Network effects of risk behavior change following prophylactic interventions.
We formulated a network-based model to understand how risk behavior change in conjunction with failure of prophylactic interventions can lead to unintended outcomes where "less (intervention) is more (effective)." Our model captures the distinction between one- and two-sided risk behavior change. In one-sided situations (e.g. influenza/H1N1) it is sufficient for either individual in an interaction to exhibit risk behavior change whereas in two-sided situations (e.g. AIDS/HIV) it is necessary for both individuals in the interaction to exhibit risk behavior change, for a potential transmission of the disease. A central discovery is that this phenomenon occurs at differing levels of intervention coverage depending upon the "sidedness" of the interaction. We find that for one-sided interactions, sufficiently high vaccination coverage is necessary for mitigating the effects of risk behavior; for two-sided interactions, it is essential to combine prophylactic treatments with programs aimed at reducing risky behavior. Furthermore, again dependent on the "sidedness," targeting highly connected nodes can be strictly worse than uniformly random interventions at the same level of coverage.
College of Computer and Information Science, Northeastern University, Boston, Massachusetts, USA.
Rajmohan
R
Rajaraman
Zhifeng
Z
Sun
Ravi
R
Sundaram
Anil Kumar S
AK
Vullikanti
D003140:Communicable Disease Control; D003141:Communicable Diseases / Q000453:epidemiology / Q000635:transmission; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D011336:Probability; D012309:Risk-Taking; D060756:Social Networking; D014611:Vaccination