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. 2021 May 19;72:103031. doi: 10.1016/j.scs.2021.103031

Interactions of SARS-CoV-2 with inanimate surfaces in built and transportation environments

Hamid Ghasemi a, Hessam Yazdani a,*, Elham H Fini b, Yaghoub Mansourpanah c
PMCID: PMC9761300  PMID: 36570725

Graphical abstract

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Keywords: COVID-19, SARS-CoV-2, Surface transmission, Sustainable development, Resilient society, Fomites coronavirus

Abstract

Understanding the interactions and transmission of pathogens with/via inanimate surfaces common in the built environment and public transport vehicles is critical to promoting sustainable and resilient urban development. Here, molecular dynamics (MD) simulations are used to study the adhesion of SARS-CoV-2 (the causative agent of COVID-19) to some of these surfaces at different temperatures (same for surfaces and ambiance) ranging from −23 to 60 °C. Surfaces simulated are aluminum, copper, copper oxide, polyethylene (PE), and silicon dioxide (SiO2). Steered MD (SMD) simulations are also used to investigate the transfer of the virus from PE and SiO2 when a contaminated surface is touched. The virus shows the lowest and highest adhesions to PE and SiO2, respectively (20 vs 534 eV). Influence of temperature is not found to be noticeable. Using simulated water molecules to represent moisture on the skin, SMD simulations show that water molecules can lift the virus from the PE surface but damage the virus when lifting it from the the SiO2 surface. The results suggest that the PE surface is a more favorable surface to transmit the virus than the other surfaces simulated in this study. The results are compared with those reported in a few experimental studies.

1. Introduction

Public health and sustainable development are inextricably linked. In the case of the COVID-19 pandemic, strong associations have been observed between its morbidity and mortality rates and attributes of the built environment such as housing and building quality (Hu et al., 2021) that are themselves associated with other confounding factors such as ethnicity and income that have shaped the course of the pandemic (Maiti et al., 2021). As ongoing vaccinations and nonpharmaceutical interventions continue to reduce the immediate health consequences of the pandemic, calls for long-term structural changes to make cities safer and more sustainable, resilient, circular, intelligent, inclusive, and connected are growing louder. Examples of these changes include rethinking the use and management of urban activity centers and public spaces, infrastructure, and essential services; recalibrating existing transportation networks by creating spaces for micro-mobility of pedestrians and cyclists; and redefining outmoded hygiene and cleanliness standards (Lambert et al., 2020; Li et al., 2021; van den Berg et al., 2020). These changes will particularly be beneficial to marginalized residents (e.g. minorities and the people at the bottom of the socioeconomic spectrum) who rely on public transport and facilities and have disproportionally been affected by the pandemic and the like. They will also help address intersecting social and economic inequalities that have shaped the course of many pandemics (Wade, 2020).

Understanding the transmission modes of pandemic strains is the first step to the development and implementation of structural changes to cities and built and transportation environments to mitigate the spread of the strains. Although knowledge regarding the etiology, pathogenesis, and severity of COVID-19 has grown considerably since its outbreak in December 2019, there is still a lack of consensus regarding its transmission routes and their relative importance in different environments. The World Health Organization (WHO) and The Centers for Disease Control and Prevention (CDC) share a similar position in this regard, stating that the disease spreads mainly through direct or close contact, while not ruling out indirect transmission via contaminated fomites and airborne and aerosol transmissions in crowded, poorly ventilated enclosed spaces and specific settings (CDC, 2021; WHO, 2021).

