Evaluation of effects of detection-tracking-isolation in infectious disease control based on individual models

Objective To evaluate the effects of different prevention and control measures for infectious diseases, a computational model was established to study the influence of detection-tracking-isolation measures on infectious disease transmission dynamics.

Methods We developed a simulation platform utilizing individual-based model and dynamic close-contact networks to simulate the spread of infectious diseases. Based on the dynamic changes of the contract network, the individuals, close contacts, secondary close contacts, and individuals with field exposures were tracked. Different individuals were managed with different control measures, including isolation and clinical detection. We used the model to simulate the epidemic trend after a local outbreak and estimate the changes in the cumulative number of infections and daily new infections.

Results In the absence of preventive measures, the incidence of infection increased rapidly after a local outbreak, daily new infections would reach peak within about a week. However, if detection-tracking-isolation measures are taken, the incidence of infection and daily new infections would all significantly decreased. Nonetheless, more stringent preventive measures are still needed for the epidemic prevention and control.

Conclusion The quantitative model calculations indicate that detection-tracking-isolation measures are the effective in the response to local outbreaks in China.