Quantifying reporting bias in social contact data collected from corporate and nursing home employees in the United States Público

Abstract

Relevance

There is a current need to obtain direct estimates of contact behavior involved in the transmission of respiratory pathogens. This can be affected by biased estimates of self-assessed behavior or reporting bias. This includes the over and under-reporting of social contacts.

 

Objective

This study aimed to measure the degree of bias in reporting of contacts from COVID-19 social contact surveys by participant demographic characteristics. 

 

Design

The data used for this study was obtained from the two cross-sectional studies, “Comprehensively Profiling Social Mixing Patterns in Workplace Settings to Model Pandemic COVID-19 and Influenza Transmission and Control” (Corporate Mix (CM)) and “Comprehensively Profiling Social Mixing Patterns in Nursing Homes to Model COVID-19 Transmission” (Nursing Home Mix (NHM)). Data was used from Rounds 2 through 4 of data collection, from November 2020 – December 2021.  A logistic regression model was used to examine the relationship between reporting type and participant demographic characteristics from the Corporate Mix study.

 

Findings

Participants in the Corporate Mix study were more likely to overreport, while those in the Nursing Home Mix study were more likely to have no difference in reporting. The demographic factors – sex, age, race/ethnicity, and education were included in the final model as explanatory variables. We determined that there was a higher likelihood of overreporting among female, younger (20-29 year old), White, Non-Hispanic, and higher educated (Bachelors or higher) participants across all Rounds 2-4 of the Corporate Mix study. An important limitation to this study was that as researchers, we are unable to determine the “true” number of social contacts that a participant has. For this reason, the categorization of over and under-reporting of contacts is arbitrary. Despite this, the results from this study allow us to gain a better understanding of how to design questionnaires to potentially reduce reporting bias in different demographic populations. 

Table of Contents

Methods 3

Corporate Mix Study 3

Nursing Home Mix Study 5

Results 6

Discussion 8

References 10

Tables and Figures 13

About this Master's Thesis

Rights statement

• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Rollins School of Public Health
Department	Epidemiology
Degree	M.P.H.
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Public Health Health Sciences, Epidemiology
Palabra Clave	Epidemiology Social contact diaries Surveys Infectious Diseases
Committee Chair / Thesis Advisor	Ben Lopman, Emory University
Committee Members	Moses Chapa Kiti, Emory University

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