The amount of information available translates into differences mostly between the break-up rates of links that may involve a potential risk for further infection (b SI , b IR , b II ), and those that do not (b SS , b SR , b RR ). Therefore, we consider one particular rate b I for links involving infected individuals (b I :b SI~bIR~bII ), and another one, b H , for links connecting healthy individuals (b H :b SS~bSR~bRR ). In general, one expects b I to be maximal when each individual has perfect information about the state of her neighbors and to be (minimal and) equal to b H when no information is available, turning the ratio between these two rates into a quantitative measure of the amount of information available or the efficiency of information use. Note that we reduce the model to two break-up rates in order to facilitate the discussion of the results. The general principles and conclusions remain valid when all break-up rates are incorporated explicitly. It is worth noticing that three out of these six rates are of particular importance for the overall disease dynamics: b SS , b SR and b SI . These three rates, combined with the rate c of creating new links, define the fraction of active SS, SR and SI links, and subsequent correlations between individuals [44] , and therefore determine the probability for a susceptible to become infected (see Methods). This probability will increase when considering higher values of c (assuming b I .b H ). In other words, when individuals create new links more often, therefore increasing the likelihood of establishing connections to infected individuals (when present), they need to be better informed about the health state of their contacts in order to escape infection. In the fast linking limit, the other three break-up rates (b II , b IR and b RR ) influence disease progression since they contribute to altering the average degree of the network.