TY - JOUR
T1 - Recommendations for the use of mathematical modelling to support decision-making on integration of non-communicable diseases into HIV care
AU - Kibachio, Joseph
AU - Mwenda, Valerian
AU - Ombiro, Oren
AU - Kamano, Jamima H.
AU - Perez-Guzman, Pablo N.
AU - Mutai, Kennedy K.
AU - Guessous, Idris
AU - Beran, David
AU - Kasaie, Paratsu
AU - Weir, Brian
AU - Beecroft, Blythe
AU - Kilonzo, Nduku
AU - Kupfer, Linda
AU - Smit, Mikaela
N1 - Funding Information:
This articles as part of the Integrating services for HIV and related comorbidities: modelling to inform policy and practice Supplement, was supported by the US National Institutes of Health, Fogarty International Center. We acknowledge joint Centre funding from the UK Medical Research Council and Department for International Development, the Civilian Research and Development Foundation Global (grant number OISE-9531011), and the National Institute of Health (grant number 1R21AG053093-01). This articles as part of the Integrating services for HIV and related comorbidities: modelling to inform policy and practice Supplement, was supported by the US National Institutes of Health, Fogarty International Center. We acknowledge joint Centre funding from the UK Medical Research Council and Department for International Development, the Civilian Research and Development Foundation Global (grant number OISE-9531011), and the National Institute of Health (grant number 1R21AG053093-01).
Funding Information:
This articles as part of the Supplement, was supported by the US National Institutes of Health, Fogarty International Center. We acknowledge joint Centre funding from the UK Medical Research Council and Department for International Development, the Civilian Research and Development Foundation Global (grant number OISE‐9531011), and the National Institute of Health (grant number 1R21AG053093‐01). Integrating services for HIV and related comorbidities: modelling to inform policy and practice
Publisher Copyright:
© 2020 The Authors. Journal of the International AIDS Society published by John Wiley & Sons Ltd on behalf of the International AIDS Society.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - 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.
AB - 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.
KW - HIV
KW - Kenya
KW - integration
KW - modelling
KW - non-communicable diseases
KW - policy
UR - http://www.scopus.com/inward/record.url?scp=85086650595&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086650595&partnerID=8YFLogxK
U2 - 10.1002/jia2.25505
DO - 10.1002/jia2.25505
M3 - Comment/debate
C2 - 32562338
AN - SCOPUS:85086650595
SN - 1758-2652
VL - 23
JO - Journal of the International AIDS Society
JF - Journal of the International AIDS Society
IS - S1
M1 - e25505
ER -