Geospatial patterns of progress towards UNAIDS '95-95-95' targets and community vulnerability in Zambia: insights from population-based HIV impact assessments.

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.

Progress Towards UNAIDS's 95-95-95 Targets in Zimbabwe: Sociodemographic Constraints and Geospatial Heterogeneity.

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.

Geospatial Patterns of Progress towards UNAIDS "95-95-95" Targets and Community Vulnerability in 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.

Interrupted time-series analysis of active case-finding for tuberculosis during the COVID-19 pandemic, Zambia.

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.

Interrupted time-series analysis of active case-finding for tuberculosis during the COVID-19 pandemic, Zambia

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.

Tuberculosis care cascade in Zambia - identifying the gaps in order to improve outcomes: a population-based analysis.

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.

Risk and Protective Factors for Cholera Deaths during an Urban Outbreak-Lusaka, Zambia, 2017-2018.

The Republic of Zambia declared a cholera outbreak in Lusaka, the capital, on October 6, 2017. By mid-December, 20 of 661 reported cases had died (case fatality rate 3%), prompting the CDC and the Zambian Ministry of Health through the Zambia National Public Health Institute to investigate risk factors for cholera mortality. We conducted a study of cases (cholera deaths from October 2017 to January 2018) matched by age-group and onset date to controls (persons admitted to a cholera treatment center [CTC] and discharged alive). A questionnaire was administered to each survivor (or relative) and to a family member of each decedent. We used univariable exact conditional logistic regression to calculate matched odds ratios (mORs) and 95% CIs. In the analysis, 38 decedents and 76 survivors were included. Median ages for decedents and survivors were 38 (range: 0.5-95) and 25 (range: 1-82) years, respectively. Patients aged > 55 years and those who did not complete primary school had higher odds of being decedents (matched odds ratio [mOR] 6.3, 95% CI: 1.2-63.0, P = 0.03; mOR 8.6, 95% CI: 1.8-81.7, P < 0.01, respectively). Patients who received immediate oral rehydration solution (ORS) at the CTC had lower odds of dying than those who did not receive immediate ORS (mOR 0.1, 95% CI: 0.0-0.6, P = 0.02). Cholera prevention and outbreak response should include efforts focused on ensuring access to timely, appropriate care for older adults and less educated populations at home and in health facilities.

Factors associated with unfavourable tuberculosis treatment outcomes in Lusaka, Zambia, 2015: a secondary analysis of routine surveillance data.

INTRODUCTION: Focus has been put on strengthening surveillance systems in high tuberculosis (TB) burden countries, like Zambia, however inadequate information on factors associated with unfavourable TB treatment outcomes is generated from the system. We determined the proportion of tuberculosis treatment outcomes and their associated factors. METHODS: We defined unfavourable outcome as death, lost-to-follow-up, treatment-failure, or not-evaluated and favourable outcome as a patient cured or completed-treatment. We purposively selected a 1st level hospital, an urban-clinic and a peri-urban clinic. We abstracted data from TB treatment registers at these three health facilities, for all TB cases on treatment from 1st January to 31st December, 2015. We calculated proportions of treatment outcomes and analysed associations between unfavourable outcome and factors such as age, HIV status, health facility, and patient type, using univariate logistics regression. We used multivariable stepwise logistic regression to control for confounding and reported the adjusted odds ratios (AOR) and 95% confidence intervals (CI). RESULTS: We included a total of 1,724 registered TB patients, from one urban clinic 694 (40%), a 1st Level Hospital 654 (38%), and one peri-urban-clinic 276 (22%). Of the total patients, 43% had unfavourable outcomes. Of the total unfavourable outcomes, were recorded as treatment-failure (0.3%), lost-to-follow-up (5%), death (9%) and not evaluated (29%). The odds of unfavourable outcome were higher among patients > 59 years (AOR=2.9, 95%CI: 1.44-5.79), relapses (AOR=1.65, 95%CI: 1.15-2.38), patients who sought treatment at the urban clinic (AOR=1.76, 95%CI:1.27-2.42) and TB/HIV co-infected patients (AOR=1.56, 95%CI:1.11-2.19). CONCLUSION: Unfavourable TB treatment outcomes were high in the selected facilities. We recommend special attention to TB patients who are > 59 years old, TB relapses and TB / HIV co-infected. The national TB programme should strengthen close monitoring of health facilities in increasing efforts aimed at evaluating all the outcomes. Studies are required to identify and test interventions aimed at improving treatment outcomes.

Cholera Epidemic - Lusaka, Zambia, October 2017-May 2018.

On October 6, 2017, an outbreak of cholera was declared in Zambia after laboratory confirmation of Vibrio cholerae O1, biotype El Tor, serotype Ogawa, from stool specimens from two patients with acute watery diarrhea. The two patients had gone to a clinic in Lusaka, the capital city, on October 4. Cholera cases increased rapidly, from several hundred cases in early December 2017 to approximately 2,000 by early January 2018 (Figure). In collaboration with partners, the Zambia Ministry of Health (MoH) launched a multifaceted public health response that included increased chlorination of the Lusaka municipal water supply, provision of emergency water supplies, water quality monitoring and testing, enhanced surveillance, epidemiologic investigations, a cholera vaccination campaign, aggressive case management and health care worker training, and laboratory testing of clinical samples. In late December 2017, a number of water-related preventive actions were initiated, including increasing chlorine levels throughout the city's water distribution system and placing emergency tanks of chlorinated water in the most affected neighborhoods; cholera cases declined sharply in January 2018. During January 10-February 14, 2018, approximately 2 million doses of oral cholera vaccine were administered to Lusaka residents aged ≥1 year. However, in mid-March, heavy flooding and widespread water shortages occurred, leading to a resurgence of cholera. As of May 12, 2018, the outbreak had affected seven of the 10 provinces in Zambia, with 5,905 suspected cases and a case fatality rate (CFR) of 1.9%. Among the suspected cases, 5,414 (91.7%), including 98 deaths (CFR = 1.8%), occurred in Lusaka residents.