FIMechE, CEng, Professor of Building Physics and Sustainable Design, Institute for Building Physics, Services and Construction, TU Graz, Graz, Austria
FCIBSE, FIBPSA, CEng, Professor of Building Physics, Institute for Building Physics, Services and Construction, TU Graz, Graz, Austria
DI MSc, University Assistant, Institute for Building Physics, Services and Construction, TU Graz, Graz, Austria
Keywords: hybrid ventilation, natural ventilation, mechanical ventilation, viral transmission, EN 16798-1, ISO 17772-1, ASHRAE standard 241, SARS-CoV-2, pandemic preparedness.
The COVID-19 pandemic caught policy makers, government agencies, school management and facility managers largely off-guard, prompting a review of existing ventilation standards in relation to the mitigating of airborne viral diseases. In light of new guidance in ASHRAE standard 241-2023 ‘Control of Infectious Aerosols’ this paper examines the relative airborne viral prophylaxis benefit of seven different ventilation scenarios, involving natural, mechanical and hybrid ventilation systems. The research aims to assess the relative merits of each approach considering current guidance in European Norm (EN 16798-1) and International Standard (ISO 17772-1) in contrast to the increased minimum equivalent clean airflow rates for classrooms in ASHRAE 241.
The results of this analysis show that increased minimum equivalent clean airflow rates have a marked effect on reducing the airborne viral transmission risk. However, even with the best performing ventilation system the risk of at least one individual becoming infected with the SARS-CoV-2 Omicron variant (after an 8 h long exposure period) was 30% (assuming that one infectious individual was present in a classroom of 20 unmasked, immunologically naïve students). By using a combined strategy involving universal FFP2 masking and ventilation the group infection risk level was dramatically reduced to 2–7% (depending on the ventilation type and flowrate) highlighting the importance of layered prophylaxis strategies at times of elevated community transmission.
An international review in 2021 by the Global Health Security (GHS) Index  highlighted the sobering fact, that “all countries remain dangerously unprepared to meet future epidemic and pandemic threats.” The GHS Index measures the capacities of 195 countries to prepare for epidemics and pandemics and the average overall GHS country score in 2021 was slightly worse (38.9 out of 100) than in 2019 (40.2 out of 100). Even the “best prepared” countries (USA, Australia, Finland) do not reach the top tier of the GHS Index (i.e. score > 80), indicating that overall pandemic preparedness is “fundamentally weak at all country income levels” (Bell and Nuzzo 2021) (Figure 1).
Figure 1. Overall risk ranking according to 2021 Global Health Security Index, which measures the capacities of countries to prepare for epidemics and pandemics (adapted from GHS Index 2021 data).
The role of schools in the transmission of the SARS-CoV2 virus has been extensively debated. Despite widespread acceptance of the need to maintain in-classroom teaching (WHO Europe 2021) there is no consensus as to what level of mitigation is needed to do this safely (Lessler et al. 2021).
International building services organisations including REHVA, CIBSE, ASHRAE (amongst others) were quick to provide detailed pandemic ventilation guidance and to continually update that information in the light of emerging knowledge. At a policy and advisory level this work is continuing, for example in July 2023 ASHRAE issued Standard 241,Control of Infectious Aerosols (ASHRAE 2023) and has revised many of its existing ventilation standards to reflect emerging scientific findings in relation to the role of ventilation in mitigating the transmission of airborne disease. Pandemic preparedness implies the practical implementation of such changes, typically in a relatively short time scale, and that this requirement is poorly aligned with traditional policy and legislative processes (Caulfield 2013). Moreover, there are financial and resource constraints, wherein for example, retrofitting a single school with an appropriately sized ducted MVHR systems might cost upwards of 10,000 Euros per classroom (Checkatrade 2022). Even ignoring the resource and sustainability implications, rolling out such a strategy at a national scale in every European country would require enormous financial investment  and could take years to implement. Even if such a strategy were considered feasible and cost-effective in the more affluent countries of the global North (and could be sustained at a 10–20-year replacement interval) it is almost inconceivable that it could be implemented equitably across the global South. Thus existing health inequalities, highlighted by the disproportionate effects of COVID-19 on poorer nations (Oxfam 2022), could be further exacerbated over the longer term by a lack of affordable public health measures to address further waves and even endemicity.
