Next Article in Journal
Geometric Mean Serum Cotinine Concentrations Confirm a Continued Decline in Secondhand Smoke Exposure among U.S. Nonsmokers—NHANES 2003 to 2018
Previous Article in Journal
Purpose in Life in Older Adults: A Systematic Review on Conceptualization, Measures, and Determinants
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Sponge Whirl-Pak Sampling Method and Droplet Digital RT-PCR Assay for Monitoring of SARS-CoV-2 on Surfaces in Public and Working Environments

by
Davide Cardinale
1,†,
Maria Tafuro
1,†,
Andrea Mancusi
2,
Santa Girardi
2,
Federico Capuano
2,
Yolande Thérèse Rose Proroga
2,
Federica Corrado
1,
Jacopo Luigi D’Auria
1,
Annachiara Coppola
1,
Giuseppe Rofrano
1,
Palmiero Volzone
1,
Pio Galdi
1,
Sabato De Vita
1,
Alfonso Gallo
1,
Elisabetta Suffredini
3,
Biancamaria Pierri
1,*,
Pellegrino Cerino
1 and
Maria Morgante
4
1
Centro di Referenza Nazionale per l’Analisi e Studio di Correlazione tra Ambiente, Animale e Uomo, Istituto Zooprofilattico Sperimentale del Mezzogiorno, Via Salute n. 2, 80055 Portici, Italy
2
Department of Food Security Coordination, Istituto Zooprofilattico Sperimentale del Mezzogiorno, Via Salute n. 2, 80055 Portici, Italy
3
Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità, Viale Regina Elena, 299, 00161 Rome, Italy
4
Azienda Sanitaria Locale Avellino, 83100 Avellino, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2022, 19(10), 5861; https://doi.org/10.3390/ijerph19105861
Submission received: 14 March 2022 / Revised: 5 May 2022 / Accepted: 8 May 2022 / Published: 11 May 2022

Abstract

:
The SARS-CoV-2 can spread directly via saliva, respiratory aerosols and droplets, and indirectly by contact through contaminated objects and/or surfaces and by air. In the context of COVID-19 fomites can be an important vehicle of virus transmission and contribute to infection risk in public environments. The aim of the study was to analyze through surface sampling (sponge method) the presence of SARS-CoV-2 in public and working environments, in order to evaluate the risk for virus transmission. Seventy-seven environmental samples were taken using sterile sponges in 17 animal farms, 4 public transport buses, 1 supermarket and 1 hotel receptive structure. Furthermore, 246 and 93 swab samples were taken in the farms from animals and from workers, respectively. SARS-CoV-2 detection was conducted by real-time RT-PCR and by digital droplet RT-PCR (dd RT-PCR) using RdRp, gene E and gene N as targets. None of the human and animal swab samples were positive for SARS-CoV-2, while detection was achieved in 20 of the 77 sponge samples (26%) using dd RT-PCR. Traces of the RdRp gene, gene E and gene N were found in 17/77 samples (22%, average concentration 31.2 g.c./cm2, range 5.6 to 132 g.c./cm2), 8/77 samples (10%, average concentration 15.1 g.c./cm2, range 6 to 36 g.c./cm2), and in 1/77 (1%, concentration 7.2 g.c./cm2). Higher detection rates were associated with sampling in animal farms and on public transport buses (32% and 30%) compared to the supermarket (21%) and the hotel (no detection). The result of the study suggests that the risk of contamination of surfaces with SARS-CoV-2 increases in environments in which sanitation strategies are not suitable and/or in highly frequented locations, such as public transportation. Considering the analytical methods, the dd RT-PCR was the only approach achieving detection of SARS-CoV-2 traces in environmental samples. Thus, dd RT-PCR emerges as a reliable tool for sensitive SARS-CoV-2 detection.

1. Introduction

On 31st December 2019, Chinese health authorities reported a number of unusual cases of pneumonia of unknown origin to the World Health Organization (WHO) in the town of Wuhan, Hubei Province, China [1]. Most of the cases were epidemiologically associated with a market of live animals (Huanan South China Seafood Market), suggesting a possible zoonotic origin (transmission from animals to humans [2]). On 7 January 2020, a new beta-coronavirus was detected through the use of unbiased sequencing in samples from patients with pneumonia. Subsequently, the Chinese authorities reported the identification of a new virus belonging to the same coronavirus family as “Severe Acute Respiratory Syndrome Coronavirus 2” (SARS-CoV-2) [3]. Because of the rapid spread of the virus, on 11 February 2020, the World Health Organization (WHO) and the local Chinese authorities announced that a human-to-human transmission had occurred. On 11 March 2020, the WHO declared the COVID-19 outbreak a global pandemic [4]. Epidemiological data suggest that SARS-CoV-2 can spread directly via saliva, respiratory aerosol and droplets, and indirectly by contact through contaminated objects and/or surfaces. The person-to-person spreading of SARS-CoV-2 occurs mainly through respiratory droplets, which a patient expels when coughing, sneezing, or speaking. The SARS-CoV-2 virus is able to remain intact in droplets suspended in the air for up to three hours [5,6,7]. Beside direct transmission through the contact between mucous membranes (mouth, eyes, nose) and infected droplets, SARS-CoV-2 can infect humans indirectly, when hands come to contact with mucosae after touching an infected person or contaminated objects [8]. As underlined by Kraay et al. (2018), the fomites have a crucial role as potential transmission vehicles of respiratory viruses or other pathogens [9,10]. In particular, the transmission mediated by fomites depends on behavioural factors (i.e., hand hygiene practices), on the physical environment (i.e., factors affecting virus viability) and on the type of surfaces that may undergo contamination. The dynamics in fomites contamination and transmission appear to be very complex as it involves multiple variables.
Studies conducted over the last two years, indeed, highlighted the impact of factors such as temperature, surface porosity, relative humidity, air drying, and direct light on SARS-CoV-2 infectivity retention, either on surfaces or in air [11,12,13,14,15,16]. In addition to this, the different persistence of the virus on surfaces of different natures (plastic, cardboard, metal, etc.) have been assessed [17,18,19,20] and predictive tools and mathematical models have been developed to calculate virus decay on surfaces based on multiple factors [21]. In the course of the COVID-19 pandemic, fomites have been considered a relevant vehicle of virus transmission, contributing to the risk of infection in public environments such as schools, long-term care facilities and hospitals [22,23,24,25]. In this context, several studies have addressed the detection of SARS-CoV-2 on inanimate surfaces in close contact with COVID-19 patients, either in hospital and healthcare settings [26,27,28,29], in households and isolation rooms [30,31,32] or in specific settings such as a cruise ship during outbreak events [33]. Less investigated, on the contrary, has been the presence of SARS-CoV-2 (either genome or infectious virus) in public spaces or in other working environments. A study performed by Silva and colleagues (2021) [34] on public urban areas in Recife, Brazil showed high positivity rates in public transportation terminals (>50%), public parks, supply centers, and markets, with toilets, bancomat, handrails, playgrounds, and other highly touched public surfaces being frequently positive for SARS-CoV-2. Similarly, sampling on public urban surfaces (crosswalk buttons, trash can handles, door handles of essential commercial services such as grocery shops, banks, gas stations, etc.) in Somerville, Massachusetts, USA between March and June 2020, achieved the detection of SARS-CoV-2 in 8.3% of samples [35] and sampling in playgrounds and on water fountains in six cities in Israel in August 2020 showed the presence of viral genome in ~4% of the samples [36]. Detection of SARS-CoV-2 genetic material on public transportation has also been addressed by several authors, with results ranging from a 17% positivity rate in transports in Quito, Ecuador [37] to 43% in Barcelona, Spain [38]. In Italy, a first study on public transportation was performed in the city of Chieti (Abruzzo region, central Italy) in May 2020 with no detection of SARS-CoV-2 RNA on surfaces [39], but a more extensive assessment of SARS-CoV-2 deposition on surfaces in public places/services has been performed in the region of Apulia, where virus presence has been investigated in supermarkets (detection in 4.3% of samples), public transportation, such as trains and buses (10.7% of positive results), and tourist recreational facilities (virus detection in 6% of swabs) [40,41,42], but no data are available for other kind of environments and for other areas of the country. These studies consider public transportation in urban areas (with high population density conditions). Moreover, the observed differences in the percentage of positivity rate could also depend on (i) the time when the study was conducted (i.e., during the first wave of contagion, March–April 2020, Italian public transportation were not frequented and, with major turnout in northern Italy rather than southern); (ii) the levels of viruses spreading at the time of surfaces sampling; (iii) the different design of the study, including the samples collection methods. Considering the analytical aspect, the current gold standard for the detection and diagnosis of SARS-CoV-2 infection is based on the real-time RT-PCR. The low levels of virus contamination are the main obstacles for the application of RT-PCR for the detection of viruses on surfaces. Furthermore, sensitivity of the method is not always enough to detect the low viral concentration. Droplet digital PCR (ddPCR) is an alternative PCR method that allows absolute quantification and is more precise than standard PCR. These properties make ddPCR a promising SARS-CoV-2 detection method for samples with low template.
The purpose of the present study was to investigate the presence of SARS-CoV-2 RNA on surfaces of widely different environments: (I) two types of public environments, buses for public transportation and a supermarket; (II) a receptive structure involved in a SARS-CoV-2 outbreak associated to a wedding party; (III) 17 farms in the territory of the Campania region chosen based on the detection of a SARS-CoV-2 infection among the employees.
We focused our attention on disparate environments, and the criteria of selection was based on the perceived risks (no medical areas, but highly frequented work environments without standard protocol of biohazard management for SARS-CoV-2 pandemic).

