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It's the Network, Stupid: Why Everything in Medicine Is Connected

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It's the Network, Stupid: Why Everything in Medicine Is Connected Editorial It’s the Network, Stupid: Why Everything in Medicine Is Connected The PLoS Medicine Editors ne need look no further the outbreak was tied to a network not emerge from studying individual than Facebook to appreciate of sexual contacts who were meeting behavior. Othe significance and power through Internet chat rooms [2]. The Lewis and colleagues conducted of social networking. (Even PLoS public health department was then able their study because of a seeming has its own thriving Facebook to initiate an electronic awareness and contradiction. Genetic studies of community, which you can join at partner notification campaign using HIV transmission networks have not http://www.facebook.com/group. the same Web-based sexual network; corresponded well with the social php?gid=2401713690.) But social 42% of named partners were identified contact networks revealed through networking is about more than just and evaluated. interview data. The authors’ use of friends reunited; it’s a framework for The observation that social relations phylodynamics—a mix of genetics, understanding even the most basic of and interdependency play a part in epidemiology, and evolutionary biological processes. Two papers in health is not surprising. But what biology—allowed a more sophisticated this month’s PLoS Medicine illustrate network theory teaches us is that look. By examining and dating the the insight that network theory brings connections, even within the most genetic sequences of men attending to basic science, and the valuable complex systems, are not random (that an HIV clinic in central London, Lewis interdisciplinarity that social network is, they are not unpredictable). Instead, and colleagues found large clusters analysis can inspire. networks behave in ways that we can comprising ten or more individuals, a Once the domain of social theorize, model, and predict. quarter of whom had transmitted the scientists—who have used social virus within several months of being network analysis to study such infected. This information is valuable diverse phenomena as kinship ties, In network analysis, for understanding HIV transmission organizational behavior, rumor the network becomes dynamics, not least because rapid spreading, and global air traffic— more important than the transmission within clusters may result network theory has now entered the in the spread of drug-resistant strains. purview of health scientists. Network individual entity. Network analysis is also used in theory is concerned with mapping Mossong and colleagues’ study on the the links between entities, and social In its simplest form, network analysis dynamics of influenza transmission, network analysis is the application can map ties between entities (whether reported in this month’s PLoS Medicine of that theory to the social sciences. elephants, humans, or genes).The same [7]. Using paper diaries completed by Searching for more social and principles that allowed researchers over 7,000 Europeans documenting environmental explanations for the to characterize the role of matriarchs their daily physical and nonphysical obesity epidemic in America, for in the social organization of the contacts, Mossong and colleagues example, Christakis and Fowler [1] endangered African elephant species found varied mixing patterns, duration showed that obesity can spread from [3] also illuminated the collective of contacts, and types of contacts. This person to person, and that this spread dynamics fueling individual donations information allowed the researchers depends on the nature of social ties: to the 2004 tsunami relief fund [4], to produce a mathematical model that a person’s chance of becoming obese and provided the techniques to model suggests that 5-19-year-olds will suffer increased by 171% if he or she had a the gene network that controls T cell the highest burden of respiratory mutual friend who had become obese activation in humans [5]. infection during any initial spread. (even if they lived far away). Their But beyond identifying simple risk increased by 40% if it was their links, network analysis also helps Citation: The PLoS Medicine Editors (2008) It’s the sibling or spouse who became obese. to illustrate the structure of those network, stupid: Why everything in medicine is Christakis and Fowler concluded ties—the nature of the relationships, connected. PLoS Med 5(3): e71. doi:10.1371/journal. that the social network is a crucial the rules that govern them, and how pmed.0050071 component—perhaps more so than we might