Time-varying optimization of COVID-19 vaccine prioritization in the context of limited vaccination capacity

Han, Shasha; Cai, Jun; Yang, Juan; Zhang, Juanjuan; Wu, Qianhui; Zheng, Wen; Shi, Hui; Ajelli, Marco; Zhou, Xiao‐Hua; Yu, Hongjie

doi:10.1038/s41467-021-24872-5

Cited by 70 publications

(80 citation statements)

References 38 publications

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“…These results are consistent with those of other model-based studies showing that the optimal vaccination strategy balancing direct and indirect protection against COVID-19 is highly determined by vaccine supply and efficacy [14,35,36] and vaccination of the most susceptible group is more efficient under a broad range of situations [37,38]. Our study adds two elements to previous approaches.…”

Section: Discussionsupporting

confidence: 91%

“…As other models used to inform optimal vaccination roll-out [14,[35][36][37], our model assumes that individuals within a given group have on average the same number of contacts. More realistic models should consider heterogeneity in the number of contacts, since it has been shown that highly skewed contact distributions, with hubs (or, equivalent from a dynamic viewpoint, super-spreader individuals or events) have important effects in immunity thresholds [39] and in vaccination strategies.…”

Section: Discussionmentioning

confidence: 99%

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Vaccination strategies in structured populations under partial immunity and reinfection

Rodriguez-Maroto

2021

Preprint

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Optimal protocols of vaccine administration to minimize the effects of infectious diseases depend on a number of variables that admit different degrees of control. Examples include the characteristics of the disease and how it impacts on different groups of individuals as a function of sex, age or socioeconomic status, its transmission mode, or the demographic structure of the affected population. Here we introduce a compartmental model of infection propagation with vaccination and reinfection and analyse the effect that variations on the rates of these two processes have on the progression of the disease and on the number of fatalities. The population is split into two groups to highlight the overall effects on disease caused by different relationships between vaccine administration and various demographic structures. We show that optimal administration protocols depend on the vaccination rate, a variable severely conditioned by vaccine supply and acceptance. As a practical example, we study COVID-19 dynamics in various countries using real demographic data. The model can be easily applied to any other disease and demographic structure through a suitable estimation of parameter values. Simulations of the general model can be carried out at this interactive webpage [1].Author summaryVaccination campaigns can have varying degrees of success in minimizing the effects of an infectious disease. It is often very difficult to assess a priori the importance and effect of different relevant factors. To gain insight into this problem, we present a model of infection propagation with vaccination and use it to study the effects of vaccination rate and population structure. We find that when the disease affects in different ways distinct population groups, the best vaccination strategy depends non-trivially on the rate at which vaccines can be administered. The application of our analysis to COVID-19 reveals that, in countries with aged populations, the best strategy is always to vaccinate first the elderly, while for youthful populations maximizing vaccination rate regardless of other considerations may save more lives.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Vaccination strategies in structured populations under partial immunity and reinfection

Rodriguez-Maroto

2021

Preprint

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“…However, this study also found that slower vaccination rates can lead to a prolonging of the COVID-19 pandemic, and a higher number of cases and deaths in the population [67]. Besides, to measure the optimal vaccine prioritisation of COVID-19 transmission, Han et al ( 2011) developed a data-driven mechanistic model in China [68]. In this model, they considered 17 age groups and divided the population into five compartments: the unvaccinated susceptible population (S); persons who received at least the first dose of vaccine but have yet to develop protection (V); persons who received the second dose of the vaccine but failed in protection (U); infectious individuals including asymptomatic and symptomatic infections (I); and recovered or immune individuals (R).…”

Section: Models With Age Structure and Vaccinationmentioning

confidence: 79%

“…Furthermore, this study recommended that, to minimise the number of deaths and ICU admissions, people over 65 years of age should be vaccinated before moving to other groups such as younger and middle-aged people. Finally, the early phase of high vaccination capacity is the key to achieving significant success of policy measures and implementations [68].…”

Section: Models With Age Structure and Vaccinationmentioning

confidence: 99%

A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas

Rahman

Kuddus

et al. 2021

Viruses

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At the end of December 2019, an outbreak of COVID-19 occurred in Wuhan city, China. Modelling plays a crucial role in developing a strategy to prevent a disease outbreak from spreading around the globe. Models have contributed to the perspicacity of epidemiological variations between and within nations and the planning of desired control strategies. In this paper, a literature review was conducted to summarise knowledge about COVID-19 disease modelling in three countries—China, the UK and Australia—to develop a robust research framework for the regional areas that are urban and rural health districts of New South Wales, Australia. In different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future.

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“…Vaccination is one of the most effective measures in influenza control. Identifying and developing universal vaccines, as well as increasing the vaccination capacity ( 15 ) are of primary importance after influenza’s long-term disruptions to seasonal patterns. However, as the influenza season is approaching and a large part of a population has not been protected by vaccines, there is an increasing call for coordinated mitigation measures.…”

Section: Discussionmentioning

confidence: 99%

The Incoming Influenza Season — China, the United Kingdom, and the United States, 2021–2022

et al. 2021

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Introduction Seasonal influenza activity has declined globally since the widespread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. There has been scarce information to understand the future dynamics of influenza — and under different hypothesis on relaxation of non-pharmaceutical interventions (NPIs) in particular — after the disruptions to seasonal patterns. Methods We collected data from public sources in China, the United Kingdom, and the United States, and forecasted the influenza dynamics in the incoming 2021–2022 season under different NPIs. We considered Northern China and Southern China separately, due to the sharp difference in the patterns of seasonal influenza. For the United Kingdom, data were collected for England only. Results Compared to the epidemics in 2017–2019, longer and blunter influenza outbreaks could occur should NPIs be fully lifted, with percent positivity varying from 10.5 to 18.6 in the studying regions. The rebounds would be smaller if the mask-wearing intervention continued or the international mobility stayed low, but sharper if the mask-wearing intervention was lifted in the middle of influenza season. Further, influenza activity could stay low under a much less stringent mask-wearing intervention coordinated with influenza vaccination. Conclusions The results added to our understandings of future influenza dynamics after the global decline during the coronavirus disease 2019 (COVID-19) pandemic. In light of the uncertainty on the incoming circulation strains and the relatively low negative impacts of mask wearing on society, our findings suggested that wearing mask could be considered as an accompanying mitigation measure in influenza prevention and control, especially for seasons after long periods of low-exposure to influenza viruses.

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Time-varying optimization of COVID-19 vaccine prioritization in the context of limited vaccination capacity

Cited by 70 publications

References 38 publications

Vaccination strategies in structured populations under partial immunity and reinfection

Vaccination strategies in structured populations under partial immunity and reinfection

A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas

The Incoming Influenza Season — China, the United Kingdom, and the United States, 2021–2022

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