As we discussed in a previous post, several causes led to a massive spike in food prices internationally in 2008 and again a few years later. The average world price of rice, for example, rose by 217% between 2006 and 2008. Classical theories have suggested that we shouldn’t worry about these spikes: that the high prices will lead to more production (attracting farmers to produce more, which will drive prices back down), people’s wages will adjust to costs of living, and people will be able to substitute for expensive items with other foods. But a new report tracking how the most-affected people have responded to the food spikes reveals that classical theories may be a bit out of touch…
Categories
Top Posts




In the olden days, doctors would travel from house to house when community members fell ill. Now, we usually expect patients to come to our office-based clinics. The modern model of care is certainly more efficient for us as physicians. But it’s also a barrier for patients to receive medicine; the highest-risk people usually make it to our clinics after being discharged from their first or second hospitalization, well after high blood pressure or diabetes has already taken its toll on their bodies. Our latest research suggests that we can statistically predict which people are most likely to end up having chronic diseases five or ten years from now. We can pinpoint these people right down to which house they live in. Such predictive models present a new opportunity to prevent disease before it becomes costly or deadly. In this week’s post, we look at a new idea for community-based disease prevention in medicine: the geographical mapping of chronic disease risks, and preemptive visits of healthcare workers to households where people are likely to become ill in the future.


