* MWRA COVID Analysis on Wed May 19 17:23:51 2021
- input data directory: ./data
- results directory: ./results
- transcript to: ./results/mwra-covid-transcript.txt
Archival:
---------
* Archived analysis script(s) to ./results:
- ./mwra-covid-2.r
Loading datasets and constructing joint dataset:
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* Reading MWRA wastewater RNA data from ./data/MWRAData20210514-data.tsv
- Structure:
o 429 rows
o 11 columns: Date, South, South.LCL, South.UCL, North, North.LCL, North.UCL, South.7, North.7, North.Variant, South.Variant
* Reading Mass COVID data from ./data/massachusetts-history.csv
- Dropping 12 empty columns (and state): state, inIcuCumulative, negativeTestsAntibody, negativeTestsPeopleAntibody, negativeTestsViral, onVentilatorCumulative, positiveTestsAntibody, positiveTestsAntigen, positiveTestsPeopleAntigen, totalTestEncountersViral, totalTestsAntibody, totalTestsAntigen
- Structure:
o 411 rows
o 29 columns: Date, death, deathConfirmed, deathIncrease, deathProbable, hospitalized, hospitalizedCumulative, hospitalizedCurrently, hospitalizedIncrease, inIcuCurrently, negative, negativeIncrease, onVentilatorCurrently, positive, positiveCasesViral, positiveIncrease, positiveScore, positiveTestsPeopleAntibody, positiveTestsViral, recovered, totalTestEncountersViralIncrease, totalTestResults, totalTestResultsIncrease, totalTestsPeopleAntibody, totalTestsPeopleAntigen, totalTestsPeopleViral, totalTestsPeopleViralIncrease, totalTestsViral, totalTestsViralIncrease
* Constructing joint dataset by inner join on dates
- Saved to ./results/mwra-covid-joint-data.tsv
- Structure:
o 362 rows
o 39 columns: Date, South, South.LCL, South.UCL, North, North.LCL, North.UCL, South.7, North.7, North.Variant, South.Variant, death, deathConfirmed, deathIncrease, deathProbable, hospitalized, hospitalizedCumulative, hospitalizedCurrently, hospitalizedIncrease, inIcuCurrently, negative, negativeIncrease, onVentilatorCurrently, positive, positiveCasesViral, positiveIncrease, positiveScore, positiveTestsPeopleAntibody, positiveTestsViral, recovered, totalTestEncountersViralIncrease, totalTestResults, totalTestResultsIncrease, totalTestsPeopleAntibody, totalTestsPeopleAntigen, totalTestsPeopleViral, totalTestsPeopleViralIncrease, totalTestsViral, totalTestsViralIncrease
Exploratory plots:
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* Plot of north vs south RNA to ./results/plot-north-south.png
Prediction set:
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* Making prediction set:
- Using 4 medical vars from COVID Tracking Project: deathIncrease, hospitalizedCurrently, inIcuCurrently, onVentilatorCurrently
- Averaging North & South RNA daily measurements
- Result: 362 rows x 6 columns
Correlation plots:
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* Correlation time courses plotted to ./results/plot-med-loads-vs-RNA-1.png
* Correlation chart plotted to ./results/plot-med-loads-vs-RNA-2.png
Lagged regressions:
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* Regressing medical vars on RNA at various lags to test predictive power
* Scatterplotting significance & strength vs RNA lag
- ./results/plot-RNA-hospitalizedCurrently-lags.png
- ./results/plot-RNA-inIcuCurrently-lags.png
- ./results/plot-RNA-onVentilatorCurrently-lags.png
- ./results/plot-RNA-deathIncrease-lags.png
* Optimal lags for each medical variable:
