摘要:This paper critically discusses the use and merits of global indices, in particular, the Global Health Security Index (GHSI; Cameron et al. https://www.ghsindex.org/#l-section--map ) in times of an imminent crisis, such as the current pandemic. This index ranked 195 countries according to their expected preparedness in the case of a pandemic or other biological threat. The coronavirus disease 2019 (Covid-19) pandemic provides the background to compare each country's predicted performance from the GHSI with the actual performance. In general, there is an inverted relation between predicted versus actual performance, i.e. the predicted top performers are among those that are the worst hit. Obviously, this reflects poorly on the potential policy uses of this index in imminent crisis management. The paper analyses the GHSI and identifies why it may have struggled to predict actual pandemic preparedness as evidenced by the Covid-19 pandemic. The paper also uses two different data sets, one from the Worldmeter on the spread of the Covid-19 pandemics, and the other from the International Network for Government Science Advice (INGSA) Evidence-to-Policy Tracker, to draw comparisons between the actual introduction of pandemic response policies and the corresponding death rate in 29 selected countries. This paper analyses the reasons for the poor match between prediction and reality in the index, and mentions six general observations applying to global indices in this respect. These observations are based on methodological and conceptual analyses. The level of abstraction in these global indices builds uncertainties upon uncertainties and hides implicit value assumptions, which potentially removes them from the policy needs on the ground. From the analysis, the question is raised if the policy community might have better tools for decision-making in a pandemic. On the basis of data from the INGSA Evidence-to-Policy Tracker, and with backing in studies from social psychology and philosophy of science, some simple heuristics are suggested, which may be more useful than a global index.