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Monday, September 4, 2017

How Pets Get Admitted and Later Leave Dallas Animal Shelters

Thanks to Dallas OpenData anyone has access to the city animal shelter records.  If you lost or found a pet it could be that he or she spent some time in a shelter - I personally took lost dogs there. It's unfortunate but every year tens of thousands of animals find their way to shelters with significant fraction never finding way out. 

What and How Many Animals are Admitted?

City of Dallas animal shelter dataset contains 5 different animal types with solid lead belonging to dogs and cats (hardly any surprise to anyone):

For consistency and plausibility of analysis we will focus on cats and dogs only

How Animals get Admitted

Each shelter record has animal's intake type (reason animal was admitted) and outcome (cause for animal disharge). Top 2 reasons why cats and dogs turn up at shelters are Stray (lost or abandoned) and Owner Surrender (willingly brought in by owner) while Confiscated (abused, no owner, etc.) is #3 for dogs but not cats

How Animals Leave Shelter

Animals leave shelters (either alive or dead) for 4 main reasons (outcomes):  Adoption (good),  Euthanized (bad), Returned to Owner (good), and Transfer (neutral):

Unfortunately, for both cats and dogs the top reason to leave shelter is being euthanized. But that's where similarity between them ends: 

  • cats don't get returned to owner anywhere near as often as dogs;
  • dogs' adoption and euthanized rates are almost the same while cats get adopted far less. 

From Admissions to Outcomes with Sankey

So what is the relationship between intake types and outcomes? Which and to what extent intake types drive outcomes? The good news there is some causality effect because each stay begins with intake type and ends with outcome. 

We begin analyzing this relationship with higher level (in that case) but visually appealing visualization called sankey diagram (or just sankey). It is a specific type of flow diagram, in which the width of the arrows is shown proportionally to the flow quantity. In our case each dog shelter stay contributes to the pipe size flowing from left (an intake type) to right (an outcome). With this we basically visualize conditional probabilities of dog leaving shelter with certain outcome given its admission intake type (first image illustrates transitions for cats and second does the same for dogs):

While Owner Surrender intake type flows similarly for both, Stray animals don't: cat outcomes are dominated by Euthanized but dogs are dominated by Adoption with Transfer and Returned to Owner outcomes together matching Euthanized.

Correlations Between Admissions and Outcomes

Next, we go beyond overall totals used in the sankey and compute correlations. To correlate intake types and outcomes we construct time series by computing monthly totals for each intake type and outcome obtaining monthly trends. Then we correlate between monthly trends (separate for cats and dogs) animals brought in and removed from Dallas animal shelters for each pair of top intake types (Confiscated, Owner Surrender, and Stray) and outcomes (Adoption, Euthanized, Returned to Owner, and Transfer) - 12 coefficients in total:

In this case strong correlation implies (at least to some extent) causation effect due to presence of temporal relationship, consistency, and plausibility criteria (see here and here). Few observations to note:
  • The highest correlation for cats (0.91) and second highest for dogs (0.77) are observed between intake Surrendered by Owner and outcomeEuthanized which is almost as obvious as unfortunate.
  • Correlation between Stray and Returned to Owner for dogs is the highest at 0.86. This is great news because it means the more dogs get lost the more of them are found. The higher this correlation the healthier the city for 2 reasons: a) lost animals return home and b) larger share of stray dogs are lost ones and not abandoned (given that the city keeps collecting them).
  • Unfortunately trend in Stray cats correlates highly with Euthanized. So while Stray dog trend drives adoptions and returns, Stray cat trend affects euthanizations the most (we've seen that in sankey as well).
  • No trends are affected by variations in Confiscated dogs, but this is likely due to smaller share of such admissions.
  • Variation in Stray dogs admitted affect every outcome (but Euthanized). Indeed Stray intake type is the largest and is almost twice as big as the 2d largest dog type Owner Surrender
  • Low correlation for dogs between Stray and Euthanized needs additional analysis because it's counter-intuitive.

Monthly Trends

But can we do better than correlations of these trends which technically are sophisticated but still aggregates? Next visual places time series instead of correlation coefficients inside the same matrix grid allowing to see and compare actual monthly trends:

Note that each plot is a 3 x 4 matrix - the same dimension as correlations matrices before. But instead of correlation coefficient each cell contains a pair of monthly trends (in fact, each correlation was computed for these exact pairs of trends, hence, a reference to its aggregation origin). Each row corresponds to an intake type (the same blue line in each) and each column to an outcome (the same red line in each). Being able to see trends over time let's record a few observations (following the matrix order top down):
  • Confiscated intake trends flat for both cats and dogs with only significant spike for dogs in January 2016. This spike is so unusual, relatively big, and contained within single month or two that it begs additional investigation into probable external event or procedural change that may have caused it.
  • Number of Confiscated animals is relatively low to noticeably affect outcomes. Still, if we can reduce effect of other intake types some relationships are possible.
  • Owner Surrender trend correlation with Euthanized outcome is so obvious that this type of visualization is sufficient to find it. Yes, it is unfortunate but people bring their old or unhealthy pets for a reason. 
  • The same applies to Stray and Owner Surrender for cats only. 
  • Owner Surrender has significant seasonal component spiking in summer possibly due to hot weather or holiday season or both. For cats only seasonal component is also strong in Stray trend.
  • Euthanized trends together with Owner Surrender which causes it to a large degree.
  • Stray dogs trend slowly upwards in Dallas and it's alarming.
  • Adoption also trends upwards but not steep enough to compensate for inflow of dogs into shelters.  Targeted campaign to encourage more adoptions of pets in the city is due.
  • Transfer outcome trending upward also compensates  for the growth in stray dogs. It's not clear if it's positive or negative though as there is no means to track what happens to dogs after transfer (or is it?).
  • Stray trend for dogs dipped in January 2016 exactly when confiscated trend spiked - it could be a coincidence or related - for sure something to consider when investigating further.
  • For dogs Euthanized trend correlates strongly with Stray intake until the summer of 2016 when they start to diverge in opposite directions - again some policy or procedural change apparently caused it. Indeed, if we observe other outcomes we notice that Returned to Owner trend began its uptick at around the same time (indeed, after I observed this I found out about this and this - significant changes in Dallas Animal Services leadership and policies around summer and fall of 2016).
I will be back with more analysis (survival analysis). R code for data processing, analysis, and visualizations from this post can be found here.

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