2. Materials and Methods

2.1. Sampling

Sampling was carried out between 14 August 2020 and 14 April 2021 in 17 farms, 4 public transportation buses, 1 supermarket and 1 hotel receptive structure distributed in the territory of the Campania region (Figure 1).
Farm sites were chosen due to connection to a previously notified case of SARS-CoV-2, involving either employees or visitors. For 6 of the 17 farms investigated, in the two months preceding sampling, five COVID-19 cases (and two fatalities) were reported in workers (one of them being a regular visitor of two farms). Based on available records, farms were managed in agreement with legislation on hygiene, animal welfare and biocontainment (where relevant), but no specific protocol besides general hygiene, distancing and face mask rules was implemented for SARS-CoV-2 in these working environments. The 17 animal farms included: buffaloes (n = 4), cattle (n = 1), goats and cattle (n = 1), goats (n = 2), hens (n = 2), horses (n = 2), pigs (n = 3), pigeons (n = 1), and rabbits (n = 1), and sampling points included milking parlor surfaces, barkers, stable walls.
The 4 public transportation buses and the supermarket were subjected to daily sanitization practices, in agreement with recommendations implemented during the COVID-19 epidemic, and sampling was performed after cleaning and before the service. Sampling points on public transportation buses included handrails, stop request buttons, walls, handles, holding supports, stamping machines, etc., and trolley and cart handles, fridge/freezer handles, weighing scales, card readers, etc. in the supermarket.
Finally, the hotel receptive structure—also operating under the guidelines for SARS-CoV-2 transmission containment—was included in the study following its involvement in a SARS-CoV-2 outbreak (20 cases infected during a wedding party) and the environmental sampling of the surfaces bar countertop, tap, kitchen table, fridge and table, dining room tables was carried out one week after the event and after sanitization.
Sponge swipe was conducted using a 3.8 × 7.6 × 1.5 cm sterile sponge (VWR International, Radnor, PA, USA) moistened with sterile peptone water (LabRobot products, Stenungsund, Sweden). During the sampling procedure, the area to be sampled (100 cm2) was identified, the bag containing the dehydrated sponge was opened and 10 mL of diluent was added to hydrate the sponge. Subsequently, the sponge was vigorously swiped on the previously defined area, first with horizontal and then with vertical movements. At the end of sampling, the sponge was placed back in its own bag, sealed by rolling the upper edge several times and placed in an insulated container equipped with dry ice packs. Transport to the laboratory for analysis was completed as soon as possible and in any case within 24 h of sampling.
To better understand the role of the environment in potential virus transmission in a complex environment such as an animal farm, each environmental (sponge) sampling was associated with sampling on human subjects (workers of the farms) and on animals. For the humans, nasopharyngeal swabs were performed, under the authorization of the GENCOVID study protocol “Health surveillance for the SARS-CoV-2 virus, responsible of COVID-19 pandemic in high-risk population or in people in direct contact with positive patients” (approved by the ethics committee of University of Naples “Federico II”, approval n° 141/20). For animals, either nasopharyngeal (buffaloes, pigs, rabbits, horses, goats, cattle) or oropharyngeal (hens and pigeons) swabs were performed. Both human and animal samplings were performed using the Copan UTM-RT system (Universal Transport Medium for Viruses) with FLOQSwabs (Copan Diagnostics, CA, USA). Samples were transported to the laboratory with triple packaging under controlled temperature (4 °C).
Overall, a total of 77 environmental samples (sponge—S), 246 animal swabs (AS) and 93 human swabs (HS) (Table 1) were taken, divided as follows: 12 AS, 2 HSand 10 S in the province of Naples, 97AS, 39HSand 13 S in the province of Caserta, 100AS, 44HSand 51 S in the province of Salerno, 16AS, 6HSand 1 S in the province of Benevento, 21AS, 2 HSand 2 S in the province of Avellino.

2.2. Nucleic Acids Extraction

For nucleic acids extraction from environmental samples, 20 mL Proteinase K solution (100 µg mL−1) (Qiagen, Hilden, Germany) were added to sponge bags. Extraction efficiency was monitored by the addition of 30 µL of internal process control (IPC) virus (Mengo virus strain MC0). Samples were incubated at 37 °C for 60 min, followed by 15 min at 60 °C and all liquid was recovered squeezing the sampling sponge. Finally, after centrifugation at 3000× g for 5 min to sediment debris, the liquid was collected, measured (on average ≈20 mL), and retained for RNA extraction. Total RNA was extracted from 500 µL of the liquid using the eGene-UP semi-automated system (bioMerieux, Marcy-l’Étoile, France) and NucliSENS buffer reagents (bioMerieux) following the manufacturer’s instructions. Elution was performed in 100 µL. A negative extraction control sample (molecular grade water) was also tested in parallel with each set of extracted samples.
Nucleic acid extraction from human and animal swabs was performed using an automated nucleic acid platform (Maelstrom 9600, TANBead, Taiwan), with a magnetic bead-based protocol, using an extraction associated kit (TANBeadNucleic Acid Extraction Kit). Following manufacturer’s instructions, 300 µL of virus transport medium for the swabs were used for nucleic acids extraction. The RNA was finally eluted in 80 µL of elution buffer in the dedicated plate provided with the kit.
Nucleic acids were stored at −80 °C until testing.