In the light of these challenges, it became apparent that low-cost easy to install (e.g. DIY, Do It Yourself) responses to ventilation and air-cleaning enhancement could play an important role in reducing viral transmission in schools, in both the short and medium term. One such idea, for a novel hybrid mechanical extract ventilation (MEV) system, was developed by the Max Plank Institute for Chemistry (MPIC) in Mainz Germany (Klimach et al. 2022) (Figure 2). This concept was subsequently trialled in several hundred schools in Germany and independently tested by the IBPSC at TU Graz, Austria (Pollozhani et al. 2022) (Eibinger et al. 2022). This study builds on previous work  by providing a comparative analysis of the airborne infection risk associated with a range of different classroom ventilation strategies whilst also evaluating the additional prophylaxis benefits of using substantially increased ventilation airflow rates, as proposed by ASHRAE 241-2023: Control of Infectious Aerosols (ASHRAE 2023).
A university seminar room at Graz University of Technology was equipped with a low-cost retrofitted mechanical extract ventilation (MEV) system developed by the Max Planck Institute for Chemistry (MPIC), (Klimach et al. 2022) (Helleis, Klimach, and Pöschl 2023). Adopting the room geometry and using ventilation flow rate data from the experimental setup seven different ventilation scenarios (Table 1) were assessed over a one-year period using the IDA ICE dynamic simulation software (EQUA 2023). Based on the room occupancy and ventilation rates an analytical model based on a method developed by Lelieveld et al. (2020) was then used to predict the corresponding seasonal risk of infection with the SARS-CoV-2 original Omicron variant. Although the original Omicron variant is no longer the prevalent strain of the SARS-CoV-2 virus the results of this analysis are still useful from the perspective of making comparative risk assessments. Moreover, the viral transmission parameters (Table 2) can be readily modified to accommodate emerging variants or viruses.
Seven scenarios were considered in this study, as described in Table 1, to provide a comparative analysis between the MPIC-MEV system and common natural and mechanical alternatives.
Table 1. Ventilation scenarios.
1. Base Case (BC)
The base case (BC) assumed that no purposeful ventilation measures were taken (i.e. all windows and doors remained closed). The purpose of this scenario was to serve as a worst-case comparator for the IAQ and infection risk, and as a best-case scenario for heating energy conservation. It should be noted, that whilst such a scenario is not uncommon in practice, it would not comply with the European standard EN 16798 (CEN 2019) or the international standard ISO 17772-1 for occupied spaces, and is not recommended.
2. Max Planck Institute for Chemistry -Mechanical Extract Ventilation (MPIC-MEV) at 10 ℓ/s.(person)
Scenario 2 examined the MPIC – MEV system installed in the seminar room. The ventilation flow rates were measured directly from the installed system and for 20 occupants were compliant with EN 16798-1:2019 category IEQ1 (see Pollozhani et al 2023, for further details).
3. Max Planck Institute for Chemistry -Mechanical Extract Ventilation (MPIC-MEV) at 20 ℓ/s.(person)
Scenario 3 examined the MPIC – MEV system installed in the seminar room under the theoretical consideration of increased airflow rates of 20 ℓ/s.(person) in accordance with the recommendation for classrooms in ASHRAE Standard 241
4. Air Handling Unit – Heat Recovery Ventilation (AHU-HRV) at 10 ℓ/s.(person)
Scenario 4 investigated the use of a conventional decentralised air handling unit (AHU) with heat recovery (HR). An AHU with a nominal air flow rate of 0.2 m³/s (i.e. 720 m³/h, at a nominal external pressure of 200 Pa) was chosen for the simulation as this corresponded closely to the air flow rates measured on the MPIC-MEV system in scenario 2. This flow rates equates to 10 ℓ/s.(person) to match scenario 2 and comply with EN 16798-1:2019 category IEQ1. During warmer periods the HR system operated in bypass mode. Thus, when the outside air temperature exceeded 16 °C the extract air was discharged through the bypass (avoiding the heat exchanger) to mitigate overheating (McLeod and Swainson 2017) (Mourkos et al. 2020).
