Estimating vaccine-prevented disease outcomes when vaccination has only direct effects
Yang, F.; Magee, A.; Morris, S. E.; Mathis, S. M.; Wiegand, R.; Iuliano, D. A.; Biggerstaff, M.; Olesen, S. W.
Show abstract
Vaccination can be a useful intervention for reducing infectious disease burden. Estimating numbers of vaccine-prevented health outcomes is one approach to quantifying the benefits of vaccination. Here we improve a method described by Foppa et al. (1) that assumes vaccination has only direct effects, that is, it cannot prevent infection or onward transmission of the disease. We rederive this method and derive an improved method that increases estimation accuracy with minimal additional analytical complexity. To evaluate the improved method, we simulated disease outbreaks and compared the accuracy of the two methods for estimating prevented disease outcomes. In 84% of simulations performed over a wide parameter space, the improved method had an equal or smaller estimation error compared to the original Foppa method, with 7.9-fold smaller mean error and 44-fold smaller standard deviation of errors. Our study improves a method for estimating prevented burden when assuming vaccination has only direct effects.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Estimation of Vaccine Efficacy for Variants that Emerge After the Placebo Group Is Vaccinated 96%
- A Double Machine Learning Approach for the Evaluation of COVID-19 Vaccine Effectiveness under the Test-Negative Design: Analysis of Québec Administrative Data 96%
- HIV Estimation Using Population-Based Surveys With Non-Response: A Partial Identification Approach * 94%
Similar papers in this journal
- Causal Estimands for Infectious Disease Count Outcomes to Investigate the Public Health Impact of Interventions 95%
- Use of recently vaccinated individuals to detect bias in test-negative case-control studies of COVID-19 vaccine effectiveness 95%
- Estimating vaccine efficacy against transmission via effect on viral load 94%
Similar papers in this journal
- Leveraging infectious disease models to interpret randomized controlled trials: controlling enteric pathogen transmission through water, sanitation, and hygiene interventions 95%
- Estimating cumulative incidence of SARS-CoV-2 with imperfect serological tests: a cutoff-free approach 95%
- Covasim: an agent-based model of COVID-19 dynamics and interventions 95%
Similar papers in this journal
- Misclassification of yellow fever vaccination status revealed through hierarchical Bayesian modeling 96%
- Using LASSO regression to estimate the population-level impact of pneumococcal conjugate vaccines 94%
- Comparative evaluation of methodologies for estimating the effectiveness of non-pharmaceutical interventions in the context of COVID-19: a simulation study 93%
Similar papers in this journal
- Using next generation matrices to estimate the proportion of cases that are not detected in an outbreak 96%
- A simulation-based approach for estimating the time-dependent reproduction number from temporally aggregated disease incidence time series data 95%
- Evaluating primary and booster vaccination prioritization strategies for COVID-19 by age and high-contact employment status using data from contact surveys 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.