Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 Survey
(1) Background: HIV drug resistance (HIVDR) poses a significant challenge to the effectiveness of antiretroviral therapy and the overall management of HIVand AIDS. Understanding the predictors of HIVDR is critical for developing strategies to mitigate its impact. The objectives of this study were to...
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2024-10-01
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| author | Munyaradzi Mapingure Solomon Mukwenha Innocent Chingombe Rutendo Birri Makota Elliot Mbunge Enos Moyo Garikayi Chemhaka John Batani Brian Moyo Godfrey Musuka |
| author_facet | Munyaradzi Mapingure Solomon Mukwenha Innocent Chingombe Rutendo Birri Makota Elliot Mbunge Enos Moyo Garikayi Chemhaka John Batani Brian Moyo Godfrey Musuka |
| author_sort | Munyaradzi Mapingure |
| collection | DOAJ |
| description | (1) Background: HIV drug resistance (HIVDR) poses a significant challenge to the effectiveness of antiretroviral therapy and the overall management of HIVand AIDS. Understanding the predictors of HIVDR is critical for developing strategies to mitigate its impact. The objectives of this study were to identify the predictors of HIVDR among Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA 2020) study participants, a national population-based survey. (2) Methods: Data from people living with HIV who participated in the ZIMPHIA 2020 were used to determine the predictors of HIVDR. (3) Results: The prevalence of HIVDR was 44.9%. Acquired HIVDR was present in 76.1% of people with a virological failure and transmitted resistance is 22.6% in naïve individuals. Factors associated with HIVDR in adjusted analysis were the number of lifetime sexual partners (aOR = 1.03, 95% CI: 1.01–1.06, <i>p</i> = 0.017), each additional year since the first HIV positive result (aOR = 1.17, 95% CI: 1.09–1.25, <i>p</i> < 0.01), each additional year on ART (aOR = 1.14, 95% CI: 1.06–1.23, <i>p</i> = 0.001), initiating ART before 2014 (aOR = 3.08, 95% CI: 1.72–5.49, <i>p</i> = 0.020), ever had switched antiretrovirals (aOR = 2.47, 95% CI: 1.15–5.29, <i>p</i> = 0.020) or had ever had a viral load test (aOR = 2.54, 95% CI: 1.54–4.17, <i>p</i> < 0.001) and a CD4 count < 350 (aOR = 2.04, 95% CI: 1.48–2.83, <i>p</i> < 0.01), while age ≥ 50 (aOR = 0.56, 95% CI: 0.32–0.98, 32 <i>p</i> = 0.04), condom use at last encounter (OR: 0.49, 95%CI: 0.33–0.73, <i>p</i> < 0.001), and not being on ART (aOR = 0.09, 95% CI: 0.06–0.13, <i>p</i> < 0.01) were associated with reduced odds of HIVDR. Conclusions: HIVDR was high among the participants. There is a need to address HIVDR and enhance the mechanisms already in place. This study introduces more information that would help in developing targeted interventions to prevent HIVDR and improve patient outcomes. |
| format | Article |
| id | doaj-art-40209aad4434425d9752e2b6af0ff018 |
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| spelling | doaj-art-40209aad4434425d9752e2b6af0ff0182025-08-20T02:27:40ZengMDPI AGTropical Medicine and Infectious Disease2414-63662024-10-0191125710.3390/tropicalmed9110257Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 SurveyMunyaradzi Mapingure0Solomon Mukwenha1Innocent Chingombe2Rutendo Birri Makota3Elliot Mbunge4Enos Moyo5Garikayi Chemhaka6John Batani7Brian Moyo8Godfrey Musuka9Department of Global Public Health and Family Medicine, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare 263, ZimbabweTexila America University, Georgetown 592, GuyanaInnovative Public Health and Development, Harare 263, ZimbabweDepartment of Biomedical Informatics and Biomedical Engineering, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare 263, ZimbabweDivision of Research, Innovation and