Availability and use of long-acting insulin analogues including their biosimilars across Africa; findings and implications

Background: Prevalence rates of diabetes mellitus are growing across Africa with an appreciable number likely to be on insulin to manage their condition. This has significant implications on future morbidity and mortality exacerbated by high complication rates. Complication rates in patients requiring insulins are enhanced by hypoglycaemia. Long-acting insulin analogues were developed to reduce hypoglycaemia and improve patient compliance. However, they are typically appreciably more expensive than human and other insulins in Africa, and continuing controversies surrounding their benefits limits their listing on national essential medicine lists (EMLs). Biosimilars can reduce the prices long-acting insulin analogues. This needs assessing. Methods: Mixed methods approach including documentation of insulin utilisation patterns and prices among a range of African countries. In addition, input from senior level government, academic, and healthcare professionals from across Africa on the current situation with long-acting insulin analogues as well as potential changes needed to enhance future funding of long-acting analogue biosimilars. Results: There is variable listing of long-acting insulin analogues on national EMLs across Africa due to their high prices and issues of affordability. Even when listed, utilisation of long-acting insulin analogues is limited by similar issues including affordability. Appreciably lowering the prices of long-acting insulin analogues via biosimilars should enhance future listing on EMLs and use accompanied by educational and other initiatives. However, this will require increased competition to lower prices. Conclusion: There are concerns with value and funding of long-acting insulin analogues across Africa including biosimilars. A number of activities have been identified to improve future funding and listing on EMLs

Application of decision analytical models to diabetes in low- and middle-income countries : a systematic review

Background: Decision analytical models (DAMs) are used to develop an evidence base for impact and health economic evaluations, including evaluating interventions to improve diabetes care and health service—an increasingly important area in low- and middle-income countries (LMICs), where the disease burden is high, health systems are weak, and resources are constrained. This study examines how DAMs–in particular, Markov, system dynamic, agent-based, discrete event simulation, and hybrid models–have been applied to investigate non-pharmacological population-based (NP) interventions and how to advance their adoption in diabetes research in LMICs. Methods: We systematically searched peer-reviewed articles published in English from inception to 8th August 2022 in PubMed, Cochrane, and the reference list of reviewed articles. Articles were summarised and appraised based on publication details, model design and processes, modelled interventions, and model limitations using the Health Economic Evaluation Reporting Standards (CHEERs) checklist. Results: Twenty-three articles were fully screened, and 17 met the inclusion criteria of this qualitative review. The majority of the included studies were Markov cohort (7, 41%) and microsimulation models (7, 41%) simulating non-pharmacological population-based diabetes interventions among Asian sub-populations (9, 53%). Eleven (65%) of the reviewed studies evaluated the cost-effectiveness of interventions, reporting the evaluation perspective and the time horizon used to track cost and effect. Few studies (6,35%) reported how they validated models against local data. Conclusions: Although DAMs have been increasingly applied in LMICs to evaluate interventions to control diabetes, there is a need to advance the use of DAMs to evaluate NP diabetes policy interventions in LMICs, particularly DAMs that use local research data. Moreover, the reporting of input data, calibration and validation that underlies DAMs of diabetes in LMICs needs to be more transparent and credible