---
# System prepended metadata

title: HECOIRA Agenda

---

# 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.




