Recommendations for the use of mathematical modelling to support decision-making on integration of non-communicable diseases into HIV care

Tackling syndemics by integrating infectious and noncommunicable diseases in health systems of low- and middle-income countries: A narrative systematic review

The co-occurrence of infectious diseases (ID) and non-communicable diseases (NCD) is widespread, presenting health service delivery challenges especially in low-and middle-income countries (LMICs). Integrated health care is a possible solution but may require a paradigm shift to be successfully implemented. This literature review identifies integrated care examples among selected ID and NCD dyads. We searched PubMed, PsycINFO, Cochrane Library, CINAHL, Web of Science, EMBASE, Global Health Database, and selected clinical trials registries. Eligible studies were published between 2010 and December 2022, available in English, and report health service delivery programs or policies for the selected disease dyads in LMICs. We identified 111 studies that met the inclusion criteria, including 56 on tuberculosis and diabetes integration, 46 on health system adaptations to treat COVID-19 and cardiometabolic diseases, and 9 on COVID-19, diabetes, and tuberculosis screening. Prior to the COVID-19 pandemic, most studies on diabetes-tuberculosis integration focused on clinical service delivery screening. By far the most reported health system outcomes across all studies related to health service delivery (n = 72), and 19 addressed health workforce. Outcomes related to health information systems (n = 5), leadership and governance (n = 3), health financing (n = 2), and essential medicines (n = 4)) were sparse. Telemedicine service delivery was the most common adaptation described in studies on COVID-19 and either cardiometabolic diseases or diabetes and tuberculosis. ID-NCD integration is being explored by health systems to deal with increasingly complex health needs, including comorbidities. High excess mortality from COVID-19 associated with NCD-related comorbidity prompted calls for more integrated ID-NCD surveillance and solutions. Evidence of clinical integration of health service delivery and workforce has grown-especially for HIV and NCDs-but other health system building blocks, particularly access to essential medicines, health financing, and leadership and governance, remain in disease silos.

Gaussian process emulation to improve efficiency of computationally intensive multidisease models: a practical tutorial with adaptable R code

BACKGROUND

The rapidly growing burden of non-communicable diseases (NCDs) among people living with HIV in sub-Saharan Africa (SSA) has expanded the number of multidisease models predicting future care needs and health system priorities. Usefulness of these models depends on their ability to replicate real-life data and be readily understood and applied by public health decision-makers; yet existing simulation models of HIV comorbidities are computationally expensive and require large numbers of parameters and long run times, which hinders their utility in resource-constrained settings.

METHODS

We present a novel, user-friendly emulator that can efficiently approximate complex simulators of long-term HIV and NCD outcomes in Africa. We describe how to implement the emulator via a tutorial based on publicly available data from Kenya. Emulator parameters relating to incidence and prevalence of HIV, hypertension and depression were derived from our own agent-based simulation model and other published literature. Gaussian processes were used to fit the emulator to simulator estimates, assuming presence of noise for design points. Bayesian posterior predictive checks and leave-one-out cross validation confirmed the emulator's descriptive accuracy.

RESULTS

In this example, our emulator resulted in a 13-fold (95% Confidence Interval (CI): 8-22) improvement in computing time compared to that of more complex chronic disease simulation models. One emulator run took 3.00 seconds (95% CI: 1.65-5.28) on a 64-bit operating system laptop with 8.00 gigabytes (GB) of Random Access Memory (RAM), compared to > 11 hours for 1000 simulator runs on a high-performance computing cluster with 1500 GBs of RAM. Pareto k estimates were < 0.70 for all emulations, which demonstrates sufficient predictive accuracy of the emulator.

CONCLUSIONS

The emulator presented in this tutorial offers a practical and flexible modelling tool that can help inform health policy-making in countries with a generalized HIV epidemic and growing NCD burden. Future emulator applications could be used to forecast the changing burden of HIV, hypertension and depression over an extended (> 10 year) period, estimate longer-term prevalence of other co-occurring conditions (e.g., postpartum depression among women living with HIV), and project the impact of nationally-prioritized interventions such as national health insurance schemes and differentiated care models.

