Covid Risk airborne, a tool to test the risk of aerosol transmission of SARS-CoV-2 under different scenarios: a pre-school classroom case study

Covid Riskairborne, a tool to test the risk of aerosol transmission of SARS-CoV-2 under different scenarios: a pre-school classroom case study Miguel Ángel Campano1*, Jesica Fernández-Agüera1, Samuel Domínguez- Amarillo1, Ignacio Acosta1 and Juan José Sendra1 1 Instituto Universitario de Arquitectura y Ciencias de la Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla, 41012 Seville, Spain. * Correspondence: [email protected]s (M.A.C.); Tel.: +34 954559517 Abstract: The COVID-19 emergency has shown that airborne transmission of SARS-CoV-2 is especially relevant in poorly bad ventilated spaces with high occupancy density, like non-university classrooms, a widespread space typology with very sensitive occupants. Of these, pre-school classrooms stand out, due to the vulnerability of children. Thus, this study has estimated the existing transmission risk of SARS-CoV-2 in a pre-school classroom, due to the especial vulnerability of the children, regarding to different indoor CO2 excess levels. This statistical evaluation has been performed through 68 calculation hypotheses, grouped into 4 cases, according to who is the primary infected occupant (one of the children or the teacher) and depending on whether the teacher wears a mask or not. It can be concluded that, to have acceptable risk conditions for airborne disease transmission (with one infected occupant) in pre-school classrooms, it is necessary to maintain sufficient ventilation conditions to reach a maximum average excess CO2 level exhaled of 150 ppm, while teachers should wear wellfitting N95 respirators. In this way, infection risk is much higher when the primary infected occupant is the teac Keywords: CO2 concentration; School buildings; SARS-CoV-2; Airborne transmission; COVID-19 infection risk 1. Introduction The airborne transmission of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is widely proven by scientific community (Morawska and Cao, 2020; Greenhalgh et al., 2021; Miller et al., 2021; Tang et al., 2021; Wang et al., 2021; World Health Organization, 2021; Burgos-Ramos, Urbieta and Rodríguez, 2022), with the main COVID-19 outbreaks occurring indoors (Qian et al., 2021; Randall et al., 2021; Wang et al., 2022). In this way, medium and long-range transmission —beyond 1.5 m— is especially relevant in poorly bad ventilated spaces (Li, 2021; Peng et al., 2022). In this way, one of the most widespread space typologies are non-university classrooms, in which children —considered as sensitive and vulnerable population— spend an average of 5-6 hours a day, from Monday to Friday during nine months a year, focused on winter and mid-seasons. In this way, classrooms are high occupancy density spaces with usually poor ventilation conditions, as several studies have pointed out in southern Spain (Fernández- Agüera et al., 2019; Villanueva et al., 2021), France (Annesi-Maesano et al., 2012), Italy (De Giuli, Da Pos and De Carli, 2012; Annesi-Maesano et al., 2013; De Giuli et al., 2014) and Portugal (Almeida et al., 2011; Campano et al., 2017), among others, due a lack of ventilation. Given that there have also been several documented COVID-19 outbreaks in educational buildings (Fontanet et al., 2021; Lorthe et al., 2022), it is necessary to promote healthy classrooms through self-protection practices and adequate indoor air quality (IAQ). Thus, the 30 removal of the virus-containing aerosols from indoor air —by ventilation, air filtration or UV radiation— is an essential part of the prevention strategy. One of the main ways to assess the degradation of the IAQ in occupied spaces —with no other significant sources or sinks of indoor carbon dioxide (CO2) — is monitoring the indoor CO2 level, which can be a good proxy to evaluate and control the aforementioned ventilation rates, especially in spaces with high occupancy density such as non-university classrooms (Persily and de Jonge, 2017; American National Standards Institute and American Society of Heating Refrigerating and Air-Conditioning Engineers, 2019; Zhu et al., 2020; Pavilonis et al., 2021; Peng and Jimenez, 2021; Peng et al., 2022). As it was mentioned already, the measurement of the excess CO2 level exhaled ( 2) can also be used to estimate the airborne transmission risk of respiratory diseases such SARS-CoV-2, tuberculosis, or measles, given that virus-containing aerosols are emitted during the respiratory process as CO2 does. Thus, the infection risk of SARS-CoV-2 can be estimated using the indoor CO2 excess as a proxy through adaptations (Jiménez Palacios and Peng, 2021; Peng and Jimenez, 2021; Peng et al., 2022; Rowe et al., 2022) of the Wells-Riley model (Rudnick and Milton, 2003). In this way, it is possible to estimate the COVID- the online tool COVID Risk airborne (https://www.covidairbornerisk.com/), non-profit developed by Campano et al. (Campano-Laborda et al., 2021) and based on the adaptation of the Wells-Riley model performed by Peng and Jiménez (Jiménez Palacios and Peng, 2021; Peng and Jimenez, 2021). The main aim of this work is to estimate and analyse the existing transmission risk of SARS-CoV-2 in a pre-school classroom, due to the especial vulnerability of the children and the lack of proper use of masks due to their age, regarding to different indoor CO2 excess levels. With the results of this theoretical study, it is possible to optimize the ventilation and self-protection strategies of the occupants. 2. Materials and Methods The following phases have been established to develop this study: Sample Boundary conditions Hypotheses under study Infection risk indicators 2.1. Sample An Andalusian pre-school classroom was chosen as the study case. Its shape, dimensions, HVAC systems, furniture and theoretical occupation are standardized according to the design standards established for non-university educational institutions (Junta de Andalucía, 2003). The premise is 50 m² and 3 meters high, designed for a maximum capacity of 24 children (Campano, 2015). It has its own bathroom, with a direct access from inside the classroom, as well as an associated schoolyard, accessible from a door on the façade of the premise (Figure 1). The classroom has no suspended ceiling or perforations in the inner partitions with the adjacent classroom nor the corridor. The external vertical wall is composed by a half-brick wall with rendering, an air chamber, projected polyurethane as thermal insulation and a plasterboard. The internal partitions are composed of two layers of plasterboard with mineral wool between them. 31 Figure 1. Ground plan of the pre-school classroom under study, following design standards for regional educational institutions. Heating system is composed by hot water (HW) radiators, with no provision for cooling systems (Campano, Sendra and Domínguez, 2011; Campano et al., 2019). Ventilation is traditionally relied by windows operation and uncontrolled infiltrations, despite the Spanish Standard on thermal installations in Buildings (RITE) (Ministerio de la Presidencia del Gobierno de España, 2021) establishes the controlled mechanical ventilation as the only option for non-residential buildings. In winter conditions, the lower limit for operative temperature set by Spanish RITE is 21 ºC, while the maximum operative temperature in summer conditions is 25 ºC. The school day in pre-school and primary public schools of Andalusia is 5 hours, usually from 9:00 a.m. to 2:00 p.m., with a half-hour break in between. Each centre can establish the starting point of said break, although it is usually in the middle of the school day (from 11:15 to 11:45). 