Strengthening private-sector medicine systems to tackle the persistence of poor-quality medicines in Africa: a proof-of-concept study

质量低劣的药品几乎或根本不含有效成分--无论是通过蓄意欺诈、糟糕的生产实践还是制造后的恶化--是低收入/中等收入国家的一个主要公共卫生威胁：每年导致非洲20多万5岁以下儿童死亡，并造成抗菌素耐药性。各国政府和国际机构通过提高发现率、加强监管和公共教育来遏制这一问题的努力，受到了资源匮乏、高度需要的情况下药品供应的经济现实的阻碍，而且--我们认为--也受到了未能充分了解药品供应系统的复杂运作的阻碍，特别是在公共部门之外。私营部门的医疗系统可以被描述为“复杂系统”，涉及多个分散的行为者，没有中央组织机构。复杂系统研究的最新进展揭示了个体的行为如何结合在一起，对整个系统产生非直观的影响。这对基于‘常识’直觉的善意政策干预具有重大影响，这可能会产生不受欢迎的意想不到的后果。我们的最终目标是了解-并预测-复杂医学系统的工作原理，以便为有效的干预提供信息，将劣质产品在LMICs中的渗透率降至最低。这将需要：绘制完整的药品供应链；了解买家、卖家和监管者的动机/行为；开发复杂的计算模型来模拟该系统；并让利益相关者参与设计基于证据的干预措施。这是一个雄心勃勃的项目，需要通过概念验证研究进行认真的基础工作，目标和活动如下：(1)评估在这些背景下的实地工作的可行性并验证研究工具：很少有人试图在监管不足的背景下追踪完整的药品供应链。为了评估可行性、安全性和伦理问题，我们将绘制有限数量的药品供应链地图，从加纳和坦桑尼亚的零售点开始，向上移动到生产点，在每个阶段获得尽可能多的相关信息。研究工具将在每个当地背景下进行验证，并在不同背景下进行重新验证，以确保一致性。(2)为了加深我们对私营部门医疗系统结构和运作的理解：将使用地理加权分析来描述供应系统的结构/组织(长度、交易点数量、垂直“崩溃”的程度/水平等)。并调查数据中的空间相关性。将使用人种学数据和二手来源的主题分析来了解行为者在每个点上的决策和行为。(3)基于经验数据建立模拟药物系统的基于主体的模型(ABM)：我们将建立一系列ABM，将加纳和坦桑尼亚的药物供应系统模拟为“复杂系统”。这些模型将使我们能够理解并最终预测，个人行为可能如何影响整个系统。我们将开发供政策制定者使用的“用户友好”模型，突出干预的潜在意外后果。(4)制定和评估让相关行为者(市场、监管、政治)参与研究和干预设计的战略：在每个国家，我们将召集国家利益相关者小组(NSG)，由政策、监管和高级别市场参与者和项目工作组(PWGs)组成，其中包括“实地”供应链行为者(买家、卖家和监管者)。通过一系列协作研讨会，我们将使用“用户友好型”模型来识别可能支撑干预措施的潜在“瓶颈”或有问题的行为逻辑。

Poor-quality medicines, containing little or no active ingredient - whether through deliberate fraud, poor manufacturing practice or post-manufacture deterioration - represent a major public health threat in low/middle-income countries (LMICs): responsible for more than 200,000 under-5 deaths each year in Africa and contributing to antimicrobial drug resistance. Efforts by governments and international agencies to curb the problem through improving detection rates, tightening regulation and public education have been hampered by the economic realities of medicine supply in resource-poor, high-need contexts, but also - we suggest - by a failure to apprehend fully the complex workings of medicine supply systems, particularly beyond the public sector. Private-sector medicine systems can be characterised as 'complex systems' involving multiple dispersed actors with no central organising authority. Recent developments in the study of complex systems have revealed how the actions of individuals can combine to have non-intuitive effects on the system as whole. This has significant implications for well-intentioned policy interventions based on 'common sense' intuition, which may have unwelcome unanticipated consequences.Our ultimate goal is to understand - and predict - the workings of complex medicine systems in order to inform effective interventions to minimise the penetration of poor-quality products in LMICs. This will require: mapping complete medicine supply chains; understanding the motivations/behaviours of buyers, sellers and regulators; developing sophisticated computational models to simulate the system; and engaging stake-holders to co-design evidence-based interventions. This is an ambitious project which needs careful groundwork through a proof-of-concept study with the following objectives and activities:(1) To assess fieldwork feasibility in these contexts and validate research instruments:Very few people have attempted to trace a full medicine supply chain in an under-regulated context. In order to assess feasibility, safety and ethical issues, we will map a limited number of medicine supply chains starting at retail outlets across Ghana and Tanzania and moving upwards to point of manufacture, obtaining as much relevant information as possible at each stage. Research instruments will be validated in each local context, and re-validated across contexts to ensure consistency.(2) To develop our understandings of the structure and operation of private-sector medicine systems:Geographically weighted analysis will be employed to describe the structure/organization of supply systems (length, number of transaction points, degree/level of vertical 'collapse', etc.) and investigate spatial dependencies in the data. Thematic analysis of ethnographic data and secondary sources will be used to understand actors' decision-making and behaviour at each point.(3) To build Agent-Based Models (ABMs) simulating medicine systems, based on empirical data:We will build a sequence of ABMs simulating medicine supply systems in Ghana and Tanzania as 'complex systems'. These models will allow us to understand, and ultimately predict, how individual behaviours might affect the system as a whole. We will develop 'user-friendly' models to use with policy-makers, highlighting potential unintended consequences of interventions.(4) To develop and evaluate strategies for engaging relevant actors (market, regulatory, political) in the research and intervention design: In each country, we will convene National Stake-holder Groups (NSGs), with policy, regulatory and high-level market actors and Project Working Groups (PWGs), comprising 'on-the-ground' supply-chain actors (buyers, sellers and regulators). Through a series of collaborative workshops, we will work with 'user-friendly' models to identify potential 'bottlenecks' or problematic behavioural logics that might underpin interventions.