Prevalence and factors associated with hypertension among peoples living with HIV in East Africa, a systematic review and meta-analysis

BACKGROUND

In recent years, improved access to effective antiretroviral therapy has meant that people living with human immune virus are living longer than before. The burden of non-communicable diseases particularly, hypertension parallels with the increase in age. Although hypertension screening is thought to be an effective indicator of overall health status and paves the way for early interventions in peoples living with human immune virus, the exact prevalence of hypertension in this population remained unknown. We aimed to report the prevalence of hypertension and examine the factors associated with hypertension among people living with human immune virus in East Africa.

METHODS

In this systematic review and meta-analysis, we searched PubMed, Science Direct, Scopus, Cochrane library, and Google Scholar databases for studies published until January 1, 2023. The search period was from January 10/2023, to February 10/ 2023. Random-effect models were used to calculate the pooled prevalence of hypertension. Subgroup analyses were conducted to explore potential heterogeneity. The Funnel plot and Egger's test were used to assess publication bias.

RESULT

A total of 15 studies with 10,916 individuals were included in the present meta-analysis. The pooled prevalence of hypertension among people living with human immune virus was19.75% (95% CI, 16.07%-23.42%)),). The prevalence of hypertension was not differed between studies conducted 2014- 2019 and, studies conducted 2020-2022. The prevalence of hypertension was lowest in Ethiopia (16.13%) and highest in Tanzania (26.76%). Alcohol consumption (Adjusted Odds Ratio (AOR): 3.39, 95% CI: 2.35-4.43), diabetes (AOR: 2.64, 95% CI: 1.89-3.39), longer duration of HIV (AOR: 1.72, 95% CI: 1.15-2.3), male sex (AOR: 1.62, 95% CI: 1.43-1.8), obesity (AOR: 2.89, 95% CI: 1.94-3.84), and older age (AOR: 2.25, 95% CI: 2.0-2.5), were the factors associated with the presence of hypertension in people living with human immune virus.

CONCLUSION

Our study shows that one in five peoples living with human immune virus have hypertension causing symptoms and impairment, therefore requiring treatment. Designing effective health screening and hypertension management intervention programs helps to prevent the occurrence of hypertension and promotes peoples' overall quality of life.

Impacts of timing, length, and intensity of behavioral interventions to COVID-19 dynamics: North Carolina county-level examples

We sought to examine how the impact of revocable behavioral interventions, e.g., shelter-in-place, varies throughout an epidemic, as well as the role that the proportion of susceptible individuals had on an intervention's impact. We estimated the theoretical impacts of start day, length, and intensity of interventions on disease transmission and illustrated them on COVID-19 dynamics in Wake County, North Carolina, to inform how interventions can be most effective. We used a Susceptible, Exposed, Infectious, and Recovered (SEIR) model to estimate epidemic curves with modifications to the disease transmission parameter (β). We designed modifications to simulate events likely to increase transmission (e.g., long weekends, holiday seasons) or behavioral interventions likely to decrease it (e.g., shelter-in-place, masking). We compared the resultant curves' shape, timing, and cumulative case count to baseline and across other modified curves. Interventions led to changes in COVID-19 dynamics, including moving the peak's location, height, and width. The proportion susceptible, at the start day, strongly influenced their impact. Early interventions shifted the curve, while interventions near the peak modified shape and case count. For some scenarios, in which the transmission parameter was decreased, the final cumulative count increased over baseline. We showed that the timing of revocable interventions has a strong impact on their effect. The same intervention applied at different time points, corresponding to different proportions of susceptibility, resulted in qualitatively differential effects. Accurate estimation of the proportion susceptible is critical for understanding an intervention's impact. The findings presented here provide evidence of the importance of estimating the proportion of the population that is susceptible when predicting the impact of behavioral infection control interventions. Greater emphasis should be placed on the estimation of this epidemic component in intervention design and decision-making. Our results are generic and are applicable to other infectious disease epidemics, as well as to future waves of the current COVID-19 epidemic. Developed into a publicly available tool that allows users to modify the parameters to estimate impacts of different interventions, these models could aid in evaluating behavioral intervention options prior to their use and in predicting case increases from specific events.

Patient-Centered, Sustainable Hypertension Care: The Case for Adopting a Differentiated Service Delivery Model for Hypertension Services in Low- and Middle-Income Countries

Expanding hypertension services in low- and middle-income countries requires efficient and effective service delivery approaches that meet the needs and expectations of people living with hypertension within the resource constraints of existing national health systems. Ideally, a hypertension program will extend treatment coverage while maintaining service quality, maximizing efficient resource utilization and improving clinical outcomes. In this article, we discuss lessons learned from HIV differentiated service delivery initiatives, and make the case that the same approach should be adopted for hypertension programs.

