{"title":"搜索峰值:谷歌趋势和意大利的第一波COVID-19浪潮","authors":"L. Serlenga, Giuliano Resce, P. Brunori","doi":"10.1504/ijcee.2022.10047365","DOIUrl":null,"url":null,"abstract":"One of the difficulties faced by policymakers during the COVID-19 outbreak in Italy was the monitoring of the virus diffusion. Due to changes in the criteria and insufficient resources to test all suspected cases, the number of 'confirmed infected' rapidly proved to be unreliably reported by official statistics. We explore the possibility of using information obtained from Google Trends to predict the evolution of the epidemic. Following the most recent developments on the statistical analysis of longitudinal data, we estimate a dynamic heterogeneous panel. This approach allows to takes into account the presence of common shocks and unobserved components in the error term both likely to occur in this context. We find that Google queries contain useful information to predict number patients admitted to the intensive care units, number of deaths and excess mortality in Italian regions.","PeriodicalId":42342,"journal":{"name":"International Journal of Computational Economics and Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Searching for the peak: Google Trends and the first COVID-19 wave in Italy\",\"authors\":\"L. Serlenga, Giuliano Resce, P. Brunori\",\"doi\":\"10.1504/ijcee.2022.10047365\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the difficulties faced by policymakers during the COVID-19 outbreak in Italy was the monitoring of the virus diffusion. Due to changes in the criteria and insufficient resources to test all suspected cases, the number of 'confirmed infected' rapidly proved to be unreliably reported by official statistics. We explore the possibility of using information obtained from Google Trends to predict the evolution of the epidemic. Following the most recent developments on the statistical analysis of longitudinal data, we estimate a dynamic heterogeneous panel. This approach allows to takes into account the presence of common shocks and unobserved components in the error term both likely to occur in this context. We find that Google queries contain useful information to predict number patients admitted to the intensive care units, number of deaths and excess mortality in Italian regions.\",\"PeriodicalId\":42342,\"journal\":{\"name\":\"International Journal of Computational Economics and Econometrics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computational Economics and Econometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijcee.2022.10047365\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational Economics and Econometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijcee.2022.10047365","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
Searching for the peak: Google Trends and the first COVID-19 wave in Italy
One of the difficulties faced by policymakers during the COVID-19 outbreak in Italy was the monitoring of the virus diffusion. Due to changes in the criteria and insufficient resources to test all suspected cases, the number of 'confirmed infected' rapidly proved to be unreliably reported by official statistics. We explore the possibility of using information obtained from Google Trends to predict the evolution of the epidemic. Following the most recent developments on the statistical analysis of longitudinal data, we estimate a dynamic heterogeneous panel. This approach allows to takes into account the presence of common shocks and unobserved components in the error term both likely to occur in this context. We find that Google queries contain useful information to predict number patients admitted to the intensive care units, number of deaths and excess mortality in Italian regions.
期刊介绍:
IJCEE explores the intersection of economics, econometrics and computation. It investigates the application of recent computational techniques to all branches of economic modelling, both theoretical and empirical. IJCEE aims at an international and multidisciplinary standing, promoting rigorous quantitative examination of relevant economic issues and policy analyses. The journal''s research areas include computational economic modelling, computational econometrics and statistics and simulation methods. It is an internationally competitive, peer-reviewed journal dedicated to stimulating discussion at the forefront of economic and econometric research. Topics covered include: -Computational Economics: Computational techniques applied to economic problems and policies, Agent-based modelling, Control and game theory, General equilibrium models, Optimisation methods, Economic dynamics, Software development and implementation, -Econometrics: Applied micro and macro econometrics, Monte Carlo simulation, Robustness and sensitivity analysis, Bayesian econometrics, Time series analysis and forecasting techniques, Operational research methods with applications to economics, Software development and implementation.