Browsing by Author "Nyimbili S"

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Assessing regional variations and sociodemographic barriers in the progress toward UNAIDS 95-95-95 targets in Zimbabwe.
(2025-Apr-09) Chowdhury MDT; Bershteyn A; Milali M; Citron DT; Nyimbili S; Musuka G; Cuadros DF; Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA. diego.cuadros@uc.edu.; Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA.; Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.; International Initiative for Impact Evaluation, Harare, Zimbabwe.; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.
BACKGROUND: The HIV/AIDS epidemic remains critical in sub-Saharan Africa, with UNAIDS establishing "95-95-95" targets to optimize HIV care. Using the 2020 Zimbabwe Population-based HIV Impact Assessment (ZIMPHIA) geospatial data, this study aimed to identify patterns in these targets and determinants impacting the HIV care continuum in underserved Zimbabwean communities. METHODS: Analysis techniques, including Gaussian kernel interpolation, optimized hotspot, and multivariate geospatial k-means clustering, were utilized to establish spatial patterns and cluster regional HIV care continuum needs. Further, we investigated healthcare availability, access, and social determinants and scrutinized the association between socio-demographic and behavioral covariates with HIV care outcomes. RESULTS: Disparities in progress toward the "95-95-95" targets were noted across different regions, with each target demonstrating unique geographic patterns, resulting in four distinct clusters with specific HIV care needs. Key factors associated with gaps in achieving targets included younger age, male gender, employment, and minority or no religious affiliation. CONCLUSIONS: Our study uncovers significant spatial heterogeneity in the HIV care continuum in Zimbabwe, with unique regional patterns in "95-95-95" targets. The spatial analysis of the UNAIDS targets presented here could prove instrumental in designing effective control strategies by identifying vulnerable communities that are falling short of these targets and require intensified efforts. We provide insights for designing region-specific interventions and enhancing community-level factors, emphasizing the need to address regional gaps and improve HIV care outcomes in vulnerable communities that lag behind.
Geospatial Patterns of Progress towards UNAIDS "95-95-95" Targets and Community Vulnerability in Zambia.
(2023-Apr-26) Cuadros DF; Chowdhury T; Milali M; Citron D; Nyimbili S; Vlahakis N; Savory T; Mulenga L; Sivile S; Zyambo K; Bershteyn A; National HIV Program, Ministry of Health, Lusaka, Zambia.; Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.; Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA.; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.
In sub-Saharan Africa, HIV/AIDS remains a leading cause of death. The UNAIDS established the "95-95-95" targets to improve HIV care continuum outcomes. Using geospatial data from the Zambia Population-based HIV Impact Assessment (ZAMPHIA), this study aims to investigate geospatial patterns in the "95-95-95" indicators and individual-level determinants that impede HIV care continuum in vulnerable communities, providing insights into the factors associated with gaps. This study used data from the 2016 ZAMPHIA to investigate the geospatial distribution and individual-level determinants of engagement across the HIV care continuum in Zambia. Gaussian kernel interpolation and optimized hotspot analysis were used to identify geospatial patterns in the HIV care continuum, while geospatial k-means clustering was used to partition areas into clusters. The study also assessed healthcare availability, access, and social determinants of healthcare utilization. Multiple logistic regression models were used to examine the association between selected sociodemographic and behavioral covariates and the three main outcomes of study. Varied progress towards the "95-95-95" targets were observed in different regions of Zambia. Each "95" displayed a unique geographic pattern, independent of HIV prevalence, resulting in four distinct geographic clusters. Factors associated with gaps in the "95s" include younger age, male sex, and low wealth, with younger individuals having higher odds of not being on ART and having detectable viral loads. Our study revealed significant spatial heterogeneity in the HIV care continuum in Zambia, with different regions exhibiting unique geographic patterns and levels of performance in the "95-95-95" targets, highlighting the need for geospatial tailored interventions to address the specific needs of different subnational regions. These findings underscore the importance of addressing differential regional gaps in HIV diagnosis, enhancing community-level factors, and developing innovative strategies to improve local HIV care continuum outcomes.
Geospatial patterns of progress towards UNAIDS '95-95-95' targets and community vulnerability in Zambia: insights from population-based HIV impact assessments.
(2023-Oct) Cuadros DF; Chowdhury T; Milali M; Citron DT; Nyimbili S; Vlahakis N; Savory T; Mulenga L; Sivile S; Zyambo KD; Bershteyn A; Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.; National HIV Program, Ministry of Health, Lusaka, Zambia.; Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA.; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.; Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA diego.cuadros@uc.edu.
