# HECOIRA Agenda 2022-03-03 ![](https://i.imgur.com/WQFsMvd.png) ## Present Martin Callaghan Marco Alex Martin Lopez-Garcia Zeyu Archie Cath ## What are the Apps? | App 1 - Single-zone | App 2 - Multi-zone | |-------|-------| |R code that assesses risk of infection from previous patient for future patient. Then schedule room with lowest risk for future patients. |CONTAM+DEVS (C++) code to calculate transient concentration of pathogen in the air and associated exposures for a multizonal model. | ## Document conversion tool [pandoc](https://pandoc.org) Converts to/from: PDF; Word; Markdown; LaTeX etc. ## Github repositories Current github for HECOIRA https://github.com/MarcoFelipeKing/HECOIRA/invitations *** # HECOIRA app(s) Timescale - May 31st Seacroft model: Pre-defined geometry Hosted on VM at Leeds (John Craske at Imperial has a python code like CONTAM) ## 1) Archie's App Requirements - Single zone: Seacroft Outpatients ### User Needs Preventing transmission amongst vulnerable patients in the Seacroft hospital outpatient clinics ### Functional requirements 1. Visual the infection risk for sequential patients - absolute or relative risk? 2. Allow the user to explore mitigation strategies a) opening windows b) air cleaner c) duration between patients d) order of patients e) which room to put which patient in f) masks on patients Assessing the risk in a clinic room to the next patient entering and how mitigations can change this risk to make the space usable Clinic has several rooms and will have several patients over a clinic session - Arrive, Seen, Left Function for scheduling - Include a patient/clinician roster ### Non-functional Parameters the model needs to visualise the risk - that the user sets - Number of rooms and Ability to change no. of rooms in settings to make the app more usable beyond Seacroft - Volume of each room - Ventilation rate of each room - actual value or good/medium/poor? - Include weather conditions - Window open/closed - Air cleaner present Y/N and if so what is the flow rate - Mask on patient Y/N and if so what type - Number of patients in the clinic session - Infections that each patient have - this could be more than one - Time of each appointment - Time between each appointment - Scheduling in each room - Activity that happens during each appointment - perhaps a flag that indicates whether the patient will be passive, medium or very active which relates to the emission rate - a weighting Parameters the model needs that the user can't set but are needed in the model - Emission rate range for each pathogen type - Breathing rate range of patients - Dose response curve for each pathogen - mask settings for different mask types ### Archie's app intergace wireframe Below is a mock up of Archie's app interface: ![](https://i.imgur.com/Asioy5m.jpg) ![](https://i.imgur.com/gMHteat.jpg) ![](https://i.imgur.com/nFjTWSq.jpg) *** ## App 2 - Multizone app: (subset of) St James' J10 ward To investigate the risk to patients within a multizone hospital ward environment based on St James ## Functional requirements * Return risk over time within zones and predict number of patient cross infections ## Non-functional requirements ## Data flow ![](https://i.imgur.com/4C1PklJ.png) ### App wireframe ![](https://i.imgur.com/TozWY6a.jpg) ![](https://i.imgur.com/ZzsVTWA.jpg) ## Actions for App2 1. All define fixed geometry 2. Zeyu to run CONTAM X from command line 3. Lee to take CONTAM output and test in DEVS. Check speed and requirements for 10K Montecarlo runs 4. MFK to create front-end Decision: 4/03/2022 - Cath, Alex, MFK: Use Case study A from Risk Analysis paper as a test-case as a static example. - Cath, Alex, MFK: Use a "chunk" of J10 post-retrofit as an example.