The role of modelling and analytics in South African COVID-19 planning and budgeting.
The role of modelling and analytics in South African COVID-19 planning and budgeting.
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DOI：
10.1371/journal.pgph.0001063
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发表时间：
2023
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南非COVID-19建模联盟（SACMC）于2020年3月下旬成立，以支持南非COVID-19相关医疗保健的规划和预算。我们针对疫情不同阶段决策者的需求开发了几种工具，让南非政府提前几个月做好规划。我们的工具包括流行病预测模型，几个成本和预算影响模型，以及在线仪表板，以帮助政府和公众可视化我们的预测，跟踪病例发展和预测住院人数。关于新变种的信息，包括德尔塔和奥密克隆，都在真实的时间内被纳入，以便在必要时转移稀缺的资源。鉴于全球和南非疫情的性质迅速变化，模型预测定期更新。有关更新反映1）疫情期间政策优先次序的转变; 2）南非数据系统的新数据可用性;及3）南非对COVID-19的应对措施不断变化，例如封锁级别及随之而来的流动性和接触率、检测和接触者追踪策略以及住院标准的变化。要深入了解人口行为，就需要结合行为异质性和对观察到的死亡率变化的行为反应等概念进行更新。我们将这些方面纳入第三波的发展方案，并开发了额外的方法，使我们能够预测所需的住院能力。最后，对2021年11月在南非首次发现的Omicron变种最重要特征的实时分析，使我们能够在第四波早期向政策制定者提供建议，即录取率可能相对较低。SACMC的模型在紧急情况下迅速发展，并定期根据当地数据进行更新，支持国家和省政府提前几个月进行规划，在需要时扩大医院容量，分配预算并在可能的情况下获得额外资源。在四波COVID-19病例中，SACMC继续满足政府的规划需求，跟踪疫情并支持全国疫苗推广。
The South African COVID-19 Modelling Consortium (SACMC) was established in late March 2020 to support planning and budgeting for COVID-19 related healthcare in South Africa. We developed several tools in response to the needs of decision makers in the different stages of the epidemic, allowing the South African government to plan several months ahead. Our tools included epidemic projection models, several cost and budget impact models, and online dashboards to help government and the public visualise our projections, track case development and forecast hospital admissions. Information on new variants, including Delta and Omicron, were incorporated in real time to allow the shifting of scarce resources when necessary. Given the rapidly changing nature of the outbreak globally and in South Africa, the model projections were updated regularly. The updates reflected 1) the changing policy priorities over the course of the epidemic; 2) the availability of new data from South African data systems; and 3) the evolving response to COVID-19 in South Africa, such as changes in lockdown levels and ensuing mobility and contact rates, testing and contact tracing strategies and hospitalisation criteria. Insights into population behaviour required updates by incorporating notions of behavioural heterogeneity and behavioural responses to observed changes in mortality. We incorporated these aspects into developing scenarios for the third wave and developed additional methodology that allowed us to forecast required inpatient capacity. Finally, real-time analyses of the most important characteristics of the Omicron variant first identified in South Africa in November 2021 allowed us to advise policymakers early in the fourth wave that a relatively lower admission rate was likely. The SACMC’s models, developed rapidly in an emergency setting and regularly updated with local data, supported national and provincial government to plan several months ahead, expand hospital capacity when needed, allocate budgets and procure additional resources where possible. Across four waves of COVID-19 cases, the SACMC continued to serve the planning needs of the government, tracking waves and supporting the national vaccine rollout.