Work

The uncertainty in effective reproduction number estimation from heterogeneous case reporting

Year: 2026

Type: article

Abstract: The effective reproduction number ( R t ) is a pivotal metric for tracking epidemic dynamics and informing public health interventions. However, its estimation is often compromised by heterogeneous case reporting, where factors such as limited testing capacity and surveillance delays cause reported cases to systematically deviate from true infection incidence. This study quantifies the uncertainty in R t estimation introduced by such heterogeneity across varying detection scenarios. We demonstrate that compared to the benchmark R t values from actual infections, estimates derived from reported data are: biased downward during the ascending phase of an outbreak; biased upward during the descending phase; and unbiased during stable periods. Our findings provide a framework for assessing the reliability of R t estimates and underscore the need for robust reporting systems.

Source: Journal of Safety Science and Resilience

DOI: 10.1016/j.jnlssr.2026.100289

Authors: Luyang Wang, Shunjiang Ni, Shuting Yu

Institution: Tsinghua University

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,200