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Potential role of particulate matter in the spreading of COVID-19 in Northern Italy: first observational study based on initial epidemic diffusion
  1. Leonardo Setti1,
  2. Fabrizio Passarini1,
  3. Gianluigi De Gennaro2,
  4. Pierluigi Barbieri3,
  5. Sabina Licen3,
  6. Maria Grazia Perrone4,
  7. Andrea Piazzalunga5,
  8. Massimo Borelli3,
  9. Jolanda Palmisani2,
  10. Alessia Di Gilio2,
  11. Emanuele Rizzo6,
  12. Annamaria Colao7,
  13. Prisco Piscitelli8,
  14. Alessandro Miani9
  1. 1Industrial Chemistry “Toso Montanari”, University of Bologna, Bologna, Emilia-Romagna, Italy
  2. 2Biology, University of Bari “Aldo Moro”, Bari, Puglia, Italy
  3. 3Chemical and Pharmaceutical Sciences, University of Trieste, Trieste, Friuli-Venezia Giulia, Italy
  4. 4TCR TECORA, Milan, Italy
  5. 5Water & Life Lab, Bergamo, Japan
  6. 6Italian Society of Environmental Medicine, SIMA, Milan, Italy
  7. 7Medicina Clinica e Chirurgia, University of Naples Federico II, Napoli, Campania, Italy
  8. 8Euro Mediterranean Scientific Biomedical Institute, Bruxelles, Belgium
  9. 9Scienze e Politiche Ambientali, University of Milan, Milano, Lombardia, Italy
  1. Correspondence to Dr Leonardo Setti; leonardo.setti{at}


Objectives A number of studies have shown that the airborne transmission route could spread some viruses over a distance of 2 meters from an infected person. An epidemic model based only on respiratory droplets and close contact could not fully explain the regional differences in the spread of COVID-19 in Italy. On March 16th 2020, we presented a position paper proposing a research hypothesis concerning the association between higher mortality rates due to COVID-19 observed in Northern Italy and average concentrations of PM10 exceeding a daily limit of 50 µg/m3.

Methods To monitor the spreading of COVID-19 in Italy from February 24th to March 13th (the date of the Italian lockdown), official daily data for PM10 levels were collected from all Italian provinces between February 9th and February 29th, taking into account the maximum lag period (14 days) between the infection and diagnosis. In addition to the number of exceedances of the daily limit value of PM10, we also considered population data and daily travelling information for each province.

Results Exceedance of the daily limit value of PM10 appears to be a significant predictor of infection in univariate analyses (p<0.001). Less polluted provinces had a median of 0.03 infections over 1000 residents, while the most polluted provinces showed a median of 0.26 cases. Thirty-nine out of 41 Northern Italian provinces resulted in the category with the highest PM10 levels, while 62 out of 66 Southern provinces presented low PM10 concentrations (p<0.001). In Milan, the average growth rate before the lockdown was significantly higher than in Rome (0.34 vs 0.27 per day, with a doubling time of 2.0 days vs 2.6, respectively), thus suggesting a basic reproductive number R0>6.0, comparable with the highest values estimated for China.

Conclusion A significant association has been found between the geographical distribution of daily PM10 exceedances and the initial spreading of COVID-19 in the 110 Italian provinces.

  • epidemiology
  • public health
  • virology

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  • Contributors LS, FP, GDG, PB, MGP, AP, MB, SL, JP, ADG, ER, AC, PP, AM equally contributed to conceive, design, write, manage and revise the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Map disclaimer The depiction of boundaries on the map(s) in this article does not imply the expression of any opinion whatsoever on the part of BMJ (or any member of its group) concerning the legal status of any country, territory, jurisdiction or area or of its authorities. The map(s) are provided without any warranty of any kind, either express or implied.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available in a public, open access repository. All data are published at and available upon request to the corresponding author email