Characterizing Sars-Cov-2 Transmission Patterns Using Viral Load Dynamics

Abstract

Background & Aims: Despite the unprecedented amount and depth of data collected during the COVID-19 pandemic, there are still gaps in our knowledge on SARS-CoV-2 transmission patterns. In this study, we propose a novel modeling framework combining within-host and between-hosts scales into a single multi-scale transmission model to deepen our understanding of SARS-CoV-2 transmission. 

Methods & Results: We developed two agent-based models of SARS-CoV-2 transmission: a traditional single-scale model and a multi-scale model. In the multi-scale model, the between-hosts component simulates transmission between individuals of a synthetic population of agents. The within-host component uses ordinary differential equations to simulate viral replication within each host based on longitudinal viral load data from 210 SARS-CoV-2 infected individuals, both symptomatic and asymptomatic. In the within-host model multiple key transmission characteristics such as generation time, serial interval, and fraction of pre-symptomatic transmission naturally emerge as a property of the model itself, providing access to metrics that are hard to estimate from epidemiological field investigations. 

By systematically comparing the multi-scale with the single-scale model, we found that both models provide comparable macro-level outcomes such as the epidemic curve and reproduction number over time produced. However, less coarse scale analyses of transmission patterns reveal stark differences between the two approaches. For instance, we estimated the generation time of asymptomatic individuals to be 5.5 days, which has never been estimated from field investigations. We estimated a contraction of 15% and 10% of the generation time and serial interval, respectively, when the reproduction number increases from 1.4 to 5. The estimated pre-symptomatic transmission ranged from 48.0% to 56.7%.

Implications: These results show that our multi-scale framework provides results similar to traditional models at the macro scale, but it provides novel insights into the transmission patterns of a pathogen at less coarse scale.

Note: This conference abstract was presented at the 9th International Conference on Infectious Disease Dynamics organized by the journal Epidemics. This abstract has not been screened by SSRN for potential for public harm and should not be used to inform any clinical decision making. No competing interests or funding statements have been declared.