The students poured into Carlos Castillo-Chavez's office soon after swine flu struck Mexico last spring. The graduate students, some from Mexico, a few from Puerto Rico, knew the Arizona State mathematician was an expert in modeling disease spread.
"They were very scared because they had relatives there," said Castillo-Chavez. "They asked, 'Is there something we can do?'"
The cadre of concerned students worked Saturdays and Sundays to model the ensuing outbreaks of H1N1, which peaked three separate times in Mexico. In the model world they created, people were either susceptible or exposed, vaccinated or not.
They found that cases of H1N1 plunged when schools shut their doors, families went on vacation, and people intentionally isolated themselves, Castillo-Chavez reported here Sunday. But they also found an intriguing, smaller effect--the coming and going through Mexico City, the beating hub connecting 20 percent of the population, predicted the weekly variations in flu cases when school closed for the summer.
Delivering vaccines quickly--more than 40 days before the next outbreak--prevented severe outbreaks in the model. That's because even if the vaccine was in short supply, allocating it wisely made the difference between a severe outbreak and a mild one.
How the Mexican government actually responded, according to Castillo-Chavez, wasn't too far from his model's optimal solution.
"Mexico did a superb job given high levels of uncertainty," said Castillo-Chavez. "They took painful and extreme measures right away," he said, like closing down businesses and giving out surgical masks. Not every country might have responded that way--Chinese public health officials were slow to admit in 2003 that SARS had broken out, he said. The World Health Organization and French president Sarkozy praised Mexico's quick response, though some first-responding doctors have said Mexico did lag a bit.
But one shortcoming of his model, and of disease prevention worldwide, is knowing exactly how many people are infected at a given time, as the number of reported cases may be low estimates.
"We can't tell how bad things are. We don't have this extensive network of high quality systems. That would be the most important thing to put in place."