2.2. Boundary conditions The calculation conditions required to estimate the existing infection in the pre-school classroom under study are listed in Table 1 (Campano-Laborda et al., 2020). The exposure time (event duration) is established in 135 minutes, given that it can be considered the average period between the lunch break and the start/end of the school day. The pre-school classroom under study is also considered to be in winter environmental conditions, with the existing HW radiator system operating to achieve compliance with the hygrothermal conditions of the RITE (Ta 21ºC and HR 40%). It has been estimated that there is always an infected occupant with a high viral load in the classroom, as a realistic hypothesis for the airborne transmission risk simulations. 32 Table 1. Boundary conditions of the case of study for the statistical study of infection risk Dimensions Area (m²) 50.0 Heigh (m) 3.0 Environmental conditions (winter season) Indoor air temperature (ºC) 21.0 Relative indoor air humidity (%) 40 Atmospheric pressure (atm) 1.0 Indoor atmosphere Still air Variant of SARS-CoV-2 Variant of SARS-CoV-2 Omicron BA.2 Percentile of viral exhalation rate (%) 85 Occupancy parameters and type of activity No. of infectious occupants 1 No. of people present 25 Mean age of occupants (years) 5 Event duration (min) 135 Intensity of activity of the children Sitting – Oral respiration Intensity of activity of the teacher Standing – Speaking 2.3. Hypotheses under study Four scenarios were considered for this study, using the average excess CO2 level exhaled (2) during 135 minutes of a regular educational day (exposure period) as a proxy to calculate how many 'quanta' inhaled each occupant (a 'quanta' can be considered as the minimum infectious dose of the aerosol pathogen whose inhalation leads to infection in 63% of vulnerable people). They are grouped in two categories, according to the occupant who was initially infected (child or teacher). CASE 1: One infected child by SARS-CoV-2 (sitting – oral respiration) and no one wearing a mask in the classroom. CASE 2a: Teacher infected (standing – speaking) and no one wearing a mask in the classroom. CASE 2b: Teacher infected (standing – speaking), wearing a surgical mask (non-fitted) and the rest of occupants with no masks. CASE 2c: Teacher infected (standing – speaking), wearing a well-fitting N95 respirator and the rest of occupants with no masks. The risk calculations defined above were performed considering increases in the average indoor-outdoor CO2 differential of 100 ppm, with an excess range of 100 to 1600 ppm, as previously measured in this type of premises (Fernández-Agüera et al., 2019). This procedure also allows to consider the following thresholds: The Spanish RITE CO2 limit value for classrooms (indoor air quality of IDA 2), which can be expressed as an increase of 500 ppm of CO2 above the outside level for spaces with high occupancy density (Ministerio de la Presidencia del Gobierno de España, 2021). The recommendations developed for schools during the COVID-19 emergency situation, which establishes a CO2 threshold of 300 ppm above the outside level (Jones et al., 2020; Minguillón et al., 2020; Plataforma Aireamos, 2021). This limit is close to the IDA 1 CO2 threshold of the Spanish RITE (350 ppm), applicable to hospitals, nurseries and nursing homes. The recommendation developed for indoor educational spaces, both for classrooms with vulnerable occupants or with no masks, and for corridors (spillway spaces), which 33 establishes a CO2 threshold of 150 ppm above the outside level (Plataforma Aireamos, 2021). 2.4. Infection Risk Indicators This statistical study is developed through two risk indicators, adapted to airborne disease transmission (Peng and Jimenez, 2021; Peng et al., 2022): Attack rate (AR): The proportion of occupants in the event who could have inhaled the necessary infectious dose of the aerosol pathogen whose inhalation leads to infection in 63% of vulnerable people ('quanta'). Relative risk of infection (Hr): Number of 'quanta' emitted by a single infected person which are inhaled by a single person for a given exposure time and premises of the volume specified. The main point of both indicators is that they are not referred to the number of vulnerable occupants (those who are