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We employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.

This study assessed the incidence of transitions in smartphone addiction proneness (SAP) among children and examined the effects of gender, use patterns (social networking sites (SNSs) use and smartphone gaming) and depression on smartphone addiction transitions. A representative sample of 2,155 children from Taipei completed longitudinal surveys in both 2015 (5th grade) and 2016 (6th grade). Latent transition analysis (LTA) was used to characterize transitions in SAP and to examine the effects of gender, use patterns and depression on SAP transitions. LTA identified four latent statuses of SAP: about half of the children were in non-SAP status, one-fifth were in tolerance status, one-sixth were in withdrawal status, and one-seventh were in high-SAP status. Both boys and girls had a higher prevalence of high-SAP and tolerance in 6th grade than in 5th grade, whereas in both grades boys had a higher prevalence of high-SAP and withdrawal, and girls had a higher prevalence of non-SAP and tolerance. Controlling for parents' education, family structure, and household income, higher use of SNSs by children, increasing use of mobile gaming and higher levels of depression were individually associated with increased odds of being in one of the three SAP statuses other than non-SAP. When all three covariates were jointly entered into the model, usage of SNSs and depression remained significant predictors. Both boys and girls tended to transition to tolerance or high-SAP statuses, while children's depression and their usage of SNSs increased the risk of smartphone addiction.

Background Studies exploring the association between physical activity, screen time and sleep and pain usually focus on a limited number of painful body sites. Nevertheless, pain at different body sites is likely to be of different nature. Therefore, this study aims to explore and compare the association between time spent in self-reported physical activity, in screen based activities and sleeping and i) pain presence in the last 7-days for 9 different body sites; ii) pain intensity at 9 different body sites and iii) global disability. Methods Nine hundred sixty nine students completed a questionnaire on pain, time spent in moderate and vigorous physical activity, screen based time watching TV/DVD, playing, using mobile phones and computers and sleeping hours. Univariate and multivariate associations between pain presence, pain intensity and disability and physical activity, screen based time and sleeping hours were investigated. Results Pain presence: sleeping remained in the multivariable model for the neck, mid back, wrists, knees and ankles/feet (OR 1.17 to 2.11); moderate physical activity remained in the multivariate model for the neck, shoulders, wrists, hips and ankles/feet (OR 1.06 to 1.08); vigorous physical activity remained in the multivariate model for mid back, knees and ankles/feet (OR 1.05 to 1.09) and screen time remained in the multivariate model for the low back (OR = 2.34. Pain intensity: screen time and moderate physical activity remained in the multivariable model for pain intensity at the neck, mid back, low back, shoulder, knees and ankles/feet (Rp 2 0.02 to 0.04) and at the wrists (Rp 2  = 0.04), respectively. Disability showed no association with sleeping, screen time or physical activity. Conclusions This study suggests both similarities and differences in the patterns of association between time spent in physical activity, sleeping and in screen based activities and pain presence at 8 different body sites. In addition, they also suggest that the factors associated with the presence of pain, pain intensity and pain associated disability are different.

About 1.25 million people worldwide die every year because of road accidents. Risk is higher when drivers use mobile phones, whereas seat belts help to prevent crash-related injury. We aimed to evaluate the prevalence, associated factors, and temporal trend of the use of seat belts and mobile phones among drivers and passengers in Florence, Italy (2005-2015). Use of seat belts and mobile phones use was monitored via direct observation in four areas in the province of Florence. We fitted Poisson regression models with robust variance to investigate the factors associated with the use of seat belts and mobile phones use by the drivers and to explore long-term trends and seasonal patterns in the two time-series. We observed a total of an overall 134,775 vehicles: seat belts were worn by 71.8% of drivers and front-seat passengers and 27.6% of back-seat passengers, while mobile phones were being used by 4.8% of drivers. Drivers were more likely to wear seat belt when transporting passengers (≥2 vs none: prevalence ratio [PR] 1.21, 95% confidence intervals [CI] 1.14-1.29) and while driving in the afternoon (PR 1.04, 95% CI 1.03-1.05), and less likely when the front-seat passenger was not wearing seat belts (PR 0.33, 95% CI 0.32-0.34). After an initial increase, seat belts use by the driver decreased over time (-0.5% each year during 2010-2015), with significant peaks and troughs in July and January, respectively. Mobile phone use by the driver was inversely associated with wearing seat belts (PR 0.67, 95% CI 0.64-0.70) and carrying passengers (≥2 vs. none PR 0.20, 95% CI 0.07-0.52). The proportion of drivers using mobile phones did not vary over time nor showed any clear seasonality. Drivers' risky behaviours (not wearing a seat belt and using a mobile phone) are associated, showing a global misperception of risk among a subset of drivers. The number of passengers and their behaviour is also associated with the driver's attitude. The effectiveness of primary enforcement laws has declined in Italy in recent years; therefore, other strategies should be devised and implemented.