2.3. SARS-CoV-2 Detection by Real-Time RT-PCR

Viral extraction efficiency in sponge samples was assessed using Mengovirus according to ISO 15216-2:2019 [43]. SARS-CoV-2 detection was performed following the Charité-Berlin protocol, both for primers/probes and for thermal profile [44] for the amplification of the SARS-CoV-2 E (Betacoronavirus screening assay), N (nucleocapsid protein) and RdRp (SARS-CoV-2 confirmatory assay) genes (Table 2).
Amplification reactions were prepared with the RNA UltraSense One-Step qRT-PCR System (Invitrogen; Waltham, MA, USA) and presence of PCR inhibitors was ruled out using TaqMan Exogenous Internal Positive Control (applied Biosystems; Waltham, MA, USA) according to manufacturer’s instructions. Results were considered acceptable if a minimum recovery of 1% was achieved and no significant inhibition was detected in the amplifications. SARS-CoV-2 detection in human and animal swabs was performed using the Allplex 2019-nCoV real-time RT-PCR assay (Seegene, South Korea) which also targets the E gene of Sarbecovirus, and the RdRp and N genes of SARS-CoV-2. An internal control (MS2 phage genome), provided with the kit, was used to monitor the process. Amplification and detection were performed on Bio-Rad CFX96 platform (Bio-Rad, Hercules, CA, USA) and results were interpreted according to the manufacturer instructions as follows: a sample was considered (I) positive if the three target genes displayed Ct values < 38, (II) presumptive positive if one or two genes were amplified with Ct values >38, (III) negative, if no amplification was detected for any of the three targets or if the three genes displayed Ct values ≥38.

2.4. SARS-CoV-2 Detection in Environmental Samples by Droplet Digital RT-PCR (dd RT-PCR)

Droplet digital RT-PCR was performed on Bio-Rad’s QX200 system (Bio-rad, Hercules, CA, USA) using the primers/probes of the Charité-Berlin protocol [18]. Two probes were used to amplify the RdRp gene at the same time: RdRP_SARSr-P1to detect SARS-CoV-2 and bat-SARS-related CoVs and RdRp_SARSr-P2 for specific detection of SARS-CoV-2. The reaction mixture (20 μL of total volume) consisted of: 5 μL One-step RT-ddPCR Advanced Kit for Probes, 2 μL Reverse transcriptase, 1 μL 300 mM DTT, 5 μL of samples RNA, primers and probes in the concentrations detailed in Table 2 and nuclease-free water as requied. Droplet generation was then performed as recommended by the manufacturer, and amplification was carried out on a CFX96 DeepWell instrument (Bio-Rad) with the following thermal profile: 50 °C for 60 min, 95 °C for 10 min followed by 95 °C for 15 s and 60 °C for 45 s (45 cycles) and by a final stage at 98 °C for 10 min. After amplification, results were acquired using the Bio-Rad QX200 Droplet Reader and QuantaSoft software (v1.7) (Bio-rad, Hercules, CA, USA) was used to count the PCR-positive or PCR-negative droplets and to provide absolute quantification of the target sequence. For each target gene, results of dd RT-PCR were used to calculate positivity rate (number of samples with SARS-CoV-2 detection on tested samples) for the different environments considered in the study, and average SARS-CoV-2 concentrations and range in positive samples. Detection rates in the different types of environments (animal farms, public transportation, supermarkets) were compared with the chi-squared test.

3. Results

In the present study, we investigated the presence of SARS-CoV-2 virus in public (transportation, supermarket, hotel) and working environments (animal farms) associated with reported COVID-19 cases in different areas of the Campania region. In animal farms, human and animal naso/oropharyngeal swabs were also taken. None of the naso/oropharyngeal swabs from humans (n = 93) and animals (n = 246) showed the presence of any of the three genetic markers (RdRp, E and N gene) of SARS-CoV-2. With regard to environmental samples (sponges), SARS-CoV-2 detection by real-time RT-PCR was also negative for all targets, in all samples (data not shown). On the contrary, dd RT-PCR achieved the detection of traces of SARS-CoV-2 RNA in several samples (Table 3).
Considering the three genetic targets (RdRp, gene E, gene N) together, 20/77 samples (26%) displayed the presence of at least one marker. In detail, RdRp gene sequences were detected in 17/77 samples (22%, concentration range 0.14–3.30 genome copies (g.c.)/µL of RNA), gene E in 8/77 (10%, concentration range 0.15–0.90 g.c./µL) and gene N in 1/77 (1%, concentration 0.18 g.c./µL). These results corresponded to estimated concentrations of SARS-CoV-2 of 31.2 g.c./cm2, range 5.6 to 132 g.c./cm2 considering RdRp, 15.1 g.c./cm2, range 6 to 36 g.c./cm2 using gene E, and 7.2 g.c./cm2 considering gene N (data not shown).
SARS-CoV-2 detection was more frequent in samples from animal farms (11/34 = 32% positive samples; positivity rate of 29%, 15% and 0% for RdRp, gene E and gene N, respectively) and in public transportation buses (6/20 = 30% positive samples; 30% RdRp, 10% gene E and 0% gene N), while each of the three SARS-CoV-2 targets were detected only in 1 of the 14 samples from supermarket (positivity rate of 7%). In these samples, however, a higher divergence of results was found, as the three targets were never detected in association but in three distinct samples. The differences in the detection rates of SARS-CoV-2 in animal farms, public transportation, and supermarkets were not statistically significant (chi-squared p-value = 0.75).
Also, virus concentration was higher in samples collected from animal farms compared to other sampling locations, RdRp average value being 1.00 g.c./µL of RNA (equivalent to 40 g.c./cm2, range 5.6 to 132) vs. 0.51 g.c./µL of RNA (equivalent to 20.4 g.c./cm2, range 7.2 to 40) of samples from public buses. Finally, none of the nine samples collected from the receptive structure of the hotel was found to harbor genetic traces of SARS-CoV-2.

