Dataset Information

Estimating deaths averted and cost per life saved by scaling up mRNA COVID-19 vaccination in low-income and lower-middle-income countries in the COVID-19 Omicron variant era: a modelling study.

ABSTRACT:

Objectives

While almost 60% of the world has received at least one dose of COVID-19 vaccine, the global distribution of vaccination has not been equitable. Only 4% of the population of low-income countries (LICs) has received a full primary vaccine series, compared with over 70% of the population of high-income nations.

Design

We used economic and epidemiological models, parameterised with public data on global vaccination and COVID-19 deaths, to estimate the potential benefits of scaling up vaccination programmes in LICs and lower-middle-income countries (LMICs) in 2022 in the context of global spread of the Omicron variant of SARS-CoV2.

Setting

Low-income and lower-middle-income nations.

Main outcome measures

Outcomes were expressed as number of avertable deaths through vaccination, costs of scale-up and cost per death averted. We conducted sensitivity analyses over a wide range of parameter estimates to account for uncertainty around key inputs.

Findings

Globally, universal vaccination in LIC/LMIC with three doses of an mRNA vaccine would result in an estimated 1.5 million COVID-19 deaths averted with a total estimated cost of US$61 billion and an estimated cost-per-COVID-19 death averted of US$40 800 (sensitivity analysis range: US$7400-US$81 500). Lower estimated infection fatality ratios, higher cost-per-dose and lower vaccine effectiveness or uptake lead to higher cost-per-death averted estimates in the analysis.

Conclusions

Scaling up COVID-19 global vaccination would avert millions of COVID-19 deaths and represents a reasonable investment in the context of the value of a statistical life. Given the magnitude of expected mortality facing LIC/LMIC without vaccination, this effort should be an urgent priority.

SUBMITTER: Savinkina A

PROVIDER: S-EPMC9471205 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating deaths averted and cost per life saved by scaling up mRNA COVID-19 vaccination in low-income and lower-middle-income countries in the COVID-19 Omicron variant era: a modelling study.

Savinkina Alexandra A Bilinski Alyssa A Fitzpatrick Meagan M Paltiel A David AD Rizvi Zain Z Salomon Joshua J Thornhill Thomas T Gonsalves Gregg G

BMJ open 20220913 9

<h4>Objectives</h4>While almost 60% of the world has received at least one dose of COVID-19 vaccine, the global distribution of vaccination has not been equitable. Only 4% of the population of low-income countries (LICs) has received a full primary vaccine series, compared with over 70% of the population of high-income nations.<h4>Design</h4>We used economic and epidemiological models, parameterised with public data on global vaccination and COVID-19 deaths, to estimate the potential benefits of ...[more]

PMID: 36100306

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Project description:ImportanceIncome has a negative, nonlinear association with all-cause mortality. Income support policies may prevent deaths among low-income populations by raising their incomes.ObjectiveTo estimate the deaths that could be averted among working-age adults age 18 to 64 years with hypothetical income support policies in the US.Design setting and populationAn open, multicohort life-table model was developed that simulated working-age adults age 18 to 64 years in the US over 5 to 40 years. Publicly available household income data and previous estimates of the income-mortality association were used to generate mortality rates by income group. Deterministic sensitivity analyses were conducted to evaluate the effect of parameter uncertainty and various model assumptions on the findings.InterventionsIn addition to a no-intervention scenario, 4 hypothetical income support policies were modeled: universal basic income, modified LIFT Act, poverty alleviation, and negative income tax.Main outcome and measuresThe main outcome was the number of deaths averted, which was calculated by subtracting the number of deaths experienced in the no-intervention scenario from the number of deaths experienced with the various income support policies.ResultsBase-case assumptions used average mortality rates by age, sex, and income group, a 20-year time horizon, and a 3-year lag time. Universal basic income worth $12 000 per year per individual was estimated to avert the most deaths among working-age adults (42 000-104 000 per year), followed by a negative income tax that guaranteed an income of 133% of the federal poverty level (19 000-67 000 per year). A modified LIFT Act that provided $6000 to individuals with annual household incomes less than $100 000 was estimated to avert 17 000 to 52 000 deaths per year. A targeted approach that alleviated poverty was estimated to prevent 12 000 to 32 000 deaths among the lowest-income, working-age adult population. Results were most sensitive to several inputs and assumptions, primarily the income-based mortality rates, analytic time horizon, and assumed time lag between when a policy was implemented and when individuals experienced the mortality benefit of having higher incomes.Conclusions and relevanceIn this modeling study, 4 hypothetical income support policies were estimated to avert thousands of deaths among working-age US adults every year. Additional research is needed to understand the true association of income gains with mortality. Discussions about the costs and benefits of income support policies should include potential gains in health.

Project description:ObjectivesFollowing well-established practices in demography, this article discusses several measures based on the number of COVID-19 deaths to facilitate comparisons over time and across populations.SettingsNational populations in 186 United Nations countries and territories and populations in first-level subnational administrative entities in Brazil, China, Italy, Mexico, Peru, Spain and the USA.ParticipantsNone (death statistics only).Primary and secondary outcome measuresAn unstandardised occurrence/exposure rate comparable to the Crude Death Rate; an indirectly age-and-sex standardised rate that can be derived even when the breakdown of COVID-19 deaths by age and sex required for direct standardisation is unavailable; the reduction in life expectancy at birth corresponding to the 2020 number of COVID-19 deaths.ResultsTo date, the highest unstandardised rate has been in New York, at its peak exceeding the state 2017 crude death rate. Populations compare differently after standardisation: while parts of Italy, Spain and the USA have the highest unstandardised rates, parts of Mexico and Peru have the highest standardised rates. For several populations with the necessary data by age and sex for direct standardisation, we show that direct and indirect standardisation yield similar results. US life expectancy is estimated to have declined this year by more than a year (-1.26 years), far more than during the worst year of the HIV epidemic, or the worst 3 years of the opioid crisis, and to reach its lowest level since 2008. Substantially larger reductions, exceeding 2 years, are estimated for Panama, Peru, and parts of Italy, Spain, the USA and especially, Mexico.ConclusionsWith lesser demand on data than direct standardisation, indirect standardisation is a valid alternative to adjust international comparisons for differences in population distribution by sex and age-groups. A number of populations have experienced reductions in 2020 life expectancies that are substantial by recent historical standards.

Dataset Information

Estimating deaths averted and cost per life saved by scaling up mRNA COVID-19 vaccination in low-income and lower-middle-income countries in the COVID-19 Omicron variant era: a modelling study.

Objectives

Design

Setting

Main outcome measures

Findings

Conclusions

Publications

Estimating deaths averted and cost per life saved by scaling up mRNA COVID-19 vaccination in low-income and lower-middle-income countries in the COVID-19 Omicron variant era: a modelling study.

Similar Datasets

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