Infectious diseases: Household modeling with missing data

Area of Science:

• Epidemiology
• Biostatistics
• Infectious Disease Modeling

Background:

• The role of children and adolescents in the transmission of SARS-CoV-2 remains incompletely understood.
• Quantifying the relative susceptibility of pediatric populations to SARS-CoV-2 compared to adults is a critical public health question.
• Existing infectious disease models often struggle with incomplete data, such as missing test results, hindering accurate analysis.

Purpose of the Study:

• To develop and validate a statistical methodology for estimating infectious disease parameters in the presence of missing data.
• To determine the relative susceptibility of children and adolescents to SARS-CoV-2 infection compared to adults.
• To apply the developed methodology to real-world SARS-CoV-2 testing data from Bnei Brak, Israel.

Main Methods:

• Generalization of a standard household infectious disease model to accommodate missing test data.
• Development of a novel Expectation-Maximization (EM) algorithm for estimating Maximum Likelihood Estimates (MLE) with missing data.
• Implementation of the estimation methodology using R software and validation through simulation studies comparing complete case analysis.

Main Results:

• The proposed EM algorithm effectively estimates model parameters in the presence of missing data, outperforming complete case analysis in simulations.
• Analysis of SARS-CoV-2 testing data from Bnei Brak, Israel, revealed significant age-dependent susceptibility.
• Adolescents demonstrated lower susceptibility than adults, and children exhibited even lower susceptibility than adolescents.

Conclusions:

• The novel EM algorithm provides a robust method for analyzing infectious disease data with missing test results.
• The study provides quantitative evidence that children and adolescents are less susceptible to SARS-CoV-2 infection than adults.
• Findings have implications for understanding transmission dynamics and informing public health strategies related to pediatric populations during pandemics.