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Budget constraint and vaccine dosing: a mathematical modelling exercise.

ABSTRACT: BACKGROUND:Increasing the number of vaccine doses may potentially improve overall efficacy. Decision-makers need information about choosing the most efficient dose schedule to maximise the total health gain of a population when operating under a constrained budget. The objective of this study is to identify the most efficient vaccine dosing schedule within a fixed vaccination budget from a healthcare payer perspective. METHODS:An optimisation model is developed in which maximizing the disease reduction is the functional objective and the constraint is the vaccination budget. The model allows variation in vaccination dosing numbers, in cost difference per dose, in vaccine coverage rate, and in vaccine efficacy. We apply the model using the monovalent rotavirus vaccine as an example. RESULTS:With a fixed budget, a 2-dose schedule for vaccination against rotavirus infection with the monovalent vaccine results in a larger reduction in disease episodes than a 3-dose scheme with the same vaccine under most circumstances. A 3-dose schedule would only be better under certain conditions: a cost reduction of >26% per dose, combined with vaccine efficacy improvement of ?5% and a target coverage rate of 75%. Substantial interaction is observed between cost reduction per dose, vaccine coverage rate, and increased vaccine efficacy. Sensitivity analysis shows that the conditions required for a 3-dose strategy to be better than a 2-dose strategy may seldom occur when the budget is fixed. The model does not consider vaccine herd effect, precise timing for additional doses, or the effect of natural immunity development. CONCLUSIONS:Under budget constraint, optimisation modelling is a helpful tool for a decision-maker selecting the most efficient vaccination dosing schedule. The low dosing scheme could be the optimal option to consider under the many scenarios tested. The model can be applied under many different circumstances of changing dosing schemes with single or multiple vaccines.

SUBMITTER: Standaert BA

PROVIDER: S-EPMC3904011 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Budget constraint and vaccine dosing: a mathematical modelling exercise.

Standaert Baudouin A BA Curran Desmond D Postma Maarten J MJ

Cost effectiveness and resource allocation : C/E 20140122 1

<h4>Background</h4>Increasing the number of vaccine doses may potentially improve overall efficacy. Decision-makers need information about choosing the most efficient dose schedule to maximise the total health gain of a population when operating under a constrained budget. The objective of this study is to identify the most efficient vaccine dosing schedule within a fixed vaccination budget from a healthcare payer perspective.<h4>Methods</h4>An optimisation model is developed in which maximizing ...[more]

PMID: 24450591

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Project description:BackgroundMalnourished and young children are particularly susceptible to severe forms of tuberculosis and poor treatment response. WHO dosing guidelines for drugs for tuberculosis treatment are based only on weight, which might lead to systematic underdosing and poor outcomes in these children. We aimed to assess and quantify the population effect of WHO guidelines for drug-susceptible tuberculosis in children in the 20 countries with the highest disease burden.MethodsWe used an integrated model that linked country-specific demographic data at the individual level from the 20 countries with the highest disease burden to pharmacokinetic, outcome, and epidemiological models. We estimated tuberculosis treatment outcomes in children younger than 5 years following WHO guidelines (children are dosed by weight bands corresponding to the number of fixed-dose combination tablets [75 mg rifampicin, 50 mg isoniazid, 150 mg pyrazinamide]) and two alternative dosing strategies: one based on a proposed algorithm that uses age, weight, and available formulations, in which underweight children would receive the same drug doses as would normal weight children of the same age; and another based on an individualised algorithm without dose limitations, in which derived doses results in target exposure attainment for the typical child.FindingsWe estimated that 57 234 (43%) of 133 302 children younger than 5 years who were treated for tuberculosis in 2017 were underdosed with WHO dosing and only 47% of children would reach the rifampicin exposure target. Underdosing and subtherapeutic exposures were more common among malnourished children than among age-matched healthy children. The proposed dosing approach improved estimated rifampicin target exposure attainment to 62% and equalised outcomes by nutritional status. An estimated third of unfavourable treatment outcomes might be resolved with this dosing strategy, saving the lives of a minimum of 2423 children in these countries annually. With individualised dosing approaches, almost all children could achieve adequate exposure for cure.InterpretationThis work shows that a simple change in dosing procedure to include age and nutritional status, requiring no additional measurements or new drug formulations, is one approach to improve tuberculosis treatment outcomes in children, especially malnourished children who are at high risk of mortality.FundingEunice Kennedy Shriver National Institute of Child Health and Human Development and UK Medical Research Council.

Project description:BackgroundThe development and widespread use of an effective SARS-CoV-2 vaccine could prevent substantial morbidity and mortality associated with COVID-19 and mitigate the secondary effects associated with non-pharmaceutical interventions.MethodsWe used an age-structured, expanded SEIR model with social contact matrices to assess age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed incident cases of COVID-19 between 1 July and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccine allocation strategies based on prioritizing different age groups, and the interactions of these strategies with concurrent non-pharmaceutical interventions. Given the uncertainty associated with COVID-19 vaccine development, we varied vaccine characteristics in the modelling simulations.ResultsPrioritizing COVID-19 vaccine allocation for older populations (i.e., >60 years) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. Preferential vaccination of this group often produced relatively higher total symptomatic infections and more pronounced estimates of peak incidence than other assessed strategies. Vaccine efficacy, immunity type, target coverage, and rollout speed significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination.ConclusionsOur findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Relative differences between allocation strategies were reduced as the speed of vaccine rollout was increased. Optimal vaccine allocation strategies will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals.

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Budget constraint and vaccine dosing: a mathematical modelling exercise.

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Budget constraint and vaccine dosing: a mathematical modelling exercise.

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