On behalf of WP1 Team Members - PowerPoint Presentation

1. On behalf of WP1 Team MembersWork Package 1Status updateAlice Simniceanu, Luca Fontana (WHO)CERN 12 September 2023

2. Objective:11/09/20232Disseminate the technology - Develop a User Interface suitable for the ‘General Public’, published by WHOWP contributors:Alice Simniceanu (WHO), Luca Fontana (WHO), Matteo Manzinello (WHO), André Henriques (CERN), Luís Aleixo (CERN), WP1 Status CERN – WHO Collaboration WP1 Airborne Risk Indoor Assessment - ARIA

3. 11/09/20233WP1 Status CERN – WHO Collaboration Background P = probability of infection for susceptible D = number of disease cases S = number of susceptibleI = number of infectors John Hopkins University https://hub.jhu.edu/2020/07/22/richard-riley-airborne-virus/p = breathing rate per person (m3/s)q = quantum generation rate by an infected person (quanta/s) t = total exposure time (s) Q = outdoor air supply rate (m3/s).The mathematical modelling of infection risk using the Wells–Riley equation to estimate the effect of ventilation rate on infection probability for known airborne diseases introduced the concept of a quanta. A quanta is defined as the amount of airborne contaminant needed to infect a susceptible host.

4. 11/09/20234WP1 Status CERN – WHO Collaboration BackgroundP = probability of infection for susceptible D = number of disease cases S = number of susceptibleI = number of infectors p = breathing rate per person (m3/s)q = quantum generation rate by an infected person (quanta/s) t = total exposure time (s) Q = outdoor air supply rate (m3/s). Beggs, C. B., Shepherd, S. J. and Kerr, K. G. (2010) ‘Potential for airborne transmission of infection in the waiting areas of healthcare premises: Stochastic analysis using a Monte Carlo model’, BMC Infectious Diseases, 10, pp. 1–8. doi: 10.1186/1471-2334-10-247Miller, S. L.; Nazaroff, W. W.; Jimenez, J. L.; Boerstra, A.; Buonanno, G.; Dancer, S. J; Kurnitski, J.; Marr, L. C; Morawska, L.; Noakes, C. (2020). Transmission of SARS-CoV-2 by inhalation of respiratory aerosol in the Skagit Valley Chorale superspreading event. Indoor Air, 2020, https://doi.org/10.1111/ina.12751 https://doi.org/10.1101/2020.06.15.20132027Buonanno G, Morawska L, Stabile L. Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications. Environment International 145 (2020) 106112 https://doi.org/10.1016/j.envint.2020.106112measlesTBInfluenzaSARS-CoV-2SARS-CoV-2a)b)

5. 11/09/20235WP1 Status CERN – WHO Collaboration BackgroundExperts from the healthcare fieldvirology, infectious diseases, infection prevention and control, epidemiology and biostatistics, public healthExperts from the engineering fieldengineering, physics, modeling, architecture, aerosol science, indoor air qualityARIA Working GroupStandardized model to quantify SARS-CoV-2 airborne risk transmission (inhalation) in different indoor settings.2. Online, user-friendly tool to assess SARS-CoV-2 airborne risk transmission in residential, public and health care settings and inform risk reduction measures.

6. 11/09/20236WP1 Status CERN – WHO Collaboration

7. 11/09/20237WP1 Status CERN – WHO Collaboration

8. 11/09/20238Systematic reviewsPICOs 9More than 25.000 papers Two independent reviewers≈ 6 months WP1 Status CERN – WHO Collaboration

9. Airborne Risk Indoor Assessment - ARIA Why ARIA is differentModules>Variables>Values>Interaction>RiskRobust and flexible50+ input parameters, all flexible and developed to be updated on regular basis Stochastic model rather than deterministici.e., viral load distribution, particle sizes, mask efficiencyViral load and particles emission rather than quantaNo reverse engineering approachDose – Response Model Exponential fitLong- & Short-range components short-distance encounters and expiratory jet dynamicFigure 4.Size-dependent aerosol deposition mechanisms to sites in the respiratory tract. Source : C. C. Wang et al., “Airborne transmission of respiratory viruses,” Science, vol. 373, no. 6558, Aug. 2021, doi: 10.1126/SCIENCE.ABD914

10. 11/09/202310WP1 Status CERN – WHO Collaboration Publication

11. 11/09/202311WP Status | Name | CAiMIRA Project | CERN – WHO Collaboration ARIA InterfaceFront-end and back-endWe built ARIA as a standalone web app using React, and included CAiMIRA as a git submodule. ARIA offers a modern interface that enhances user experience and performs front-end data validation.The React-based web app operates within CAiMIRA's Jinja templates and undergoes a data-mapping process to reach the output page. This converts ARIA's new form outputs into JSON data that's compatible with the CAiMIRA backend.

12. https://partnersplatform.who.int/aria

13. WP1 Status CERN – WHO Collaboration Next steps Model transition to other pathogens with airborne transmission as a possible route of transmissionViral diseases: Influenza, severe acute respiratory syndrome (SARS), Norwalk-like viruses (NLVs) and hantavirus disease, measles, varicella, etc.Bacterial diseases : Legionnaires’ disease, tuberculosis, and non-tubercule mycobacterial disease, etc. Fungal diseases : histoplasmosis, coccidiomycosis, blastomycosis, cryptococcosis, and aspergillosis, etc.Inform risk-base indoor ventilation standardsPathogen-specific recommendations for a more effective and efficient use of resources.Real-time risk assessment & risk communication‘’Safe space’’ specifications and certificationCO2 monitoring > CO2 norms and standards

14. 14Thank you and enjoy the meeting

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