Preexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical models
Preexposure prophylaxis (PrEP) with tenofovir and emtricitabine can prevent new HIV-1 infections, but there is a concern that use of PrEP could increase HIV drug resistance resulting in loss of treatment options. We compared standardized outcomes from three independent mathematical models simulating...
Main Authors: | , , , , , , , , , , , |
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格式: | Journal article |
語言: | English |
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Lippincott, Williams and Wilkins
2013
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_version_ | 1826287479276175360 |
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author | van de Vijver, DAMC Nichols, BE Abbas, UL Boucher, CAB Cambiano, V Eaton, JW Glaubius, R Katrina Lythgoe Mellors, J Phillips, A Sigaloff, KC Hallett, TB |
author_facet | van de Vijver, DAMC Nichols, BE Abbas, UL Boucher, CAB Cambiano, V Eaton, JW Glaubius, R Katrina Lythgoe Mellors, J Phillips, A Sigaloff, KC Hallett, TB |
author_sort | van de Vijver, DAMC |
collection | OXFORD |
description | Preexposure prophylaxis (PrEP) with tenofovir and emtricitabine can prevent new HIV-1 infections, but there is a concern that use of PrEP could increase HIV drug resistance resulting in loss of treatment options. We compared standardized outcomes from three independent mathematical models simulating the impact of PrEP on HIV transmission and drug resistance in sub-Saharan African countries.All models assume that people using PrEP receive an HIV test every 3-6 months. The models vary in structure and parameter choices for PrEP coverage, effectiveness of PrEP (at different adherence levels) and the rate with which HIV drug resistance emerges and is transmitted.The models predict that the use of PrEP in conjunction with antiretroviral therapy will result in a lower prevalence of HIV than when only antiretroviral therapy is used. With or without PrEP, all models suggest that HIV drug resistance will increase over the next 20 years due to antiretroviral therapy. PrEP will increase the absolute prevalence of drug resistance in the total population by less than 0.5% and amongst infected individuals by at most 7%. Twenty years after the introduction of PrEP, the majority of drug-resistant infections is due to antiretroviral therapy (50-63% across models), whereas 40-50% will be due to transmission of drug resistance, and less than 4% to the use of PrEP.HIV drug resistance resulting from antiretroviral therapy is predicted to far exceed that resulting from PrEP. Concern over drug resistance should not be a reason to limit the use of PrEP. |
first_indexed | 2024-03-07T01:59:18Z |
format | Journal article |
id | oxford-uuid:9cca44c0-f0e3-48ea-ab2b-627459e72956 |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-07T01:59:18Z |
publishDate | 2013 |
publisher | Lippincott, Williams and Wilkins |
record_format | dspace |
spelling | oxford-uuid:9cca44c0-f0e3-48ea-ab2b-627459e729562022-03-27T00:38:38ZPreexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical modelsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9cca44c0-f0e3-48ea-ab2b-627459e72956EnglishSymplectic Elements Lippincott, Williams and Wilkins2013van de Vijver, DAMCNichols, BEAbbas, ULBoucher, CABCambiano, VEaton, JWGlaubius, RKatrina LythgoeMellors, JPhillips, ASigaloff, KCHallett, TBPreexposure prophylaxis (PrEP) with tenofovir and emtricitabine can prevent new HIV-1 infections, but there is a concern that use of PrEP could increase HIV drug resistance resulting in loss of treatment options. We compared standardized outcomes from three independent mathematical models simulating the impact of PrEP on HIV transmission and drug resistance in sub-Saharan African countries.All models assume that people using PrEP receive an HIV test every 3-6 months. The models vary in structure and parameter choices for PrEP coverage, effectiveness of PrEP (at different adherence levels) and the rate with which HIV drug resistance emerges and is transmitted.The models predict that the use of PrEP in conjunction with antiretroviral therapy will result in a lower prevalence of HIV than when only antiretroviral therapy is used. With or without PrEP, all models suggest that HIV drug resistance will increase over the next 20 years due to antiretroviral therapy. PrEP will increase the absolute prevalence of drug resistance in the total population by less than 0.5% and amongst infected individuals by at most 7%. Twenty years after the introduction of PrEP, the majority of drug-resistant infections is due to antiretroviral therapy (50-63% across models), whereas 40-50% will be due to transmission of drug resistance, and less than 4% to the use of PrEP.HIV drug resistance resulting from antiretroviral therapy is predicted to far exceed that resulting from PrEP. Concern over drug resistance should not be a reason to limit the use of PrEP. |
spellingShingle | van de Vijver, DAMC Nichols, BE Abbas, UL Boucher, CAB Cambiano, V Eaton, JW Glaubius, R Katrina Lythgoe Mellors, J Phillips, A Sigaloff, KC Hallett, TB Preexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical models |
title | Preexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical models |
title_full | Preexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical models |
title_fullStr | Preexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical models |
title_full_unstemmed | Preexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical models |
title_short | Preexposure prophylaxis will have a limited impact on HIV-1 drug resistance in sub-Saharan Africa: a comparison of mathematical models |
title_sort | preexposure prophylaxis will have a limited impact on hiv 1 drug resistance in sub saharan africa a comparison of mathematical models |
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