liable to contract the disease), so they can be used regardless of the number of people vaccinated or the effectiveness of the different vaccines. There are three categories of risk (low, medium, and high) for these indicators, according to previous studies of different indoor scenarios and existing documented outbreaks, as it can be seen in Table 2 (Peng and Jimenez, 2021; Peng et al., 2022). For the Wild-type SARS-CoV-2, it can be considered that there are no documented outbreaks when AR was under 0.5% (Peng et al., 2022), which can be correlated with a value of Hr<0.001. Table 2. Limits for relative risk (Hr) and attack rate (AR) indicators (Peng and Jimenez, 2021) corrected for SARS-CoV-2 Omicron variant BA.2 sublineage. Low Medium High AR (%) < 0.5 < 5.0 Hr (h²/m³) for wild-type SARS-CoV-2 < 0.00100 < 0.01000 000 Corrected Hr (h²/m³) for Omicron variant BA.2 < 0.00035 < 0.00294 294 2.5. Calculation tool The simulation software used to evaluate the aforementioned infection risk indicators (AR and Hr) is COVID Riskairborne (https://www.covidairbornerisk.com/), developed by Campano et al. (Campano-Laborda et al., 2021). This tool (Figure 2) estimates the SARS-CoV-2 - (Jiménez Palacios and Peng, 2021; Peng and Jimenez, 2021; Peng et al., 2022) of the Wells-Riley model for simulating disease propagation (Rudnick and Milton, 2003). 34 Figure 2. Landing page of Covid Riskairborne tool. This methodology has been validated by comparison with existing COVID-19 outbreaks (Peng et al., 2022), as it can be seen in Figure 3. Figure 3. Graphic analysis of the Attack Rate (AR) versus the Relative risk of infection (Hr), calculated via COVID Riskariborne using the methodology of Peng et al. (Peng et al., 2022). 35 Among the various considerations made by this tool, it should be noted that: The increased transmissibility of the SARS-CoV-2 variants is obtained from the reports of the European and North American Centres for Disease Control and Prevention (Campbell et al., 2021; Centers for Disease Control and Prevention, 2022). The estimation of the airborne viral emission is performed through the expiratory activity, which depends on the metabolic and vocalization activities (Morawska et al., 2009; Buonanno, Stabile and Morawska, 2020). The evaluation of the average ventilation rate and the recommended short-term exposure values for inhalation, in m³/h per occupant, are calculated through the metabolic rate, which depends on activity, age and gender (Wang et al., 2011; Peng et al., 2022), as well as the CO2 emission (Persily and de Jonge, 2017). The decay rate of the virus infectivity in aerosols depends on the Air Temperature (Ta), Relative Humidity of the air (HR), the UV index and the deposition of virus-containing aerosols to surfaces (Schuit et al., 2020; Smither et al., 2020; van Doremalen et al., 2020). The theoretical aerosol retention efficiency of masks, respirators and face shields (Davies et al., 2013; Milton et al., 2013; Melikov, 2015) is considered as: Surgical mask (non-fitted): 32.5% Well-fitting N95 respirator: 90.0% 3. Results and discussion 3.1. Results The graphical evolution of Hr with respect to AR can be seen in Figure 4. Figure 4. Graphical analysis of the Attack Rate (AR) with respect to the Relative risk of infection (Hr) for the 4 case studies of the pre-school classroom. Exposure time of 135 minutes. The mean values of Hr and AR parameters are listed in Table 3 for the four cases under analysis, with respect to 2. 