Integrated screening and treatment services for HIV, hypertension and diabetes in Kenya: assessing the epidemiological impact and cost-effectiveness from a national and regional perspective

Abstract

Introduction: As people with HIV age, prevention and management of other communicable and non-communicable diseases (NCDs) will become increasingly important. Integration of screening and treatment for HIV and NCDs is a promising approach for addressing the dual burden of these diseases. The aim of this study was to assess the epidemiological impact and cost-effectiveness of a community-wide integrated programme for screening and treatment of HIV, hypertension and diabetes in Kenya.

Methods: Coupling a microsimulation of cardiovascular diseases (CVDs) with a population-based model of HIV dynamics (the Spectrum), we created a hybrid HIV/CVD model. Interventions were modelled from year 2019 (baseline) to 2023, and population was followed to 2033. Analyses were carried at a national level and for three selected regions (Nairobi, Coast and Central).

Results: At a national level, the model projected 7.62 million individuals living with untreated hypertension, 692,000 with untreated diabetes and 592,000 individuals in need of ART in year 2018. Improving ART coverage from 68% at baseline to 88% in 2033 reduced HIV incidence by an estimated 64%. Providing NCD treatment to 50% of diagnosed cases from 2019 to 2023 and maintaining them on treatment afterwards could avert 116,000 CVD events and 43,600 CVD deaths in Kenya over the next 15 years. At a regional level, the estimated impact of expanded HIV services was highest in Nairobi region (averting 42,100 HIV infections compared to baseline) while Central region experienced the highest impact of expanded NCD treatment (with a reduction of 22,200 CVD events). The integrated HIV/NCD intervention could avert 7.76 million disability-adjusted-life-years (DALYs) over 15 years at an estimated cost of $6.68 billion ($445.27 million per year), or $860.30 per DALY averted. At a cost-effectiveness threshold of $2,010 per DALY averted, the probability of cost-effectiveness was 0.92, ranging from 0.71 in Central to 0.92 in Nairobi region.

Conclusions: Integrated screening and treatment of HIV and NCDs can be a cost-effective and impactful approach to save lives of people with HIV in Kenya, although important variation exists at the regional level. Containing the substantial costs required for scale-up will be critical for management of HIV and NCDs on a national scale.

Keywords: HIV; Kenya; computer simulation; cost-benefit analysis; diabetes mellitus; hypertension.

Figure 1

Hybrid HIV/CVD model overview. Panel A illustrates the method for defining eight cardiovascular disease (CVD) risk categories using data from the 2015 STEPwise survey in Kenya. Panel B shows the schematic model of CVD events, namely cardiac arrest (CA), angina, myocardial infarction (MI) and stroke. Following a CVD event, individuals experience a probability of acute mortality in the first year. If they survive, they subsequently move to a post‐event state in which they experience an increased annual risk of mortality, risk of new/repeated CVD events, and disability for future life years lived in the model. Dashed arrows showed in orange mark the risk of stroke among those in post‐cardiovascular heart disease (CHD) states. Panel C shows the relationships and flow of information between Spectrum and the HIV/CVD microsimulation. Panel D shows the simulation timeline, starting in year 2019 and ending in 2033. Annual outputs from the Spectrum model are used to inform the demographic processes and HIV dynamics in the HIV/CVD microsimulation. To ensure a precision of results, the baseline and intervention scenarios are modelled across 2000 random simulations. All outcomes are reported as median values across these simulations.

Figure 2

Projected outcomes from combined HIV/NCD diagnosis and management in Kenya. The intervention runs from 2019‐2023, screening 20% of the population on an annual basis for HIV, hypertension and diabetes. Panel A shows the annual number of people diagnosed with hypertension and/or diabetes. The intervention further provides treatment to a proportion of those diagnosed with HIV, hypertension and/or diabetes. Panel B shows the number of individuals receiving treatment for hypertension and/or diabetes over time. Costs are divided into two groups, including additional costs required for disease screening and treatment (Panel C) and costs saved by averting future CVD events (Panel D). ART, antiretroviral therapy; NCD, non‐communicable diseases; CVD, cardiovascular disease.

Figure 3

Cost‐effectiveness acceptability curves for integrated HIV and NCD diagnosis and management in Kenya. The x‐axis shows the cost per disability‐adjusted life year (DALY) averted by the intervention, and the y‐axis shows the proportion of stochastic simulations falling below the corresponding cost‐effectiveness threshold. Vertical lines represent alternative thresholds for evaluating cost‐effectiveness at $500, $1000 and $2010 (Kenya’s 2019 per‐capita gross domestic product). NCD, non‐communicable diseases.

Figure 4

One‐way sensitivity analysis to value of selected model parameters. Panels show the sensitivity of epidemiological outputs, including the number of CVD events (panel A) and deaths (panel B) averted, and costing outcomes, including the incremental cost of intervention (panel C) and DALYs averted (panel D), under one‐way variation in the value of selected model parameters. Each parameter value is followed by an up/down arrow, denoting a 15% increase (circle marks) or decrease (square marks) in the input parameter value as listed in Table 3. Each scenario is simulated starting in year 2019 and is followed to year 2033. The bars and arrows represent the median and interquartile ranges across 500 simulations. The triangle mark and dashed line represent the main model with no parameter variation. The results are summarized by showing the ten parameters for which variation resulted in the largest variations from the main model (decreasing impact from top to bottom. CVD, cardiovascular disease; NCD, non‐communicable diseases; DALY, disability‐adjusted life year; ART, antiretroviral therapy.