biostudies-literatureZhang GNSF244https://www.ebi.ac.uk/biostudies/studies/S-EPMC12574068biostudies-literatureUnknown25(1)<h4>Background</h4>Human behavioral responses to changes in risks are often delayed. Methods for estimating these delayed responses either rely on rigid assumptions about the delay distribution (e.g., Erlang distribution), producing a poor fit, or yield period-specific estimates (e.g., estimates from the Autoregressive Distributed Lag (ARDL) model) that are difficult to integrate into simulation models. We propose a hybrid ARDL-Erlang approach that yields an interpretable summary of behavioral responses suitable for incorporation into simulation models.<h4>Method</h4>We apply the ARDL-Erlang approach to estimate the effect of COVID-19 deaths on mobility across US counties from October 2020 to July 2021. A standard panel autoregressive distributed lag (ARDL) model first estimates the effectBMC medical research methodologyIdentifying delayed human response to external risks: an econometric analysis of mobility change during a pandemic.PMC125740682229819Zhang GGhaffarzadegan NXu ROsi ARahmandad HfalseIdentifying delayed human response to external risks: an econometric analysis of mobility change during a pandemic.<h4>Background</h4>Human behavioral responses to changes in risks are often delayed. Methods for estimating these delayed responses either rely on rigid assumptions about the delay distribution (e.g., Erlang distribution), producing a poor fit, or yield period-specific estimates (e.g., estimates from the Autoregressive Distributed Lag (ARDL) model) that are difficult to integrate into simulation models. We propose a hybrid ARDL-Erlang approach that yields an interpretable summary of behavioral responses suitable for incorporation into simulation models.<h4>Method</h4>We apply the ARDL-Erlang approach to estimate the effect of COVID-19 deaths on mobility across US counties from October 2020 to July 2021. A standard panel autoregressive distributed lag (ARDL) model first estimates the effect2025-01-01T00:00:00Z2025 Oct2026-06-05T09:40:34.341Z2026-05-15T03:12:14.608ZS-EPMC125740684116295210.1186/s12874-025-02696-x