predict various relationships Copyright: © 2008 The PLoS Medicine Editors. This genetics—in explaining obesity, a or outcomes under various conditions. is an open-access article distributed under the terms of the Creative Commons Attribution License, problem normally thought of as solely The network becomes more important which permits unrestricted use, distribution, and biological and behavioral. than the individual entity. In this reproduction in any medium, provided the original Similarly, a major advance in month’s PLoS Medicine paper by Lewis author and source are credited. stemming an outbreak of early syphilis and colleagues [6], for example, E-mail: [email protected] in San Francisco was accomplished investigating the transmission network The PLoS Medicine Editors are Virginia Barbour, through understanding social networks. (and its episodic nature) provides Jocalyn Clark, Larry Peiperl, Emma Veitch, and Gavin Klausner and colleagues found that insights into HIV prevention that would Yamey. PLoS Medicine | www.plosmedicine.org 0333 March 2008 | Volume 5 | Issue 3 | e71 Mossong and colleagues’ work The same insights generated from 4. Schweitzer F, Mach R (2008) The epidemics of donations: Logistic growth and power-laws. illustrates how the patterning of social social network analysis about the PLoS ONE 3: e1458. doi:10.1371/journal. contacts—between and within groups, spread of disease hold the key to pone.0001458 and in different social settings—and developing effective interventions to 5. Palacios R, Goni J, Martinez-Forero I, Iranzo J, Sepulcre J, et al. (2007) A network analysis not just contact rates can influence halt that spread. The nature of social of the human t-cell activation gene network how new emerging diseases spread. networks that drive transmission of identifies jagged1 as a therapeutic target for Physical exposure to an infectious syphilis and other sexually transmitted autoimmune diseases. PLoS ONE 2: e1222. doi:10.1371/journal.pone.0001222 agent, the authors conclude, is thus infections, for example, demonstrate 6. Lewis F, Hughes GJ, Rambaut A, Pozniak best modeled by taking into account that the Internet is an appropriate A, Leigh Brown AJ (2008) Episodic sexual the social network of close contacts and place to deliver safe sex education transmission of HIV revealed by molecular phylodynamics. PLoS Med 5: e50. doi:10.1371/ its patterning. [9–11]. Exploiting the peer influences journal.pmed.0050050 The physicist Albert-László Barabási that feed the social network of obesity 7. Mossong J, Hens N, Jit M, Beutels P, Auranen Linked K, et al. (2008) Social contacts and mixing argues in his book, , that “there is (or smoking, or substance abuse) patterns relevant to the spread of infectious a path between any two neurons in our could be a meaningful way to spread diseases. PLoS Med 5: e74. doi:10.1371/ brain, between any two companies in healthy behaviors. Even in diseases that journal.pmed.0050074 8. Barabási A-L (2003) Linked: How everything the world, between any two chemicals appear intractable to our campaigns is connected to everything else and what it in our body. Nothing is excluded and controls, we might best inform means. New York: Plume. 304 p. from this highly interconnected web policy makers and health promoters by 9. Benotsch EG, Kalichman S, Cage M (2002) Men who have met sex partners via the of life” [8]. As health professionals, considering: It’s the network, stupid. Internet: Prevalence, predictors, and we might find network analysis useful implications for HIV prevention. Arch Sex References in helping us describe and explain Behav 31: 177–183. 1. Christakis NA, Fowler JH (2007) The spread of 10. Bolding G, Davis M, Hart G, Sherr L, Elford the connections in matters of health, obesity in a large social network over 32 years. J (2005) Gay men who look for sex on the whether they be at the cellular or N Engl J Med 357: 370–379. Internet: Is there more HIV/STI risk with population level. But we will also want 2. Klausner JD, Wolf W, Fischer-Ponce L, Zolt I, online partners? AIDS 19: 961–968. Katz MH (2000) Tracing a syphilis outbreak 11. Curioso WH, Blas MM, Nodell B, Alva to act. through cyberspace. JAMA 284: 447–449. IE, Kurth AE (2007) Opportunities for Indeed, the greatest value in 3. McComb K, Moss C, Durant SM, Baker L, providing web-based interventions to prevent Sayialel S (2001) Matriarchs as repositories of sexually transmitted infections in Peru. understanding networks lies in what social knowledge in African elephants. Science PLoS Med 4: e11. doi:10.1371/journal. they can tell us about taking action. 292: 491–494. pmed.0040011 PLoS Medicine | www.plosmedicine.org 0334 March 2008 | Volume 5 | Issue 3 | e71 .
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