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Virulence-mediated infectiousness and activity trade-offs and their impact on transmission potential of patients infected with influenza

Citation

McKay, Brian et al. (2020), Virulence-mediated infectiousness and activity trade-offs and their impact on transmission potential of patients infected with influenza, Dryad, Dataset, https://doi.org/10.5061/dryad.51c59zw4v

Abstract

Communicable diseases are often virulent, i.e., they cause morbidity symptoms in those infected. While some symptoms may be transmission-enhancing, other symptoms are likely to reduce transmission potential. For human diseases, the reduction in transmission opportunities is commonly caused by reduced activity. There is limited data regarding the potential impact of virulence on transmission potential. We performed an exploratory data analysis of 324 influenza patients at a university health center during the 2016/2017 influenza season. We classified symptoms as infectiousness-related or morbidity-related and calculated two scores. The scores were used to explore the relationship between infectiousness, morbidity (virulence), and activity level. We found a decrease in activity level with increasing morbidity scores. There was no consistent pattern between activity level and infectiousness score. We also found a positive correlation between morbidity and infectiousness scores. Overall, we find that increasing virulence leads to increased infectiousness and reduced activity, suggesting a trade-off that can impact overall transmission potential. Our findings indicate that a reduction of systemic symptoms may increase host activity without reducing infectiousness. Therefore, interventions should target both systemic and infectiousness related symptoms to reduce overall transmission potential. Our findings can also inform simulation models that investigate the impact of different interventions on transmission.

Methods

Students with a primary complaint related to a respiratory infection who made an appointment at the health center of a large research university from December 2016 to February 2017 filled out an electronic questionnaire. The questionnaire collected data about their current symptoms and activity level. A response was required for all symptom-related questions when they scheduled their appointments. We included all symptoms collected by the questionnaire in this analysis. The complete questionnaire is available.

Usage Notes

Description of Included Files

  • Virulence_Trade-off.Rproj” This file lets R know the relative file paths for loading and saving files.
  • SymptomActivity.bib” This file has all of the citation saved as a bibTex.
  • Symptom Questionnaire_Redacted.pdf”: This is a copy of the electronic questionnaire patients with an upper respiratory symptoms were required to fill out. All identifying information has been redacted.
  • DataDictionary_VirulenceTradeOff.xlsx”: This document provides a description of all the variables included in the analysis.
  • 1 Anonymized Data” folder contains the de-identified data for the analyses
    • An R script that merges all of the individual data sets and creates and saves “Data.Rda” and “Data.csv” in the “1 Anonymized Data” Folder. This script is not included since the raw data sets are not included to protect patient privacy.
  • 2 Data Cleaning Script” folder contains one R script that cleans the data for the analyses
    • Data Merging Script.R”: R script that merges all of the individual data sets and creates and saves “Data.Rda” in the “1 Anonymized Data” Folder. This script is not included since the raw data sets are not included to protect patient privacy.
    • Data Cleaning.R”: This R script does all of the data preparation, creating all the required variables for the analysis. This script also produces the data sets used for the analyses and saves them in the “3 Clean Data” folder.
  • 4 Analysis Scripts” folder has 4 R scripts that analyze the clean data and produce the results presented in the main text and supplement.
    • Flu Symptoms Activity Models.R” This script creates the univariate/multivariate linear regression table, the Spearman rank correlation, and the CMH trend tests. Results are saved in “5 Results”
    • Flu Symptoms Activity Plots.R” This script creates all of the plots. Results are saved in “5 Results”
    • Flu Symptoms Activity Tables.R” This script creates all of the tables. Results are saved in “5 Results”
    • Multivariate Subset Selection.R” This script does the variable selection for the multivariate model. Results are saved in “5 Results”
  • 6 Manuscript” folder has 2 files in it used to create the manuscript.
    • Manuscript.Rmd” This Rmd file creates the basic manuscript word document (formatting will not be identical)
    • proceedings-of-the-royal-society-b.csl” is a style file to format the citations in the manuscript
  • 7 Supplemental Material” folder has 2 files used to create this document
    • Supplemental Material.Rmd” This Rmd file creates the basic supplemental material word document (formatting will not be identical)
    • proceedings-of-the-royal-society-b.csl” is a style file to format the citations in the supplement

Reproducing The Results

The files required to reproduce the results are 2 R Markdown files, 4 R script, and one anonymized data file. These files allow the reproduction of all results shown in the main text and SM. To reproduce the results follow these steps.

First, install R, Rstudio, and Pandoc (when you install Rstudio Pandoc should automatically install). Microsoft Word or Open Office Word is also required.

Second, save the zip file from Dryad on your local computer. Open the folder and double click “Virulence_Trade-off”. This should open Rstudio (if prompted, select Rstudio as the app to open this file type). Then open and run the files below in the specified order.

  1. R script “Data Cleaning.R” in the “2 Data Cleaning Script” folder uses “Data.Rda” and produces two clean data sets used for all further analyses. The data sets are all saved in the “3 Clean Data” folder and include:
    1. “SympAct_Any_Pos.Rda” Contains data for all influenza patients regardless of diagnosis method.
    2. “SympAct_Lab_Pos.Rda” Contains data for influenza patients diagnosed based on a PCR or rapid antigen test.

It is important to note that “SympAct_Lab_Pos.Rda” is a subset of “SympAct_Any_Pos.Rda” based on the method of diagnosis.

  1. Four R scripts in the “4 Analysis Scripts” folder (“Flu Symptoms Activity Univariate Model.R”, “Flu Symptoms Activity Univariate Plots.R”, and “Flu Symptoms Activity Univariate Tables.R”, “Multivariate Subset Selection.R”). The order you run these scripts does not matter. Results of each script are automatically saved in the “5 Results” folder.
  2. R Markdown “Manuscript.Rmd” is in the “6 Manuscript” folder. This combines all the relevant results and creates the main text as a Word document (some reformatting is required).
  3. R Markdown “Supplemental Material.Rmd” in the “7 Supplemental Material” folder generates the supplementary material as Word document.

Funding

National Institutes of Health, Award: U19AI117891

Roche