@article {10.1371/journal.pcbi.1007517,
	title = {Efficient sentinel surveillance strategies for preventing epidemics on networks},
	journal = {PLOS Computational Biology},
	volume = {15},
	number = {11},
	year = {2019},
	month = {11},
	pages = {1-19},
	publisher = {Public Library of Science},
	abstract = {Author summary In a network of individuals susceptible to some infectious disease, what are the best locations to monitor in order to detect the infection before most damage can be done? In this paper we address this question by considering various heuristic strategies for sentinel placement that can potentially be implemented in real-world situations without requiring excessive amounts of computation, or even having perfect data about the structure of the network. We find that strategies that attempt to distribute sentinels over different regions of the network perform best in highly modular or spatially embedded networks, whereas the strategy of targeting the most well connected individuals works best when there is a considerable amount of contact heterogeneity between individuals. Our results may be used as a guideline to help decide when certain strategies should, or should not, be implemented.},
	doi = {10.1371/journal.pcbi.1007517},
	url = {https://doi.org/10.1371/journal.pcbi.1007517},
	author = {Colman, Ewan and Holme, Petter and Sayama, Hiroki and Gershenson, Carlos}
}
@article {10.3389/fphy.2018.00045,
	title = {Rank Dynamics of Word Usage at Multiple Scales},
	journal = {Frontiers in Physics},
	volume = {6},
	year = {2018},
	pages = {45},
	abstract = {The recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books $N$-grams dataset to analyze the temporal evolution of word usage in several languages. We apply measures proposed recently to study rank dynamics, such as the diversity of $N$-grams in a given rank, the probability that an $N$-gram changes rank between successive time intervals, the rank entropy, and the rank complexity. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. We also propose a null model to explore the relevance of linguistic structure across multiple scales, concluding that $N$-gram statistics cannot be reduced to word statistics. We expect our results to be useful in improving text prediction algorithms, as well as in shedding light on the large-scale features of language use, beyond linguistic and cultural differences across human populations.},
	issn = {2296-424X},
	doi = {10.3389/fphy.2018.00045},
	url = {https://www.frontiersin.org/article/10.3389/fphy.2018.00045},
	author = {Morales, Jos{\'e} A. and Colman, Ewan and S{\'a}nchez, Sergio and S{\'a}nchez-Puig, Fernanda and Pineda, Carlos and I{\~n}iguez, Gerardo and Cocho, Germinal and Flores, Jorge and Gershenson, Carlos}
}
