Are you getting sick? Predicting influenza-like symptoms using human mobility behaviors [0.03%]
利用人类行为预测流感症状
Gianni Barlacchi,Christos Perentis,Abhinav Mehrotra et al.
Gianni Barlacchi et al.
Understanding and modeling the mobility of individuals is of paramount importance for public health. In particular, mobility characterization is key to predict the spatial and temporal diffusion of human-transmitted infections. However, the...
Krittika D&#x;Silva,Anastasios Noulas,Mirco Musolesi et al.
Krittika D&#x;Silva et al.
Estimating revenue and business demand of a newly opened venue is paramount as these early stages often involve critical decisions such as first rounds of staffing and resource allocation. Traditionally, this estimation has been performed t...
Capturing the fast-food landscape in England using large-scale network analysis [0.03%]
利用大规模网络分析捕捉英格兰的快餐景观
Magda Baniukiewicz,Zachariah L Dick,Philippe J Giabbanelli
Magda Baniukiewicz
Fast-food outlets play a significant role in the nutrition of British children who get more food from such shops than the school canteen. To reduce young people's access to fast-food meals during the school day, many British cities are impl...
Marco Pangallo,Michele Loberto
Marco Pangallo
Online activity leaves digital traces of human behavior. In this paper we investigate if online interest can be used as a proxy of housing demand, a key yet so far mostly unobserved feature of housing markets. We analyze data from an Italia...
Inferences about spatiotemporal variation in dengue virus transmission are sensitive to assumptions about human mobility: a case study using geolocated tweets from Lahore, Pakistan [0.03%]
关于登革热病毒传播时空变化的推论会对人类移动性的假设很敏感：使用巴基斯坦拉合尔市地理定位微博进行案例研究
Moritz U G Kraemer,D Bisanzio,R C Reiner et al.
Moritz U G Kraemer et al.
Billions of users of mobile phones, social media platforms, and other technologies generate an increasingly large volume of data that has the potential to be leveraged towards solving public health challenges. These and other big data resou...
Lawrence E Hunter
Lawrence E Hunter
Computational manipulation of knowledge is an important, and often under-appreciated, aspect of biomedical Data Science. The first Data Science initiative from the US National Institutes of Health was entitled "Big Data to Knowledge (BD2K)....
Enhancing disease surveillance with novel data streams: challenges and opportunities [0.03%]
新型数据流在疾病监测中的挑战与机遇
Benjamin M Althouse,Samuel V Scarpino,Lauren Ancel Meyers et al.
Benjamin M Althouse et al.
Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public h...
Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors [0.03%]
使用可穿戴接近传感器量化肯尼亚农村家庭环境中的社会接触
Moses C Kiti,Michele Tizzoni,Timothy M Kinyanjui et al.
Moses C Kiti et al.
Close proximity interactions between individuals influence how infections spread. Quantifying close contacts in developing world settings, where such data is sparse yet disease burden is high, can provide insights into the design of interve...
Open source data reveals connection between online and on-street protest activity [0.03%]
开源数据揭示了线上和线下抗议活动之间的联系
Hong Qi,Pedro Manrique,Daniela Johnson et al.
Hong Qi et al.
There is enormous interest in inferring features of human behavior in the real world from potential digital footprints created online - particularly at the collective level, where the sheer volume of online activity may indicate some changi...
Testing the hypothesis of preferential attachment in social network formation [0.03%]
检验社会网络形成中优先附着假说的假设测试问题
Thomas House,Jonathan M Read,Leon Danon et al.
Thomas House et al.
The hypothesis of preferential attachment (PA) - whereby better connected individuals make more connections - is hotly debated, particularly in the context of epidemiological networks. The simplest models of PA, for example, are incompatibl...