Increased airborne transmission of COVID-19 with new variants, implications for health policies

Abstract

New COVID-19 variants, either of higher viral load such as delta or higher contagiousness like omicron, can lead to higher airborne transmission than historical strains. This paper highlights their implications for health policies, based on a clear analytical understanding and modeling of the airborne contamination paths, of the dose following exposure, and the importance of the counting unit for pathogens, itself linked to the dose-response law. Using the counting unit of Wells, i.e. the quantum of contagium, we develop the conservation equation of quanta which allows deriving the value of the quantum concentration at steady state for a well-mixed room. The link with the monitoring concentration of carbon dioxide is made and used for a risk analysis of a variety of situations for which we collected CO₂ time-series observations. The main conclusions of these observations are that 1) the present norms of ventilation, are both insufficient and not respected, especially in a variety of public premises, leading to high risk of contamination and that 2) air can often be considered well-mixed. Finally, we insist that public health policy in the field of airborne transmission should be based on a multi parameter analysis such as the time of exposure, the quantum production rate, mask wearing and the infector proportion in the population in order to evaluate the risk, considering the whole complexity of dose evaluation. Recognizing airborne transmission requires thinking in terms of time of exposure rather than in terms of proximal distance.

Keywords: Adequacy and respect of standards; Airborne transmission; COVID-19; Health policies; Indoor ventilation; Infectious risk assessment.

Fig. 1

δ probability of airborne infection versus initial strain for a ratio of VL in respiratory fluids of 10 and 100 (all other parameters being equal).

Fig. 2

Probability of infection contours as a function of time of exposure and ventilation rate per person, assuming a quantum rate of 40 h⁻¹, an expiratory rate of 0.50 m³/h and an infector proportion of 0.01.

Fig. 3

Probability of infection when the ventilation is poor (see 2.5). Calculations are made using an expiratory rate of 0.50 m³/h; a quantum rate of 40 h⁻¹; an infector proportion of 0.01 and a room volume of 150 m³ typical of a lecture room.

Fig. 4

CO₂ time evolution within examples of indoor spaces – complementary information are given in Table 1: (a) two lecture rooms (ULR5 and ULR20); (b) two lecture halls (UAE and UAW); (c) schoolroom over one week, L: Lunch, P: Playtime; (d) restaurant over a week (numbers close to the CO₂ peaks represent the strength of the wind in Beaufort scale, LP: Lunch Peak).