While the literature lacks empirical studies on the transmission modes of COVID-19 among human populations, computational modeling and simulations have provided insight into the spread of SARS-CoV-2 (the causative agent of COVID-19, aka the novel coronavirus) and its interactions with the environment. For instance, computational fluid dynamics and physics-based modeling have been used to study the aerial transmission of the virus in urban buses (Zhang et al., 2021), airplanes (Desai, Sawant, & Keene, 2021), classrooms (Abuhegazy et al., 2020), rooms (Sun & Zhai, 2020), clinics (Zhou & Ji, 2021), and various indoor layouts (Vuorinen et al., 2020). However, while the surface transmission of the virus has been highlighted as a critical area for additional research related to the pandemic (Awada et al., 2021), to the best of the Authors’ knowledge, the nanoscale interactions of the virus with surfaces have been the subject of only one study where molecular dynamics simulations were used to understand the interactions of the virus with cellulose and graphite as materials with distinct properties that are widely used in adsorbents and filters (Malaspina & Faraudo, 2020). Cellulose is a hydrophilic and lipophilic material with a large number of hydrogen-bond donors and receptors that enable it to establish hydrogen bonding. Graphite is strongly lipophilic and mildly hydrophilic; therefore, it is unable to create hydrogen bonds and prone to strong hydrophobic interactions. The results indicated that cellulose adsorbed the binding domains (spike surface glycoprotein) of the virus in stable configurations without causing structural changes to them, whereas graphite induced substantial structural changes to the adsorbed proteins, suggesting graphite has the potential to inactivate the spike glycoproteins.

Only limited data on the survival of SARS-CoV-2 and its response to environmental stressors are available. This is because working with SARS-CoV-2 requires specially trained personnel working under BSL-3 laboratory containment conditions which poses significant challenges in studying the virus—BSL-3 (biosafety level 3) is appropriate for work involving infectious agents or toxins that can cause serious and potentially lethal disease via the inhalation route—In a laboratory study, Van Doremalen et al. (2020) showed that the virus remained viable for three hours in aerosols, four hours on copper, 24 h on cardboard, 48 h on plastic, and 72 h on stainless steel. Chin et al. (2020) investigated the stability of the virus on different surfaces at room temperature and relative humidity of around 65 % and reported that the virus remained stable on printing and tissue papers for three days, on treated wood and cloth for two days, on glass and banknote/bill for four days, and on stainless steel and plastic for seven days. A more recent study (Riddell et al., 2020) reported D values (time taken to achieve a 90 % reduction in titer) of 4.8 h to 9.1 days on stainless steel, polymer and paper bills, glass, cotton, and vinyl, depending on the temperature (20–40 °C). These reports, however, have been criticized for using excessive inoculum that has little resemblance to real-life scenarios and for “exaggerating” the risk of transmission by fomites (Goldman, 2020). Given that 80 % of infectious diseases are transmitted via contaminated surfaces (Megahed & Ghoneim, 2020), further research is needed to understand the adhesion mechanisms of the coronavirus and its affinity for different surfaces, and the potential to pick up the virus from casual contact.

This paper reports the results of an extensive series of molecular dynamics simulations that were carried out to quantify the affinity of the virus for different materials that are common in built and transportation environments. The study outcomes combined with parallel efforts to contain the pandemic will help researchers, policy-makers, and other stakeholders in several ways. They will 1) provide insights into plausible infectious disease transmission pathways and how the environmental conditions (e.g. temperature) mediate transmission, 2) inform the formation and implementation of economically and socially sustainable nonpharmaceutical strategies to reduce the spread of respiratory diseases (Rahmani & Mirmahaleh, 2021), 3) help strike a balance between personal hygiene care and long-term community preferences regarding shared mobility and restore trust in public transport (Shokouhyar et al., 2021), 4) quantify the vulnerability of spaces and surfaces to SARS-CoV-2 contamination, for triaging their sanitization, especially in shelters for the homeless and the housing insecure as well as in fast-growing slums or informal settlements, which host over one billion people, particularly in Eastern and South-Eastern Asia, sub-Saharan Africa, and Central and Southern Asia (UN Statistics Division, 2020), 5) relate the chemistry of inanimate surfaces to viral adhesion, 6) provide insight into engineering an “antivirus built environment” (Megahed & Ghoneim, 2020), and 7) steer the design of innovative broad-spectrum antiviral/antimicrobial materials for construction, manufacturing, and personal protective equipment (PPE, e.g. more effective masks) that will not only mitigate the risk of transmission, but also reduce the use of disposable PPE, in turn promoting the preservation of resources and the creation of sustainable urban environments and healthcare systems (McGain et al., 2021).

