Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization

Abstract

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

An integrated chance constraints approach for optimal vaccination strategies under uncertainty for COVID-19

“…We list the publication, approach used, and the type of setting regarding the model or methodology. In the context of COVID-19, the closely related works include Acuña-Zegarra et al [18] , Bubar et al [17] , Miura et al [31] , and Rachaniotis et al [32] . These works are listed in Table 2 in terms of the publication, approach used, and whether or not the proposed model incorporates different households, heterogeneity in terms of age-specific differences in disease susceptibility and infectivity, and household vaccination status.…”

Optimizing two-dose vaccine resource allocation to combat a pandemic in the context of limited supply: The case of COVID-19

“…The significant challenge facing public health authorities is how to allocate scarce vaccines to mitigate the negative effects of a pandemic. This type of problem is referred to as vaccine allocation for epidemic control, and it has recently received widespread attention from the scientific community attention (37,47,(49)(50)(51)(52)(53)(54)(55)(56).…”

Asymptotic Analysis of Optimal Vaccination Policies

“…Examples of this occur when the population is divided by age for diseases such as COVID-19 (Miura et al. 2021 ) and seasonal influenza (Molinari et al. 2007 ).…”