Cost-effectiveness of Coronavirus Disease 2019 Vaccination in Low- and Middle-Income Countries
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Abstract
Background
Despite the advent of safe and effective coronavirus disease 2019 vaccines, pervasive inequities in global vaccination persist.
Methods
We projected health benefits and donor costs of delivering vaccines for up to 60% of the population in 91 low- and middle-income countries (LMICs). We modeled a highly contagious (Re at model start, 1.7), low-virulence (infection fatality ratio [IFR], 0.32%) “Omicron-like” variant and a similarly contagious “severe” variant (IFR, 0.59%) over 360 days, accounting for country-specific age structure and healthcare capacity. Costs included vaccination startup (US$630 million) and per-person procurement and delivery (US$12.46/person vaccinated).
Results
In the Omicron-like scenario, increasing current vaccination coverage to achieve at least 15% in each of the 91 LMICs would prevent 11 million new infections and 120 000 deaths, at a cost of US$0.95 billion, for an incremental cost-effectiveness ratio (ICER) of US$670/year of life saved (YLS). Increases in vaccination coverage to 60% would additionally prevent up to 68 million infections and 160 000 deaths, with ICERs <US$8000/YLS. ICERs were <US$4000/YLS under the more severe variant scenario and generally robust to assumptions about vaccine effectiveness, uptake, and costs.
Conclusions
Funding expanded COVID-19 vaccine delivery in LMICs would save hundreds of thousands of lives, be similarly or more cost-effective than other donor-funded global aid programs, and improve health equity.
Article activity feed
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SciScore for 10.1101/2021.04.28.21256237: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This analysis has several limitations. First, natural history inputs were originally derived and validated as part of an analysis based in South Africa8. We used inputs calibrated to data from South Africa for three reasons: 1) accurate IFR data from other countries, particularly many LMICs, is limited; 2) age is well-established as the …
SciScore for 10.1101/2021.04.28.21256237: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This analysis has several limitations. First, natural history inputs were originally derived and validated as part of an analysis based in South Africa8. We used inputs calibrated to data from South Africa for three reasons: 1) accurate IFR data from other countries, particularly many LMICs, is limited; 2) age is well-established as the greatest risk factor for COVID-19 mortality and, after accounting for age, additional co-morbidities appear to have little additional effect on expected and reported mortality in LMICs46,47; and 3) use of data from South Africa is likely to more closely reflect SARS-CoV-2 natural history estimates in LMICs than data from high-income countries. Second, our model assumes homogeneous mixing, such that all individuals within a country are equally likely to become infected and transmit to others, and we do not include transmission between countries. The homogenous mixing assumption may underestimate transmissions in high contact and densely populated settings while overestimating transmissions in low contact and rural settings. Not including transmission between countries might also underestimate the value of increased global vaccine distribution. Third, our model includes data on vaccine efficacy, hesitancy, and costs, which are all from published studies but subject to uncertainty. Despite this, our findings were robust to plausible ranges in these parameters. Fourth, we did not account for the potential secondary health benefits of COVID-19 vacc...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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