And that's all crimes, including petty and property crimes... At least in 2019, according to reported crime, and visitor estimates.

But, how does that work out?

Isn't Baltimore the most dangerous city in the US?

Well, sort of.

There are a few things that skew the current "Crime Rate" calculation worth noting:

**1. Only populations over 250,000 are included**

This means everywhere in the US with a population

**under 250,000**is**automatically excluded and exempt**from the "Most Dangerous Places" listThis is NOT because there isn't crime outside these larger cities. Rather, often the crime data in those areas is poorly reported, so larger jurisdictions end up being the 'most dangerous places' because they are the only ones with competent reporting. All the smaller ones are considered "crime free" and "safe" simply by default, because they have no data to consider, or are simply left out of consideration (which of course, doesn't make them safer).

**2. Visitors aren't included**

Crime rate is based on resident population, not the number of people who occupy the space.

As a result, tourist locations have an artificially inflated crime rate, since the crimes committed by and to visitors count toward crime totals, but the individual visitors don't count as ever having been there.

As an example, Ocean City MD has 7,100 residents and up to 8 million visitors a year. Their crime rate is based only on the 7,100 residents. It's a huge statistical error, that needs correcting.

**3. Severity is done poorly**

This simply means that crimes are reported based on their type, not their severity.

As a result, you can have the same types of crimes (say, "Common Assault") that range from a minor nuisance.... all the way to hospitalization, with long term emotional and physical damage.

**4. Crime Rate isn't Probability of Crime**

Probability is the number of events, divided by the number of possible outcomes

Crime Rate is just the number of crimes, divided by the number of people living there, multiplied by 100,000

Probability of crime, at its most general, requires you to count not just the number of crimes, but also the number of non-crimes (ie. the times that crime could have occured and didn't).

This isn't all the problems (__see more__), but it's a good majority

If we wanted to try calculating an actual probability of "**Safety from crime**" in a given place, it would look like this:

Count the number of days people spent there

Count all days where

**1 crime**occurred for**1 person**Count all the days where

**0 crimes**occurred for**1 person**Run the probabilities for each

If we did that for Baltimore in **2018**, it would looks like this:

**Baltimore Residents**spent**223,404,432 days**in Baltimore**Visitors**spent**26,000,000 days**in Baltimore

So, **people spent a total of 249,404,432... or 1/4 billion days in Baltimore** in 2018.

Of those 1/4 billion days spent in Baltimore:

**Victim of 1 Crime****48,359**days, 1 crime occurred for 1 person**Crime-Free**- On**249,356,073**days, someone had a completely crime free day

That means, the probability in **2018 **for:

A

**Crime-Free day in Baltimore**=**99.98061%**

A

**day as a victim of 1 crime**=**0.01939%**

The numbers for **2019** were similar at:

**Crime-Free days**=**99.98168%****Days as a victim of 1 crime**=**0.01832%**

And this is for ALL reported crimes... even the "petty" ones.

**We can take it further by subdividing crime types by severity.**

We hear a lot about Baltimore murders and Covid-19, so those are easy comparisons to start with.

If we took a Covid severity format, and applied it to Baltimore crime, what would it look like?

Covid-19 stats are typically broken into 4 levels of severity:

**Deaths****Hospitalizations**- Severe**Minor Symptoms**- No Hospital**Asymptomatic**- No symptoms

We don't have Hospitalization stats related to crimes, but if we calculate the rest, and show each amount as space, relative to the size of Baltimore city, it'd look like this:

Again, that's:

Deaths

Minor Symptoms

All Cases (the rest being Asymptomatic)

The equation looks like this:

To map all cases with symptoms, in 2019 there were 45,692 reported crimes.

To our scale of 10 sq ft for every 1 crime, that's 456,920 sq ft (or about 11 acres), which is roughly the same size as a medium sized grocery store and it's parking lot. Specifically, it's the same size as the Canton Safeway and it's parking lot (pictured below), relative to the size of the city.

To map all murders, in 2019 there were 348.

To our scale of 10 sq ft per case, that's 3480 sq ft, which is 2-4x the sq footage of a single floor in a home. Or, in this map, about the same size as the Bakery section in Safeway.

Again, this accounts for ALL days where someone is a victim of crime in Baltimore.

This means that every other day that someone spends in Baltimore, they are 100% crime free. Or in our case, being criminally 'Asymptomatic' for a day in Baltimore.

That map, and those numbers look like this:

Now, this doesn't take a lot into account, like:

Half Days

People traveling away from the city

Drive through commuters

Longer impacts of harm

Other causes of harm beyond crime

But it is a better place to start in terms of predicting "**Probability of Safety from Crime**".

Now, while we don't have hospitalizations related to Baltimore crime, we do have it for the flu, and so can compare Baltimore Crime's "Any Symptoms" category to the Flu's hospitalizations.

While a 'case of **a day in Baltimore**' only has a **0.01832% chance** of having 'Any crime related symptoms', the **flu has a 1.1% chance** of sending you to the hospital.

So, arguably, a case of the flu is far more harmful than a day in Baltimore.

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