INTRODUCTION: In sub-Saharan Africa, HIV/AIDS remains a leading cause of death. The UNAIDS established the '95-95-95' targets to improve HIV care continuum outcomes. Using geospatial data from the Zambia Population-based HIV Impact Assessment (ZAMPHIA), this study aims to investigate geospatial patterns in the '95-95-95' indicators and individual-level determinants that impede HIV care continuum in vulnerable communities, providing insights into the factors associated with gaps. METHODS: This study used data from the 2016 ZAMPHIA to investigate the geospatial distribution and individual-level determinants of engagement across the HIV care continuum in Zambia. Gaussian kernel interpolation and optimised hotspot analysis were used to identify geospatial patterns in the HIV care continuum, while geospatial k-means clustering was used to partition areas into clusters. The study also assessed healthcare availability, access and social determinants of healthcare utilisation. Multiple logistic regression models were used to examine the association between selected sociodemographic and behavioural covariates and the three main outcomes of study. RESULTS: Varied progress towards the '95-95-95' targets were observed in different regions of Zambia. Each '95' displayed a unique geographical pattern, independent of HIV prevalence, resulting in four distinct geographical clusters. Factors associated with gaps in the '95s' include younger age, male sex, and low wealth, with younger individuals having higher odds of not being on antiretroviral therapy and having detectable viral loads. CONCLUSIONS: Our study revealed significant spatial heterogeneity in the HIV care continuum in Zambia, with different regions exhibiting unique geographical patterns and levels of performance in the '95-95-95' targets, highlighting the need for geospatial tailored interventions to address the specific needs of different subnational regions. These findings underscore the importance of addressing differential regional gaps in HIV diagnosis, enhancing community-level factors and developing innovative strategies to improve local HIV care continuum outcomes.
Interrupted time-series analysis of active case-finding for tuberculosis during the COVID-19 pandemic, Zambia.
(2022-Mar-01) Lungu PS; Kerkhoff AD; Muyoyeta M; Kasapo CC; Nyangu S; Kagujje M; Chimzizi R; Nyimbili S; Khunga M; Kasese-Chanda N; Musonda V; Tambatamba B; Kombe CM; Sakulanda C; Sampa K; Silumesii A; Malama K; National Tuberculosis and Leprosy Control Programme, Ministry of Health, Ndeke House, Haile-Selaise Road, PO Box 30205, Lusaka, Zambia.; United States Agency for International Development, Lusaka, Zambia.; Eradicate Tuberculosis Project, United States Agency for International Development, Lusaka, Zambia.; Ministry of Health, Lusaka, Zambia.; Division of HIV, Infectious Diseases and Global Medicine, University of California San Francisco, San Francisco, United States of America.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
OBJECTIVE: To evaluate the impact of the coronavirus disease 2019 (COVID-19) pandemic and the subsequent implementation of tuberculosis response measures on tuberculosis notifications in Zambia. METHODS: We used an interrupted time-series design to compare monthly tuberculosis notifications in Zambia before the pandemic (January 2019 to February 2020), after implementation of national pandemic mitigation measures (April 2020 to June 2020) and after response measures to improve tuberculosis detection (August 2020 to September 2021). The tuberculosis response included enhanced data surveillance, facility-based active case-finding and activities to generate demand for services. We used nationally aggregated, facility-level tuberculosis notification data for the analysis. FINDINGS: Pre-pandemic tuberculosis case notifications rose steadily from 2890 in January 2019 to 3337 in February 2020. After the start of the pandemic and mitigation measures, there was a -22% (95% confidence interval, CI: -24 to -19) immediate decline in notifications in April 2020. Larger immediate declines in notifications were seen among human immunodeficiency virus (HIV)-positive compared with HIV-negative individuals (-36%; 95% CI: -38 to -35; versus -12%; 95% CI: -17 to -6). Following roll-out of tuberculosis response measures in July 2020, notifications immediately increased by 45% (95% CI: 38 to 51) nationally and across all subgroups and provinces. The trend in notifications remained stable through September 2021, with similar numbers to the predicted number had the pandemic not occurred. CONCLUSION: Implementation of a coordinated public health response including active tuberculosis case-finding was associated with reversal of the adverse impact of the pandemic and mitigation measures. The gains were sustained throughout subsequent waves of the pandemic.
Progress Towards UNAIDS's 95-95-95 Targets in Zimbabwe: Sociodemographic Constraints and Geospatial Heterogeneity.
