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docs/api/covidcast-signals/chng.md

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@@ -26,6 +26,8 @@ commercial purposes.
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| --- | --- |
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| `smoothed_outpatient_covid` | Estimated percentage of outpatient doctor visits with confirmed COVID-19, based on Change Healthcare claims data that has been de-identified in accordance with HIPAA privacy regulations, smoothed in time using a Gaussian linear smoother |
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| `smoothed_adj_outpatient_covid` | Same, but with systematic day-of-week effects removed; see [details below](#day-of-week-adjustment) |
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| `smoothed_outpatient_cli` | Estimated percentage of outpatient doctor visits primarily about COVID-related symptoms, based on Change Healthcare claims data that has been de-identified in accordance with HIPAA privacy regulations, smoothed in time using a Gaussian linear smoother |
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| `smoothed_adj_outpatient_cli` | Same, but with systematic day-of-week effects removed; see [details below](#day-of-week-adjustment) |
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## Table of contents
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{: .no_toc .text-delta}
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## Qualifying Conditions
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We receive data on the following two categories of counts:
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We receive data on the following six categories of counts:
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- Denominator: Daily count of all unique outpatient visits.
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- Covid: Daily count of all unique visits with primary ICD-10 code in any of:
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{U07.1, B97.21, or B97.29}.
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- COVID-like: Daily count of all unique outpatient visits with primary ICD-10 code
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of any of: {U071, U072, B9729, J1281, Z03818, B342, J1289}.
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- Flu-like: Daily count of all unique outpatient visits with primary ICD-10 code
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of any of: {J22, B349}. The occurrence of these codes in an area is
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correlated with that area's historical influenza activity, but are
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diagnostic codes not specific to influenza and can appear in COVID-19 cases.
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- Mixed: Daily count of all unique outpatient visits with primary ICD-10 code of
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any of: {Z20828, J129}. The occurance of these codes in an area is
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correlated to a blend of that area's COVID-19 confirmed case counts and
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influenza behavior, and are not diagnostic codes specific to either disease.
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- Flu: Daily count of all unique outpatient visits with primary ICD-10 code of
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any of: {J09\*, J10\*, J11\*}. The asterisk `*` indicates inclusion of all
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subcodes. This set of codes are assigned to influenza viruses.
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For the COVID signal, we consider only the *Denominator* and *Covid* counts.
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For the CLI signal, if a patient has multiple visits on the same date (and hence
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multiple primary ICD-10 codes), then we will only count one of and in descending
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order: *Flu*, *COVID-like*, *Flu-like*, *Mixed*. This ordering tries to account for
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the most definitive confirmation, e.g. the codes assigned to *Flu* are only used
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for confirmed influenza cases, which are unrelated to the COVID-19 coronavirus.
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## Estimation
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### COVID-Like Illness
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### COVID Illness
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For a fixed location $$i$$ and time $$t$$, let $$Y_{it}$$
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denote the Covid counts and let $$N_{it}$$ be the
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\hat p_{it} = 100 \cdot \frac{Y_{it}}{N_{it}}
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$$
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### COVID-Like Illness
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For a fixed location $$i$$ and time $$t$$, let $$Y_{it}^{\text{Covid-like}}$$,
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$$Y_{it}^{\text{Flu-like}}$$, $$Y_{it}^{\text{Mixed}}$$, $$Y_{it}^{\text{Flu}}$$
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denote the correspondingly named ICD-filtered counts and let $$N_{it}$$ be the
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total count of visits (the *Denominator*). Our estimate of the CLI percentage is
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given by
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$$
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\hat p_{it} = 100 \cdot \frac{Y_{it}^{\text{Covid-like}} +
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\left((Y_{it}^{\text{Flu-like}} + Y_{it}^{\text{Mixed}}) -
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Y_{it}^{\text{Flu}}\right)}{N_{it}}
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$$
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### Day-of-Week Adjustment
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The fraction of visits due to COVID-19 is dependent on the day of the week. On
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We then use these adjusted counts to estimate the COVID-19 percentage as described
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above.
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For the CLI indicator, we apply the same method to the numerator $$Y_{it} =
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Y_{it}^{\text{Covid-like}} + \left((Y_{it}^{\text{Flu-like}} +
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Y_{it}^{\text{Mixed}}) - Y_{it}^{\text{Flu}}\right)$$
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### Backwards Padding
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To help with the reporting delay, we perform the following simple

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