Induction of Social Contagion Across Diverse Outcomes in Structured Experiments in Isolated Honduras Villages (Science, 2024)
9 | Maternal and Child Health (MNCH) , Experiment , Network Targeting , Contagion Intervention , Breadboard Software , Global Health , LIMC , Social Contagion , Social Network

Citation:

Airoldi EM, Christakis NA. Induction of social contagion for diverse outcomes in structured experiments in isolated villages. Science. 2024 May 3;384(6695):eadi5147. doi: 10.1126/science.adi5147. Epub 2024 May 3. PMID: 38696582.

Algorithms for seeding social networks can enhance the adoption of a public health intervention in urban India (PNAS, 2022)
15 | Methodology , NAC Favorite , PNAS , India , Contagion Intervention , Experiment , Global Health , Social Contagion , Social Network , Sociocentric Network , Maternal and Child Health (MNCH) , LIMC , RCT , Trellis Software , Network Targeting

Citation:

M. Alexander, L. Forastiere, N. A. Christakis, and S. Gupta, “Algorithms for seeding social networks can enhance the adoption of a public health intervention in urban India,” PNAS, 119(30) e2120742119 (May 2022) DOI: https://doi.org/10.1073/pnas.2120742119

​Characterizing super-spreaders using population-level weighted social networks in rural communities
8 | Methodology , Honduras , Epidemic Disease , Infectious Disease , Social Network , Sociocentric Network , Trellis Software , Network Targeting

Citation:

S. Vishnempet Shridhar, M. Alexander, and N. A. Christakis, “​Characterizing super-spreaders using population-level weighted social networks in rural communities,” Philosophical Transactions of the Royal Society A, 380(2214) (Nov 2021) DOI: 10.1098/rsta.2021.0123​

Collective Communication and Behaviour in Response to Uncertain “Danger” in Network Experiments
8 | Connection Intervention , Breadboard Software , Social Network , Sociocentric Network , Experiment , NAC Favorite , Social Contagion , Network Targeting

Citation:

H. Shirado, F. Crawford, and N. A. Christakis, “Collective Communication and Behaviour in Response to Uncertain “Danger” in Network Experiments,” Proceedings A of the Royal Society, 476(2237): 1-19 (May 2020) DOI: 10.1098/rspa.2019.0685

Exploiting Social Influence to Magnify Population-Level Behavior Change in Maternal and Child Health: A Randomized Controlled Trial of Network Targeting Algorithms in Rural Honduras
11 | Methodology , Trellis Software , RCT , Social Network , Sociocentric Network , Experiment , Maternal and Child Health (MNCH) , Honduras , Global Health , Contagion Intervention , Network Targeting

Citation:

H.B. Shakya, D. Stafford, D.A. Hughes, T. Keegan, R. Negron, J. Broome, M. McKnight, E. Nicoll, J.A. Nelson, E. Iriarte, J.H. Fowler, and N.A. Christakis, "Exploiting Social Influence to Magnify Population-Level Behavior Change in Maternal and Child Health: A Randomized Controlled Trial of Network Targeting Algorithms in Rural Honduras" BMJ Open, (2017) 7(3), p.e012996.

Social network targeting to maximise population behaviour change: a cluster randomised controlled trial
11 | RCT , NAC Favorite , Contagion Intervention , Honduras , Social Contagion , Social Network , Sociocentric Network , Experiment , Global Health , Trellis Software , Network Targeting

Citation:

D.A. Kim, A.R. Hwong, D. Stafford, D.A. Hughes, A.J. O’Malley, J.H. Fowler, and N.A. Christakis, "Social network targeting to maximise population behaviour change: a cluster randomised controlled trial" The Lancet, Published online May 5, 2015 http://dx.doi.org/10.1016/S0140-6736(15)60095-2

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