The Drive to Develop Rapid COVID-19 Guidance and its Influence on the Design of Proposed HTA Methods in South Africa

Published May 3, 2022

The COVID-19 pandemic posed challenges to as well as created opportunities for the practice of evidence-informed decision-making in South Africa. Local guidelines were needed urgently but decision-makers were forced to rely on early, often incomplete evidence. The situation stimulated the demand for evidence-driven processes and demonstrated how health technology assessment (HTA) might be undertaken even outside the context of the COVID-19 pandemic.

The National Department of Health Essential Drugs Programme in South Africa relies on the ministerially appointed National Essential Medicines List Committee (NEMLC) to select and guide the use of medicines in the public sector. Like decision-makers elsewhere, NEMLC was faced with an urgent need for guidance that could not be met using standard evidence review processes. In response, a rapid review mechanism was implemented to streamline and accelerate the identification and synthesis of evidence to inform treatment and prevention recommendations for COVID-191. The adoption of these rapid methods was supported by rigorous processes, including the use of high-quality living reviews2, the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach3, and an explicit evidence-to-decision framework. To build trust in the process, key documents were made available to the public and criteria for a review update were made explicit. The turn-around time for these reviews ranged from 1 to 3 weeks. 

At the same time as rapid review methods were being piloted by NEMLC, another group of researchers came together under the banner of MOSAIC (Modelling COVID-19 Strategies in South Africa Collective) with the objective of providing rapid HTA-related policy guidance4.  Among their various activities, MOSAIC developed a cost-effectiveness analysis to evaluate in-patient interventions for COVID-19 and were guided by four key considerations: uncertainty, rapidity, rigour, and transparency. With work starting in the early days of the pandemic, there was limited data and limited experience of COVID-19 in South Africa; however, decisions were needed rapidly to guide investment. Given the importance of making the right investment decisions, the analyses needed to be rigorous and transparent.   To these ends, the team developed a fully flexible decision model using the International Decision Support Initiative (iDSI) reference case5 and uploaded it to an open access platform, thereby providing full transparency and exploration of uncertainty.  The design also allowed for the rapid and continuous update of results as the evidence base for interventions evolved.  Where relevant, the results of the economic modelling were used to inform evidence-based recommendations by NEMLC.

The pandemic has demonstrated the technical capacity and commitment of South Africa’s researchers to improving health and health care through evidence-based decision-making. As part of the government’s ongoing National Health Insurance reforms, increased attention is being given to formalising local HTA processes and methods to guide resource allocation. Indeed, a recent consultation on new HTA methods for the NEMLC process is a leap forward and recognises the growing experience with and openness to explicit HTA methods in decision-making. As evidenced from the COVID-19 pandemic response, it is clear that HTA in South Africa does not need to wait for the perfect system to be implemented. Rigorous, transparent, and rapid analyses can be conducted using available data and local expertise and, when appropriately funded and applied to right priorities, can improve decision-making and strengthen the sustainability of the health system.   

Information provided by Laura Sawyer, MSc, President, ISPOR South Africa Chapter.


  2. The COVID-NMA initiative. URL:
  3. Guyatt G, Oxman AD, Akl EA, et al. GRADE guidelines: Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol, 2011; 64(4):383−394. DOI:10.1016/j.jclinepi.2010.04.026
  5. Wilkinson T, Sculpher MJ, Claxton K, Revill P, Briggs A, Cairns JA, Teerawattananon Y, Asfaw E, Lopert R, Culyer AJ, Walker DG. The International Decision Support Initiative Reference Case for Economic Evaluation: An Aid to Thought. Value Heal, 2016; 19:921–928.
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