(2023-Jul-28) Chowdhury MT; Bershteyn A; Milali M; Citron D; Nyimbili S; Musuka G; Cuadros DF; International Initiative for Impact Evaluation, Harare, Zimbabwe.; Digital Epidemiology Laboratory, Digital Futures, University of Cincinnati, Cincinnati, OH, USA.; Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA.; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.
The HIV/AIDS epidemic remains critical in sub-Saharan Africa, with UNAIDS establishing "95-95-95" targets to optimize HIV care. Using the Zimbabwe Population-based HIV Impact Assessment (ZIMPHIA) geospatial data, this study aimed to identify patterns in these targets and determinants impacting the HIV care continuum in underserved Zimbabwean communities. Analysis techniques, including Gaussian kernel interpolation, optimized hotspot, and multivariate geospatial k-means clustering, were utilized to establish spatial patterns and cluster regional HIV care continuum needs. Further, we investigated healthcare availability, access, and social determinants and scrutinized the association between socio-demographic and behavioral covariates with HIV care outcomes. Disparities in progress toward the "95-95-95" targets were noted across different regions, with each target demonstrating unique geographic patterns, resulting in four distinct clusters with specific HIV care needs. Key factors associated with gaps in achieving targets included younger age, male sex, employment, and minority or no religious affiliation. Our study uncovers significant spatial heterogeneity in the HIV care continuum in Zimbabwe, with unique regional patterns in "95-95-95" targets. The spatial analysis of the UNAIDS targets presented here could prove instrumental in designing effective control strategies by identifying vulnerable communities that are falling short of these targets and require intensified efforts. Our result provides insights for designing region-specific interventions and enhancing community-level factors, emphasizing the need to address regional gaps and improve HIV care outcomes in vulnerable communities lagging behind.
Tuberculosis care cascade in Zambia - identifying the gaps in order to improve outcomes: a population-based analysis.
(2021-Aug-10) Lungu P; Kerkhoff AD; Kasapo CC; Mzyece J; Nyimbili S; Chimzizi R; Silumesii A; Kagujje M; Subbaraman R; Muyoyeta M; Malama K; Department of Public Health and Research, Ministry of Health, Lusaka, Zambia.; National Tuberculosis and Leprosy Control Programme, Lusaka, Zambia patrickpj456@yahoo.co.uk.; Tuberculosis Department, Center for Infectious Disease Research in Zambia, Lusaka, Zambia.; Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, USA.; National Tuberculosis and Leprosy Control Programme, Lusaka, Zambia.; Department of Internal Medicine, University Teaching Hospital, Lusaka, Zambia.; Ministry of Health, Lusaka, Zambia.; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, California, USA.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
OBJECTIVE: Tuberculosis (TB) remains a leading cause of morbidity and mortality in Zambia, especially for people living with HIV (PLHIV). We undertook a care cascade analysis to quantify gaps in care and align programme improvement measures with areas of need. DESIGN: Retrospective, population-based analysis. SETTING: We derived national-level estimates for each step of the TB care cascade in Zambia. Estimates were informed by WHO incidence estimates, nationally aggregated laboratory and notification registers, and individual-level programme data from four provinces. PARTICIPANTS: Participants included all individuals with active TB disease in Zambia in 2018. We characterised the overall TB cascade and disaggregated by drug susceptibility results and HIV status. RESULTS: In 2018, the total burden of TB in Zambia was estimated to be 72 495 (range, 40 495-111 495) cases. Of these, 43 387 (59.8%) accessed TB testing, 40 176 (55.4%) were diagnosed with TB, 36 431 (50.3%) were started on treatment and 32 700 (45.1%) completed treatment. Among all persons with TB lost at any step along the care cascade (n=39 795), 29 108 (73.1%) were lost prior to accessing diagnostic services, 3211 (8.1%) prior to diagnosis, 3745 (9.4%) prior to initiating treatment and 3731 (9.4%) prior to treatment completion. PLHIV were less likely than HIV-negative individuals to successfully complete the care cascade (42.8% vs 50.2%, p<0.001). Among those with rifampicin-resistant TB, there was substantial attrition at each step of the cascade and only 22.8% were estimated to have successfully completed treatment. CONCLUSIONS: Losses throughout the care cascade resulted in a large proportion of individuals with TB not completing treatment. Ongoing health systems strengthening and patient-centred engagement strategies are needed at every step of the care cascade; however, scale-up of active case finding strategies is particularly critical to ensure individuals with TB in the population reach initial stages of care. Additionally, a renewed focus on PLHIV and individuals with drug-resistant TB is urgently needed to improve TB-related outcomes in Zambia.