# Impact of exposure frequency on disease burden of the common cold – A mathematical modeling perspective

## TL;DR

This paper uses mathematical models to show that more frequent exposure to common cold viruses can reduce overall disease burden in populations.

## Contribution

The study introduces two novel mathematical models (CC-ODE and CC-IB) to analyze how exposure frequency affects common cold disease burden.

## Key findings

- Increased exposure to common cold pathogens can lower average disease burden under certain conditions.
- Population-level and individual-level models both show reduced disease burden with higher exposure rates.
- The models can be adapted to study other common cold pathogens and scenarios.

## Abstract

The common cold is a frequent disease in humans and can be caused by a multitude of different viruses. Despite its typically mild nature, the high prevalence of the common cold causes significant human suffering and economic costs. Oftentimes, strategies to reduce contacts are used in order to prevent infection. To better understand the dynamics of this ubiquitous ailment, we develop two novel mathematical models: the common cold ordinary differential equation (CC-ODE) model at the population level, and the common cold individual-based (CC-IB) model at the individual level. Our study aims to investigate whether the frequency of population / individual exposure to an exemplary common cold pathogen influences the average disease burden associated with such a virus. Results derived for this situation can also be applied to other common cold pathogens.

On the one hand, the CC-ODE model captures the dynamics of the common cold within a population, considering factors such as infectivity and contact rates, as well as development of specific immunity in the population. On the other hand, the CC-IB model provides a granular perspective by simulating individual-level interactions and infection dynamics, incorporating heterogeneity in contact rates. In both modeling approaches, we show that under specific parameter configurations (i.e., characteristics of the virus and the population), increased exposure can result in a lower average disease burden. While increasing contact rates may be ethically justifiable for low-mortality common cold pathogens, we explicitly do not advocate for such measures in severe illnesses. The mathematical approaches we introduce are simple yet powerful and can be taken as a starting point for the investigation of specific common cold pathogens and scenarios.