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 PM exceeding a daily limit of 50 µg/m.
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 PM 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 PM, we also considered population data and daily travelling information for each province.
Results: Exceedance of the daily limit value of PM 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 PM levels, while 62 out of 66 Southern provinces presented low PM 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 R>6.0, comparable with the highest values estimated for China.
Conclusion: A significant association has been found between the geographical distribution of daily PM exceedances and the initial spreading of COVID-19 in the 110 Italian provinces.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517216 | PMC |
http://dx.doi.org/10.1136/bmjopen-2020-039338 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!