4. Discussion

The SARS-CoV-2can survive in the air and on surfaces for several hours and up to several days, depending on environmental conditions [45], but being infected following contact with contaminated surfaces seems to be a remote risk [46]. Despite this, public health agencies underline that surfaces may pose a risk for virus transmission and should be disinfected frequently, prioritizing efforts to prevent the spread of the virus [47]. The objective of our study was to characterize SARS-CoV-2 contamination in selected public and working environments, using the sponge method for surface sampling and droplet digital PCR for detection [48,49]. To date, indeed, several studies have assessed SARS-CoV-2 contamination in hospital or healthcare settings, but still few have addressed the risk of surface contamination in public- or work- places [38]. Environmental sampling is a critical component of verification of the effectiveness of sanitation processes and, in order to detect the presence of viruses that may be present in traces on the investigated surfaces, the use of efficient sampling systems is a compelling requirement [50]. The sponge sampling method allows a more vigorous scrubbing of the surfaces, an extensive adhesion of the sampler to the surface (also on objects with uneven shapes or with crevices), and an increased adsorption of detached materials. Over time, swabs with higher recovery performance towards viruses on surfaces [51] have been developed, through adaptation of shape and materials, and have also been successfully used for SARS-CoV-2 sampling from plastic objects such as glasses, cups and bottles that may come into contact with infected individuals [52]. However, in the context of official controls performed by the local health authorities, it has long been demonstrated that swabs have a capture capacity not exceeding ~20% of the target on the surface, therefore the sponge sampling confirms its functionality because of the higher recovery efficiency [53,54,55,56,57,58]. Further to an effective sampling strategy, high sensitivity should also be provided by the molecular analytical methods used for testing of environmental samples. The current gold standard for the detection and diagnosis of SARS-CoV-2 infection is based on the real-time RT-PCR assay but has several downsides [59]. False-negative real-time RT-PCR assay results can arise because of insufficient viral material in samples, while weak positive results (i.e., high Ct values) can be difficult to interpret and to differentiate from technical artifacts (e.g., fluorescence increase due to sample background or probe degradation) [44]. For this reason, in recent years, droplet digital RT-PCR (dd RT-PCR) has been considered a good alternative to real time RT-PCR assays, considering its high sensitivity in the detection and quantification of RNA targets [60,61] and its ability to provide consistent and reliable results also at low target concentrations [62]. Moreover, using Poisson’s distribution, the absolute concentration of the target can be calculated without the use of standard curves [63] and, due to sample partitioning, reactions are less affected by the presence of inhibitors [64]. Therefore, in this study, sponge sampling was coupled with real time RT-PCR as well as with dd RT-PCR, which, in the end, was the only analytical approach providing positive results. Our investigation showed traces of SARS-CoV-2 in 26% of the surface samples collected from the different environments considered in the study (animal farms, public transportation buses, supermarkets, hotel receptive structures), some of which interested from previous outbreak events. Overall, considering the results of the RdRp gene as a reference, SARS-CoV-2concentration in the positive samples was of 31.2 g.c./cm2(range 5.6 to 132 g.c./cm2). Quantitative data on SARS-CoV-2 contaminated surfaces are scarce and are almost exclusively related to high risk closed environments used for COVID-19 patients [29], therefore direct comparison of our results, which derive from different environments, with other studies is not feasible. With regard to sampling performed on public transportation buses, positive results (always considering the RdRp gene as a reference) were obtained in 30% of samples, with an average concentration of 40 g.c./cm2(range 5.6 to 132g.c./cm2). These results are intermediate to those stated by studies from other countries [37,38] and only slightly higher than those reported for the period May–June 2021 in another Italian region, Apulia, in which SARS-CoV-2 was overall detected on 10.7% of the tested surfaces and, more specifically, in 19.3% of bus surfaces and 2% of train surfaces [42]. It should be noted, however, that the different prevalence might also be related to the different sampling techniques (swabs vs. sponges), which—as stated before—might affect viral recovery from surfaces. Interestingly, the viral concentrations achieved in the present study seem significantly higher than those reported in one [38] of the few other studies including quantitative data. Indeed, in the study by Moreno and colleagues (2021) [38] on public transportation in Barcelona, depending on the target sequence (IP2, IP4, gene E), SARS-CoV-2 contamination ranged from 5 to 490 c.g./m2 in public buses and from 18 to 714 c.g./m2 in the subway, i.e., approximately 4 log lower than in our study. This significant divergence in quantitative results, however, should be considered in the light of both the deep difference in the analytical methods (sampling techniques, molecular targets, real-time PCR vs. dd RT-PCR, standards for calibrations, etc.) and the different epidemiological situations registered during the two studies (May–June 2020 for the study in Barcelona, March 2021 for the current study). Considering the samples taken from the supermarket, a certain variability of results was observed, as overall 3 samples of 14 (21%) showed traced of SARS-CoV-2 genome. These results are higher than those reported by Caggiano and colleagues [40] for supermarkets tested in Apulia, Italy in April–May 2021 (4.3%) or by Singh et al. [65] in Ontario, Canada during October–November 2020 (no detection of SARS-CoV-2). However, the three studies differ under several aspects, including different sampling techniques (swab vs. sponges), molecular detection (real-time vs. dd RT-PCR), as well for the fact that only this study targets multiple genome regions of SARS-CoV-2, hence increasing the chance of detection. It should also be noted that the three positive results of the present study were all associated only with one genetic target (none of the three tested genes were ever detected simultaneously). This could be due to high viral degradation, possibly in relation to the stricter cleaning and sanitation procedures applied in food stores. Indeed, while detection of SARS-CoV-2 is a clear indication of a contamination event, little can be said on viral infectivity particularly if detection is related to surfaces periodically subjected to disinfection.
Effectiveness of cleaning and sanitation procedures (for the deactivation of SARS-CoV-2 as well as for removal of any residual inactivated virus particle), together with the natural decay of viruses on surfaces, may also explain the results obtained in the samples collected from the hotel receptive structure, which was sampled due to its association with a SARS-CoV-2 outbreak event following a wedding party. Indeed, in this case sampling was performed one week after the event and after extensive sanitation. Sampling of receptive structures in a different context (e.g., under routine use of the environments and with standard cleaning activities) may indeed lead to SARS-CoV-2 detection also in such environments, as demonstrated by Montagna and colleagues (2021) [41], that found traces of the viral genome in 6% of the tested surfaces. Finally, with regard to the samples taken in animal farms (buffaloes, cattle, pigs, goats, horses, rabbits, hens and pigeons), 32% of surface samples were found positive for at least one genetic target of SARS-CoV-2. With the exception of studies dealing with mink farms, in which SARS-CoV-2 on surfaces was investigated due to the outbreaks associated with the CoV-2 mink-specific variant [66,67], the present study is, to our knowledge, the first one dealing with environmental contamination by SARS-CoV-2 in animal farms. Significantly, the absence of SARS-CoV-2 detection in the workers and in the animals at the moment of testing (no detection in 339 swabs) confirms that the 11 positive surface samples were related to previous infection events, during which the virus had been deposited on work surfaces, walls and utensils. Further to this, higher viral concentrations were found in samples taken from animal farms (40 g.c./cm2 vs. 20.4 g.c./cm2 of public transportation, with a range significantly more extended, 5.6–132 vs. 7.2–40). This is in agreement with the fact that cleaning and sanitation procedures are less feasible in animal husbandry, and therefore removal of viruses deposited on surfaces is more difficult. One of these, buffaloes farm n°4, provided three positive samples (two of which from the milking parlor surfaces) and had registered two COVID-19 fatalities among workers in the two months preceding our sampling. The other two farms, buffaloes farm n°2 and n°3, also regularly visited by one of these workers, showed instead no traces of SARS-CoV-2 on the tested surfaces, hence displaying a certain variability of viral deposition on surfaces, depending on the environment.

5. Conclusions

Data obtained suggests that the risk of contamination increases in environments with a higher presence of people and where decontamination strategies are not always feasible. At the same time our observations also suggest that improving the quality of the environmental sanitation can reduce the spreading of the pathogen. Comparing data on human swabs and on surface sponges, it has been previously shown that, after disinfection, several environments, even those affected by proven human contamination, do not present traces of SARS-CoV-2, which instead are revealed in different surfaces collected from environments not thoroughly sanitized [68]. A rapid SARS-CoV-2 inactivation is possible by using commonly available chemicals and biocides on inanimate surfaces (e.g., EtOH 70% or sodium hypochlorite) [69]. Further to this, this study showed the reliability of dd RT-PCR method for the detection of SARS-CoV-2 traces on surfaces. Further studies are required to improve and standardize surface-sampling methods for viral analysis, to estimate viral infectivity on surfaces, and to assess the risk of viral transmission, thereby providing additional information on the relevance of SARS-CoV-2 contamination of fomites.