2. Atomistic simulations

2.1. Molecular dynamics (MD) technique

MD is a simple yet powerful simulation technique in computational statistical mechanics that is used to study the temporal evolution (fluctuations and conformational changes) of atomistic and molecular systems over short time scales. It is a modern manifestation of an old idea in science that asserts that the equilibrium and motion of an interacting multi-constituent system can be computed if the initial and boundary conditions of the system and the interactions among its constituents are known. The interactions are defined by the potential function and are used to calculate the energy of the system. An MD simulation begins from an initial state under a set of thermodynamic constraints defined by ensembles and proceeds step by step where in each step the classical equations of motion are solved to update the energy of the system, calculate forces on the constituents, and derive the properties of the system and build its trajectory (Rapaport, 2004). MD simulations can handle a broad range of complexity at the nano- and micro-scales and provide insight into nanoscopic and microscopic phenomena that would otherwise remain unobserved or poorly understood if conventional laboratory characterization techniques were used. Although MD simulations typically reproduce macro- and continuum-scale trends observed in the laboratory, their results often shift to some degree from experimental results. Such discrepancies are due to several factors such as size effect, failure to fully represent defects in laboratory specimens, and the inaccuracy of the potential functions used, among others, as discussed by the Authors elsewhere (Yazdani et al., 2019). Also, demanding computational costs of MD simulations bounds their applicability to length and time scales in the order of nanometers and nanoseconds.

2.2. Details of MD simulations carried out in this study

MD simulations were used in this study to investigate the interactions of the SARS-CoV-2 spike glycoprotein (S) with the surface of each material listed in Table 1 . The virus uses its S glycoprotein to bind to the host cells and interact with surfaces. The materials studied are some of the most common materials in built and transportation environments: silicon dioxide (silica – SiO2) is found in concrete and glass, which is used in high-touch devices such as smartphones, bank ATMs, supermarket self-checkout machines, and airport check-in kiosks; copper (Cu), cupric oxide (CuO), and aluminum (Al) are typical materials for faucets, doorknobs, kitchen sinks, elevator control panels, and bus and train handrails/handholds; and polyethylene (PE) is a representative of polymers used in making products such as toilet seats, electrical outlets and wall panels, water pipes, sanitary ducts, and bus and train safety straps and seats—it should be noted that many materials are produced in composite form to achieve desirable properties beyond what would otherwise be possible using their constituents alone (Yazdani et al., 2016). However, given the wide range of compositions that composites feature, their properties would be in a wide range spanning those of their constituents in pure form. Therefore, the materials included in this study were assumed to be in either pure or oxide form—Temperatures of −23, 17, 27, and 37 °C (250, 290, 300, and 310 K, respectively) were used to represent land surface temperatures in most cold and hot regions (The NASA Earth Observatory, 2021) and temperatures in meat processing and cold food storage facilities and cover typical fluctuations in room temperature (Melikov et al., 1997). A higher temperature of 60 °C (333 K) was also considered which was piloted by Ford Motor Company to decontaminate its Police Interceptor Utility in March 2020 (Ford, 2020). The materials were modeled as a thin film whose in-plane dimensions were selected based on the lateral extent of the virus and the unit cell of the material. Periodic boundary conditions were applied in the in-plane directions of the films. In the thickness direction, the films comprised three layers made of the same material: 1) a 5 Å-thick “frozen” (i.e. absolute zero) layer at the bottom of the film to prevent the movement of the film, 2) a >10 Å top layer that interacted with the spike protein, and 3) a middle 5 Å layer as a thermostat to avoid any energy exchange between the frozen layer and the spike protein due to temperature difference. The virus was positioned at an initial distance of at least 0.3 nm above each film and then allowed to interact with the film until the energy of the system plateaued after 0.1–1.5 ns, depending on the surface material, indicating equilibrium. Time steps of 0.5 fs were used in all simulations. The intra-actions of the films were represented by the potential functions listed in Table 1. The CHARMM force field (MacKerell et al., 1998) was used to update the trajectory of the virus in each time step, and the Lorentz-Berthelot rules were used to calculate interaction energies between nonbonded atoms. The model proposed by Xia et al. (RCSB Protein Data Bank, 2020; Xia et al., 2020) was adopted to represent the virus (Fig. 1 ). The simulations were carried out with the software LAMMPS (Plimpton, 1995), and each case was simulated three times with different seed numbers to account for randomness.

