Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Jul 1;5(4):e00441-20.
doi: 10.1128/mSphere.00441-20.

Increasing Temperature and Relative Humidity Accelerates Inactivation of SARS-CoV-2 on Surfaces

Affiliations

Increasing Temperature and Relative Humidity Accelerates Inactivation of SARS-CoV-2 on Surfaces

Jennifer Biryukov et al. mSphere. .

Abstract

Coronavirus disease 2019 (COVID-19) was first identified in China in late 2019 and is caused by newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Previous studies had reported the stability of SARS-CoV-2 in cell culture media and deposited onto surfaces under a limited set of environmental conditions. Here, we broadly investigated the effects of relative humidity, temperature, and droplet size on the stability of SARS-CoV-2 in a simulated clinically relevant matrix dried on nonporous surfaces. The results show that SARS-CoV-2 decayed more rapidly when either humidity or temperature was increased but that droplet volume (1 to 50 μl) and surface type (stainless steel, plastic, or nitrile glove) did not significantly impact decay rate. At room temperature (24°C), virus half-life ranged from 6.3 to 18.6 h depending on the relative humidity but was reduced to 1.0 to 8.9 h when the temperature was increased to 35°C. These findings suggest that a potential for fomite transmission may persist for hours to days in indoor environments and have implications for assessment of the risk posed by surface contamination in indoor environments.IMPORTANCE Mitigating the transmission of SARS-CoV-2 in clinical settings and public spaces is critically important to reduce the number of COVID-19 cases while effective vaccines and therapeutics are under development. SARS-CoV-2 transmission is thought to primarily occur through direct person-to-person transfer of infectious respiratory droplets or through aerosol-generating medical procedures. However, contact with contaminated surfaces may also play a significant role. In this context, understanding the factors contributing to SARS-CoV-2 persistence on surfaces will enable a more accurate estimation of the risk of contact transmission and inform mitigation strategies. To this end, we have developed a simple mathematical model that can be used to estimate virus decay on nonporous surfaces under a range of conditions and which may be utilized operationally to identify indoor environments in which the virus is most persistent.

Keywords: COVID-19; SARS-CoV-2; contamination; coronavirus; fomite; half-life; humidity; temperature; transmission.

PubMed Disclaimer

Figures

FIG 1
FIG 1
Impact of droplet size, surface type, temperature, and relative humidity on SARS-CoV-2 decay. SARS-CoV-2 or fluorescently labeled polystyrene latex (PSL) beads were diluted 1:10 in simulated saliva, and then droplets (1, 5, or 50 μl) were deposited onto stainless steel (SS), acrylonitrile butadiene styrene (ABS) plastic, or nitrile glove (NG) coupons and incubated within an environmentally controlled chamber. During each experiment, three virus test coupons and one PSL bead coupon were chosen randomly at various time points over a period of 48 h. Both virus and PSL beads were recovered by resuspension into culture medium and then either quantified by a cell-based infectivity assay on Vero cells to determine the median tissue culture infectious dose (TCID50/ml) or assayed for fluorescence with a multimode plate reader. The mean half-life estimates (measured in hours) for SARS-CoV-2 in simulated saliva under each set of conditions were derived from fitting a generalized linear model with a normal distribution and identity link function to infectivity data from each trial over time. (A) Representative data comparing SARS-CoV-2 infectivity (TCID50/ml) and PSL microsphere relative fluorescence units (RFU) across a range of temperature and RH conditions. Data from six of the trials are shown where 5-μl droplets were deposited onto stainless steel. Red horizontal dashed lines indicate the lower limit of detection for the TCID50 assay (0.2 log10 TCID50/ml). Error bars indicate standard deviations for each time point. (B) Estimated virus half-life on different surfaces from all 32 trials across a range of a droplet sizes, temperatures, and relative humidities. Individual half-life estimates are shown as points, and the mean half-life value for each surface is indicated by a horizontal line. (C and D) Comparisons of virus half-life estimates among various RH (20 to 80%) conditions (C) and temperature (24 and 35°C) and RH (20 to 80%) conditions (D). Bars represent means of results from each group, and error bars indicate standard deviations. Statistical significance (P < 0.05) is indicated by brackets and asterisks (*). A one-way ANOVA and a Student’s t test were used to calculate the data presented in panels C and D, respectively.
FIG 2
FIG 2
Temperature and humidity response model for SARS-CoV-2 decay. (A) Using empirically determined estimates of SARS-CoV-2 half-life data collected under various temperature and RH conditions (24 to 35°C, 20 to 60% RH), a regression analysis was performed to determine a predictive decay model. The equation shown, where xT is temperature (°C) and xRH is percent RH, can be used to estimate half-life (t1/2) (in hours) for SARS-CoV-2 on stainless steel, ABS plastic, or nitrile glove rubber within the range of environmental conditions tested in this study. Actual half-life data are plotted against predicted half-life estimates. The mean of all data is indicated by a horizontal blue line. The regression fit line is shown in red. The shaded region indicates the 95% confidence interval of the regression fit line. RMSE, root mean square error. (B) Contour plot representing the predicted estimates of SARS-CoV-2 half-life data in simulated saliva on stainless steel, ABS plastic, or nitrile rubber as a function of temperature and RH.

References

    1. Chia PY, Coleman KK, Tan YK, Ong SWX, Gum M, Lau SK, Lim XF, Lim AS, Sutjipto S, Lee PH, Son TT, Young BE, Milton DK, Gray GC, Schuster S, Barkham T, De PP, Vasoo S, Chan M, Ang BSP, Tan BH, Leo YS, Ng OT, Wong MSY, Marimuthu K, Singapore Novel Coronavirus Outbreak Research Team. 2020. Detection of air and surface contamination by SARS-CoV-2 in hospital rooms of infected patients. Nat Commun 11:2800. doi:10.1038/s41467-020-16670-2. - DOI - PMC - PubMed
    1. Guo Z-D, Wang Z-Y, Zhang S-F, Li X, Li L, Li C, Cui Y, Fu R-B, Dong Y-Z, Chi X-Y, Zhang M-Y, Liu K, Cao C, Liu B, Zhang K, Gao Y-W, Lu B, Chen W. 2020. Aerosol and surface distribution of severe acute respiratory syndrome coronavirus 2 in hospital wards, Wuhan, China, 2020. Emerg Infect Dis 26 doi:10.3201/eid2607.200885. - DOI - PMC - PubMed
    1. Ong SWX, Tan YK, Chia PY, Lee TH, Ng OT, Wong MSY, Marimuthu K. 2020. Air, surface environmental, and personal protective equipment contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a symptomatic patient. JAMA 323:1610–1612. doi:10.1001/jama.2020.3227. - DOI - PMC - PubMed
    1. Wu S, Wang Y, Jin X, Tian J, Liu J, Mao Y. 2020. Environmental contamination by SARS-CoV-2 in a designated hospital for coronavirus disease 2019. Am J Infect Control doi:10.1016/j.ajic.2020.05.003. - DOI - PMC - PubMed
    1. Ye G, Lin H, Chen L, Wang S, Zeng Z, Wang W, Zhang S, Rebmann T, Li Y, Pan Z, Yang Z, Wang Y, Wang F, Min Qian Z, Wang X. 2020. Environmental contamination of SARS-CoV-2 in healthcare premises. J Infect doi:10.1016/j.jinf.2020.04.034. - DOI - PMC - PubMed

Publication types

MeSH terms

LinkOut - more resources