Author Contributions

Conceptualization, D.C. and P.C.; Data curation, F.C. (Federica Corrado), J.L.D., A.C., G.R., P.V., P.G., S.D.V. and A.G.; Formal analysis, M.T. and A.M.; Investigation, D.C., M.T. and A.M.; Methodology, D.C., A.M., S.G. and Y.T.R.P.; Project administration, D.C., P.C. and M.M.; Supervision, F.C. (Federico Capuano), Y.T.R.P. and M.M.; Validation, F.C. (Federico Capuano), Y.T.R.P. and E.S.; Visualization, E.S. and B.P.; Writing—original draft, D.C., M.T. and A.M.; Writing—review and editing, M.T., E.S. and B.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. She, J.; Jiang, J.; Ye, L.; Hu, L.; Bai, C.; Song, Y. 2019 novel coronavirus of pneumonia in Wuhan, China: Emerging attack and management strategies. Clin. Transl. Med. 2020, 9, 19. [Google Scholar] [CrossRef] [PubMed]
  2. Andersen, K.G.; Rambaut, A.; Lipkin, W.I.; Holmes, E.C.; Garry, R.F. The proximal origin of SARS-CoV-2. Nat. Med. 2020, 26, 450–452. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Al-Qahtani, A.A. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): Emergence, history, basic and clinical aspects. Saudi J. Biol. Sci. 2020, 27, 2531–2538. [Google Scholar] [CrossRef] [PubMed]
  4. Cucinotta, D.; Vanelli, M. WHO Declares COVID-19 a Pandemic. Acta Bio Med. Atenei Parm. 2020, 91, 157–160. [Google Scholar] [CrossRef]
  5. Morawska, L.; Johnson, G.R.; Ristovski, Z.D.; Hargreaves, M.; Mengersen, K.; Corbett, S.; Chao, C.Y.H.; Li, Y.; Katoshevski, D. Size distribution and sites of origin of droplets expelled from the human respiratory tract during expiratory activities. J. Aerosol Sci. 2009, 40, 256–269. [Google Scholar] [CrossRef] [Green Version]
  6. Stadnytskyi, V.; Bax, C.E.; Bax, A.; Anfinrud, P. The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission. Proc. Natl. Acad. Sci. USA 2020, 117, 11875–11877. [Google Scholar] [CrossRef]
  7. Santarpia, J.L.; Rivera, D.N.; Herrera, V.L.; Morwitzer, M.J.; Creager, H.M.; Santarpia, G.W.; Crown, K.K.; Brett-Major, D.M.; Schnaubelt, E.R.; Broadhurst, M.J.; et al. Aerosol and surface contamination of SARS-CoV-2 observed in quarantine and isolation care. Sci. Rep. 2020, 10, 12732. [Google Scholar] [CrossRef]
  8. Kenneth McIntosh, M.; Martin, S.; Hirsch, M.; Allyson Bloom, M. Coronavirus disease 2019 (COVID-19). UpToDate Hirsch MS Bloom 2020, 5, 873. [Google Scholar]
  9. Kraay, A.N.M.; Hayashi, M.A.L.; Hernandez-Ceron, N.; Spicknall, I.H.; Eisenberg, M.C.; Meza, R.; Eisenberg, J.N.S. Fomite-mediated transmission as a sufficient pathway: A comparative analysis across three viral pathogens 11 Medical and Health Sciences 1117 Public Health and Health Services. BMC Infect. Dis. 2018, 18, 540. [Google Scholar]
  10. Rusin, P.; Maxwell, S.; Gerba, C. Comparative surface-to-hand and fingertip-to-mouth transfer efficiency of gram-positive bacteria, gram-negative bacteria, and phage. J. Appl. Microbiol. 2002, 93, 585–592. [Google Scholar] [CrossRef]
  11. Mohammad, N.S.; Nazli, R.; Zafar, H.; Fatima, S. Effects of lipid based multiple micronutrients supplement on the birth outcome of underweight pre-eclamptic women: A randomized clinical trial. Pakistan, J. Med. Sci. 2022, 38, 219–226. [Google Scholar] [CrossRef]
  12. Biryukov, J.; Boydston, J.A.; Dunning, R.A.; Yeager, J.J.; Wood, S.; Ferris, A.; Miller, D.; Weaver, W.; Zeitouni, N.E.; Freeburger, D.; et al. SARS-CoV-2 is rapidly inactivated at high temperature. Environ. Chem. Lett. 2021, 19, 1773–1777. [Google Scholar] [CrossRef]
  13. Biryukov, J.; Boydston, J.A.; Dunning, R.A.; Yeager, J.J.; Wood, S.; Reese, A.L.; Ferris, A.; Miller, D.; Weaver, W.; Zeitouni, N.E.; et al. Increasing Temperature and Relative Humidity Accelerates Inactivation of SARS-CoV-2 on Surfaces. mSphere 2020, 5, e00441-20. [Google Scholar] [CrossRef]
  14. Casanova, L.M.; Jeon, S.; Rutala, W.A.; Weber, D.J.; Sobsey, M.D. Effects of Air Temperature and Relative Humidity on Coronavirus Survival on Surfaces. Appl. Environ. Microbiol. 2010, 76, 2712–2717. [Google Scholar] [CrossRef] [Green Version]
  15. Wang, D.; Freed, D.C.; He, X.; Li, F.; Tang, A.; Cox, K.S.; Dubey, S.A.; Cole, S.; Medi, M.B.; Liu, Y.; et al. A replication-defective human cytomegalovirus vaccine for prevention of congenital infection. Sci. Transl. Med. 2016, 8, 747–766. [Google Scholar] [CrossRef]
  16. Raiteux, J.; Eschlimann, M.; Marangon, A.; Rogée, S.; Dadvisard, M.; Taysse, L.; Larigauderie, G. Inactivation of SARS-CoV-2 by Simulated Sunlight on Contaminated Surfaces. Microbiol. Spectr. 2021, 9, e00333-21. [Google Scholar] [CrossRef]
  17. Chin, A.W.H.; Chu, J.T.S.; Perera, M.R.A.; Hui, K.P.Y.; Yen, H.L.; Chan, M.C.W.; Peiris, M.; Poon, L.L.M. Stability of SARS-CoV-2 in different environmental conditions. Lancet Microbe 2020, 1, e10. [Google Scholar] [CrossRef]
  18. Van Doremalen, N.; Bushmaker, T.; Morris, D.H.; Holbrook, M.G.; Gamble, A.; Williamson, B.N.; Tamin, A.; Harcourt, J.L.; Thornburg, N.J.; Gerber, S.I.; et al. Aerosol and surface stability of HCoV-19 (SARS-CoV-2) compared to SARS-CoV-1. medRxiv 2020. [Google Scholar] [CrossRef] [Green Version]
  19. Bonil, L.; Lingas, G.; Coupeau, D.; Lucet, J.C.; Guedj, J.; Visseaux, B.; Muylkens, B. Survival of SARS-CoV-2 on non-porous materials in an experimental setting representative of fomites. Coatings 2021, 11, 371. [Google Scholar] [CrossRef]
  20. Hirose, R.; Miyazaki, H.; Bandou, R.; Watanabe, N.; Yoshida, T.; Daidoji, T.; Itoh, Y.; Nakaya, T. Stability of SARS-CoV-2 and influenza virus varies across different paper types. J. Infect. Chemother. 2022, 28, 252–256. [Google Scholar] [CrossRef]
  21. Di Novo, N.G.; Carotenuto, A.R.; Mensitieri, G.; Fraldi, M.; Pugno, N.M. Modeling of Virus Survival Time in Respiratory Droplets on Surfaces: A New Rational Approach for Antivirus Strategies. Front. Mater. 2021, 8, 56. [Google Scholar] [CrossRef]