Association between HIV infection and hypertension: a global systematic review and meta-analysis of cross-sectional studies

BACKGROUND

Improved access to effective antiretroviral therapy has meant that people living with HIV (PLHIV) are surviving to older ages. However, PLHIV may be ageing differently to HIV-negative individuals, with dissimilar burdens of non-communicable diseases, such as hypertension. While some observational studies have reported a higher risk of prevalent hypertension among PLHIV compared to HIV-negative individuals, others have found a reduced burden. To clarify the relationship between HIV and hypertension, we identified observational studies and pooled their results to assess whether there is a difference in hypertension risk by HIV status.

METHODS

We performed a global systematic review and meta-analysis of published cross-sectional studies that examined hypertension risk by HIV status among adults aged > 15 (PROSPERO: CRD42019151359). We searched MEDLINE, EMBASE, Global Health and Cochrane CENTRAL to August 23, 2020, and checked reference lists of included articles. Our main outcome was the risk ratio for prevalent hypertension in PLHIV compared to HIV-negative individuals. Summary estimates were pooled with a random effects model and meta-regression explored whether any difference was associated with study-level factors.

RESULTS

Of 21,527 identified studies, 59 were eligible (11,101,581 participants). Crude global hypertension risk was lower among PLHIV than HIV-negative individuals (risk ratio 0.90, 95% CI 0.85-0.96), although heterogeneity between studies was high (I² = 97%, p < 0.0001). The relationship varied by continent, with risk higher among PLHIV in North America (1.12, 1.02-1.23) and lower among PLHIV in Africa (0.75, 0.68-0.83) and Asia (0.77, 0.63-0.95). Meta-regression revealed strong evidence of a difference in risk ratios when comparing North American and European studies to African ones (North America 1.45, 1.21-1.74; Europe 1.20, 1.03-1.40).

CONCLUSIONS

Our findings suggest that the relationship between HIV status and prevalent hypertension differs by region. The results highlight the need to tailor hypertension prevention and care to local contexts and underscore the importance of rapidly optimising integration of services for HIV and hypertension in the worst affected regions. The role of different risk factors for hypertension in driving context-specific trends remains unclear, so development of further cohorts of PLHIV and HIV-negative controls focused on this would also be valuable.

Recommendations for the use of mathematical modelling to support decision-making on integration of non-communicable diseases into HIV care

INTRODUCTION

Integrating services for non-communicable diseases (NCDs) into existing primary care platforms such as HIV programmes has been recommended as a way of strengthening health systems, reducing redundancies and leveraging existing systems to rapidly scale-up underdeveloped programmes. Mathematical modelling provides a powerful tool to address questions around priorities, optimization and implementation of such programmes. In this study, we examine the case for NCD-HIV integration, use Kenya as a case-study to highlight how modelling has supported wider policy formulation and decision-making in healthcare and to collate stakeholders' recommendations on use of models for NCD-HIV integration decision-making.

DISCUSSION

Across Africa, NCDs are increasingly posing challenges for health systems, which historically focused on the care of acute and infectious conditions. Pilot programmes using integrated care services have generated advantages for both provider and user, been cost-effective, practical and achieve rapid coverage scale-up. The shared chronic nature of NCDs and HIV means that many operational approaches and infrastructure developed for HIV programmes apply to NCDs, suggesting this to be a cost-effective and sustainable policy option for countries with large HIV programmes and small, un-resourced NCD programmes. However, the vertical nature of current disease programmes, policy financing and operations operate as barriers to NCD-HIV integration. Modelling has successfully been used to inform health decision-making across a number of disease areas and in a number of ways. Examples from Kenya include (i) estimating current and future disease burden to set priorities for public health interventions, (ii) forecasting the requisite investments by government, (iii) comparing the impact of different integration approaches, (iv) performing cost-benefit analysis for integration and (v) evaluating health system capacity needs.

CONCLUSIONS

Modelling can and should play an integral part in the decision-making processes for health in general and NCD-HIV integration specifically. It is especially useful where little data is available. The successful use of modelling to inform decision-making will depend on several factors including policy makers' comfort with and understanding of models and their uncertainties, modellers understanding of national priorities, funding opportunities and building local modelling capacity to ensure sustainability.