusions: Our results suggest that focusing the vaccination strategy on the working-age population can curb the spread of SARS-CoV-2. However, even with high vaccination coverage in adults, lifting NPIs to pre-pandemic levels is not advisable since a resurgence is expected to occur, especially with earlier reopening.

The cost-effectiveness of patient-applied treatments for anogenital warts

2003 ◽  
Vol 14 (4) ◽  
pp. 228-234 ◽  
Author(s):  
Paul Williams ◽  
Geo von Krogh
Keyword(s):  
Cost Effectiveness ◽  
Health Service ◽  
Drug Acquisition ◽  
Sensitivity Analyses ◽  
Controlled Trials ◽  
Anogenital Warts ◽  
Health Service Provider ◽  
Wide Range ◽  
The Cost ◽  
The Impact

A model was developed to estimate the cost-effectiveness of podophyllotoxin and imiquimod for self-treatment of anogenital warts. The effectiveness endpoint was sustained clearance after treatment and a subsequent follow-up period of approximately 12 weeks. Effectiveness of podophyllotoxin was estimated from a quantitative summary of nine placebo-controlled trials, while effectiveness of imiquimod was based on a quantitative summary of six placebo-controlled trials. Costs were considered from a UK health service provider perspective; drug acquisition costs were obtained from the British National Formulary and health service costs of clinic attendance were based on a recent survey of GUM clinics. The impact of uncertainty was explored in a wide range of one-way and probabilistic (multi-way) sensitivity analyses. The cost per sustained clearance was 313 for podophyllotoxin and 606 for imiquimod. The modest and statistically insignificant incremental effectiveness of imiquimod was purchased at high cost—2476 per additional sustained clearance. Sensitivity analyses showed the economic superiority of podophyllotoxin to be robust and statistically very significant.

scholarly journals Assessment of Social Distancing for Controlling COVID-19 in Korea: An Age-Structured Modeling Approach

2020 ◽  
Vol 17 (20) ◽  
pp. 7474
Author(s):  
Yongin Choi ◽  
James Slghee Kim ◽  
Heejin Choi ◽  
Hyojung Lee ◽  
Chang Hyeong Lee
Keyword(s):  
Mathematical Model ◽  
Age Groups ◽  
Epidemiological Data ◽  
The Elderly ◽  
Model Parameters ◽  
Social Distancing ◽  
First Case ◽  
Age Structured ◽  
Epidemiological Characteristics ◽  
The Impact

The outbreak of the novel coronavirus disease 2019 (COVID-19) occurred all over the world between 2019 and 2020. The first case of COVID-19 was reported in December 2019 in Wuhan, China. Since then, there have been more than 21 million incidences and 761 thousand casualties worldwide as of 16 August 2020. One of the epidemiological characteristics of COVID-19 is that its symptoms and fatality rates vary with the ages of the infected individuals. This study aims at assessing the impact of social distancing on the reduction of COVID-19 infected cases by constructing a mathematical model and using epidemiological data of incidences in Korea. We developed an age-structured mathematical model for describing the age-dependent dynamics of the spread of COVID-19 in Korea. We estimated the model parameters and computed the reproduction number using the actual epidemiological data reported from 1 February to 15 June 2020. We then divided the data into seven distinct periods depending on the intensity of social distancing implemented by the Korean government. By using a contact matrix to describe the contact patterns between ages, we investigated the potential effect of social distancing under various scenarios. We discovered that when the intensity of social distancing is reduced, the number of COVID-19 cases increases; the number of incidences among the age groups of people 60 and above increases significantly more than that of the age groups below the age of 60. This significant increase among the elderly groups poses a severe threat to public health because the incidence of severe cases and fatality rates of the elderly group are much higher than those of the younger groups. Therefore, it is necessary to maintain strict social distancing rules to reduce infected cases.

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