5. Air Handling Unit – Heat Recovery Ventilation (AHU-HRV) at 20 ℓ/s.(person)
Scenario 5 examined the AHU-HR system under the theoretical consideration of increased airflow rates of 20 ℓ/s.(person) in accordance with the recommendation for classrooms in ASHRAE Standard 241
6. Natural Ventilation – Tilted windows (NV-T)
Scenario 4 examined the ventilation of the seminar room by the means of tilted windows. For this case, it was assumed that all five windows of the room were continuously tilted (with a maximum opening depth of 0.18 m, providing a total window opening area of 0.5 m² per window, calculated according to Mourkos et al. (2020) during occupied periods (i.e., from 8 a.m. till 12 p.m. and from 1 p.m. till 5 p.m.). This scenario was designed to reflect the background ventilation which would occur through the use of constantly tilted windows without necessitating continual occupant intervention.
7. Natural Ventilation – Purge ventilation (NV-P)
Scenario 5 investigated purge ventilation patterns using fully opened windows. This strategy was advocated by the German environmental agency (German: Umweltbundesamt, (UBA)) at the outbreak of the pandemic. UBA recommended that classrooms should be purge ventilated at regular intervals, using wide-open windows instead of tilted windows (UBA 2021). In this scenario it was defined that all five windows of the seminar room were fully opened every 20 minutes for a duration of 4 minutes during the months of October through to April. In May and June, when the average daily temperatures were around 17- 20 °C, the windows were opened for an extended period, of 15 minutes, every 20 minutes to compensate for the reduced air- pressure differentials between the inside and outside air masses at this time.
Table 2. Parameters used in the analytical infection risk model (after Lelieveld et al. (2020)).
Virus lifetime - tvirus
e-folding time in aerosol (Lelieveld et al. 2020) (van Doremalen et al. 2020)
Viral load - cv
for original Omicron variant (MPIC 2021)
Infective dose - D50
for original Omicron variant (MPIC 2021)
PRNA = 1−e^(ln(0.5)⁄D50 ) (Lelieveld et al. 2020)
Wet aerosol diameter - da
(Lelieveld et al. 2020), (MPIC 2021)
Particle emission breathing -pe, b
Particle emission speaking -pe, s
Speaking/ breathing ratio
Resulting particle emission - pe, t
pe,t = pe,s ∙ 0,1 + (1−0,1) pe,b
Mask factor (exhalation)- fmask,e
with filter efficiency of 80% (1=no mask) (MPIC 2021)
Mask factor (inhalation)- fmask,in
with filter efficiency of 70% (1=no mask) (MPIC 2021)
Lung deposition factor- flung
(Lelieveld et al. 2020), (MPIC 2021)
Breathing rate - qb,e
(Lelieveld et al. 2020), (MPIC 2021)
Effective breathing rate - qb,eff
qb,eff = qb,e ∙ fmask,in ∙ flung
RNA conc. exhaled breath - CRNA,b
CRNA,b = π/6∙ da³∙cv∙10-12∙ pe,t ∙10³
Emission factor - E
E = CRNA,b ∙ qb,e ∙ fmask,e
The seminar room chosen for this study is typical of many naturally ventilated university teaching rooms, designed for approximately 30 occupants. The room is occupied from 8 a.m. to 5 p.m. daily, during term-time, for a variety of purposes including lectures, workshops, and exams. This means that the room occupancy varies over the course of a day and according to academic cycles. Since occupant density is known to be a significant factor in predicting infection risk (Clayson et al. 2022) a range of typical occupancy levels (n=10, 20 and 30) were investigated in this study.
Figure 2. Concept schematic (left, image courtesy MPIC, copyright A. Koppenborg) and final assembly (right) of the MPIC-MEV system showing extract hoods, ductwork and extract-fan.
Figure 3 shows the floor plan of the seminar room with the MPIC-MEV system overlaid. The room is located on the first floor of a five-storey high university building which was constructed in 1994. The room measured 6.5 by 8.1 m with a height of 3.05 m which (minus three vertical columns) results in a net internal volume of 147.3 m³. The exterior wall faces southwest, with five openable (tilt and turn) windows measuring 0.9 by 1.8 m providing a window-to-wall ratio of 33% (8.1 m² of 24.7 m² interior wall). The windows were equipped with external fixed-angle louvers, which shade approximately half of the windows’ solar aperture.
Figure 3. Floor plan of the seminar room showing the layout of the MPIC-MEV system.
