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Research article
ART coverage and viral load suppression rates as correlates to HIV positivity in Kenya; Spatial-temporal analyses 2015-17
Anthony Waruru
Centers for Disease Control and Prevention
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4281-6345
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Introduction
High antiretroviral therapy (ART) coverage and high rates of viral load suppression (VLS) should reduce transmission of HIV, and ultimately, HIV incidence and the number of new HIV diagnoses out of the number tested (HIV positivity). We used 3 years of HIV program data in Kenya to assess whether trends in the number of new HIV diagnoses were associated with ART coverage and VLS rates and spatial-temporally auto-correlated at county level.
Methods
We analyzed routine program county-level aggregate data on ART coverage and VLS (proportion of persons on ART with VL<1000 copies/mL) from 3 years (2015-2017). We examined the association between ART coverage and VLS rates to HIV positivity by fitting spatial and spatial-temporal semi-parametric Poisson regression models using R-Integrated Nested Laplace Approximation (INLA) package. We used the extended Cochran-Mantel-Haenszel stratified test of association to test for trend for rates across years and Kruskal-Wallis equality-of-populations nonparametric rank test to compare medians for continuous variables. We fit a structural equation model to assess direct and total effects between the two exogenous covariates to adjusted newly HIV-diagnosed as the endogenous variable adjusting for clustering by 47 counties. Finally, we mapped adjusted HIV positivity using QGIS version 3.2.
Results and discussion
A spatial-temporal model with covariates was better in explaining geographical variation in HIV positivity (deviance information criterion (DIC) 381.2), than either a non-temporal spatial model (DIC 418.6) or temporal model without covariates (DIC 449.2). Overall, the adjusted HIV positivity decreased over 3 years from median of 2.9% in 2015, [interquartile range (IQR): 1.9-3.4] to 1.5% in 2017, IQR(1.3-2.0), p=0.032. While adjusting for clustering and covariance, VLS had a direct effect on HIV positivity rates p=0.004, but ART coverage did not, p=0.843.
Conclusions
From 2015-2017, there has been improved ART coverage and sustained VL coverage and suppression rates. We have observed a general decline of rates of HIV positivity associated with VLS rates. To assess the trends and impact of implementation of scaled-up care and treatment, spatial-temporal analyses help to identify geographic areas that need focused interventions.
Keywords
ART coverage, viral load suppression rates, HIV positivity, spatial, spatial-temporal, structural equation model, Kenya
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This is a preprint. It has not completed peer review.
Research article
ART coverage and viral load suppression rates as correlates to HIV positivity in Kenya; Spatial-temporal analyses 2015-17
Anthony Waruru
Centers for Disease Control and Prevention
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4281-6345
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 20 Jan, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Infectious Diseases
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Introduction
High antiretroviral therapy (ART) coverage and high rates of viral load suppression (VLS) should reduce transmission of HIV, and ultimately, HIV incidence and the number of new HIV diagnoses out of the number tested (HIV positivity). We used 3 years of HIV program data in Kenya to assess whether trends in the number of new HIV diagnoses were associated with ART coverage and VLS rates and spatial-temporally auto-correlated at county level.
Methods
We analyzed routine program county-level aggregate data on ART coverage and VLS (proportion of persons on ART with VL<1000 copies/mL) from 3 years (2015-2017). We examined the association between ART coverage and VLS rates to HIV positivity by fitting spatial and spatial-temporal semi-parametric Poisson regression models using R-Integrated Nested Laplace Approximation (INLA) package. We used the extended Cochran-Mantel-Haenszel stratified test of association to test for trend for rates across years and Kruskal-Wallis equality-of-populations nonparametric rank test to compare medians for continuous variables. We fit a structural equation model to assess direct and total effects between the two exogenous covariates to adjusted newly HIV-diagnosed as the endogenous variable adjusting for clustering by 47 counties. Finally, we mapped adjusted HIV positivity using QGIS version 3.2.
Results and discussion
A spatial-temporal model with covariates was better in explaining geographical variation in HIV positivity (deviance information criterion (DIC) 381.2), than either a non-temporal spatial model (DIC 418.6) or temporal model without covariates (DIC 449.2). Overall, the adjusted HIV positivity decreased over 3 years from median of 2.9% in 2015, [interquartile range (IQR): 1.9-3.4] to 1.5% in 2017, IQR(1.3-2.0), p=0.032. While adjusting for clustering and covariance, VLS had a direct effect on HIV positivity rates p=0.004, but ART coverage did not, p=0.843.
Conclusions
From 2015-2017, there has been improved ART coverage and sustained VL coverage and suppression rates. We have observed a general decline of rates of HIV positivity associated with VLS rates. To assess the trends and impact of implementation of scaled-up care and treatment, spatial-temporal analyses help to identify geographic areas that need focused interventions.
Figure 1
Figure 2
Figure 3