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COVID19 calculator supermarkt

Estimation of COVID-19 aerosol transmission: Case of supermarket work

This is a general spreadsheet applicable to any situation, under the assumptions of this model - See notes specific to this case (if applicable) at the very bottom

Important inputs as highlighted in orange - change these for your situation

Other, more specialized inputs are highlighted in yellow - change only for more advanced applications

Calculations are not highlighted - don't change these unless you are sure you know what you are doing

Results are in blue -- these are the numbers of interest for most people

Environmental Parameters

Value

Value in other units

Source / Comments

Length of room

ft

m

Can enter as ft or as m (once entered as m, changing in ft does not work)

Width of room

ft

=

m

Can enter as ft or as m (once entered as m, changing in ft does not work)

sq ft

m2

Can overwrite the m2 one. If you want to enter sq ft, enter "=B15*0.305^2" in the m2 cell, where B15 is the cell w/ sq ft

Height

ft

=

m

Can enter as ft or as m (once entered as m, changing in ft does not work)

Volume

m3

Volume, calculated. (Can also enter directly, then changing dimensions does not work)

Pressure

atm

Used only for CO2 calculation

Temperature

C

Use web converter if needed for F --> C. Used for CO2 calculation, eventually for survival rate of virus

Relative Humidity

50

%

Not yet used, but may eventually be used for survival rate of virus

Background CO2 Outdoors

ppm

See readme

Duration of event

min

h

Value for your situation of interest

Number of repetitions of event

times

For e.g. multiple class meetings, multiple commutes in public transportation etc.

Ventilation w/ outside air

h-1

Value in h-1: Readme: Same as "air changes per hour". Value in L/s/per to compare to guidelines (e.g. ASHRAE 62.1)

Decay rate of the virus

h-1

See Readme, can estimate for a given T, RH, UV from DHS estimator

Deposition to surfaces

h-1

Buonnano et al. (2020), Miller et al. (2020). Could vary 0.24-1.5 h-1, depending on particle size range

Additional control measures

h-1

E.g. filtering of recirc. air, HEPA air cleaner, UV disinfection, etc. See FAQs, Readme for calc for portable HEPA filter

Total first order loss rate

h-1

Sum of all the first-order rates

Ventilation rate per person

L/s/person

This is the value of ventilation that really matters for disease transmission. Includes additional control measures

Parameters related to people and activity in the room

Total N people present

Value for your situation of interest

Infective people

person

Keep this at one unless you really want to study a different cases - see conditional and absolute results

Fraction of population inmune

From vaccination or disease (seroprevalence reports), will depend on each location and time, see Readme

Susceptible people

people

Value for your situation of interest

Density (area / person) in room

sq ft / person

Density (people / area) in room

persons / m2

Density (volume / person) in room

m3 / person

Breathing rate (susceptibles)

m3 / h

See Readme sheet - varies a lot with activity level

Relative breathing rate factor

Ratio between the actual and base breathing rates

CO2 emission rate (1 person)

L/s (@ 273 K and 1 atm)

From tables in Readme page. This does not affect infection calculation, only use of CO2 as indicator, could ignore

CO2 emission rate (all persons)

L/s (@ at actual P & T of room)

Previous, multiplied by number of people, and applying ideal gas law to convert to ambient P & T

Quanta exhalation rate (infected)

infectious doses (quanta) h-1

See Readme file. Depends strongly on activity, also like person.This is the most uncertain parameter, try different values.

Q. enhancement due to variants

1 for the original variant, can be higher for variants of concern. See Readme file.

Relative quanta exhalation rate

Dimensionless (ratio to breathing)

For calculation of infection risk parameters. See Readme file.

Exhalation mask efficiency

0 if infective person is not wearing a mask. See Readme sheet

Fraction of people w/ masks

Value for your situation. It is applied to everybody for both emission & inhalation. Modify formulas manually if needed

Inhalation mask efficiency

See Readme sheet

Parameters related to the COVID-19 disease

Probability of being infective

Very important parameter, specific for each region and time period. For ABSOLUTE results (prob. given prevalence of disease in the population). See Readme sheet

Hospitalization rate

From news reports. Varies strongly with age and risk factors

Death rate

From news reports. Varies strongly with age and risk factors (1% typical - Higher for older / at risk people)

CONDITIONAL result for ONE EVENT: we assume the number of infected people above, and get the results under that assumption

More appropriate to simulate known outbreaks (e.g. choir, restaurant etc.), and an worst-case scenario for regular events (if one is unlucky enough to have infective people in attendance of a given event)

