The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
SARS-Cov-2RNA found on particulate matter of Bergamo in Northern Italy: First evidence
Open accessAbstract
Background The burden of COVID-19 was extremely severe in Northern Italy, an area characterized by high concentrations of particulate matter (PM), which is known to negatively affect human health. Consistently with evidence already available for other viruses, we initially hypothesized the possibility of SARS-CoV-2 presence on PM, and we performed a first experiment specifically aimed at confirming or excluding this research hyphotesys. Methods We have collected 34 PM10 samples in Bergamo area (the epicenter of the Italian COVID-19 epidemic) by using two air samplers over a continuous 3-weeks period. Filters were properly stored and underwent RNA extraction and amplification according to WHO protocols in two parallel blind analyses performed by two different authorized laboratories. Up to three highly specific molecular marker genes (E, N, and RdRP) were used to test the presence of SARS-CoV-2 RNA on particulate matter. Results The first test showed positive results for gene E in 15 out of 16 samples, simultaneously displaying positivity also for RdRP gene in 4 samples. The second blind test got 5 additional positive results for at least one of the three marker genes. Overall, we tested 34 RNA extractions for the E, N and RdRP genes, reporting 20 positive results for at least one of the three marker genes, with positivity separately confirmed for all the three markers. Control tests to exclude false positivities were successfully accomplished. Conclusion This is the first evidence that SARS-CoV-2 RNA can be present on PM, thus suggesting a possible use as indicator of epidemic recurrence.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR
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. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.3.2000045 · Cited by 7,344
Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M. G., Borelli, M., Palmisani, J., Di Gilio, A., Piscitelli, P., & Miani, A. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17082932 · Cited by 670
Self-citationExposure to air pollution and COVID-19 mortality in the United States
Wu, X., Nethery, R. C., Sabath, B. M., Braun, D., & Dominici, F. (2020) · ISEE Conference Abstracts · doi:10.1289/isee.2020.virtual.o-os-638 · Cited by 372
Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Licen, S., Perrone, M. G., Piazzalunga, A., Borelli, M., Palmisani, J., Di Gilio, A., et al. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-039338 · Cited by 282
Self-citationCollection, particle sizing and detection of airborne viruses
Pan, M., Lednicky, J. A., & Wu, C. ‐. (2019) · Journal of Applied Microbiology · doi:10.1111/jam.14278 · Cited by 261
Deposition rates of viruses and bacteria above the atmospheric boundary layer
Reche, I., D’Orta, G., Mladenov, N., Winget, D. M., & Suttle, C. A. (2018) · The ISME Journal · doi:10.1038/s41396-017-0042-4 · Cited by 234
An integrated model to predict the atmospheric spread of foot-and-mouth disease virus
SØRENSEN, J. H., MACKAY, D. K. J., JENSEN, C. Ø., & DONALDSON, A. I. (2000) · Epidemiology and Infection · doi:10.1017/s095026889900401x · Cited by 189
Optimized DNA extraction and metagenomic sequencing of airborne microbial communities
Jiang, W., Liang, P., Wang, B., Fang, J., Lang, J., Tian, G., Jiang, J., & Zhu, T. F. (2015) · Nature Protocols · doi:10.1038/nprot.2015.046 · Cited by 149
Zhao, Y., Richardson, B., Takle, E. S., Chai, L., Schmitt, D. C., & Xin, H. (2019) · Scientific Reports · doi:10.1038/s41598-019-47788-z · Cited by 146
Setti, L., Passarini, F., de Gennaro, G., Barbieri, P., Pallavicini, A., Ruscio, M., Piscitelli, P., Colao, A., & Miani, A. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17092986 · Cited by 120
Self-citation
Cited by
Identifying airborne transmission as the dominant route for the spread of COVID-19
Zhang, R., Li, Y., Zhang, A. L., Wang, Y., & Molina, M. J. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2009637117 · Cited by 1,236
Aerosol transmission of SARS-CoV-2? Evidence, prevention and control
Tang, S., Mao, Y., Jones, R. M., Tan, Q., Ji, J. S., Li, N., Shen, J., Lv, Y., Pan, L., Ding, P., et al. (2020) · Environment International · doi:10.1016/j.envint.2020.106039 · Cited by 553
Comunian, S., Dongo, D., Milani, C., & Palestini, P. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17124487 · Cited by 464
Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Licen, S., Perrone, M. G., Piazzalunga, A., Borelli, M., Palmisani, J., Di Gilio, A., et al. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-039338 · Cited by 282
Self-citationBourdrel, T., Annesi-Maesano, I., Alahmad, B., Maesano, C. N., & Bind, M.-A. (2021) · European Respiratory Review · doi:10.1183/16000617.0242-2020 · Cited by 224
Metadata
- Authors
- Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M. G., Borelli, M., Palmisani, J., Di Gilio, A., Torboli, V., Fontana, F., Clemente, L., Pallavicini, A., Ruscio, M., Piscitelli, P., & Miani, A.
- Venue
- Environmental Research
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 188
- Pages
- 109754
- ISSN
- 0013-9351 (ISSN-L)
- OpenAlex
- W3030030602
- Cited by
- 508
- References
- 12
- FWCI
- 13.37
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SARS-Cov-2RNA found on particulate matter of Bergamo in Northern Italy: First evidence. https://app.cochat.ai/papers/10.1016/j.envres.2020.109754
- The paper
- Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M. G., Borelli, M., Palmisani, J., Di Gilio, A., Torboli, V., Fontana, F., Clemente, L., Pallavicini, A., Ruscio, M., Piscitelli, P., & Miani, A. (2020). SARS-Cov-2RNA found on particulate matter of Bergamo in Northern Italy: First evidence. Environmental Research. https://doi.org/10.1016/j.envres.2020.109754
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.