Dryad
Published January 10, 2019 | Version v1
Dataset Open

Data from: Indirect protection from vaccinating children against influenza in households

Description

Vaccination is an important intervention to prevent influenza virus infection, but indirect protection of household members of vaccinees is not fully known. Here, we analyze a cluster household randomized control trial, with one child in each household randomized to receive vaccine or placebo, for an influenza B epidemic in Hong Kong. We apply statistical models to estimate household transmission dynamics and quantify the direct and indirect protection of vaccination. Direct vaccine efficacy is 71%. The infection probability of unvaccinated household members in vaccinated households was only 5% lower than in control households, because only 10% of infections are attributed to household transmission. Even when that proportion rises to 30% and all children are vaccinated, we predict that the infection probability for unvaccinated household members is only reduced by 20%. This suggests that benefits of individual vaccination remain important even when other household members are vaccinated.

Notes

Read me (data file explanations)
Data file
This data file contains data from the kiddivax study at 2009-2010. This is in a wide format that each row is a household.
data.csv
Data file
This is the long format that each row is a participant.
data_long.csv
Data file
This is the format that each row is a participant for each round.
data_round.csv
Influenza surveillance data
The influenza proxy used in the analysis.
ILILAB.csv
Data file
This file contains information on the baseline titer distribution.
sub_inf.csv
Data file (MCMC result)
The mcmc result for the manuscript.
mcmc_result.csv
R syntax to fit the digraph model
R syntax to fit the digraph model on the household data. This will create a data file [mcmc_result.csv] for further analysis. Noted that Supplementary Table 5 was also generated from this file.
indirect_benefit_main.R
R syntax
The file that are used by [indirect_benefit_main.r].
indirect_benefit.cpp
R syntax
The file that are used by [prediction.R].
indirect_benefit_prediction.cpp
R syntax to condcut prediction
R syntax to condcut prediction based on the posterior distribution of model parameter [mcmc_result.csv].
prediction.R
R syntax to generate prediciton for different scenarios
R syntax to use [prediction.R] file to generate prediciton for different scenarios. This should generate 15 files in the format of [predictionVW.Rdata]: V: 1: no vaccination in households. 2: vaccinating one child in households. 3: vaccination all children in households W: 1-5 for the proportion of infection attributed to household transmission is 10% (1), 20% (2), 30% (3), 40% (4) and 50% (5).
prediction_generator.R
R syntax for Figure 2
Contain the R syntax to reproduce Figure 2.
Figure_2.R
R syntax for Figure 3
Contain the R syntax to reproduce Figure 3.
Figure_3.R
R syntax for Figure 4
Contain the R syntax to reproduce Figure 4.
Figure_4.R
R syntax for Figure 5 & S_Figure 1-5
Contain the R syntax to reproduce Figure 5 in the main text, and supplementary Figure 1-5.
Figure_5.R
R syntax for Supplementary Table 1
R syntax to reproduce results in Supplementary Table 1.
Table_S1.R
R syntax for Supplementary Table 2-4
R syntax to reproduce results in Supplementary Table 2,3 and 4.
Table_S2_3_4.R
R syntax for Supplementary Table 6
R syntax to reproduce results in Supplementary Table 6.
Table_S6.R

Files

data.csv

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Additional details

Related works

Is cited by
10.1038/s41467-018-08036-6 (DOI)