  22. Wu, S.; Wang, Y.; Jin, X.; Tian, J.; Liu, J.; Mao, Y. Environmental contamination by SARS-CoV-2 in a designated hospital for coronavirus disease 2019. Am. J. Infect. Control 2020, 48, 910–914. [Google Scholar] [CrossRef]
  23. Chia, P.Y.; Coleman, K.K.; Tan, Y.K.; Ong, S.W.X.; Gum, M.; Lau, S.K.; Lim, X.F.; Lim, A.S.; Sutjipto, S.; Lee, P.H.; et al. Detection of air and surface contamination by SARS-CoV-2 in hospital rooms of infected patients. Nat. Commun. 2020, 11, 2800. [Google Scholar] [CrossRef]
  24. Li, Y.H.; Fan, Y.Z.; Jiang, L.; Wang, H.B. Aerosol and environmental surface monitoring for SARS-CoV-2 RNA in a designated hospital for severe COVID-19 patients. Epidemiol. Infect. 2020, 148, e154. [Google Scholar] [CrossRef]
  25. Razzini, K.; Castrica, M.; Menchetti, L.; Maggi, L.; Negroni, L.; Orfeo, N.V.; Pizzoccheri, A.; Stocco, M.; Muttini, S.; Balzaretti, C.M. SARS-CoV-2 RNA detection in the air and on surfaces in the COVID-19 ward of a hospital in Milan, Italy. Sci. Total Environ. 2020, 742, 140540. [Google Scholar] [CrossRef]
  26. Coil, D.A.; Albertson, T.; Banerjee, S.; Brennan, G.; Campbell, A.J.; Cohen, S.H.; Dandekar, S.; Díaz-Muñoz, S.L.; Eisen, J.A.; Goldstein, T.; et al. SARS-CoV-2 detection and genomic sequencing from hospital surface samples collected at UC Davis. PLoS ONE 2021, 16, e0253578. [Google Scholar] [CrossRef]
  27. Alam, S.; Darul Ehsan, S. Environmental surface sampling of SARS-CoV-2 in selected hospitals in Malaysia. Trop. Biomed. 2021, 38, 462–468. [Google Scholar] [CrossRef]
  28. Ben-Shmuel, A.; Brosh-Nissimov, T.; Glinert, I.; Bar-David, E.; Sittner, A.; Poni, R.; Cohen, R.; Achdout, H.; Tamir, H.; Yahalom-Ronen, Y.; et al. Detection and infectivity potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) environmental contamination in isolation units and quarantine facilities. Clin. Microbiol. Infect. 2020, 26, 1658–1662. [Google Scholar] [CrossRef]
  29. Moore, G.; Rickard, H.; Stevenson, D.; Aranega-Bou, P.; Pitman, J.; Crook, A.; Davies, K.; Spencer, A.; Burton, C.; Easterbrook, L.; et al. Detection of SARS-CoV-2 within the healthcare environment: A multi-centre study conducted during the first wave of the COVID-19 outbreak in England. J. Hosp. Infect. 2021, 108, 189–196. [Google Scholar] [CrossRef]
  30. Marcenac, P.; Park, G.W.; Duca, L.M.; Lewis, N.M.; Dietrich, E.A.; Barclay, L.; Tamin, A.; Harcourt, J.L.; Thornburg, N.J.; Rispens, J.; et al. Detection of SARS-CoV-2 on surfaces in households of persons with COVID-19. Int. J. Environ. Res. Public Health 2021, 18, 8154. [Google Scholar] [CrossRef]
  31. Hu, X.; Xing, Y.; Ni, W.; Zhang, F.; Lu, S.; Wang, Z.; Gao, R.; Jiang, F. Environmental contamination by SARS-CoV-2 of an imported case during incubation period. Sci. Total Environ. 2020, 742, 140620. [Google Scholar] [CrossRef] [PubMed]
  32. Ong, S.W.X.; Tan, Y.K.; Chia, P.Y.; Lee, T.H.; Ng, O.T.; Wong, M.S.Y.; Marimuthu, K. Air, Surface Environmental, and Personal Protective Equipment Contamination by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) from a Symptomatic Patient. JAMA-J. Am. Med. Assoc. 2020, 323, 1610–1612. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Yamagishi, T.; Ohnishi, M.; Matsunaga, N.; Kakimoto, K.; Kamiya, H.; Okamoto, K.; Suzuki, M.; Gu, Y.; Sakaguchi, M.; Tajima, T.; et al. Environmental sampling for severe acute respiratory syndrome coronavirus 2 during a COVID-19 outbreak on the diamond princess cruise ship. J. Infect. Dis. 2020, 222, 1098–1102. [Google Scholar] [CrossRef] [PubMed]
  34. Silva, S.J.R.; Nascimento, J.C.F.; Santos Reis, W.P.M.; Silva, C.T.A.; Silva, P.G.; Mendes, R.P.G.; Mendonça, A.A.; Santos, B.N.R.; Magalhães, J.J.F.; Kohl, A.; et al. Widespread contamination of SARS-CoV-2 on highly touched surfaces in Brazil during the second wave of the COVID-19 pandemic. Environ. Microbiol. 2021, 23, 7382–7395. [Google Scholar] [CrossRef] [PubMed]
  35. Harvey, A.P.; Fuhrmeister, E.R.; Cantrell, M.E.; Pitol, A.K.; Swarthout, J.M.; Powers, J.E.; Nadimpalli, M.L.; Julian, T.R.; Pickering, A.J. Longitudinal Monitoring of SARS-CoV-2 RNA on High-Touch Surfaces in a Community Setting. Environ. Sci. Technol. Lett. 2021, 8, 168–175. [Google Scholar] [CrossRef]
  36. Kozer, E.; Rinott, E.; Kozer, G.; Bar-Haim, A.; Benveniste-Levkovitz, P.; Klainer, H.; Perl, S.; Youngster, I. Presence of SARS-CoV-2 RNA on playground surfaces and water fountains. Epidemiol. Infect. 2021, 149, e67. [Google Scholar] [CrossRef]
  37. Guadalupe, J.J.; Rojas, M.I.; Pozo, G.; Erazo-Garcia, M.P.; Vega-Polo, P.; Terán-Velástegui, M.; Rohwer, F.; Torres, M.D.L. Presence of SARS-CoV-2 RNA on surfaces of public places and a transportation system located in a densely populated urban area in South America. Viruses 2022, 14, 19. [Google Scholar] [CrossRef]
  38. Moreno, T.; Pintó, R.M.; Bosch, A.; Moreno, N.; Alastuey, A.; Minguillón, M.C.; Anfruns-Estrada, E.; Guix, S.; Fuentes, C.; Buonanno, G.; et al. Tracing surface and airborne SARS-CoV-2 RNA inside public buses and subway trains. Environ. Int. 2021, 147, 106326. [Google Scholar] [CrossRef]
  39. Di Carlo, P.; Chiacchiaretta, P.; Sinjari, B.; Aruffo, E.; Stuppia, L.; De Laurenzi, V.; Di Tomo, P.; Pelusi, L.; Potenza, F.; Veronese, A.; et al. Air and surface measurements of SARS-CoV-2 inside a bus during normal operation. PLoS ONE 2020, 15, e0235943. [Google Scholar] [CrossRef]
  40. Caggiano, G.; Triggiano, F.; Apollonio, F.; Diella, G.; Lopuzzo, M.; D’ambrosio, M.; Fasano, F.; Stefanizzi, P.; Sorrenti, G.T.; Magarelli, P.; et al. SARS-CoV-2 rna and supermarket surfaces: A real or presumed threat? Int. J. Environ. Res. Public Health 2021, 18, 404. [Google Scholar] [CrossRef]
  41. Montagna, M.T.; De Giglio, O.; Calia, C.; Pousis, C.; Apollonio, F.; Campanale, C.; Diella, G.; Lopuzzo, M.; Marzella, A.; Triggiano, F.; et al. First Detection of Severe Acute Respiratory Syndrome Coronavirus 2 on the Surfaces of Tourist-Recreational Facilities in Italy. Int. J. Environ. Res. Public Health 2021, 18, 3252. [Google Scholar] [CrossRef]