ObjectiveSome studies have reported increasing trends in certain brain tumours and a possible link with mobile phone use has been suggested. We examined the incidence time trends of brain tumour in Australia for three distinct time periods to ascertain the influence of improved diagnostic technologies and increase in mobile phone use on the incidence of brain tumours.DesignIn a population-based ecological study, we examined trends of brain tumour over the periods 1982–1992, 1993–2002 and 2003–2013. We further compared the observed incidence during the period of substantial mobile phone use (2003–2013) with predicted (modelled) incidence for the same period by applying various relative risks, latency periods and mobile phone use scenarios.SettingNational Australian incidence registration data on primary cancers of the brain diagnosed between 1982 and 2013.Population16 825 eligible brain cancer cases aged 20–59 from all of Australia (10 083 males and 6742 females).Main outcome measuresAnnual percentage change (APC) in brain tumour incidence based on Poisson regression analysis.ResultsThe overall brain tumour rates remained stable during all three periods. There was an increase in glioblastoma during 1993–2002 (APC 2.3, 95% CI 0.8 to 3.7) which was likely due to advances in the use of MRI during that period. There were no increases in any brain tumour types, including glioma (−0.6, –1.4 to 0.2) and glioblastoma (0.8, –0.4 to 2.0), during the period of substantial mobile phone use from 2003 to 2013. During that period, there was also no increase in glioma of the temporal lobe (0.5, –1.3 to 2.3), which is the location most exposed when using a mobile phone. Predicted incidence rates were higher than the observed rates for latency periods up to 15 years.ConclusionsIn Australia, there has been no increase in any brain tumour histological type or glioma location that can be attributed to mobile phones.

We prospectively examined trends in cell phone use among children in the Danish National Birth Cohort. Cell phone use was assessed at ages 7 and 11 years, and we examined use patterns by age, by year of birth, and in relation to specific individual characteristics. There was an increase in cell phone use from age 7 (37%) to 11 years (94%). There was a clear pattern of greater reported cell phone use among children at age 7 years with later birth year, but this trend disappeared at age 11. Girls and those who used phones at age 7 talked more often and for longer durations at age 11 years. Low socio-economic status and later year of birth were associated with voice calls at age 7 but not at age 11 years. At age 11 most used cell phones for texting and gaming more than for voice calls. Further, children who started using cell phones at age 7 years were more likely to be heavy cell phone voice users at age 11 years, making early use a marker for higher cumulative exposure regardless of year of birth. As cell phone technology continues to advance, new use patterns will continue to emerge, and exposure assessment research among children must reflect these trends.

Mobile data are a feasible way for us to understand and reveal the feature of human mobility. However, it is extremely hard to have a fine-grained picture of large-scale mobility data, in particular at an urban scale. Here, we present a large-scale dataset of 2-million mobile phone users with time-varying locations, denoted as the temporal network of individuals, conducted by an open-data program in Changchun Municipality. To reveal human mobility across locations, we further construct the aggregated mobility network for each day by taking cellular base stations as nodes coupled by edges weighted by the total number of users' movements between pairs of nodes. The resulting temporal network of mobile phone users and the dynamic, weighted and directed mobility network are released in simple formats for easy access to motivating research using this new and extensive data of human mobility.

The energy-efficiency drive at the information factories that serve us Facebook, Google and Bitcoin. The energy-efficiency drive at the information factories that serve us Facebook, Google and Bitcoin.

(1) Background: There has been an ongoing concern for several decades that radiofrequencies emitted from mobile phones are related to brain cancer risk. We calculated temporal trends in brain cancer incidence rates in adults and children and compared them to mobile phone subscription data over the same time period. (2) Methods: We analyzed the Surveillance, Epidemiology and End Results (SEER 22) cancer database between 2000 and 2021. Age-standardized incidence rates (ASR) per 100,000 people were calculated and the annual percentage change (APC) for malignant and benign brain cancer and vestibular schwannomas (acoustic neuromas of the 8th cranial nerve) was established. The total number of mobile phone subscriptions in the United States was plotted for the period 1985–2024. (3) Results: The APC for adolescents and adults was −0.6 (p = 0.0004) for malignant tumors, −0.06 (p = 0.551) for temporal lobe tumors, and 1.9 (p = 0.00003) for benign tumors. The APC for benign acoustic neuroma was 0.09 (p = 0.8237), suggesting that mobile phone use is unlikely to be associated with this tumor type. There was a 1200-fold increase in the number of cell phone subscriptions during this period. (4) Conclusions: These findings suggest that mobile phone use does not appear to be associated with an increased risk of brain cancer, either malignant or benign.

Mobile phones emit electromagnetic radiations that are classified as possibly carcinogenic to humans. Evidence for increased risk for brain tumours accumulated in parallel by epidemiologic investigations remains controversial. This paper aims to investigate whether methodological quality of studies and source of funding can explain the variation in results. PubMed and Cochrane CENTRAL searches were conducted from 1966 to December 2016, which was supplemented with relevant articles identified in the references. Twenty-two case control studies were included for systematic review. Meta-analysis of 14 case–control studies showed practically no increase in risk of brain tumour [OR 1.03 (95% CI 0.92–1.14)]. However, for mobile phone use of 10 years or longer (or >1640 h), the overall result of the meta-analysis showed a significant 1.33 times increase in risk. The summary estimate of government funded as well as phone industry funded studies showed 1.07 times increase in odds which was not significant, while mixed funded studies did not show any increase in risk of brain tumour. Metaregression analysis indicated that the association was significantly associated with methodological study quality ( p  < 0.019, 95% CI 0.009–0.09). Relationship between source of funding and log OR for each study was not statistically significant ( p  < 0.32, 95% CI 0.036–0.010). We found evidence linking mobile phone use and risk of brain tumours especially in long-term users (≥10 years). Studies with higher quality showed a trend towards high risk of brain tumour, while lower quality showed a trend towards lower risk/protection.