• Indoor Air Quality (IIAQ) and Infection Probability Rate (IPR): Developing better spread risk models

    Jose R. Vigil1, Jose L. Conesa1, Lucia Estrada1, Mario Alfonso1, Jimena Cabrejas2, Jose L. Unibaso2, Eneko Montero2, Juan Angel Martin3

    1. R+D Dept. Alteria Automation, Madrid, Spain.
    2. Embedded dev, Dept. BYTEK, Bilbao, Spain.
    3. R+D Dept. Visual Presencia, Madrid, Spain.

    Abstract: The development and future use of two new indexes related to the risk of airborne disease propagation are proposed in this paper: Indoor Air Quality Index (IIAQ) and Infection Probability Rate (IPR)
    Research published up-to-date takes into account mainly Carbon Dioxide concentrations. The authors have implemented the IIAQ and IRP indexes taking into additional factors such as the concentration of aerosols and other environmental variables such as occupancy and voice sound pressure level in the room.
    This paper is partially inspired by the recent works by Martin Z. Bazant et al, where the risks of airborne disease infection such as Covid-19 were evaluated. That previous research was based on the CO2 concentrations measured by an NDIR gas sensor. Nonetheless, the authors expressed that the risks were also dependent on other factors such as the concentration of aerosols, the speech sound pressure level produced by occupants, and the occupancy rate itself. However, no device to quantify and include those variables on the risk assessment was proposed on the mentioned work. The purpose of this paper is to follow the findings by Martin Z. Bazant et al. and develop a practical air quality monitoring device design that evaluates:
    • IIAQ or Indoor Air Quality Index. A new IAQ
    index created by the authors
    • IPR or Infection Probability Rate. A new concept derived from the Wells-Riley model The Wells-Riley model is used by Martin Z. Bazant et al. and other previous work (Chung Min Liao et al. and Freja Nordsiek et al) The model was further developed to include additional variables beyond the CO2 concentration.

    Keywords: Airborne disease spread, COVID-19 risks, Infection Probability Rate, Indoor Air Quality, Airborne Infection propagation model, CO2 sensors.

    Pages: 49 – 68 | Full PDF Paper