Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India.
MRC Centre for Global Infectious Disease Analysis, and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College, London, UK.
BMJ Glob Health. 2022 May;7(5). doi: 10.1136/bmjgh-2022-008710.
Mathematical modelling has been a helpful resource for planning public health responses to COVID-19. However, there is a need to improve the accessibility of models built within country contexts in the Global South. Immediately following the overwhelming 'second wave' of COVID-19 in India, we developed a user-friendly, web-based modelling simulator in partnership with the public health experts and health administrators for subnational planning. The purpose was to help policy-makers and programme officials at the state and district levels, to construct model-based scenarios for a possible third wave. Here, we describe our experiences of developing and deploying the simulator and propose the following recommendations for future such initiatives: early preparation will be the key for pandemic management planning, including establishment of networks with potential simulator users. Ideally, this preparedness should be conducted during 'peace time', and coordinated by agencies such as WHO. Second, flexible modelling frameworks will be needed, to respond rapidly to future emergencies as the precise nature of any pandemic is impossible to predict. Modelling resources will, therefore, need to be rapidly adaptable to respond as soon as a novel pathogen emerges. Third, limitations of modelling must be communicated clearly and consistently to end users. Finally, systematic mechanisms are required for monitoring the use of models in decision making, which will help in providing modelling support to those local authorities who may benefit most from it. Overall, these lessons from India can be relevant for other countries in the South-Asian-Region, to incorporate modelling resources into their pandemic preparedness planning.
数学建模一直是规划应对 COVID-19 的公共卫生措施的有用资源。然而，在全球南方的国家背景下，需要提高模型的可访问性。在印度 COVID-19 的压倒性“第二波”之后，我们与公共卫生专家和卫生行政人员合作，立即在国家以下各级规划中开发了一个用户友好的基于网络的建模模拟器。目的是帮助州和地区级别的政策制定者和计划官员，为可能的第三波疫情构建基于模型的情景。在这里，我们描述了开发和部署模拟器的经验，并为未来的此类举措提出以下建议：大流行管理规划的关键将是早期准备，包括与潜在模拟器用户建立网络。理想情况下，这一准备工作应在“和平时期”进行，并由世卫组织等机构协调。其次，需要灵活的建模框架，以便对未来的紧急情况迅速做出反应，因为任何大流行的确切性质都无法预测。因此，建模资源需要迅速适应，一旦出现新的病原体就能够迅速做出反应。第三，必须向最终用户清楚一致地传达建模的局限性。最后，需要有系统的机制来监测模型在决策中的使用情况，这将有助于为那些最有可能从中受益的地方当局提供建模支持。总的来说，这些来自印度的经验教训对于南亚地区的其他国家来说是相关的，可以将建模资源纳入其大流行防范规划中。
