When Sandy hit New York on October 29th 2012 there were those who wondered about the fate of its underground scene. Not the underground arts scene but the literal underground rats scene. It was speculated that they either drowned in droves or got relocated into the safer and drier neighborhoods. As the news articles show, there were anecdotal evidences of rats becoming more of a problem in different neighborhoods.

I thought it would be an interesting exercise to see if that this can be picked up by the existing data we have on rats: rat sightings made to 311. I downloaded the rat sightings file from the NYC Open Data website and plotted the geocoded sightings made a month before Sandy and a month after. I was expecting to see some strong spatial signature, something that shows that the rats got washed away from the areas near the water fronts into the inner parts of each borough. However, other than a reduction in the total number of sightings (were there really less rats or were people less likely to report them?) the map does not suggest that anything interesting happened.

If such a spatial signature would have been apparent in the data then it could have been an interesting natural experiment that could have helped us learn about the effects that rats have on health and infrastructure. Especially if that signature were to persist for several months until the rats recolonized the flooded niches and reached their max capacity again.

Even if such a signature did exist then it could still be easily argued that Sandy is not close enough to the ideal experiment of randomly reshuffling rats around the city and that Sandy itself would have an impact on some of the outcome variables of interest. This is a larger issue of conducting bioeconomics inference. We want to learn more about the dynamics and the causal relationship between certain species and our outcome of interest, but rarely do we have a proper setting that allows for such inference.

Wondering just how many rats there are in the city? Here is a nicely estimated number, and its coverage in the media.

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