Background Although the economic burden of multiple sclerosis (MS) in high-income countries (HICs) has been extensively studied, information on the costs of MS in low- and middle‐income countries (LMICs) remains scarce. Moreover, no review synthesizing and assessing the costs of MS in LMICs has yet been undertaken. Objective Our objective was to systematically identify and review the cost of illness (COI) of MS in LMICs to critically appraise the methodologies used, compare cost estimates across countries and by level of disease severity, and examine cost drivers. Methods We conducted a systematic literature search for original studies in English, French, and Dutch containing prevalence or incidence-based cost data of MS in LMICs. The search was conducted in MEDLINE (Ovid), PubMed, Embase (Ovid), Cochrane Library, National Health Service Economic Evaluation Database (NHS EED), Econlit, and CINAHL (EBSCO) on July 2020 without restrictions on publication date. Recommended and validated methods were used for data extraction and analysis to make the results of the COI studies comparable. Costs were adjusted to $US, year 2019 values, using the World Bank purchasing power parity and inflated using the consumer price index. Results A total of 14 studies were identified, all of which were conducted in upper-middle-income economies. Eight studies used a bottom-up approach for costing, and six used a top-down approach. Four studies used a societal perspective. The total annual cost per patient ranged between $US463 and 58,616. Costs varied across studies and countries, mainly because of differences regarding the inclusion of costs of disease-modifying therapies (DMTs), the range of cost items included, the methodological choices such as approaches used to estimate healthcare resource consumption, and the inclusion of informal care and productivity losses. Characteristics and methodologies of the included studies varied considerably, especially regarding the perspective adopted, cost data specification, and reporting of costs per severity levels. The total costs increased with greater disease severity. The cost ratios between different levels of MS severity within studies were relatively stable; costs were around 1–1.5 times higher for moderate versus mild MS and about two times higher for severe versus mild MS. MS drug costs were the main cost driver for less severe MS, whereas the proportion of direct non-medical costs and indirect costs increased with greater disease severity. Conclusion MS places a huge economic burden on healthcare systems and societies in LMICs. Methodological differences and substantial variations in terms of absolute costs were found between studies, which made comparison of studies challenging. However, the cost ratios across different levels of MS severity were similar, making comparisons between studies by disease severity feasible. Cost drivers were mainly DMTs and...

Objectives To systematically identify the latest versions of official economic evaluation guidelines (EEGs) in low- and middle-income countries (LMICs) and explore similarities and differences in their content. Methods We conducted a systematic search in MEDLINE (Ovid), PubMed, EconLit, Embase (Ovid), the Cochrane Library, and the gray literature. Using a predefined checklist, we extracted the key features of economic evaluation and the general characteristics of EEGs. We conducted a comparative analysis, including a summary of similarities and differences across EEGs. Results Thirteen EEGs were identified, three pertaining to lower-middle-income countries (Bhutan, Egypt, and Indonesia), nine to upper-middle-income countries (Brazil, China, Colombia, Cuba, Malaysia, Mexico, Russian Federation, South Africa, and Thailand), in addition to Mercosur, and none to low-income countries. The majority (n = 12) considered cost–utility analysis and health-related quality-of-life outcome. Half of the EEGs recommended the societal perspective, whereas the other half recommended the healthcare perspective. Equity considerations were required in ten EEGs. Most EEGs (n = 11) required the incremental cost-effectiveness ratio and recommended sensitivity analysis, as well as the presentation of a budget impact analysis (n = 10). Seven of the identified EEGs were mandatory for pharmacoeconomics submission. Methodological gaps, contradictions, and heterogeneity in terminologies used were identified within the guidelines. Conclusion As the importance of health technology assessment is increasing in LMICs, this systematic review could help researchers explore key aspects of existing EEGs in LMICs and explore differences among them. It could also support international organizations in guiding LMICs to develop their own EEGs and improve the methodological framework of existing ones.

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In 2019, we embarked on a study on the economic burden of multiple sclerosis (MS) in Lebanon, in collaboration with a premier Lebanese MS center. This coincided with a triple disaster in Lebanon, comprising the drastic economic and financial crisis, the COVID-19 pandemic, and the consequences of the explosion of Beirut’s port. Specifically, the economic and financial turmoil made the valuation of costs challenging. Researchers could face similar challenges, particularly in low- and middle-income countries (LMICs) where economic crises and recessions are recurrent phenomena. This paper aims to discuss steps taken to overcome the fluctuation of the prices of resources to get a valid valuation of societal costs during times of a financial and economic crisis. In the absence of local costing data and guidelines for conducting cost-of-illness (COI) studies, this paper provides empirical recommendations on the valuation of costs that are particularly relevant in LMICs. We recommend (1) clear reporting and justification of the country-specific context, year of costing, assumptions, data sources, and valuation methods, as well as the indicators used to adjust cost for inflation during different periods of fluctuation of prices; (2) collecting prices of each resource from multiple and various sources; (3) conducting a sensitivity analysis; and (4) reporting costs in local currency and Purchasing Power Parity dollars (PPP$). Precision and transparency in reporting prices of resources and their sources are markers of the reliability of the COI studies.

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