Rats and mice are common, but preventable. In NYC, rats tend to be seen on streets, alleys and sidewalks, and in yards and basements, while mice are almost always found inside buildings.

Rats and mice thrive where there are sources of food and shelter and where property owners fail to prevent and adequately respond to their presence.

Mice, Rats and Health

Today, rats are recognized for their contribution to neighborhood stress, poor quality of life, contamination of food, potential threat to public health, and for their contribution to the destruction of infrastructure. Mice can contaminate food, and their urine and dander are potent allergens, which can exacerbate the symptoms of asthma in sensitive people.

Prevention

Simple steps can be taken to prevent mice and rats both inside and outside:

• Report evidence of, or conditions that attract rats and mice to 311. Property owners are responsible for keeping their properties free of pests.

• Clean up. Garbage and clutter give rats and mice a place to eat and nest.

• Store all your food and food waste in hard side containers with tight fitting lids whether it’s inside or outside of the building.

• Seal up cracks and holes inside and outside your building or apartment to prevent the free movement of rats and mice.

• Keep yards and outdoor areas trimmed and free of clutter to avoid creating a harbor for rats.

Visit this resource to learn more about managing mice and rats: www.nyc.gov/rats.

Key Messages

The NYC Health Department uses an inspection technique called “rat indexing” to proactively evaluate the presence of rats in NYC neighborhoods. Rat indexing allows the Department to assess entire neighborhoods for their rat activity and rapidly notify property owners of conditions found on their properties. Both private properties and public properties receive detailed advice on what conditions were found and how to improve them. By engaging the public, the Department encourages whole blocks and neighborhoods to simultaneously concentrate their resources to maximize the effect of neighborhood level extermination and cleanup efforts. Free training is provided to property owners, managers, and city agency staff. Visit www.nyc.gov/rats to learn more.

There are many schemes of neighborhood boundaries (or geographies) available for different datasets. These include:

• Citywide
• Borough
• United Hospital Fund 42 (UHF42) and United Hospital Fund 34 (UHF34) neighborhoods
• Community Districts (CD), and, related, Community District Tabulation Areas (CDTA)
• Public Use Microdata Areas (PUMA)
• Neighborhood Tabulation Areas (NTA)

We try to make data available at as fine a geographic resolution as we can. Read more about different geographies at this data story.

It would be convenient if each dataset could be made available at the same geography, but this is not always possible. The neighborhood boundaries available depend on the specifics of the underlying dataset.

When we have multiple years of data, we show the data as trend charts.

Trends for individual neighborhoods tend to be very unstable (or "bouncy"), due to small counts for outcomes in individual neighborhoods. To show clearer trends, we usually aggregate up and show trend data by Borough.

Options on some indicators let you compare this indicator to other similar indicators.

We try to make data available as soon as we can.

Many datasets take a long time to reach us — a "lag" of several years, during which data are gathered from different entities to try to create a complete dataset; data are processed (cleaned, deduplicated, etc), and analyzed. It can take several years to prepare a dataset — so a dataset that is several years old is sometimes the most up-to-date information available. Still, this data continues to show us valuable trends and insights.

We also try to display datasets that have been available for many years. Some datasets (like those that are asked on surveys) are not asked every year of the survey, which means that we cannot provide annual data.

For some datasets, we have to aggregate time periods in order to break down data by borough or neighborhood.

Measures are the numeric ways that a dataset (or indicator) are expressed. Examples of different measures might be: number, percent or rate.

A number tells us how much of an outcome is in a certain area. But a rate (usually expressed as, for example, 40 per 100,000) tells us how much of an outcome there is, relative to the population of the area in question. This lets us compare neighborhoods of different sizes.

On this site, we try to show how environmental factors might be connected to health outcomes. One way we do this is with Correlates. We choose potentially-related datasets and display them on a scatterplot so you can see how these two datasets are correlated.

The Disparities view displays neighborhoods by poverty category to show underlying disparities in the data.

Read more about correlation here.