The impacts of SARS-CoV-2 vaccine dose separation and targeting on the COVID-19 epidemic in England

Keeling, Matthew James; Moore, Samuel; Penman, Bridget S.; Hill, Edward M.

doi:10.1038/s41467-023-35943-0

Cited by 20 publications

(10 citation statements)

References 40 publications

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“…We do not investigate other counterfactual scenarios based on changes in vaccination protocols, such as for example delaying the time between doses. This strategy, which aims to prioritize one-dose protection coverage, has been shown to be effective in the first ten months of the rollout in the United Kingdom 50 . Finally, the counterfactual scenarios do not consider changes in the global allocation of doses, the real global availability of vaccines, nor the local cost of the supply chain necessary to receive, store, distribute and administer doses.…”

Section: Resultsmentioning

confidence: 99%

“…Vaccine hesitancy, expiration dates, logistic issues, and vaccine nationalism all played a role, especially in high-income countries 53 , 54 . Moreover, the overall number of doses available at any given time is influenced by many variables such as production choices, supply chain capabilities, vaccination protocols (e.g., the time between first and second doses) 50 , and national/international policies among others. The choices made to affect these variables evolved over time, clearly showing that alternative models are possible.…”

Section: Resultsmentioning

confidence: 99%

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Estimating the impact of COVID-19 vaccine inequities: a modeling study

et al. 2023

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Access to COVID-19 vaccines on the global scale has been drastically hindered by structural socio-economic disparities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) selected from all WHO regions. We investigate and quantify the potential effects of higher or earlier doses availability. In doing so, we focus on the crucial initial months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that more than 50% of deaths (min-max range: [54−94%]) that occurred in the analyzed countries could have been averted. We further consider scenarios where LMIC had similarly early access to vaccine doses as high income countries. Even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [6−50%]) could have been averted. In the absence of the availability of high-income countries, the model suggests that additional non-pharmaceutical interventions inducing a considerable relative decrease of transmissibility (min-max range: [15−70%]) would have been required to offset the lack of vaccines. Overall, our results quantify the negative impacts of vaccine inequities and underscore the need for intensified global efforts devoted to provide faster access to vaccine programs in low and lower-middle-income countries.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Estimating the impact of COVID-19 vaccine inequities: a modeling study

et al. 2023

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“…The nature of these functions allow for the dual consideration of health-associated costs in addition to control-associated costs when deciding upon an optimal strategy. Previous research articles have investigated the impacts of vaccination in the context of the COVID-19 pandemic using scenario modelling, including considering different vaccine effectiveness and uptake levels [19], deployment strategies [5, 31] and assumptions surrounding the health and economic benefits of vaccination [20]. Modelling of this type is increasingly used in real-time during infectious disease outbreaks to guide policy decisions.…”

Section: Discussionmentioning

confidence: 99%

When should lockdown be implemented? Devising cost-effective strategies for managing epidemics amid vaccine uncertainty

Doyle,

Cumming,

Thompson

et al. 2024

Preprint

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During an infectious disease outbreak, public health policy makers are tasked with strategically implementing control interventions whilst balancing competing objectives. To provide a quantitative framework that can be used to guide these decisions, it is helpful to devise a clear and specific objective function that can be evaluated to determine the optimal outbreak response. In this study, we have developed a mathematical modelling framework representing outbreaks of a novel emerging pathogen for which non-pharmaceutical interventions (NPIs) are imposed or removed based on thresholds for hospital occupancy. These thresholds are set at different levels to define four unique control strategies. We illustrate that the optimal intervention strategy is contingent on the choice of objective function. Specifically, the optimal strategy depends on the extent to which policy makers prioritise reducing health costs due to infection over the costs associated with control interventions. Motivated by the scenario early in the COVID-19 pandemic, we incorporate the development of a vaccine into our modelling framework and demonstrate that a policy maker's belief about when a vaccine will become available in future, and its eventual coverage (and/or effectiveness), affects the optimal control strategy to adopt early in the outbreak. Furthermore, we show how uncertainty in these quantities can be accounted for when deciding which interventions to introduce. This research highlights the benefits of policy makers being explicit about the precise objectives of introducing interventions.

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“…The individual seeks to optimise the utility function Eq (6) by choosing a κ(t) while being subject to Eq (2). The population dynamics s(t), i(t) and behaviour k(t) are taken as exogenous.…”

Section: Plos Onementioning

confidence: 99%

“…Vaccination is often the most successful policy tool against highly infectious diseases [1,2]. In the absence of an effective vaccine, a wealth of alternative interventions become necessary.…”

Section: Introductionmentioning

confidence: 99%

Rational social distancing in epidemics with uncertain vaccination timing

et al. 2023

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During epidemics people may reduce their social and economic activity to lower their risk of infection. Such social distancing strategies will depend on information about the course of the epidemic but also on when they expect the epidemic to end, for instance due to vaccination. Typically it is difficult to make optimal decisions, because the available information is incomplete and uncertain. Here, we show how optimal decision-making depends on information about vaccination timing in a differential game in which individual decision-making gives rise to Nash equilibria, and the arrival of the vaccine is described by a probability distribution. We predict stronger social distancing the earlier the vaccination is expected and also the more sharply peaked its probability distribution. In particular, equilibrium social distancing only meaningfully deviates from the no-vaccination equilibrium course if the vaccine is expected to arrive before the epidemic would have run its course. We demonstrate how the probability distribution of the vaccination time acts as a generalised form of discounting, with the special case of an exponential vaccination time distribution directly corresponding to regular exponential discounting.

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The impacts of SARS-CoV-2 vaccine dose separation and targeting on the COVID-19 epidemic in England

Cited by 20 publications

References 40 publications

Estimating the impact of COVID-19 vaccine inequities: a modeling study

Estimating the impact of COVID-19 vaccine inequities: a modeling study

When should lockdown be implemented? Devising cost-effective strategies for managing epidemics amid vaccine uncertainty

Rational social distancing in epidemics with uncertain vaccination timing

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