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

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.

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

Epidemiology and Infection ◽

10.1017/s0950268811002354 ◽

2011 ◽

Vol 140 (8) ◽

pp. 1503-1514 ◽

Cited By ~ 10

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.

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

Journal of Biological System ◽

10.1142/s0218339020400094 ◽

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.

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

10.21203/rs.3.rs-33480/v1 ◽

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.

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

10.1101/2021.09.25.21264082 ◽

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.

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Modelling the impact of immunization on the epidemiology of varicella zoster virus

Epidemiology and Infection ◽

10.1017/s0950268800004714 ◽

2000 ◽

Vol 125 (3) ◽

pp. 651-669 ◽

Cited By ~ 169

Author(s):

M. BRISSON ◽

W. J. EDMUNDS ◽

N. J. GAY ◽

B. LAW ◽

G. DE SERRES

Keyword(s):

First Year ◽

Varicella Zoster ◽

Vaccination Strategies ◽

Short And Long Term ◽

Catch Up ◽

Age Structured ◽

Age Structured Model ◽

The Impact ◽

Do So

The objective of this study was to develop and apply a dynamic mathematical model of VZV transmission to predict the effect of different vaccination strategies on the age-specific incidence and outcome of infection. To do so a deterministic realistic age-structured model (RAS) was used which takes account of the increased potential for transmission within school aged groups. Various vaccine efficacy scenarios, vaccine coverages and vaccination strategies were investigated and a sensitivity analysis of varicella incidence predictions to important parameters was performed. The model predicts that the overall (natural and breakthrough) incidence and morbidity of varicella would likely be reduced by mass vaccination of 12-month-old children. Furthermore, adding a catch-up campaign in the first year for 1–11 year olds seems to be the most effective strategy to reduce both varicella incidence and morbidity (in the short and long term), though with the possible detrimental effect of increasing the incidence of zoster.

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The Impact of Universal Mask Use on SARS-COV-2 in Victoria, Australia on the Epidemic Trajectory of COVID-19

Frontiers in Public Health ◽

10.3389/fpubh.2021.625499 ◽

2021 ◽

Vol 9 ◽

Author(s):

Valentina Costantino ◽

Chandini Raina MacIntyre

Keyword(s):

Mathematical Modeling ◽

Deterministic Model ◽

Face Mask ◽

Control Measures ◽

Contact Tracing ◽

Epidemic Size ◽

Community Transmission ◽

Age Structured ◽

The Impact ◽

Mask Effectiveness

Objective(s): To estimate the impact of universal community face mask use in Victoria, Australia along with other routine disease control measures in place.Methods: A mathematical modeling study using an age structured deterministic model for Victoria, was simulated for 123 days between 1 June 2020 and 1 October 2020, incorporating lockdown, contact tracing, and case findings with and without mask use in varied scenarios. The model tested the impact of differing scenarios of the universal use of face masks in Victoria, by timing, varying mask effectiveness, and uptake.Results: A six-week lockdown with standard control measures, but no masks, would have resulted in a large resurgence by September, following the lifting of restrictions. Mask use can substantially reduce the epidemic size, with a greater impact if at least 50% of people wear a mask which has an effectiveness of at least 40%. Early mask use averts more cases than mask usage that is only implemented closer to the peak. No mask use, with a 6-week lockdown, results in 67,636 cases and 120 deaths by 1 October 2020 if no further lockdowns are used. If mask use at 70% uptake commences on 23 July 2020, this is reduced to 7,961 cases and 42 deaths. We estimated community mask effectiveness to be 11%.Conclusion(s): Lockdown and standard control measures may not have controlled the epidemic in Victoria. Mask use can substantially improve epidemic control if its uptake is higher than 50% and if moderately effective masks are used. Early mask use should be considered in other states if community transmission is present, as this has a greater effect than later mask wearing mandates.

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Assessing vaccination strategies for the COVID-19 epidemic in Minas Gerais (Brazil)

Semina Ciências Exatas e Tecnológicas ◽

10.5433/1679-0375.2021v42n1suplp35 ◽

2021 ◽

Vol 42 (1 Supl) ◽

pp. 35

Author(s):

Marcelo Domingos Marchesin ◽

Mehran Sabeti

Keyword(s):

The Elderly ◽

Minas Gerais ◽

Elderly Group ◽

Age Group ◽

Age Classes ◽

Seir Model ◽

Current Strategy ◽

Vaccination Strategies ◽

Brazilian State ◽

Age Structured

In this work we analyze the effectiveness of vaccination strategies for the COVID-19 epidemic in the Brazilian state of Minas Gerais. Firstly we study the effectiveness of general vaccination in the decreasing of the number of infected individuals using a traditional non structured SEIR model. Secondly we consider an age-structured SEIR model with three age classes (youngster, adult and elderly) and we analyze the current strategy in the Brazilian state of Minas Gerais, of focusing the vaccination on the elderly group. We conclude by showing this strategy to be mistaken and that a vaccination focusing on the age group of the adults would be much more efficient in decreasing the total number of infected individuals.

