Forecasting Births Using Google

Abstract de la ponencia[EN] Monitoring fertility change is particularly important for policy and planning purposes. New data may help us in this monitoring. We propose a new leading indicator based on Google web-searches. We then test its predictive power using US data. In a deep out-of sample comparison we show that popular time series specifications augmented with web-search-related data improve their forecasting performance at forecast horizons of 6 to 24 months. The superior performance of these augmented models is confirmed by formal tests of equal forecast accuracy. Moreover, our results survive a falsification test and are confirmed also when a forecast horse race is conducted using different out-of-sample tests, and at the state rather than at the federal level. Conditioning on the same information set, the forecast error of our best model for predicting 2009 births is 35% lower than the Census bureau projections. Our findings indicate the potential use of Googe web-searches in monitoring fertility change and in informing fertility forecasts.Billari, F.; D'amuri, F.; Marcucci, J. (2016). Forecasting Births Using Google. En CARMA 2016: 1st International Conference on Advanced Research Methods in Analytics. Editorial Universitat Politècnica de València. 119-119. https://doi.org/10.4995/CARMA2016.2015.4301OCS11911

Non-alcoholic fatty liver disease (NAFLD), metabolic syndrome and cardiovascular events in atrial fibrillation. a prospective multicenter cohort study

Whether non-alcoholic fatty liver disease (NAFLD) is associated with an increased risk of cardiovascular events (CVEs) independently from metabolic syndrome (MetS) is still matter of debate. Aim of the study was to investigate the risk of CVEs in a high-risk population of patients with non-valvular atrial fibrillation (AF) according to the presence of MetS and NAFLD. Prospective observational multicenter study including 1,735 patients with non-valvular AF treated with vitamin K antagonists (VKAs) or direct oral anticoagulants (DOACs). NAFLD was defined by a fatty liver index≥60. We categorized patients in 4 groups: 0=neither MetS or NAFLD (38.6%), 1=NAFLD alone (12.4%), 2=MetS alone (19.3%), 3=both MetS and NAFLD (29.7%). Primary endpoint was a composite of CVEs. Mean age was 75.4±9.4years, and 41.4% of patients were women. During a mean follow-up of 34.1±22.8months (4,926.8 patient-years), 155 CVEs were recorded (incidence rate of 3.1%/year): 55 occurred in Group 0 (2.92%/year), 12 in Group 1 (2.17%/year), 45 in Group 2 (4.58%/year) and 43 in Group 3 (2.85%/year). Multivariable Cox regression analysis showed that use of DOACs, and female sex were inversely associated with CVEs, whilst age, heart failure, previous cardiac and cerebrovascular events, and group 2 (Group 2, Hazard Ratio 1.517, 95% Confidence Interval, 1.010-2.280) were directly associated with CVEs. In patients with AF, MetS increases the risk of CVEs. Patients with NAFLD alone have lower cardiovascular risk but may experience higher liver-related complications

Posterior-stabilized (PS) total knee arthroplasty: a matched pair analysis of a classic and its evolutional design

Background: Total knee arthroplasty (TKA) designs continue to be modified to optimize patient's outcome. This study was designed to compare clinical and radiological results of classic worldwide used TKA posterior-stabilized (PS) design to those of its recent evolution. Methods: A consecutive group of 100 patients undergoing TKA using a classic cemented fixed-bearing PS TKA system was matched by age, gender, body max index to 100 patients having the newer cemented fixed-bearing PS design, both by the same manufacturer. Patients were assessed preoperatively, at 12 months and at 24 months minimum follow-up (range, 24-46) in a standard prospective fashion. The outcome assessments used were the Oxford Knee Score, the Knee Society Score, range of motion, and a satisfaction survey. A 2-sample t test comparing the 2 groups was performed. Results: No patients were lost at follow-up. At 2-year follow-up, differences in clinical and radiological Knee Society Score (P = .09), Oxford Score (P = .08), and overall satisfaction rate did not reach statistical significance. Implant group 2 showed a statistically significant decrease in postoperative anterior knee pain (P = .006). At final follow-up, 16% of group 1 knees achieved > 130° flexion compared with 37% in group 2 (P = .0009). There were 2 revisions for any reason in group 1 and none in group 2. Conclusions: Design modifications applied to the newer TKA system allowed greater flexion and lower patellofemoral complications but did not appear to achieve better overall clinical scores

Sublingual immunotherapy in children: facts and needs

Allergen specific immunotherapy (SIT) is the practice of administering gradually increasing doses of the specific causative allergen to reduce the clinical reactivity of allergic subjects, and is the only treatment targeting the causes of hypersensitivity and not only the symptoms, as done by drugs. The traditional, subcutaneous immunotherapy (SCIT) was burdened by the problem of systemic reactions which may be sometimes severe and - though very rarely - even fatal. This was the background to develop non injections routes for SIT and particularly sublingual immunotherapy (SLIT), that emerged as a real treatment option for respiratory allergy

"Google it!" Forecasting the US unemployment rate with a Google job search index

In this paper we suggest the use of an internet job-search indicator (Google Index, GI) as the best leading indicator to predict the US unemployment rate. We perform a deep out-of-sample comparison of many forecasting models. With respect to the previous literature we concentrate on the monthly series extending the out-of-sample forecast comparison with models that adopt both our preferred leading indicator (GI), the more standard initial claims or combinations of both. Our results show that the GI indeed helps in predicting the US unemployment rate even after controlling for the effects of data snooping. Robustness checks show that models augmented with the GI perform better than traditional ones even in most state-level forecasts and in comparison with the Survey of Professional Forecasters' federal level predictions