The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effects
Abstract Introduction Over the course of the HIV pandemic, prevention and treatment interventions have reduced HIV incidence, but there is still scope for new prevention tools to further control HIV. Studies of the cost‐effectiveness of HIV prevention tools are often done using detailed, “transmissi...
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| Format: | Article |
| Language: | English |
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Wiley
2025-05-01
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| Series: | Journal of the International AIDS Society |
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| Online Access: | https://doi.org/10.1002/jia2.26494 |
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| author | Geoff P. Garnett Joshua T. Herbeck Adam Akullian |
| author_facet | Geoff P. Garnett Joshua T. Herbeck Adam Akullian |
| author_sort | Geoff P. Garnett |
| collection | DOAJ |
| description | Abstract Introduction Over the course of the HIV pandemic, prevention and treatment interventions have reduced HIV incidence, but there is still scope for new prevention tools to further control HIV. Studies of the cost‐effectiveness of HIV prevention tools are often done using detailed, “transmission‐aware” models, but there is a role for simpler analyses. Discussion We present equations to calculate the cost‐effectiveness, budget impact and epidemiological impact of HIV prevention interventions including equations allowing for multiple interventions and heterogeneity in risk across populations. As HIV incidence declines, the number needed to cover to prevent one HIV acquisition increases. Along with the benefits of averting HIV acquisitions, the cost‐effectiveness of HIV prevention interventions is driven by incidence, along with efficacy, duration and costs of the intervention. The budget impact is driven by cost, size of the population and coverage achieved, and impact is determined by the effective coverage of interventions. HIV incidence has declined in sub‐Saharan Africa, making primary HIV prevention less cost‐effective and decreasing the price at which new prevention products provide value. Heterogeneity in risk could in theory allow for focusing HIV prevention, but current screening tools do not appear to sufficiently differentiate risk in populations where they have been applied. The simple calculations shown here provide rough initial estimates that can be compared with more sophisticated transmission dynamic and health economic models. Conclusions Simple equations show how the observed declines in HIV incidence in sub‐Saharan Africa make primary prevention tools less cost‐effective. If we require prevention to be more cost‐effective, either we need primary prevention tools to be used disproportionately by those most at risk of acquiring HIV, or they need to be less expensive. |
| format | Article |
| id | doaj-art-b8c05a946cbc4d6b99c795d1dfd3b422 |
| institution | DOAJ |
| issn | 1758-2652 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of the International AIDS Society |
| spelling | doaj-art-b8c05a946cbc4d6b99c795d1dfd3b4222025-08-20T03:19:25ZengWileyJournal of the International AIDS Society1758-26522025-05-01285n/an/a10.1002/jia2.26494The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effectsGeoff P. Garnett0Joshua T. Herbeck1Adam Akullian2TB & HIV Team, Bill & Melinda Gates Foundation Seattle Washington USAInstitute for Disease Modeling Bill & Melinda Gates Foundation Seattle Washington USAInstitute for Disease Modeling Bill & Melinda Gates Foundation Seattle Washington USAAbstract Introduction Over the course of the HIV pandemic, prevention and treatment interventions have reduced HIV incidence, but there is still scope for new prevention tools to further control HIV. Studies of the cost‐effectiveness of HIV prevention tools are often done using detailed, “transmission‐aware” models, but there is a role for simpler analyses. Discussion We present equations to calculate the cost‐effectiveness, budget impact and epidemiological impact of HIV prevention interventions including equations allowing for multiple interventions and heterogeneity in risk across populations. As HIV incidence declines, the number needed to cover to prevent one HIV acquisition increases. Along with the benefits of averting HIV acquisitions, the cost‐effectiveness of HIV prevention interventions is driven by incidence, along with efficacy, duration and costs of the intervention. The budget impact is driven by cost, size of the population and coverage achieved, and impact is determined by the effective coverage of interventions. HIV incidence has declined in sub‐Saharan Africa, making primary HIV prevention less cost‐effective and decreasing the price at which new prevention products provide value. Heterogeneity in risk could in theory allow for focusing HIV prevention, but current screening tools do not appear to sufficiently differentiate risk in populations where they have been applied. The simple calculations shown here provide rough initial estimates that can be compared with more sophisticated transmission dynamic and health economic models. Conclusions Simple equations show how the observed declines in HIV incidence in sub‐Saharan Africa make primary prevention tools less cost‐effective. If we require prevention to be more cost‐effective, either we need primary prevention tools to be used disproportionately by those most at risk of acquiring HIV, or they need to be less expensive.https://doi.org/10.1002/jia2.26494cost‐effectiveness analysisHIV preventionHIVincidencemathematical modellingnumber needed to treat |
| spellingShingle | Geoff P. Garnett Joshua T. Herbeck Adam Akullian The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effects Journal of the International AIDS Society cost‐effectiveness analysis HIV prevention HIV incidence mathematical modelling number needed to treat |
| title | The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effects |
| title_full | The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effects |
| title_fullStr | The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effects |
| title_full_unstemmed | The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effects |
| title_short | The changing cost‐effectiveness of primary HIV prevention: simple calculations of direct effects |
| title_sort | changing cost effectiveness of primary hiv prevention simple calculations of direct effects |
| topic | cost‐effectiveness analysis HIV prevention HIV incidence mathematical modelling number needed to treat |
| url | https://doi.org/10.1002/jia2.26494 |
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