No abstract

Non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-CoV-2 were often implemented under considerable uncertainty and a lack of scientific evidence. Assessing the effectiveness of the individual interventions is critical to inform future preparedness response plans. Here we quantify the impact of 4,579 NPIs implemented in 76 territories on the effective reproduction number, Rt, of COVID-19. We use a hierarchically coded data set of NPIs and propose a novel modelling approach that combines four computational techniques, which together allow for a worldwide consensus rank of the NPIs based on their effectiveness in mitigating the spread of COVID-19. We show how the effectiveness of individual NPIs strongly varies across countries and world regions, and in relation to human and economic development as well as different dimensions of governance. We quantify the effectiveness of each NPI with respect to the epidemic age of its adoption, i.e., how early into the epidemics. The emerging picture is one in which no one-fits-all solution exists, and no single NPI alone can decrease Rt below one and that a combination of NPIs is necessary to curb the spread of the virus. We show that there are NPIs considerably less intrusive and costly than lockdowns that are also highly effective, such as certain risk communication strategies and voluntary measures that strengthen the healthcare system. By allowing to simulate ``what-if'' scenarios at the country level, our approach opens the way for planning the most likely effectiveness of future NPIs.

In response to the COVID-19 pandemic, governments have implemented a wide range of nonpharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020.