movement of any pathogens they carry, but they’ve only recently been used in
this context. Current models often make simplifying assumptions that aren’t
borne out in real life. For example, they assume that if the government imposes a
quarantine, people will obey it. In Singapore during the SARS epidemic,
however, the threat of fines and jail time proved insufficient to persuade
quarantined people to stay home. Authorities ultimately installed webcams in the
homes of everyone quarantined, telephoned them three times a day, and
required them to take their temperature on camera. Such measures probably
wouldn’t be tolerated in a less authoritarian state. To deal with similar public
health challenges in the future, we need to foster collaborations between
mathematical scientists and researchers from the economic, social, and
behavioral sciences.
Figure 4: A cholera hospital can be set up relatively quickly, saving the lives of those
infected and helping to control the spread of the disease. Mathematical models were
used to help officials decide where to place such hospitals during the 2010 cholera
epidemic in Haiti. Since a cholera epidemic was first confirmed in October in Haiti’s
Artibonite region, hospitals were set up and teams have treated more than 10,
suspected cases nationwide. Credit: Richard Accidat/MSF, Nov 11, 2010.Mathematical and statistical models need to be developed that allow forimperfect compliance with quarantines and that help to determine the
combination of punishments and rewards that will be sufficient to keep
quarantined individuals in their homes with minimal intrusions on their freedom
and privacy. Similar issues arise in introducing model assumptions about
compliance with vaccination orders, travel restrictions, or other public health
interventions. Developing mathematical models for issues like these – much of