Estimating the impact of COVID-19 vaccine inequities: a modeling study
Abstract Access to COVID-19 vaccines on the global scale has been drastically hindered by structural socio-economic disparities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC)...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-06-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-39098-w |
| _version_ | 1797806645674246144 |
|---|---|
| author | Nicolò Gozzi Matteo Chinazzi Natalie E. Dean Ira M. Longini Jr M. Elizabeth Halloran Nicola Perra Alessandro Vespignani |
| author_facet | Nicolò Gozzi Matteo Chinazzi Natalie E. Dean Ira M. Longini Jr M. Elizabeth Halloran Nicola Perra Alessandro Vespignani |
| author_sort | Nicolò Gozzi |
| collection | DOAJ |
| description | Abstract Access to COVID-19 vaccines on the global scale has been drastically hindered by structural socio-economic disparities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) selected from all WHO regions. We investigate and quantify the potential effects of higher or earlier doses availability. In doing so, we focus on the crucial initial months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that more than 50% of deaths (min-max range: [54−94%]) that occurred in the analyzed countries could have been averted. We further consider scenarios where LMIC had similarly early access to vaccine doses as high income countries. Even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [6−50%]) could have been averted. In the absence of the availability of high-income countries, the model suggests that additional non-pharmaceutical interventions inducing a considerable relative decrease of transmissibility (min-max range: [15−70%]) would have been required to offset the lack of vaccines. Overall, our results quantify the negative impacts of vaccine inequities and underscore the need for intensified global efforts devoted to provide faster access to vaccine programs in low and lower-middle-income countries. |
| first_indexed | 2024-03-13T06:10:25Z |
| format | Article |
| id | doaj.art-6189260a6f994ee9826fd2a058a8843f |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-13T06:10:25Z |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-6189260a6f994ee9826fd2a058a8843f2023-06-11T11:17:55ZengNature PortfolioNature Communications2041-17232023-06-0114111010.1038/s41467-023-39098-wEstimating the impact of COVID-19 vaccine inequities: a modeling studyNicolò Gozzi0Matteo Chinazzi1Natalie E. Dean2Ira M. Longini Jr3M. Elizabeth Halloran4Nicola Perra5Alessandro Vespignani6Networks and Urban Systems Centre, University of GreenwichLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern UniversityDepartment of Biostatistics and Bioinformatics, Emory UniversityDepartment of Biostatistics, College of Public Health and Health Professions, University of FloridaFred Hutchinson Cancer CenterLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern UniversityLaboratory for the Modeling of Biological and Socio-technical Systems, Northeastern UniversityAbstract Access to COVID-19 vaccines on the global scale has been drastically hindered by structural socio-economic disparities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) selected from all WHO regions. We investigate and quantify the potential effects of higher or earlier doses availability. In doing so, we focus on the crucial initial months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that more than 50% of deaths (min-max range: [54−94%]) that occurred in the analyzed countries could have been averted. We further consider scenarios where LMIC had similarly early access to vaccine doses as high income countries. Even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [6−50%]) could have been averted. In the absence of the availability of high-income countries, the model suggests that additional non-pharmaceutical interventions inducing a considerable relative decrease of transmissibility (min-max range: [15−70%]) would have been required to offset the lack of vaccines. Overall, our results quantify the negative impacts of vaccine inequities and underscore the need for intensified global efforts devoted to provide faster access to vaccine programs in low and lower-middle-income countries.https://doi.org/10.1038/s41467-023-39098-w |
| spellingShingle | Nicolò Gozzi Matteo Chinazzi Natalie E. Dean Ira M. Longini Jr M. Elizabeth Halloran Nicola Perra Alessandro Vespignani Estimating the impact of COVID-19 vaccine inequities: a modeling study Nature Communications |
| title | Estimating the impact of COVID-19 vaccine inequities: a modeling study |
| title_full | Estimating the impact of COVID-19 vaccine inequities: a modeling study |
| title_fullStr | Estimating the impact of COVID-19 vaccine inequities: a modeling study |
| title_full_unstemmed | Estimating the impact of COVID-19 vaccine inequities: a modeling study |
| title_short | Estimating the impact of COVID-19 vaccine inequities: a modeling study |
| title_sort | estimating the impact of covid 19 vaccine inequities a modeling study |
| url | https://doi.org/10.1038/s41467-023-39098-w |
| work_keys_str_mv | AT nicologozzi estimatingtheimpactofcovid19vaccineinequitiesamodelingstudy AT matteochinazzi estimatingtheimpactofcovid19vaccineinequitiesamodelingstudy AT natalieedean estimatingtheimpactofcovid19vaccineinequitiesamodelingstudy AT iramlonginijr estimatingtheimpactofcovid19vaccineinequitiesamodelingstudy AT melizabethhalloran estimatingtheimpactofcovid19vaccineinequitiesamodelingstudy AT nicolaperra estimatingtheimpactofcovid19vaccineinequitiesamodelingstudy AT alessandrovespignani estimatingtheimpactofcovid19vaccineinequitiesamodelingstudy |