Two hydronic wall mounted radiators (measuring 1.4 m by 0.5 m each) with an estimated combined design output of 4,700 W) provide heat to the room during the colder months. The seminar room is illuminated by 16 compact fluorescent lamps with an electric power consumption of 25 W each (400 W in total, with an estimated 30% convective heat fraction). In addition, a ceiling mounted projector with a power consumption of 150 W is installed in the room. Resulting in a maximum total internal heat gain of 550 W for lights and equipment. Occupant sensible and latent heat gains were assumed at 126 W/person at an average metabolic equivalent task (MET) rate of 1.2 (ISO 2005). The thermal specifications of the construction assemblies were sourced from an energy certificate issued in 2012. An average infiltration rate of 0.2 h−1was derived using human-generated CO₂ concentration decays in the space, based on the approach described by Persily (1997) and Cui et al. (2015).
In order to establish the in-situ performance of the non-commercial MPIC-MEV system, a fully functioning system was installed in the seminar room using materials widely available from building merchants, at a total cost of around 500 Euros (for more information about the ventilation system see (Klimach et al. 2021) (Helleis, Klimach, and Pöschl 2022)). The system is designed to extract stale room-air close to the ceiling and supply fresh air nearer to the floor level, through a tilted window (Figure 2). In the context of SARS-CoV-2, CFD studies have demonstrated that properly designed displacement ventilation provides an effective means of mitigating long-range transmission (Bhagat and Linden 2020) (Bhagat et al. 2020). Osman et al. (2023) also showed displacement systems are capable of reducing the range of horizontal droplet transfer from coughing episodes. Experimental evidence from the MPIC shows that the addition of extract hoods can further improve the removal of respiratory aerosols by about 30–50% (Helleis, Klimach, and Pöschl 2023).
A summary of the system parameters and operational schedules used the IDA ICE simulations can be seen in Table 3.
Table 3. List of scenarios and simulation parameters.
2. MPIC-MEV (10)
3. MPIC-MEV (20)
4. AHU-HRV (10)
5. AHU-HRV (20)
Air flow [ℓ/s(m²)]
Occupancy schedule de
8 am – 12 pm, 1 pm – 5 pm
Fan, window, equipt. schedule.
8 am – 12 pm, 1 pm – 5 pm
AHU set-back schedule f
7 - 8 am
7 - 8 am
12 - 1 pm
12 - 1 pm
Number of open windows g
5 fully open
HX thermal efficiency [%]
Active internal heat gains
100% of internal gains due to occupants, equipment, light
Temp. setpoint [°C]
20 °C (2 °C P-band for proportional temperature control)
a Value achieved solely by infiltration (which is not considered purposeful ventilation)
b See section 3.1 for the occupancy dependent ventilation control strategies used in scenarios 2 and 3
c ‘variable’ because values were determined by IDA ICE tool for transient external/ internal boundary conditions
d Metabolic rate of 126 W (sensible and latent heat, at 1.2 met and 70 W/m²) acc. to ISO 7730:2005 
e Weekends and holidays (acc. to Austrian university curriculum, i.e. Feb., Jul., Aug., Sept.) lecture free
f Set-back rate of one volumetric air change within two hours prior to occupancy (0.5 h-1) acc. to EN 16798‑1:2019
g Total free opening area of 0.5 m² per tilted window and 1.8 m² per fully open window.
h The power consumption of 47W at 2.90 ℓ/s(m²) and 71W at 4.45 ℓ/s(m²) was measured on the installed system.
Based on the transient ventilation rates and design occupancy assumptions the infection risk, which is the main focus of this study, was analytically assessed based on a method developed by Lelieveld et al. (2020) using the parameters and value set out in Table 2.
For the original Omicron variant of the SARS-CoV-2 virus, 154 inhaled RNA copies were expected to correspond to an infectious dose (D50), the mean number of vial copies that would cause an infection in 50% of susceptible subjects . The individual infection risk Ri(t) for each susceptible individual is calculated with the following formula (Eq.1) depending on the number of inhaled virus particles nv(t) and the probability PRNA that a single virus particle causes an infection:
Whilst the risk of a single individual from a group of individuals becoming infected is expressed as a function of the number of susceptible people in the room according to Eq. 2.
Ri(t)is the individual infection risk for each person [%],
R(t)is the probability of a single person getting infected from a group of susceptible people [%],
n is the number of susceptible (i.e. non-infected) individuals in the room,
nv(t) is the number of virus particles inhaled per person,
and PRNA is the probability that a single virus particle causes an infection.