36 Table 3. Mean values of Attack Rate (AR) and Relative Risk of infection (Hr) of SARS-CoV-2 (Omicron BA.2) per case, based on indoor boundary conditions Case 1 Case 2a Case 2b Case 2c Average CO2 value Child - no masks Teacher - no masks Teacher - surgical mask Teacher – well-fitting N95 respirator Oral breathing Talking Speaking Speaking 2 (ppm) AR (%) Hr (h²/m³) AR (%) Hr (h²/m³) AR (%) Hr (h²/m³) AR (%) Hr (h²/m³) 1600 24.7 0.0160 92.5 0.1463 82.6 0.0988 22.8 0.0146 1500 23.8 0.0153 91.6 0.1399 81.2 0.0945 21.9 0.0140 1400 22.8 0.0147 90.5 0.1334 79.6 0.0900 21.0 0.0133 1300 21.8 0.0139 89.3 0.1266 77.9 0.0855 20.1 0.0127 1200 20.8 0.0132 87.9 0.1196 76.0 0.0807 19.1 0.0120 1100 19.8 0.0124 86.3 0.1123 73.8 0.0758 18.0 0.0112 1000 18.6 0.0117 84.3 0.1047 71.3 0.0707 16.9 0.0105 900 17.4 0.0108 82.0 0.0969 68.5 0.0654 15.7 0.0097 800 16.2 0.0100 79.1 0.0885 65.2 0.0598 14.5 0.0089 700 14.8 0.0091 75.6 0.0797 61.4 0.0538 13.1 0.0080 600 13.3 0.0081 71.2 0.0704 56.8 0.0475 11.7 0.0070 500 (IDA 2) 11.7 0.0070 65.7 0.0605 51.4 0.0408 10.1 0.0060 400 9.9 0.0059 58.5 0.0497 44.8 0.0336 8.4 0.0050 300 7.8 0.0046 49.1 0.0382 36.6 0.0258 6.5 0.0038 200 5.4 0.0032 36.4 0.0256 26.4 0.0173 4.4 0.0026 150 4.1 0.0024 28.5 0.0190 20.2 0.0128 3.3 0.0019 100 2.6 0.0015 19.1 0.0120 13.3 0.0081 2.1 0.0012 As can be seen both in Table 3 and in Figure 4, the relative infection risk (Hr) of almost all the situations studied is high. There are no situations with low risk, existing two categories: High risk (<25%): The primary infected occupant is a child, or is the teacher, who is wearing a well-fitting N95 respirator. Very high risk (>25%): The primary infected occupant is the teacher, who is wearing no mask or a surgical one (non-fitted). The graphical evolution of 2 with respect to AR can be seen in Figure 5. On the one hand, the hypotheses studied which have AR under 5% (threshold for high risk of outbreaks) are: One of the children is the infectious occupant which is sedentary, silent, and breathing orally and there is a low interior CO2 excess ( 2 150 ppm). The teacher is infectious occupant which is standing and speaking, being the only one wearing a well-fitting N95 respirator and there is a low interior CO2 excess ( 2 00 ppm). 37 Figure 5. Graphical analysis of the Attack Rate (AR) with respect to the average excess CO2level exhaled (2) for the 4 case studies of the pre-school classroom. Exposure time of 135 minutes. This 2value of 150 ppm agrees with the recommendations developed by Aireamos for indoor spaces with vulnerable occupants or with no masks. On the other hand, the proportion of occupants who can inhale a sufficient viral dose (AR) rises much more markedly with respect to 2when the primary infected occupant is the teacher. This is due to a higher to a greater emission of potentially virus-laden aerosols, both their increased vocalization activity and their increased metabolic rate (because of their age and weight). In this way, when the teacher was the primary infected occupant and was not wearing a well-fitting N95 respirator, there was no situation with AR under 20% but with 2100 ppm. When AR is analysed according to RITE threshold ( 2of 500 ppm), it can be seen that: If the infectious occupant is either one of the children, or the teacher (wearing a wellfitting N95 respirator): AR is 10-11%, doubling the admissible threshold. The teacher is infectious occupant, who either is wearing no mask or a non-fitted surgical one: AR is over 50-65%, 10-12 times the admissible threshold. 3.2. Study limitations The present study has the following limitations: It was developed through a set of simulations, despite the method was previously validated by comparison with existing COVID-19 outbreaks. Whilst it is not an epidemiological model, it can be used as a component of such approaches to estimate variations in aerosol propagation across a range of inputs. The model excludes droplet and contact/fomite transmission and assumes that 2 m (6 ft) social distancing is honoured. Otherwise, the infection rates calculated would be higher. Several parameters used in the model are uncertain, as they were estimated based on current knowledge. These simulations, of a statistical nature, simplify the existing problem by considering that the atmosphere in the classroom is uniformly distributed, so the results may differ slightly from real cases. The hypotheses proposed are conservative, since they are based on a maximum occupancy of the enclosure, in which there is also an infected person with a high viral 38