Curran et al. tackle an important problem: coping with epidemics, for example, seasonal influenza, that can be challenging for healthcare organizations due to sudden surges in patient volume.

Health informatics solutions and health surveillance systems allow for better preparedness for the impact of epidemics. Social networks, that is, microblogs, can be used to collect additional syndromic data on earliest indicators in advance of disease outbreaks.

The authors emphasize the importance of continually integrating available information from all potential sources in a close to real-time manner to create a realistic picture of the health threats. The paper suggests integration of big data analytics with simulation functionality to ensure that hospitals have better prediction strategies and are prepared for the epidemic-generated surge in service requests.

To model hospital surge capacity, the paper uses an extension of the susceptible, exposed, infectious, and recovered (SEIR) model based on the system dynamics approach to simulation.

The intended audience is academics in management science and capacity planning and management, and hospital analysts. The audience will appreciate the novelty of the authors’ approach of extending current models by incorporating big data sources of social networks into the sound methodology of simulation modeling with system dynamics. The proposed conceptual framework may lead to solid implementations with important healthcare impacts. Readers who are interested in this topic can find additional information on the subject [1,2].