The Last 10%

Now that we have taken stock of our successes and established how imminently treatable the Canine Parvovirus is in an Animal Shelter setting, we can turn our attention to the areas where we have room for improvement— i.e. the last 10% of Parvo dogs that do not survive, despite receiving the same care as the 90% who do. It is interesting to note that this is not a limitation of the APA! treatment protocol, and, in fact, no one in the world knows how to save this last 10%. Several experimental treatments are possible for saving this group, but it is difficult to tell who should receive such treatments before they have reached a severity level where the efficacy of any treatment is doubtful. Our goal, as Data Scientists, should be to identify these animals before they reach a theoretical “point of no return” so an alternate treatment may be attempted. To this end, a survival model can be employed to determine what measured, critical factors contribute to the probability of death, and, moreover, how successful we can be with the basic metrics in predicting which dogs will not respond to the treatment.

When constructing a Survival Model, we will use a Cox Proportional Hazard Model which allows us to determine risk associated with the occurrence of an event in time, given some observed quantities. In this case, we can observe:

Subjective Status/Attitude (Comatose, Lethargic, Quiet and Responsive, Bright and Responsive)

Gum Color (White, Gray, Pale Pink, Pink)

Paw Temperature (Cold, Warm)

Appetite (No Interest, Voluntarily Eats Small Amount, Normal)

Drinking Water (Yes, No)

Feces (1–7 scale between solid and normal and bloody diarrhea)

Vomiting (Severe, Moderate, Mild, or None)

Sex (Male, Female)

Intake Age

Intake Weight

Note that Subjective Status is, in and of itself, a measure of Severity. However, when we look at it alone, we see it simply tracks with their time since intake (bifurcating if they get worse or better). It is not particularly resolute and does not offer much possibility of being a sole predictor of non-responsiveness as animals can arrive at variable stages of disease progression.