Based on the results reported in Section 3.3, we have shown that the proposed intervention based on estimated infection networks is very effective in limiting the scale and slowing down the spread of infectious disease epidemics. However, as discussed in Section 3.2, the estimated infection networks are not always accurate, especially when the proportion of unreported incidences is high. Figure 4a suggests that the estimation accuracy goes to zero at censor rate C T ,100%. This implies that it might be difficult to do network estimation in the US, where censor rates for mild illnesses are close to 100% because of the expensive medical insurance and co-payments. However, we stand a better chance of making the scheme work in Singapore as the low medical cost and the necessity to obtain medical certificates to stay away from work promote doctor consultations even for mild symptoms. To further improve the accuracy, the incidence data can be easily complemented with other types of relevant data. For instance, cell-phone and GPS co-location information can be used to rule out a large proportion of tentative links connecting pairs of individuals that have never been found in the same location over the infection time step of about three days. This will reduce the rate of forming false links significantly, thus improving the accuracy of the estimation.