BackgroundTravel restrictions were implemented on an unprecedented scale in 2015 in Sierra Leone to contain and eliminate Ebola virus disease. However, the impact of epidemic travel restrictions on mobility itself remains difficult to measure with traditional methods. New ‘big data’ approaches using mobile phone data can provide, in near real-time, the type of information needed to guide and evaluate control measures.MethodsWe analysed anonymous mobile phone call detail records (CDRs) from a leading operator in Sierra Leone between 20 March and 1 July in 2015. We used an anomaly detection algorithm to assess changes in travel during a national ‘stay at home’ lockdown from 27 to 29 March. To measure the magnitude of these changes and to assess effect modification by region and historical Ebola burden, we performed a time series analysis and a crossover analysis.ResultsRoutinely collected mobile phone data revealed a dramatic reduction in human mobility during a 3-day lockdown in Sierra Leone. The number of individuals relocating between chiefdoms decreased by 31% within 15 km, by 46% for 15–30 km and by 76% for distances greater than 30 km. This effect was highly heterogeneous in space, with higher impact in regions with higher Ebola incidence. Travel quickly returned to normal patterns after the restrictions were lifted.ConclusionsThe effects of travel restrictions on mobility can be large, targeted and measurable in near real-time. With appropriate anonymization protocols, mobile phone data should play a central role in guiding and monitoring interventions for epidemic containment.

Ramos, S, Volossovitch, A, Ferreira, AP, Barrigas, C, Fragoso, I, and Massuça, L. Differences in maturity, morphological and fitness attributes between the better- and lower-ranked male and female U-14 Portuguese elite regional basketball teams. J Strength Cond Res XX(X): 000-000, 2018-During a national championship, the anthropometric, physiological, and maturation attributes of 13-14-year-old players of regional selection basketball teams and their association with team's final classification were analyzed. Body parameters (weight, height, skinfolds, and lengths) were measured and physiological capacities assessed by sprint (20 m), agility, jump, and upper-body strength tests. Chronological age, maturity offset (years from age at peak height velocity; YAPHV), and predicted age at peak height velocity were calculated. In both sexes, no significant differences were found for maturity. Anthropometric and physiological analysis indicated that male players from finalist's teams were significantly faster, were more agile, threw the medicine ball longer, and showed lower percentages of body fat than players from lower-ranked teams. Further, semifinalists were faster than lower-ranked players. In the same sense, female players from semifinalist teams demonstrated to be significantly faster, more agile, and threw the medicine ball longer than female players from lower-ranked teams. In addition, discriminant analysis showed that speed (in boys) and the combination of speed and upper limb strength (in girls) could successfully discriminate players with different performances in a championship. In conclusion, speed and upper limb strength appear to be the physical attributes associated with better team performance in youth basketball. Coaches should be aware of the relationship between the improvement of these physical attributes and the teaching-learning process of the basketball game.

The present study aims (i) to compare the maturational, morphological and fitness attributes of young basketball players of primary and secondary teams of an elite basketball academy, and (ii) to identify the set of morphological and fitness attributes which better discriminate the players from the two teams. A total of 116 male basketball players of an elite basketball academy were divided into primary (team A) and secondary (team B) teams in two age groups (U-14 and U-16). All the players were evaluated during two consecutive seasons and data related to players' practice experience, maturational, morphological and fitness attributes were collected at the beginning of the competition period. The results of the study suggest that: (i) in both age categories, team A players were older, more mature, bigger in size and had greater fitness profiles than team B players; (ii) stature and abdominal resistance were identified as discriminant attributes for youth basketball player performance; (iii) aerobic capacity for U-14 and agility for U-16 were identified as specific discriminant attributes for performance in youth basketball. Coaches are recommended to avoid premature talent identification and provide players with opportunities to progress through the talent pathway, at least until U-16 age category.

The association of the biological maturation, morphological attributes, and fitness attributes of 13-to 14-year-old players selected to regional basketball teams, which participated in the Portuguese Festival of Youth Basketball, was analyzed in the study. A total of 416 under-14 Portuguese elite basketball players (male, n = 224; female, n = 192) were evaluated in this cross-sectional study. Maturational parameters (maturity offset and predicted age at peak height velocity), morphological attributes (body mass, stature, skinfolds, and lengths), and fitness (sprint, agility, jump, and upper-body strength) attributes were measured. In addition, basketball game performance was assessed using technical statistics (rebounds and point averages) and the performance index rating (PIR). Correlation analyses indicated that male players with better PIR/minute were taller, had a longer hand span, had more free-fat mass, and demonstrated better results in all jumping tests, upper-body strength tests, 20-m speed test, and agility T-test. Female players with better PIR/minute were significantly older, more matured, heavier, taller, and had longer arm and hand span. They also demonstrated better results in jumping tests, medicine ball throw, had greater practice experience, and were subjected to higher training loads. Multiple regression analysis showed that combined stature, handgrip strength, agility, and countermovement jump (with arm swing power) can be considered strong predictors of PIR per time played for male players. The prediction model for female players indicated that maturity offset, practice experience, and agility were the strongest predictors of basketball performance. In conclusion, the results of this study indicate that around puberty, physical fitness attributes of elite basketball players of both sexes are associated with game performance parameters. Two regression models have been estimated to predict the performance of youth basketball players of both genders.

The aims of the present study were: (i) to describe the structural and functional attributes of young male Portuguese basketball players aged 12–16 years and (ii) to generate normative data according to chronological age and years from peak height velocity. A total of 281 male Portuguese young basketball players between the ages of 12 and 16 years were assessed in this study. Chronological age, maturity parameters (maturity offset and predicted age at peak height velocity), morphological (body mass, height, and skinfolds and length), and fitness (sprint, change of direction ability, jump, and upper body strength) attributes were measured. Descriptive statistics were determined for the age and maturity status, and the 10th, 25th, 50th, 75th, and 90th percentiles were chosen as reference values. Descriptive and normative values of the players' morphological and fitness attributes, stratified by age and maturity status, are provided. The normative values of age at peak height velocity (category YAPHV = 0) showed that regional basketball players presented average values (50th percentile) of 169.8 cm for height, 173.3 cm for arm span, 55.6 kg for body mass, 3.34 s for the 20-m speed test, 10.31 s for the T-test, 4.75 m for the 2-kg medicine ball throw, 66.9 kg for the combined right and left handgrip strength, and 30.1 and 35.9 cm for jump height in the countermovement jump (CMJ) and CMJ with arm swing, respectively. In conclusion, these results may be helpful to quantify and control an athlete's performance over time and to adjust strength and conditioning programs to biological demands.