Suchergebnisse

As COVID-19 spreads worldwide, national (and sub-national) governments and development partners are making use of a rapidly growing body of evidence to develop policies mitigating against this devastating pandemic. Mathematical models and computational simulation models play a unique role to inform resource planning and policy development (among other uses) through scenario analysis and short-term forecasting. Already in the first six months of this outbreak, we have seen many models at the sub-national, national, regional and global level being developed at an impressive speed.

The development of COVID-19 vaccines does not imply the end of the global pandemic as now countries have to purchase enough COVID-19 vaccine doses and work towards their successful rollout. Vaccination across the world has progressed slowly in all, but a few high-income countries (HICs) as governments learn how to vaccinate their entire populations amidst a pandemic. Most low- and middle-income countries (LMICs) have been relying on the COVID-19 Vaccines Global Access (COVAX) Facility to obtain vaccines. COVAX aims to provide these countries with enough doses to vaccinate 20% of their populations. LMICs will likely encounter additional barriers and challenges rolling out vaccines compared HICs despite their significant experience from the Expanded Programme on Immunisation (EPI). This study explores potential barriers that will arise during the COVID-19 vaccine rollout in lower-middle-income countries and how to overcome them. We conducted sixteen semi-structured interviews with national-level stakeholders from Ghana and Bangladesh (eight in each country). Stakeholders included policymakers and immunisation programme experts. Data were analysed using a Framework Analysis technique. Stakeholders believed their country could use existing EPI structures for the COVID-19 vaccine rollout despite existing challenges with the EPI and despite its focus on childhood immunisation rather than vaccinating the entire population over a short period of time. Stakeholders suggested increasing confidence in the vaccine through community influencers and by utilising local government accredited institutions such as the Drug Authorities for vaccine approval. Additional strategies they discussed included training more health providers and recruiting volunteers to increase vaccination speed, expanding government budgets for COVID-19 vaccine purchase and delivery, and exploring other financing opportunities to address in-country vaccine shortages. Stakeholders also believed that LMICs may encounter challenges complying with priority ...

Antimicrobial resistance is a serious challenge to the success and sustainability of our healthcare systems. There has been increasing policy attention given to antimicrobial resistance in the last few years, and increased amounts of funding have been channeled into funding for research and development of antimicrobial agents. Nevertheless, manufacturers doubt whether there will be a market for new antimicrobial technologies sufficient to enable them to recoup their investment. Health technology assessment (HTA) has a critical role in creating confidence that if valuable technologies can be developed they will be reimbursed at a level that captures their true value. We identify 3 deficiencies of current HTA processes for appraising antimicrobial agents: a methods-centric approach rather than problem-centric approach for dealing with new challenges, a lack of tools for thinking about changing patterns of infection, and the absence of an approach to epidemiological risks. We argue that, to play their role more effectively, HTA agencies need to broaden their methodological tool kit, design and communicate their analysis to a wider set of users, and incorporate long-term policy goals, such as containing resistance, as part of their evaluation criteria alongside immediate health gains.

Background: Mathematical models have been used throughout the COVID-19 pandemic to inform policymaking decisions. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was established to provide country governments, particularly low- and middle-income countries (LMICs), and other model users with an overview of the aims, capabilities and limits of the main multi-country COVID-19 models to optimise their usefulness in the COVID-19 response. Methods: Seven models were identified that satisfied the inclusion criteria for the model comparison and had creators that were willing to participate in this analysis. A questionnaire, extraction tables and interview structure were developed to be used for each model, these tools had the aim of capturing the model characteristics deemed of greatest importance based on discussions with the Policy Group. The questionnaires were first completed by the CMCC Technical group using publicly available information, before further clarification and verification was obtained during interviews with the model developers. The fitness-for-purpose flow chart for assessing the appropriateness for use of different COVID-19 models was developed jointly by the CMCC Technical Group and Policy Group. Results: A flow chart of key questions to assess the fitness-for-purpose of commonly used COVID-19 epidemiological models was developed, with focus placed on their use in LMICs. Furthermore, each model was summarised with a description of the main characteristics, as well as the level of engagement and expertise required to use or adapt these models to LMIC settings. Conclusions: This work formalises a process for engagement with models, which is often done on an ad-hoc basis, with recommendations for both policymakers and model developers and should improve modelling use in policy decision making.