MedVar Lag p Adj.R2
1 hospitalizedCurrently 9 1.342097e-28 0.3763869
2 inIcuCurrently 11 2.224528e-20 0.2855915
3 onVentilatorCurrently 19 2.627499e-73 0.7578718
4 deathIncrease 11 7.615366e-18 0.2397525
Final regressions:
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* Trying some regressions at the optimal lag for each variable:
- Regressing hospitalizedCurrently on RNA at lag 9 days:
Call:
lm(formula = as.formula(sprintf("%s ~ RNA", mv)), data = transform(predictionSet,
RNA = lagVector(predictionSet[, "RNA"], lag)))
Residuals:
Min 1Q Median 3Q Max
-2122.3 -373.4 -193.1 124.1 2740.9
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 731.3388 54.3004 13.47 <2e-16 ***
RNA 1.3628 0.1084 12.57 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 652.7 on 259 degrees of freedom
(101 observations deleted due to missingness)
Multiple R-squared: 0.3788, Adjusted R-squared: 0.3764
F-statistic: 157.9 on 1 and 259 DF, p-value: < 2.2e-16
2.5 % 97.5 %
(Intercept) 624.412289 838.265328
RNA 1.149224 1.576302
o Plot to ./results/plot-RNA-hospitalizedCurrently-regression.png
- Regressing inIcuCurrently on RNA at lag 11 days:
Call:
lm(formula = as.formula(sprintf("%s ~ RNA", mv)), data = transform(predictionSet,
RNA = lagVector(predictionSet[, "RNA"], lag)))
Residuals:
Min 1Q Median 3Q Max
-460.27 -84.63 -41.73 18.65 850.49
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 151.6012 14.2327 10.65 <2e-16 ***
RNA 0.2840 0.0281 10.11 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 168.7 on 252 degrees of freedom
(108 observations deleted due to missingness)
Multiple R-squared: 0.2884, Adjusted R-squared: 0.2856
F-statistic: 102.1 on 1 and 252 DF, p-value: < 2.2e-16
2.5 % 97.5 %
(Intercept) 123.5710620 179.6314436
RNA 0.2286727 0.3393658
o Plot to ./results/plot-RNA-inIcuCurrently-regression.png
- Regressing onVentilatorCurrently on RNA at lag 19 days:
Call:
lm(formula = as.formula(sprintf("%s ~ RNA", mv)), data = transform(predictionSet,
RNA = lagVector(predictionSet[, "RNA"], lag)))
Residuals:
Min 1Q Median 3Q Max
-290.442 -27.243 -9.693 28.312 126.246
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 50.807314 3.775317 13.46 <2e-16 ***
RNA 0.196188 0.007275 26.97 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 43.42 on 231 degrees of freedom
(129 observations deleted due to missingness)
Multiple R-squared: 0.7589, Adjusted R-squared: 0.7579
F-statistic: 727.2 on 1 and 231 DF, p-value: < 2.2e-16
2.5 % 97.5 %
(Intercept) 43.3688571 58.2457716
RNA 0.1818531 0.2105221
o Plot to ./results/plot-RNA-onVentilatorCurrently-regression.png
- Regressing deathIncrease on RNA at lag 11 days:
Call:
lm(formula = as.formula(sprintf("%s ~ RNA", mv)), data = transform(predictionSet,
RNA = lagVector(predictionSet[, "RNA"], lag)))
Residuals:
Min 1Q Median 3Q Max
-75.027 -15.556 -8.420 8.256 132.561
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 26.229521 2.340979 11.205 <2e-16 ***
RNA 0.043903 0.004748 9.248 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 28.86 on 267 degrees of freedom
(93 observations deleted due to missingness)
Multiple R-squared: 0.2426, Adjusted R-squared: 0.2398
F-statistic: 85.52 on 1 and 267 DF, p-value: < 2.2e-16
2.5 % 97.5 %
(Intercept) 21.62039353 30.83864786
RNA 0.03455541 0.05325004
o Plot to ./results/plot-RNA-deathIncrease-regression.png
* MWRA COVID Analysis completed Wed May 19 17:23:52 2021 (1.8 sec elapsed).