Net emission rate

infectious doses (quanta) h-1

Includes the number of infective people present

Avg Quanta Concentration

infectious doses (quanta) m-3

Analytical solution of the box model. Equation (4) in Miller et al. (2020)

Quanta inhaled per person

infectious doses (quanta)

Conditional Results for A GIVEN PERSON & ONE EVENT (assuming number of infected above, typically 1)

Probability of infection (1 person)

Applying Wells-Riley infection model to the amount of infectious doses inhaled. Equation (1) in Miller et al. (2020)

Prob. of hospitalization (1 person)

Prob. of death (1 person)

Ratio to risk of car travel death

times larger risk

See FAQs for rough estimate of death traveling by car on a given day

Conditional Results for ALL ATTENDEES & ONE EVENT (assuming number of infected above, typically 1)

Number of COVID cases arising

Number of people. Multiplies probability of one person, times the number of susceptible people present

N of hospitalizations arising

Number of people

N of deaths arising

Number of people

Airborne Infection Risk Parameters (From Peng et al., 2021, submitted)

Infection Risk Parameter (H)

h2 person / m3

Indicator of risk in terms of OUTBREAK SIZE. Low risk: H<0.05; Med: H<0.5; High: H>0.5; From Peng et al. (2021)

Relative Inf. risk Parameter (Hr)

h2 / m3

Indicator of risk in terms of ATTACK RATE. Low risk: Hr< 0.001; Med< 0.01; High>0.01 From Peng et al. (2021)

Results for CO2 as an indicator of risk (not needed for infection estimation, can ignore for simplicity)

Avg CO2 mixing ratio

ppm (including 400 ppm background)

Analytical solution of the box model. Equation (4) in Miller et al. (2020). See FAQ page for differences w/ quanta calc

Avg CO2 concentration

g m-3 (excluding 400 ppm background)

Conversion from Atmos. Chem. Cheat Sheet, plus ideal gas law

Exhaled CO2 re-inhaled per person

grams (excluding 400 ppm background)

This parameter is the most analogous to risk. See FAQ page for limitations

Exhaled CO2 re-inhaled per person

ppm * h (maybe easier units, excludes 400 ppm background)

This parameter is the most analogous to risk. See FAQ page for limitations

Exhaled CO2 re-inhaled per person

%CO2 * h (same as above, different unit, for use next)

Ratio of prob of infection to Ex_CO2

% chance of infection for 1 person per %CO2 * h inhaled

CO2 to inhale 1 hr for 1% infect.

ppm

This is another metric of risk

ABSOLUTE result for ONE EVENT: we use the prevalence of the disease in the community to estimate how many infected people may be present in our event, and calculate results based on that

More appropriate for general risk estimation, e.g. in a college classroom, indoor gathering etc., where often infective people will not be present

N of infective people present

It has to be interpreted statistically. This would be the average over e.g. 100 repetitions of the event in a given location

Absolute results for A GIVEN PERSON & ONE EVENT (using disease prevalence in community)

Probability of infection (1 person)

Prob. of hospitalization (1 person)

Prob. of death (1 person)

Ratio to risk of car travel death

times larger risk

See FAQs for rough estimate of death traveling by car on a given day

Absolute results for ALL ATTENDEES & ONE EVENT (using disease prevalence in community)

Number of COVID cases arising

Number of people

N of hospitalizations arising

Number of people

N of deaths arising

Number of people

CO2 to inhale 1 hr for 1% infect.

ppm

This is another metric of risk

ABSOLUTE result for events that are REPEATED MULTIPLE TIMES (e.g. many class meetings during a semester, or a daily commute on public transportation) - Ignore for a single event

Absolute results for A GIVEN PERSON & MULTIPLE EVENTS (using disease prevalence in community)

Probability of infection (1 person)

Prob. of hospitalization (1 person)

Prob. of death (1 person)

Ratio to risk of car travel death

times larger risk (than traveling same N of days)

See FAQs for rough estimate of death traveling by car on a given day

Absolute results for ALL ATTENDEES & MULTIPLE EVENTS (using disease prevalence in community)

Number of COVID cases arising

Number of people

N of hospitalizations arising

Number of people

N of deaths arising

Number of people

Specific notes for this case

Based on a specific supermarket in Boulder, Colorado.

Horizontal dimensions estimated from Google Maps (using scale), height using pictures from Google Street View (using people present for scale)

Ventilation rate estimated from ASHRAE standard in Readme page

Occupancy typical daily average, based on my visits to the space pre-pandemic (may be lower now.

Other parameters estimated per Readme for this situation

This is for a supermarket worker. For a customer, change the time spent in the story to e.g. 1 hr, 4 times a week to simulate 1 month