The time-dependent airborne virus particle concentration (cv(t)) in the experimental room (under the assumption of one infectious person being present for the duration of time (t)) and the resulting quantity of inhaled virus particles per occupant (nv(t)) were determined for all five scenarios on sample days at different outside boundary temperatures according to the respective air exchange rates resulting from the dynamic simulation with the following formulas:
cv(t)is the concentration of infectious particles (virions) in the indoor air [No./m³] at time (t),
nvois the number of viral particles already inhaled by a person [No.],
cvo is the existing viral concentration in the room air [No./m³] at the start of the classes (t = 0),
qb,eff is the effective breathing rate [ℓ/min] (as described in table 2),
Eis the Emission factor [No./h] or rate at which viral copies are released (as described in Table 2)
Note, to account for the “hood effect” (ηhood) in the MPIC-MEV system the emission factor is modified as follows, EMPIC = E · (1− ηhood)
Results and analysis – comparative infection risk assessment
The risk of infection by the original Omicron variant of the SARS-CoV-2 virus, under the seven different ventilation scenarios (Table 1), was analysed for 20 occupants on the coldest (12th January) and warmest (30th June) design days to examine the influence of seasonal temperature variations on the natural and hybrid ventilation scenarios. Figure 4 shows the virus-containing respiratory aerosol concentration in the room air across the day c(t) (left) and the resulting group infection risk as a function of the exposure duration (right). The latter is the combined probability that at least one susceptible person from any of the group members (of n=20 people) will become infected. For the hybrid (MPIC-MEV) and mechanical (AHU) systems the results for airflow rates of 10 ℓ/s.(person) in accordance with EN16798-1:2019 (solid line, Figure 4) and 20 ℓ/s.(person) as recommended by ASHRAE Standard 241 (dashed lines, Figure 4) are shown. Note that the model assumes that the room is unoccupied and unventilated for one hour during the lunch period (12:00-13:00 h) (grey bar, Figure 4) and that the same occupants re-enter the room after lunch.
Figure 4. Virus concentration [No./m³] (left) and the probability of at least one person becoming infected [%] as a function of time (right) for 20 unmasked occupants on the coldest day (12th of January) and the warmest day (30th of June) of the year. Grey bars indicate the lunch break period (12:00-13:00 h) where the ventilation systems are turned off and the room is unoccupied. [Double column fitted]
Note that, due to the significantly higher viral concentration in the base case (scenario 1) it is depicted on a secondary x-axis with a different scaling (Figure 4, left), therefore, the slope of the base case appears disproportionally low compared to the other scenarios. It can be seen that by providing a constant air exchange rate in the hybrid and mechanical scenarios (orange and blue lines, Figure 4, left) a state of equilibrium is reached in the virus particle concentration present in the room. Conversely, as might be expected, varying air exchange rates, as seen in the purge-vent scenario (pale grey line, Figure 4, left), resulted in fluctuating viral particle counts.
Table 4. Infection risk probability [%] results for any one individual in a group of 20 people (with and without universal FFP2 masking) after 8 hours of exposure on the coldest day (12th of January, left) and the warmest day (30th of June, right) of the academic year.
Cold day risk (12th January) [%]
Warm day risk (30th June) [%]
2. MPIC-MEV 10 ℓ/s(p)
3. MPIC-MEV 20 ℓ/s(p)
4. AHU-HRV 10 ℓ/s(p)
5. AHU-HRV 20 ℓ/s(p)
As might be expected, the results (Table 4) show the highest risk of infection occurs in scenario 1 as there is no active ventilation. Under this scenario (assuming an immunologically naïve population) based on an occupancy of 20 persons, there is a probability of 100% that at least one person in the room would get infected during the 8-hour exposure period. If all people present in the room were to wear an FFP2 masks, this value could be reduced to 27%. Scenario 2 resulted in a risk of 47% without masking and 4% with masking that one out of the 20 people present in the room would become infected after a duration of 8 hours for both the best-case (cold outdoor temperatures) and worst-case (warm outdoor temperatures). Despite the same air exchange rates as for scenario 2, scenario 4 displayed a slightly higher risk of one amongst the 20 occupants becoming infected, with 57% without masking and 5% with masking. This difference between scenarios 2 and 4 can be attributed to the reduced room aerosol emission intensity achieved by the distributed (i.e. localised) extraction of potentially infectious aerosols using the MPIC-MEV system extract hoods.