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Adult pertussis vaccination strategies and their impact on pertussis in the United States: evaluation of routine and targeted (cocoon) strategies

Epidemiology and Infection ◽

10.1017/s0950268807009041 ◽

2007 ◽

Vol 136 (5) ◽

pp. 604-620 ◽

Cited By ~ 43

Author(s):

L. COUDEVILLE ◽

A. VAN RIE ◽

P. ANDRE

Keyword(s):

Booster Dose ◽

The United States ◽

Infection Rates ◽

Pertussis Infection ◽

Immunization Strategies ◽

Adult Vaccination ◽

Epidemiology Data ◽

Age Structured ◽

Coverage Rates ◽

The Impact

SUMMARYA compartmental, age-structured mathematical model was developed and recent US pertussis epidemiology data were used to evaluate the impact on pertussis infection rates of routine and targeted adult immunization strategies. Model simulations predict that the implementation of adolescent immunization only could reverse the current rise in pertussis infection rates but may lead to a resurgence of pertussis in subsequent decades. In contrast, inclusion of a routine adult strategy is likely to lead to sustained control of pertussis. Routine adult vaccination could control the disease even with relatively low coverage rates of 40% for routine vaccination of all adults every 10 years, or 65% for a targeted vaccination of close contacts of newborns completed by one booster dose for all adults. The model also predicts that the optimal age for this booster dose is 40 years. These results support the 2006 American Academy of Immunization Practices' recommendations for adolescent and adult vaccination against pertussis.

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How to Reduce the Transmission Risk of COVID-19 More Effectively in New York City: An Age-Structured Model Study

Frontiers in Medicine ◽

10.3389/fmed.2021.641205 ◽

2021 ◽

Vol 8 ◽

Author(s):

Miaolei Li ◽

Jian Zu ◽

Zongfang Li ◽

Mingwang Shen ◽

Yan Li ◽

...

Keyword(s):

New York ◽

New York City ◽

York City ◽

Age Groups ◽

Transmission Risk ◽

Age Group ◽

Infected People ◽

Age Structured ◽

The Impact ◽

Second Wave

Background: In face of the continuing worldwide COVID-19 epidemic, how to reduce the transmission risk of COVID-19 more effectively is still a major public health challenge that needs to be addressed urgently.Objective: This study aimed to develop an age-structured compartment model to evaluate the impact of all diagnosed and all hospitalized on the epidemic trend of COVID-19, and explore innovative and effective releasing strategies for different age groups to prevent the second wave of COVID-19.Methods: Based on three types of COVID-19 data in New York City (NYC), we calibrated the model and estimated the unknown parameters using the Markov Chain Monte Carlo (MCMC) method.Results: Compared with the current practice in NYC, we estimated that if all infected people were diagnosed from March 26, April 5 to April 15, 2020, respectively, then the number of new infections on April 22 was reduced by 98.02, 93.88, and 74.08%. If all confirmed cases were hospitalized from March 26, April 5, and April 15, 2020, respectively, then as of June 7, 2020, the total number of deaths in NYC was reduced by 67.24, 63.43, and 51.79%. When only the 0–17 age group in NYC was released from June 8, if the contact rate in this age group remained below 61% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC. When both the 0–17 and 18–44 age groups in NYC were released from June 8, if the contact rates in these two age groups maintained below 36% of the pre-pandemic level, then a second wave of COVID-19 could be prevented in NYC.Conclusions: If all infected people were diagnosed in time, the daily number of new infections could be significantly reduced in NYC. If all confirmed cases were hospitalized in time, the total number of deaths could be significantly reduced in NYC. Keeping a social distance and relaxing lockdown restrictions for people between the ages of 0 and 44 could not lead to a second wave of COVID-19 in NYC.

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Evaluating the impact of two training interventions to improve diagnosis and case-management of malaria and pneumonia in Uganda

Epidemiology and Infection ◽

10.1017/s0950268816002107 ◽

2016 ◽

Vol 145 (1) ◽

pp. 194-207

Author(s):

D. M. SSEBULIBA ◽

R. OUIFKI ◽

C. PRETORIUS ◽

S. M. BURNETT ◽

M. K. MBONYE ◽

...

Keyword(s):

Mathematical Model ◽

Case Management ◽

Support Services ◽

Integrated Management ◽

Age Groups ◽

Malaria Prevalence ◽

Age Group ◽

Training Interventions ◽

Age Structured ◽

The Impact

SUMMARYWe present an age-structured mathematical model of malaria and pneumonia to study the effect of two capacity-building interventions: Integrated Management of Infectious Diseases (IMID) and On-site Support Services (OSS). IMID leads to a reduction in malaria prevalence by more than 2·4% across the [0,5), [5,14) and [14,50) age groups. IMID + OSS reduces it by more than 16·0% across all age groups. IMID decreases pneumonia prevalence by more than 3·0% across all age groups while IMID + OSS decreases it by more than 1·0% across all age groups. The number of malaria and pneumonia deaths is reduced by 7·8% by IMID across all age groups and IMID + OSS decreases this number by 30·5% across all age groups, which translates to saving a life of a child per month. Prevalence of malaria-pneumonia for the [0,5) age group is 0·52% at baseline, and IMID and IMID + OSS reduce it by 6·6% and 23·6%, respectively. There is no change in incidence of malaria or pneumonia disease episodes. The results also indicate that triaging of children contributes more than 50% to the effect of the interventions in reduction of deaths and a range of 14–91% in reduction of disease cases.

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