Engagement, Mangosuthu University of Technology, Umlazi, Durban 4031, South AfricaSchool of Nursing and Public Health, Faculty of Medicine and Health Sciences, University of Kwazulu Natal, Durban 4031, South AfricaDepartment of Statistics and Demography, Faculty of Social Sciences, University of Eswatini, Private Bag 4, Kwaluseni Campus, Kwaluseni 268, EswatiniFaculty of Engineering and Technology, Botho University, Maseru 100, LesothoAIDS and TB Programmes, Ministry of Health and Child Care, Harare 263, ZimbabweInternational Initiative for Impact Evaluation, Harare 263, Zimbabwe(1) Background: HIV drug resistance (HIVDR) poses a significant challenge to the effectiveness of antiretroviral therapy and the overall management of HIVand AIDS. Understanding the predictors of HIVDR is critical for developing strategies to mitigate its impact. The objectives of this study were to identify the predictors of HIVDR among Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA 2020) study participants, a national population-based survey. (2) Methods: Data from people living with HIV who participated in the ZIMPHIA 2020 were used to determine the predictors of HIVDR. (3) Results: The prevalence of HIVDR was 44.9%. Acquired HIVDR was present in 76.1% of people with a virological failure and transmitted resistance is 22.6% in naïve individuals. Factors associated with HIVDR in adjusted analysis were the number of lifetime sexual partners (aOR = 1.03, 95% CI: 1.01–1.06, <i>p</i> = 0.017), each additional year since the first HIV positive result (aOR = 1.17, 95% CI: 1.09–1.25, <i>p</i> < 0.01), each additional year on ART (aOR = 1.14, 95% CI: 1.06–1.23, <i>p</i> = 0.001), initiating ART before 2014 (aOR = 3.08, 95% CI: 1.72–5.49, <i>p</i> = 0.020), ever had switched antiretrovirals (aOR = 2.47, 95% CI: 1.15–5.29, <i>p</i> = 0.020) or had ever had a viral load test (aOR = 2.54, 95% CI: 1.54–4.17, <i>p</i> < 0.001) and a CD4 count < 350 (aOR = 2.04, 95% CI: 1.48–2.83, <i>p</i> < 0.01), while age ≥ 50 (aOR = 0.56, 95% CI: 0.32–0.98, 32 <i>p</i> = 0.04), condom use at last encounter (OR: 0.49, 95%CI: 0.33–0.73, <i>p</i> < 0.001), and not being on ART (aOR = 0.09, 95% CI: 0.06–0.13, <i>p</i> < 0.01) were associated with reduced odds of HIVDR. Conclusions: HIVDR was high among the participants. There is a need to address HIVDR and enhance the mechanisms already in place. This study introduces more information that would help in developing targeted interventions to prevent HIVDR and improve patient outcomes.https://www.mdpi.com/2414-6366/9/11/257HIVdrug resistancepredictorsZimbabweantiretroviral therapy |
| spellingShingle | Munyaradzi Mapingure Solomon Mukwenha Innocent Chingombe Rutendo Birri Makota Elliot Mbunge Enos Moyo Garikayi Chemhaka John Batani Brian Moyo Godfrey Musuka Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 Survey Tropical Medicine and Infectious Disease HIV drug resistance predictors Zimbabwe antiretroviral therapy |
| title | Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 Survey |
| title_full | Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 Survey |
| title_fullStr | Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 Survey |
| title_full_unstemmed | Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 Survey |
| title_short | Prevalence and Risk Factors of HIV Drug Resistance in Zimbabwe: Evidence from Zimbabwe Population-Based HIV Impact Assessment (ZIMPHIA) 2020 Survey |
| title_sort | prevalence and risk factors of hiv drug resistance in zimbabwe evidence from zimbabwe population based hiv impact assessment zimphia 2020 survey |
| topic | HIV drug resistance predictors Zimbabwe antiretroviral therapy |
| url | https://www.mdpi.com/2414-6366/9/11/257 |
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