  42. Caggiano, G.; Apollonio, F.; Triggiano, F.; Diella, G.; Stefanizzi, P.; Lopuzzo, M.; D’ambrosio, M.; Bartolomeo, N.; Barbuti, G.; Sorrenti, G.T.; et al. SARS-CoV-2 and public transport in Italy. Int. J. Environ. Res. Public Health 2021, 18, 1415. [Google Scholar] [CrossRef]
  43. ISO. UNI EN ISO 15216-2:2019; Microbiology of the Food Chain—Horizontal Method for Determination of Hepatitis A Virus and Norovirus Using Real-Time RT-PCR—Part 2: Method for Detection; International Organization for Standardization: Geneva, Switzerland, 2019. [Google Scholar]
  44. Corman, V.M.; Landt, O.; Kaiser, M.; Molenkamp, R.; Meijer, A.; Chu, D.K.; Bleicker, T.; Brünink, S.; Schneider, J.; Schmidt, M.L.; et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance 2020, 25, 23. [Google Scholar] [CrossRef] [Green Version]
  45. Dargahi, A.; Jeddi, F.; Vosoughi, M.; Karami, C.; Hadisi, A.; Ahamad Mokhtari, S.; Ghobadi, H.; Alighadri, M.; Haghighi, S.B.; Sadeghi, H. Investigation of SARS-CoV-2 virus in environmental surface. Environ. Res. 2021, 195, 110765. [Google Scholar] [CrossRef]
  46. Goldman, E. Exaggerated risk of transmission of COVID-19 by fomites. Lancet Infect. Dis. 2020, 20, 892–893. [Google Scholar] [CrossRef]
  47. Samudrala, P.K.; Kumar, P.; Choudhary, K.; Thakur, N.; Wadekar, G.S.; Dayaramani, R.; Agrawal, M.; Alexander, A. Virology, pathogenesis, diagnosis and in-line treatment of COVID-19. Eur. J. Pharmacol. 2020, 883, 173375. [Google Scholar] [CrossRef]
  48. Abdel-Hady, A.; Worth Calfee, M.; Aslett, D.; Lee, S.D.; Wyrzykowska-Ceradini, B.; Robbins Delafield, F.; May, K.; Touati, A. Alternative fast analysis method for cellulose sponge surface sampling wipes with low concentrations of Bacillus Spores. J. Microbiol. Methods 2019, 156, 5–8. [Google Scholar] [CrossRef]
  49. Mancusi, A.; Capuano, F.; Girardi, S.; Di Maro, O.; Suffredini, E.; Di Concilio, D.; Vassallo, L.; Cuomo, M.C.; Tafuro, M.; Signorelli, D.; et al. Detection of SARS-CoV-2 RNA in Bivalve Mollusks by Droplet Digital RT-PCR (dd RT-PCR). Int. J. Environ. Res. Public Health 2022, 19, 943. [Google Scholar] [CrossRef]
  50. Kraay, A.N.M.; Hayashi, M.A.L.; Berendes, D.M.; Sobolik, J.S.; Leon, J.S.; Lopman, B.A. Risk of fomite-mediated transmission of SARS-CoV-2 in child daycares, schools, and offices: A modeling study. medRxiv 2020. [Google Scholar] [CrossRef]
  51. Park, G.W.; Chhabra, P.; Vinjé, J. Swab Sampling Method for the Detection of Human Norovirus on Surfaces. J. Vis. Exp. 2017, 120, 55205. [Google Scholar] [CrossRef]
  52. Di Maria, F.; La Rosa, G.; Bonato, T.; Pivato, A.; Piazza, R.; Mancini, P.; Bonanno Ferraro, G.; Veneri, C.; Iaconelli, M.; Beccaloni, E.; et al. An innovative approach for the non-invasive surveillance of communities and early detection of SARS-CoV-2 via solid waste analysis. Sci. Total Environ. 2021, 801, 149743. [Google Scholar] [CrossRef]
  53. Hindson, C.M.; Chevillet, J.R.; Briggs, H.A.; Gallichotte, E.N.; Ruf, I.K.; Hindson, B.J.; Vessella, R.L.; Tewari, M. Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat. Methods 2013, 10, 1003–1005. [Google Scholar] [CrossRef]
  54. Park, C.; Lee, J.; ul Hassan, Z.; Ku, K.B.; Kim, S.J.; Kim, H.G.; Park, E.C.; Park, G.S.; Park, D.; Baek, S.H.; et al. Comparison of digital pcr and quantitative pcr with various SARS-CoV-2 primer-probe sets. J. Microbiol. Biotechnol. 2021, 31, 358–367. [Google Scholar] [CrossRef]
  55. Tenhagen, B.A.; Arth, O.; Bandick, N.; Fetsch, A. Comparison of three sampling methods for the quantification of methicillin-resistant Staphylococcus aureus on the surface of pig carcases. Food Control 2011, 22, 643–645. [Google Scholar] [CrossRef]
  56. Nguyen, H.; Morgan, D.A.F.; Cull, S.; Benkovich, M.; Forwood, M.R. Sponge swabs increase sensitivity of sterility testing of processed bone and tendon allografts. J. Ind. Microbiol. Biotechnol. 2011, 38, 1127–1132. [Google Scholar] [CrossRef]
  57. Engelhardt, N.E.P.; Foster, N.F.; Hong, S.; Riley, T.V.; McGechie, D.B. Comparison of two environmental sampling tools for the detection of Clostridium difficile spores on hard bathroom surfaces in the hospital setting. J. Hosp. Infect. 2017, 96, 295–296. [Google Scholar] [CrossRef]
  58. Gallina, S.; Bianchi, D.M.; Ru, G.; Maurella, C.; Barzanti, P.; Baioni, E.; Virgilio, S.; Mioni, R.; Lanni, L.; Migliazzo, A.; et al. Microbiological recovery from bovine, swine, equine, and ovine carcasses: Comparison of excision, sponge and swab sampling methods. Food Control 2015, 50, 919–924. [Google Scholar] [CrossRef]
  59. Yu, F.; Yan, L.; Wang, N.; Yang, S.; Wang, L.; Tang, Y.; Gao, G.; Wang, S.; Ma, C.; Xie, R.; et al. Quantitative detection and viral load analysis of SARS-CoV-2 in infected patients. Clin. Infect. Dis. 2020, 71, 793–798. [Google Scholar] [CrossRef] [Green Version]
  60. Cassinari, K.; Alessandri-Gradt, E.; Chambon, P.; Charbonnier, F.; Gracias, S.; Beaussire, L.; Alexandre, K.; Sarafan-Vasseur, N.; Houdayer, C.; Etienne, M.; et al. Assessment of Multiplex Digital Droplet RT-PCR as a Diagnostic Tool for SARS-CoV-2 Detection in Nasopharyngeal Swabs and Saliva Samples. Clin. Chem. 2021, 67, 736–741. [Google Scholar] [CrossRef]
  61. Long, S.; Berkemeier, B. Ultrasensitive detection and quantification of viral nucleic acids with Raindance droplet digital PCR (ddPCR). Methods 2021, 201, 49–64. [Google Scholar] [CrossRef] [PubMed]
  62. Sedlak, R.H.; Cook, L.; Cheng, A.; Magaret, A.; Jerome, K.R. Clinical utility of droplet digital PCR for human cytomegalovirus. J. Clin. Microbiol. 2014, 52, 2844–2848. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Dube, S.; Qin, J.; Ramakrishnan, R. Mathematical Analysis of Copy Number Variation in a DNA Sample Using Digital PCR on a Nanofluidic Device. PLoS ONE 2008, 3, e2876. [Google Scholar] [CrossRef] [PubMed]
