{"doi":"10.1136/bmjopen-2022-061752","title":"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.","journal":"BMJ Open","year":2022,"id":241046,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":43,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9422,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":605858,"name":"Alyssa Bilinski","orcid":"0000-0001-9108-6660","position":1,"is_corresponding":false},{"id":225894,"name":"Meagan C. Fitzpatrick","orcid":"0000-0002-5248-2668","position":2,"is_corresponding":false},{"id":226455,"name":"A. David Paltiel","orcid":"0000-0002-4861-3290","position":3,"is_corresponding":false},{"id":870461,"name":"Zain Rizvi","orcid":null,"position":4,"is_corresponding":false},{"id":22312,"name":"Joshua A. Salomon","orcid":"0000-0003-3929-5515","position":5,"is_corresponding":false},{"id":869644,"name":"Thomas Thornhill","orcid":"0000-0003-4632-5890","position":6,"is_corresponding":false},{"id":691301,"name":"Gregg Gonsalves","orcid":"0000-0002-5789-9841","position":7,"is_corresponding":false},{"id":272229,"name":"Alexandra Savinkina","orcid":"0000-0002-5257-866X","position":0,"is_corresponding":true}],"reference_count":25,"raw_metadata":null,"created_at":"2026-07-19T00:22:56.227656Z","pmid":"36100306","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}