|
| 1 | +## Plans |
| 2 | +- Overview: Old GHT, new Google Symptoms. Go through previous notebook (copy |
| 3 | + that notebook into this directory) |
| 4 | +- Demo correlations notebook: very crude time analysis where we aggregate over |
| 5 | + all counties and examine the correlation with respect to time |
| 6 | +- Open problems; each one can be its own notebook: |
| 7 | + - Amount of missingness by county, symptom. Should we just discard some |
| 8 | + of the symptoms because it's available so rarely? Many of the symptoms |
| 9 | + seem _a priori_ totally unrelated to COVID-19, e.g., excessive hoarding, |
| 10 | + should we toss those out to make our lives easier? |
| 11 | + - Overwhelming number of symptoms reported: 422. How to efficiently |
| 12 | + perform a correlations analysis for all of them at once? (We would |
| 13 | + want to examine over time; across counties; at various time lags |
| 14 | + against cases) |
| 15 | + - Correlations analysis can give us a sense of what symptoms to include |
| 16 | + in a new indicator; then we would need to weigh them appropriately |
| 17 | + into the new indicator. Unexpected correlations (that are not |
| 18 | + spurious) may provide new insight. |
| 19 | +- My view on two approaches to a new indicator (we could do both, assuming |
| 20 | + we have the people): |
| 21 | + - "Scientifically guided approach": consult medical / public health |
| 22 | + literature & experts to obtain a subset of symptoms, weigh them |
| 23 | + appropriately, this is the new indicator. Google considered such an |
| 24 | + approach, but decided to defer construction to users because of |
| 25 | + lack of uniform advice across different agencies with which they |
| 26 | + consulted. PRO: May give us signal beyond (often unreliable) case |
| 27 | + reporting. |
| 28 | + - "Brute force approach": set up supervised problem(s) against cases |
| 29 | + (at various lags), through in all of the symptoms, see what allows us |
| 30 | + to best mimic cases. PRO: Should be well-correlated with cases; if |
| 31 | + trained against appropriately backfilled cases, it can give a "nowcast" |
| 32 | + of cases. |
| 33 | + |
0 commit comments