Table 1.

Surfaces used in this study, with their corresponding potential functions and dimensions.

Surface Potential function Dimensions (nm)
Aluminum (Al) EAM/alloy (Cai & Ye, 1996) 14.2 × 14.3 × 2.3
Copper (Cu) COMB3 (Liang et al., 2013) 13.9 × 13.9 × 2.6
Copper oxide (CuO) COMB3 (Liang et al., 2013) 14.4 × 14.3 × 2.3
Polyethylene (PE) Combinations of harmonic potential functions for bonding, bending, torsion, and vdW (Zhang et al., 2013) 14.5 × 14.6 × 2.4
Silicon dioxide (SiO2) Tersoff (Munetoh et al., 2007) 14.6 × 14.6 × 2.2
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Fig. 1.

Fig. 1

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Graphic representation of the S-protein structure in the SARS-CoV-2 model used in this study (RCSB Protein Data Bank, 2020; Xia et al., 2020).

Steered molecular dynamics (SMD) simulations were also carried out to investigate the fomite-to-finger transfer of the virus and the mechanisms associated with that for the surfaces that exhibited the weakest affinity (PE) and strongest affinity (SiO2) for the virus, as explained later. The PE and SiO2 films were modeled as previously described. Fingertips were modeled by a layer of water representing moisture/sweat on the skin because human fingertips secrete moisture from the sweat pores when the nerves in the fingers sense the hardness of a surface (Dzidek et al., 2017). The water layer was 13 nm × 13 nm × 0.7 nm containing 4000 water molecules modeled by TIP4P (Jorgensen et al., 1983) and was initially positioned 1 nm above the virus, which was deposited on the film. The SMD simulations were carried out at room temperature (27 °C) and pressure of 1 atm. Following equilibrium, the water molecules were pulled up at a speed of 10 m/s to simulate the detachment of fingertips while recording the force-displacement data and associated trajectories.

3. Results and discussion

The binding energy of the virus to each surface considered in this study is shown in Fig. 2 , and representative snapshots of their configurations at different temperatures are shown in Fig. 3 (also see Supplementary Movies 1–5 for PE, Cu, Al, CuO, and SiO2 at 27 °C, respectively). The results for binding energy indicate that the virus has the lowest affinity for PE. This can be explained by the hydrophobicity of PE which leaves a relatively lower number of binding sites (and in turn leads to weaker interactions) for moieties of S glycoproteins anchored in the lipid envelope to become adsorbed to the surface. This explanation is consistent with the configuration that the virus adopts in contact with PE (Fig. 3). The maximum adhesion for the virus was observed to be to SiO2. This observation can be attributed to the large number of hydrogen-bond donors and receptors on the SiO2 surface that enable it to establish hydrogen bonding with the virus’s S glycoproteins (Fig. 3). The virus has been observed to be more stable on plastic and stainless steel than on copper and cardboard (Suman et al., 2020; van Doremalen et al., 2020) and glass and bills (Chin et al., 2020). This limited laboratory evidence corroborates our findings considering the negative association between the stability of pathogens and their adhesion (binding energy) to surfaces—high binding energies disrupt the structure of pathogens, shortening their stability (Sibilo et al., 2020).

Fig. 2.

Fig. 2

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Binding energy of the virus to various surfaces at different temperatures. The error bars indicate one standard deviation from the mean of three independent simulations.

Fig. 3.