  64. Teo, C.R.L.; Rajan-Babu, I.S.; Law, H.Y.; Lee, C.G.; Chong, S.S. Tolerance of Droplet-Digital PCR vs. Real-Time Quantitative PCR to Inhibitory Substances. Clin. Chem. 2013, 59, 1670–1672. [Google Scholar]
  65. Singh, M.; Sadat, A.; Abdi, R.; Colaruotolo, L.A.; Francavilla, A.; Petker, K.; Nasr, P.; Moraveji, M.; Cruz, G.; Huang, Y.; et al. Detection of SARS-CoV-2 on surfaces in food retailers in Ontario. Curr. Res. Food Sci. 2021, 4, 598–602. [Google Scholar] [CrossRef] [PubMed]
  66. Chaintoutis, S.C.; Thomou, Z.; Mouchtaropoulou, E.; Tsiolas, G.; Chassalevris, T.; Stylianaki, I.; Lagou, M.; Michailidou, S.; Moutou, E.; Koenen, J.J.H.; et al. Outbreaks of SARS-CoV-2 in naturally infected mink farms: Impact, transmission dynamics, genetic patterns, and environmental contamination. PLoS Pathog. 2021, 17, e1009883. [Google Scholar] [CrossRef]
  67. De Rooij, M.M.T.; Hakze-Van Der Honing, R.W.; Hulst, M.M.; Harders, F.; Engelsma, M.; Van De Hoef, W.; Meliefste, K.; Nieuwenweg, S.; Oude Munnink, B.B.; Van Schothorst, I.; et al. Occupational and environmental exposure to SARS-CoV-2 in and around infected mink farms. Occup. Environ. Med. 2021, 78, 893–899. [Google Scholar] [CrossRef]
  68. Montse, M.; José, L.D. Contamination of inert surfaces by SARS-CoV-2: Persistence, stability and infectivity. A review. Environ. Res. 2021, 193, 110559. [Google Scholar]
  69. Kampf, G.; Todt, D.; Pfaender, S.; Steinmann, E. Persistence of coronaviruses on inanimate surfaces and their inactivation with biocidal agents. J. Hosp. Infect. 2020, 104, 246–251. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Sample distribution on the territory of Campania.
Figure 1. Sample distribution on the territory of Campania.
Ijerph 19 05861 g001
Table 1. Samples analyzed in the study, divided by sampling location.
Table 1. Samples analyzed in the study, divided by sampling location.
Sampling LocationDistrictEnvironmental SamplesAnimal SwabsHuman Swabs
Buffaloes farm_1Caserta1207
Buffaloes farm_2Caserta12211
Buffaloes farm_3Caserta12312
Buffaloes farm_4Caserta10329
Cattle farmSalerno-101
Goat and cattle farmSalerno2172
Goat farm_1Salerno16-
Goat farm_2Salerno-101
Hen farm_1Salerno1105
Hen farm_2Salerno11110
Horse stall_1Salerno463
Horse stall_2Salerno6144
Pig farmSalerno197
Pig farmBenevento1166
Pig farmAvellino2212
Pigeon farmNapoli1122
Rabbits farmSalerno1711
Bus_1Salerno5--
Bus_2Salerno5--
Bus_3Salerno5--
Bus_4Salerno5--
SupermarketSalerno14--
Hotel receptive structureNapoli9--
Total 7724693
Table 2. Sequence and concentrations of primers and probes used for real-time RT-PCR and Droplet Digital-RT-PCR detection of SARS-CoV-2 in environmental samples.
Table 2. Sequence and concentrations of primers and probes used for real-time RT-PCR and Droplet Digital-RT-PCR detection of SARS-CoV-2 in environmental samples.
Primers and ProbesSequenceConcentrations
RdRp_SARSr-FGTGARATGGTCATGTGTGGCGG600 nM
RdRp_SARSr-RCARATGTTAAASACACTATTAGCATA800 nM
RdRP_SARSr-P1FAM-CCAGGTGGWACRTCATCMGGTGATGC-BBQ100 nM
RdRp_SARSr-P2FAM-CAGGTGGAACCTCATCAGGAGATGC-BBQ100 nM
E_Sarbeco_FACAGGTACGTTAATAGTTAATAGCGT400 nM
E_Sarbeco_RATATTGCAGCAGTACGCACACA400 nM
E_Sarbeco_P1FAM-ACACTAGCCATCCTTACTGCGCTTCG-BBQ200 nM
N_Sarbeco_FCACATTGGCACCCGCAATC600 nM
N_Sarbeco_RGAGGAACGAGAAGAGGCTTG800 nM
N_Sarbeco_PFAM-ACTTCCTCAAGGAACAACATTGCCA-BBQ200 nM
FAM: 6-carboxy-fluorescein; BBQ: BlackBerry Quencher.
Table 3. Detection of SARS-CoV-2 marker genes in environmental samples by droplet digital RT-PCR.
Table 3. Detection of SARS-CoV-2 marker genes in environmental samples by droplet digital RT-PCR.
Sampling LocationMunicipalityN° of Samplesdd RT-PCR
RdRpE GeneN Gene
Buffaloes farm_1Caserta1+--
Buffaloes farm_2Caserta1---
Buffaloes farm_3Caserta1---
Buffaloes farm_4Caserta1+--
Buffaloes farm_4Caserta2++-
Buffaloes farm_4Caserta7---
Cattle farmSalerno1---
Goat and cattle farmSalerno1---
Goat farm_1Salerno1---
Goat farm_2Salerno1+--
Hen farm_1Salerno1+--
Hen farm_2Salerno1---
Horse stall_1Salerno2---
Horse stall_1Salerno2++-
Horse stall_1Salerno2+--
Horse stall_2Salerno4---
Pig farmSalerno1---
Pig farmBenevento1---
Pig farmAvellino1---
Pigeon farmNapoli1---
Rabbits farmSalerno1-+-
subtotal 3410 (29%)5 (15%)0 (0%)
Bus_1Salerno3---
Bus_1Salerno1+--
Bus_1Salerno1++-
Bus_2Salerno1+--
Bus_2Salerno4---
Bus_3Salerno1++-
Bus_3Salerno3---
Bus_3Salerno1+--
Bus_4Salerno4---
Bus_4Salerno1+--
subtotal 206 (30%)2 (10%)0 (0%)
SupermarketSalerno11---
SupermarketSalerno1-+-
SupermarketSalerno1--+
SupermarketSalerno1+--
subtotal 141 (7%)1 (7%)1 (7%)
Hotel receptive structureNapoli9---
subtotal 90 (0%)0 (0%)0 (0%)
Total 7717 (22%)8 (10%)1 (1%)
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Cardinale, D.; Tafuro, M.; Mancusi, A.; Girardi, S.; Capuano, F.; Proroga, Y.T.R.; Corrado, F.; D’Auria, J.L.; Coppola, A.; Rofrano, G.; et al. Sponge Whirl-Pak Sampling Method and Droplet Digital RT-PCR Assay for Monitoring of SARS-CoV-2 on Surfaces in Public and Working Environments. Int. J. Environ. Res. Public Health 2022, 19, 5861. https://doi.org/10.3390/ijerph19105861

AMA Style

Cardinale D, Tafuro M, Mancusi A, Girardi S, Capuano F, Proroga YTR, Corrado F, D’Auria JL, Coppola A, Rofrano G, et al. Sponge Whirl-Pak Sampling Method and Droplet Digital RT-PCR Assay for Monitoring of SARS-CoV-2 on Surfaces in Public and Working Environments. International Journal of Environmental Research and Public Health. 2022; 19(10):5861. https://doi.org/10.3390/ijerph19105861

Chicago/Turabian Style

Cardinale, Davide, Maria Tafuro, Andrea Mancusi, Santa Girardi, Federico Capuano, Yolande Thérèse Rose Proroga, Federica Corrado, Jacopo Luigi D’Auria, Annachiara Coppola, Giuseppe Rofrano, and et al. 2022. "Sponge Whirl-Pak Sampling Method and Droplet Digital RT-PCR Assay for Monitoring of SARS-CoV-2 on Surfaces in Public and Working Environments" International Journal of Environmental Research and Public Health 19, no. 10: 5861. https://doi.org/10.3390/ijerph19105861

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop