Browsing by Author "Haushona, Ndamonaonghenda"

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    An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk
    (2020) Haushona, Ndamonaonghenda; Esterhuizen, Tonya M; Thabane, Lehana
    Introduction: Competing risks arise when subjects are exposed to multiple mutually exclusive failure events, and the occurrence of one failure hinders the occurrence of other failure events. In the presence of competing risks, it is important to use methods accounting for competing events because failure to account for these events might result in misleading inferences. Methods and Objective: Using data from a multisite retrospective observational longitudinal study done in Ethiopia, we performed sensitivity analyses using Fine-Gray model, Cause-specific Cox (Cox-CSH) model, Cause-specific Accelerated Failure Time (CS-AFT) model, accounting for death as a competing risk to deter- mine baseline covariates that are associated with a composite of unfavourable retention in care outcomes in people living with Human Immune Virus who were on both Isoniazid preventive therapy (IPT) and antiretrovi- ral therapy (ART). Non-cause specific (non-CSH) model that does not account for competing risk was also per- formed. The composite outcome comprises of loss to follow-up, stopped treatment and death. Age, World Health Organisation (WHO) stage, gender, and CD4 count were the considered baseline covariates. Results: We included 3578 patients in our analysis. WHO stage III-or-IV was significantly associated with the composite of unfavourable outcomes, Sub-hazard ratio (SHR) = 1.31, 95% confidence interval (CI):1.04–1.65 for the sub-distribution hazard model, hazard ratio [HR] = 1.31, 95% CI:1.05–1.65, for the Cox-CSH model, and HR = 0.81, 95% CI:0.69–0.96, for the CS-AFT model. Gender and WHO stage were found to be signifi- cantly associated with the composite of unfavourable outcomes, HR = 1.56, 95% CI:1.27–1.90, HR = 1.28, 95% CI: 1.06–1.55 for males and WHO stage III-or-IV, respectively for the non-CSH model. Conclusions: Results show that WHO stage III-or-IV is significantly associated with unfavourable outcomes. The results from competing risk models were consistent. However, results obtained from the non-CSH model were inconsistent with those obtained from competing risk analysis models.
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    A scoping review of spatial analysis approaches using health survey data in Sub-Saharan Africa
    (MDPI, 2020-04) Manda, Samuel; Haushona, Ndamonaonghenda; Bergquist, Robert
    Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.