2021 launching Portascanner COVID-19

INTRODUCING new solution Portascanner® COVID-19 to reduce the spread of airborne disease by inspecting rooms for leaks. Designed as a result of British Government COVID-19 Emergency Response Grant.

Portascanner COVID-19 pre-launch

Ask for the free Portascanner COVID-19 brochure now

    Hospital Air Contamination & Infection Control

    Hospital ICU wards rely on negative-pressurisation to reduce the spread of airborne infectious diseases and other contaminants like fungi, pollen & chemicals.

    1. Adequate ventilation requires a minimum of airtightness.
    2. Without this, “patch and hope” measures are often used i.e. taping obvious areas of leakage (pictured below).
    3. Current existing methods are disruptive and costly and do not allow operators to identify specific areas of leakage.

    Improve airtightness in intensive care units

    Portascanner® COVID-19 locates leaks in hospital wards, quantifies the leaks in regard to their cross-sectional area and calculates the air flow rate through them. This generates an air permeability value for an entire ICU Ward which the user can compare against the required value for negative pressurisation.

    Hospital COVID 19 patient isolation room

    Solve Your Air Permeability Now

    Reduce the spread of COVID-19 in healthcare

    A December 2020 study on COVID-19 and air contamination indicates that 50% of air samples taken from hospital hallways and 20% from hospital bathrooms have high levels of coronavirus. Source: JAMA Network Open. 2020;3(12):e2033232.doi:10.1001/jamanetworkopen.2020.33232.

    Use Portascanner® to help stop COVID-19 spread

    The only alternative to Portascanner® COVID-19 is 3rd party contracted door fan testing which is more invasive, time consuming, and costly. It cannot be used with patients in the room. Our instrument can. Without this, “patch and hope” measures are often used i.e. taping obvious areas of leakage (pictured below).

    BBC Panorama hospital-coronavirus-special-episode-1 13m54s