It really depends on making (and training) an adaptation to your per-frame detector to incorporate prediction priors, then devising a method for making the prediction priors from previous frames' output. I'm not that familiar with the specifics of your particular problem to add much more, I'm afraid.

In the most general sense, tracking is the same as detection, but with priors based on a prediction of what you're expecting to see from past history. So tracking obviously requires an image sequence, and detection only a single timestep. Tracking can potentially be faster and more accurate, because you have access to this extra information which limits your search space, but is also reliant on the quality of your prediction; bad prediction mean tracking failures.

I'm not completely sure if this is the level of answer you're looking for though.

This is an annoyingly gross generalisation. Obviously one really, really bad day can dramatically affect your whole life, and saying "don't let it" really doesn't help you at all, just makes you write snarky Reddit comments like this one. But saying "slightly bad days" l instead wouldn't be as catchy.