In contrast the infection risk under the naturally ventilated scenarios showed a stronger dependence on the outdoor air temperatures. Due to the relatively high air exchange rates with continually tilted windows in cold weather (on12th of January) scenario 6 resulted in a lower risk (42% without masks and 3% with masks) cf. scenario 7 (purge ventilation) (59% without masks and 5% with masks). This finding is attributed to the 20-minute phases (between purges) in which the room was not ventilated at all, during which the concentration of virus-containing particles sharply increased to relatively high values (≈10 particles per m³ of room air, see Figure 4). In contrast, with warmer external air temperatures in summer, higher risk values were found with tilted windows (72% without masking and 7% with masking) due to the lower air exchange rate. Under the same conditions the use of purge venting resulted in a lower risk (59% without masking and 5% with masking), although it should be noted that the duration of the purge phase opening time was extended from 4 minutes to 15 minutes (every 20 minutes) in the summer months (Table 3). This finding highlights the importance of adjusting purge duration intervals in accordance with outside air temperatures or room CO₂ concentration.
By using larger fans and increasing the mechanical ventilation flow rate from 10 to 20 ℓ/s.(person), in line with ASHRAE Standard 241, the infection risks were further reduced for the MPIC-MEV system (scenario3) (to 30% without masking and 2% with masking) and for the AHU-HRV system (scenario 5) (to 37% without masking and 3% with masking). The additional benefit achieved by the MPIC system can be attributed to the use of hoods above the occupants.
Conclusion and limitations
The findings of this study have shown that the infectious virus particle load suspended in room air, and the resultant infection risk are closely dependent on the ventilation rate. During the colder months natural ventilation using tilted windows and the use of the Max Plank Institute for Chemistry Mechanical Extract Ventilation (MPIC-MEV) system (at a flow rate of 10 ℓ/s.(person) both provided a risk reduction of more than 50% relative to the base case scenario (which assumed no purposeful ventilation in the room). During the warmer months extended purge ventilation cycles had a greater effect than tilt ventilation, however only the MPIC-MEV system was able to reduce the (unmasked) transmission risk by over 50% year-round.
When the mechanical ventilation flow rates were increased from 10 to 20 ℓ/s.(person), in accordance with recommendations for classrooms in ASHRAE Standard 24-2023, a significant reduction in the infection risk was observed (with a 17% improvement in the MPIC-MEV system and a 20% improvement in the AHU-MVHR system). Accordingly, the lowest overall risk of one individual becoming infected after an 8 h exposure period was 30% in the case of the MPIC-MEV system, operating at 20 ℓ/s.(person), and the highest risk was 72% on a warm day using tilted windows.
Applying universal FFP2 masking in the base case scenario (in the absence of any purposeful ventilation over an 8 h period) reduced the risk of infection from 100% to 27%. These benefits are further amplified when ventilation was used in conjunction with masking. Notably using the MPIC-MEV system (at 20 ℓ/s.(person) in conjunction with FFP2 masking reduced the risk of any individual becoming infected (after an 8 h exposure period, in a room with one infectious individual) to 2%.
It should be noted that the infection model used here assumes complete mixing of the room air, and therefore the displacement effect was not incorporated in the infection risk model of the mechanical systems. The benefits of using hoods above the occupants to capture viral aerosols were incorporated in the model (for the MPIC-MEV system) using a conservative figure of 30% (based on secondary evidence). Further research is needed to quantify the additional benefits of using displacement ventilation and hood capture in combination, which are likely to be influenced by seasonal changes in the supply air temperature and a number of other factors.
In practical terms these findings highlight the benefit of using higher ventilation flow rates as well as the use of multiple prophylaxis measures, in combination, when community transmission rates are high. Since few existing ventilation systems will be capable of delivering the equivalent clean airflow rates in ASHRAE Standard 241-2023, ways of providing additional clean air capacity (e.g. via filtration units) without creating a significant energy burden and/or exacerbating thermal or acoustic discomfort need to be carefully considered.
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 The Global Health Security Index is an assessment which benchmarks health security and related capabilities, across six categories and 37 indicators, for 195 countries The GHS Index was developed in partnership by the Nuclear Threat Initiative (NTI) and the Johns Hopkins Center for Health Security at the Bloomberg School of Public Health, working with Economist Impact.
 Where most schools are naturally ventilated, even in a relatively small European country such as Austria (with approximately 52,000 classrooms) would entail an investment of around 0.5 Billion Euros.
 Readers seeking to understand the multiple dimensions of this issue (i.e. including consideration of indoor air quality, thermal comfort, heating, and operational energy aspects) are referred to Pollozhani et al. (2023).