Can we consider high correlation to be a good predictor? The problem of predicting the daily number of COVID-19 cases is indeed challenging and many (external) factors should be taken into account to come up with a reasonable predictor. However, we have studied Twitter for a specific country (not English) for the period Mar-Nov 2020, and found out that the volume of daily tweets related to symptom X is highly correlated with the number of confirmed cases in that country (pearson correlation 0.84 with p-value 0.00031).
In the field of data science, would this suffice, at least partially, to say daily tweets of X is a good predictor for the number of COVID-19 cases?
In this case, I would fit a linear model (lm(tweets ~ cases)) and then use bootstrap or cross-validation to test the model.