Estimates of Influenza Vaccine Effectiveness from Observational Studies Open Access
Shi, Meng (Summer 2020)
Published
Abstract
Influenza is an infectious disease caused by influenza virus. Due to the variety of influenza viruses, a new vaccine must be developed each season, and the influenza vaccine effectiveness (VE) has to be re-estimated in every season. As annual influenza vaccination is now widely recommended, randomized clinical trials for estimating VE are no longer ethical in many populations, and observational studies based on patients seeking care for acute respiratory illnesses (ARI) remain the only option.
In the first topic, we developed a probability model for comparing the bias of VE estimates from two popular case-control designs: traditional case-control (TCC) de- sign and test-negative (TN) design, under non-random vaccination. Our model allows non-random vaccination and confounding. In addition, we consider two outcomes of interest: symptomatic influenza (SI) and medically-attended influenza (MAI). Since the bias of VE estimates depends on the outcome against which the vaccine is sup- posed to protect, it is important to specify the outcome of interest when evaluating the bias.
In a stochastic agent-based model, the disease transmission process is governed by the behavior of each individual, and incorporates elements of random processes into the system. In topic 2, we present a stochastic agent-based simulation program, SimFlu, for the transmission of influenza in a stratified population, and use it to evaluate bias and precision of estimates of VE from 4 observational study designs (two case-control studies and two cohort studies). Besides that, we proposed several methods to correct the bias for test negative study.
The exact timing and duration of flu season can vary. Most of the time, the influenza activity peaks between December and February, and the duration of the annual influenza epidemic can last as late as May. However, influenza vaccines are now available as early as July. As a result, there may be relatively long periods between vaccination and potential exposure, raising concerns about the possibility of waning vaccine efficacy over a single season. In this study, we analyze data generated from SimFlu using three different methods for the evaluation of waning vaccine efficacy in both cohort and test negative studies.
Table of Contents
1 Introduction ..................................... 1
1.1 Epidemiology of Influenza ..................................... 2
1.2 Influenza Vaccination ..................................... 5
1.3 Evaluation of the Effects of Vaccines ..................................... 6
1.3.1 Vaccine Efficacy..................................... 7
1.3.2 Vaccine Effectiveness (VE) ..................................... 7
1.4 Outcomes of Interest for influenza Vaccine Effectiveness Studies ..................................... 8
1.4.1 Non-specific Outcomes ..................................... 9
1.4.2 Laboratory-confirmed Outcomes..................................... 11
1.4.3 Symptomatic Influenza and Medically attended Influenza ..................................... 12
1.5 Observational Studies to Estimates VE ..................................... 12
1.5.1 Case-control Studies ..................................... 13
1.5.2 Cohort Studies ..................................... 16
1.5.3 Main Sources of Bias in Observational Studies ..................................... 18
1.6 Objectives of this dissertation ..................................... 19
2 A Comparison of the Test-Negative and the Traditional Case-Control Study Designs for Estimation of Influenza Vaccine Effectiveness under Nonrandom Vaccination..................................... 21
2.1 Introduction ..................................... 22
2.2 Methodology ..................................... 23
2.2.1 The study population ..................................... 23
2.2.2 The study designs ..................................... 23
2.2.3 Outcome of interest and true VE ..................................... 24
2.2.4 Estimation of VE and bias of VE estimates ..................................... 24
2.2.5 The model ..................................... 24
2.2.6 True VE in our model ..................................... 28
2.2.7 Estimates of VE in our model ..................................... 29
2.2.8 Bias and standard errors of estimates ..................................... 30
2.2.9 Probability Ratios ..................................... 31
2.3 Results ..................................... 32
2.3.1 Sources of Bias ..................................... 32
2.3.2 Summary of Results ..................................... 34
2.4 Discussion ..................................... 42
3 Estimation of Influenza Vaccine Effectiveness Using Agent-based Stochastic Simulation Model in Observational Studies ..................................... 46
3.1 Introduction ..................................... 47
3.2 Methodology ..................................... 49
3.2.1 Scenario ..................................... 49
3.2.2 Outcome of interest ..................................... 49
3.2.3 Observational Study ..................................... 50
3.2.4 SimFlu ..................................... 51
3.2.5 Covariates: Health Status and Health Awareness ..................................... 52
3.2.6 True VE ..................................... 53
3.2.7 VE Estimates ..................................... 53
3.2.8 Sources of Bias ..................................... 54
3.2.9 Calculations ..................................... 57
3.2.10 Corrections for Bias for Test Negative Study ..................................... 59
3.3 Results ..................................... 64
3.3.1 Bias of VE Estimate from Observational Studies ..................................... 64
3.3.2 Corrections for Bias for TN Study ..................................... 67
3.4 Discussion ..................................... 70
4 Waning of Influenza Vaccine Effectiveness in Cohort and Test-Negative Studies ..................................... 79
4.1 Introduction ..................................... 80
4.2 Methodology ..................................... 84
4.2.1 Data ..................................... 84
4.2.2 Methods ..................................... 85
4.3 Results ..................................... 87
4.4 Discussion ..................................... 91
A Appendix for Chapter 2 ..................................... 93
B Appendix for Chapter 3 ..................................... 112
B.1 Correction for Bias A ..................................... 112
B.2 Sample Parameter File for SimFlu ..................................... 114
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