Predicting dengue incidence leveraging internet-based data sources. A case study in 20 cities in Brazil.

The dengue virus affects millions of people every year worldwide, causing large epidemic outbreaks that disrupt people's lives and severely strain healthcare systems. In the absence of a reliable vaccine against dengue or an effective treatment to manage the illness in humans, most efforts to combat dengue infections have focused on preventing its vectors, mainly the Aedes aegypti mosquito, from flourishing across the world. These mosquito-control strategies need reliable disease activity surveillance systems to be deployed. Despite significant efforts to estimate dengue incidence using a variety of data sources and methods, little work has been done to understand the relative contribution of the different data sources to improved prediction. Additionally, scholarship on the topic had initially focused on prediction systems at the national- and state-levels, and much remains to be done at the finer spatial resolutions at which health policy interventions often occur. We develop a methodological framework to assess and compare dengue incidence estimates at the city level, and evaluate the performance of a collection of models on 20 different cities in Brazil. The data sources we use towards this end are weekly incidence counts from prior years (seasonal autoregressive terms), weekly-aggregated weather variables, and real-time internet search data. We find that both random forest-based models and LASSO regression-based models effectively leverage these multiple data sources to produce accurate predictions, and that while the performance between them is comparable on average, the former method produces fewer extreme outliers, and can thus be considered more robust. For real-time predictions that assume long delays (6-8 weeks) in the availability of epidemiological data, we find that real-time internet search data are the strongest predictors of dengue incidence, whereas for predictions that assume short delays (1-3 weeks), in which the error rate is halved (as measured by relative RMSE), short-term and seasonal autocorrelation are the dominant predictors. Despite the difficulties inherent to city-level prediction, our framework achieves meaningful and actionable estimates across cities with different demographic, geographic and epidemic characteristics.

Golf habits among physicians and surgeons: observational cohort study.

OBJECTIVES: To examine patterns of golfing among physicians: the proportion who regularly play golf, differences in golf practices across specialties, the specialties with the best golfers, and differences in golf practices between male and female physicians. DESIGN: Observational study. SETTING: Comprehensive database of US physicians linked to the US Golfing Association amateur golfer database. PARTICIPANTS: 41 692 US physicians who actively logged their golf rounds in the US Golfing Association database as of 1 August 2018. MAIN OUTCOME MEASURES: Proportion of physicians who play golf, golf performance (measured using golf handicap index), and golf frequency (number of games played in previous six months). RESULTS: Among 1 029 088 physicians, 41 692 (4.1%) actively logged golf scores in the US Golfing Association amateur golfer database. Men accounted for 89.5% of physician golfers, and among male physicians overall, 5.5% (37 309/683 297) played golf compared with 1.3% (4383/345 489) among female physicians. Rates of golfing varied substantially across physician specialties. The highest proportions of physician golfers were in orthopedic surgery (8.8%), urology (8.1%), plastic surgery (7.5%), and otolaryngology (7.1%), whereas the lowest proportions were in internal medicine and infectious disease (<3.0%). Physicians in thoracic surgery, vascular surgery, and orthopedic surgery were the best golfers, with about 15% better golf performance than specialists in endocrinology, dermatology, and oncology. CONCLUSIONS: Golfing is common among US male physicians, particularly those in the surgical subspecialties. The association between golfing and patient outcomes, costs of care, and physician wellbeing remain unknown.