Fig. 3

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At-rest configurations of the virus on different surfaces and at different temperatures. The color bar denotes the z-position of the virus species relative to the surfaces.

The virus showed weaker binding to Cu surfaces compared with its oxide counterpart, CuO. This observation could be due to the presence of oxygen atoms on the surface of the metal oxides that serve as additional sites for strong binding with S glycoproteins.

The influence of temperature was not noticeable except with Cu where higher binding energies are seen to be associated with higher temperatures. This could be explained by the thermally-assisted rearrangement and reorientation of the virus residues over the surface at high temperatures, which lead to greater accessibility to binding sites. The stability of the virus, however, has been reported to be sensitive to heat, with the time for virus inactivation to reduce from 14 days to 5 min. as temperature increased from 4 °C to 70 °C (Chin et al., 2020). A similar trend has been observed in studies on the survival of the virus in meat processing and cold food storage facilities (Fisher, Reilly, Zheng, Cook, & Anderson, 2020; Riddell et al., 2020).

Results of the SMD simulations (Fig. 4 ) show that, as expected, the force required to detach the virus from a surface increases with binding energy. Trajectories of the simulations at different steps during the lifting stage show the mechanisms involved in the detachment of the virus. In the case of PE, the water molecules completely surrounded the virus and detached it from the surface without causing any visible disintegration in its structure (Supplementary Movie 6). In contrast, the strong adhesion of the virus to the SiO2 surface provided resistance against the pull-up force, causing a rupture in the structure of the virus (Supplementary Movie 7). These results suggest that plastic surfaces are more likely to transmit the virus than the other surfaces simulated.

Fig. 4.

Fig. 4

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Detachment response of the virus from PE and SiO2 surfaces.

4. Conclusion

Using molecular dynamics simulations of SARS-CoV-2, the causative agent of COVID-19, this study investigated the virus’s binding energy to the surfaces of several materials commonly found in the built environment and the virus’s detachment from two of these materials, polyethylene (PE) and silica (SiO2). Snapshots of the simulations showed that the virus adopted different configurations in response to its interactions with the surfaces and the temperatures applied. The virus exhibited its lowest adhesion to PE, attributed to the hydrophobicity of PE. The virus exhibited its highest adhesion to SiO2, attributed to the large number of sites available on the surface of SiO2 for the adsorption of spike glycoproteins anchored in the lipid envelope of the virus. The low affinity of the virus for PE provided favorable conditions for water molecules representing moisture on the skin to lift the virus from the PE surface, suggesting that infected plastics are most likely to transmit the coronavirus. The high affinity of the virus for SiO2 led to damage to the virus when water molecules lifted the virus from the SiO2 surface.

The results of this study provided insights into how surfaces and environmental conditions (e.g. temperature) mediate transmission of the virus. They also suggest that plastic surfaces are more vulnerable to the coronavirus contamination and should be prioritized for sanitization in resource-stressed settings such as shelters for the homeless and the housing insecure and informal settlements. The simulations conducted in this study can be extended and used to design novel broad-spectrum antiviral/antimicrobial coating materials that can be designed to contain the virus and mitigate its further spread, in turn helping the development of sustainable and resilient urban systems and communities.

The present study did not consider the stability and viability of the virus on inanimate surfaces. Further research is also necessary to understand factors such as porosity and surface roughness, which become substantial at larger length scales (Guo et al., 2020), and surface chemistry on the interactions of the virus with surfaces. Until validated empirical evidence regarding transmission routes of COVID-19 becomes available, caution is advised in the interpretation and use of the results reported in this study and similar studies.

Declaration of Competing Interest

The authors report no declarations of interest.

Acknowledgments

Some of the computing for this project was performed at the OU Supercomputing Center for Education & Research (OSCER) at the University of Oklahoma (OU). The authors also acknowledge Research Computing at Arizona State University for providing HPC resources that have contributed to the research results reported within this paper.

Footnotes

Appendix A

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.scs.2021.103031.

Appendix A. Supplementary data

The following are Supplementary data to this article:

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