Critical Reasoning

Lyme disease is caused by a bacterium transmitted to humans by deer ticks. Generally,
deer ticks pick up the bacterium while in the larval stage from feeding on infected white-footed mice. However, certain other species on which the larvae feed do not harbor the bacterium. Therefore, if the population of these other species were increased, the number of ticks acquiring the bacterium and hence the number of people contracting Lyme disease would likely decline.

Which of the following, if true, most strengthens the argument?

A. Ticks do not suffer any adverse consequences from carrying the bacterium that causes Lyme disease in humans.
B. There are no known cases of a human's contracting Lyme disease through contact with white-footed mice.
C. A deer tick feeds only once while in the larval stage.
D. A single host animal can be the source of bacteria for many tick larvae.
E. None of the other species on which deer tick larvae feed harbor other bacteria that ticks transmit to humans.

Intensive discussion has been done here, but I have created a new thread because I was afraid that my question might get lost in that lengthy thread.

My Question:
Is there something like " Predictive causal statements and non-predictive casual statements."
Some of my colleague told me, and I searched on the Internet, but couldn't find that.

" Predictive causal statements and non-predictive casual statements". Such statements are part of LSAT exam I am unsure whether they could be part of GMAT or not but for more info on this you can refer any LSAT book you will find your answer.

My Question:
Is there something like " Predictive causal statements and non-predictive casual statements."
Some of my colleague told me, and I searched on the Internet, but couldn't find that.

Critical Reasoning always comes down to rigorous logic. My guess is that the distinction here is between two cases.

Case 1: There is an observed correlation between x and y, therefore, someone deduces that x causes y. Here we'd think about the possibility that y might cause x, or that z might cause both. In essence, we're trying to differentiate between causation and mere correlation.

Case 2: If we do x, then y will happen. (Notice the future tense.) We'd treat this type of argument as a simple prediction. Now we're thinking about what factors might make 'y' more or less likely to happen, rather than considering what else could cause y.