Evaluation of the combined effect of mobility and seasonality on the COVID-19 pandemic: a Lombardy-based study

Evaluation of the combined effect of mobility and seasonality on the COVID-19 pandemic: a Lombardy-based study


  • Yuri Matteo Falzone a:1:{s:5:"en_US";s:72:"1. Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy";}
  • Luca Bosco
  • Giacomo Sferruzza
  • Tommaso Russo
  • Marco Vabanesi
  • Carlo Signorelli
  • Massimo Filippi


SARS-CoV2, UV, environmental factors, transmissibility, GAM analysis


Restrictions to human mobility had a significant role in limiting SARS-CoV-2 spread. It has been suggested that seasonality might affect viral transmissibility. Our study retrospectively investigates the combined effect that seasonal environmental factors and human mobility played on transmissibility of SARS-CoV-2 in Lombardy, Italy, in 2020.

Environmental data were collected from accredited open-source web services. Aggregated mobility data for different points of interests were collected from Google Community Reports. The Reproduction number (Rt), based on the weekly counts of confirmed symptomatic COVID-19, non-imported cases, was used as a proxy for SARS-CoV-2 transmissibility. Assuming a non-linear correlation between selected variables, we used a Generalized Additive Model (GAM) to investigate with univariate and multivariate analyses the association between seasonal environmental factors (UV-index, temperature, humidity, and atmospheric pressure), location-specific mobility indices, and Rt.

UV-index was the most effective environmental variable in predicting Rt. An optimal two-week lag-effect between changes in explanatory variables and Rt was selected. The association between Rt variations and individually taken mobility indices differed: Grocery & Pharmacy, Transit Station and Workplaces displayed the best performances in predicting Rt when individually added to the multivariate model together with UV-index, accounting for 85.0%, 85.5% and 82.6% of Rt variance, respectively. According to our results, both seasonality and social interaction policies played a significant role in curbing the pandemic. Non-linear models including UV-index and location-specific mobility indices can predict a considerable amount of SARS-CoV-2 transmissibility in Lombardy during 2020, emphasizing the importance of social distancing policies to keep viral transmissibility under control, especially during colder months.


WHO. Rolling updates on coronavirus disease (COVID-19). Available from: https://www. who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they- happen (accessed December 20, 2020).

Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? The Lancet. 2020;395:1225–8.

Google - COVID-19 Community Mobility Reports. Available from: https://www.google.com/covid19/mobility/ (accessed December 20, 2020).

Badr HS, Du H, Marshall M, Dong E, Squire MM, Gardner LM. Association between mobility patterns and COVID-19 transmission in the USA: a mathematical modelling study. The Lancet Infectious Diseases. 2020;20:1247–54.

Li Y, Campbell H, Kulkarni D, Harpur A, Nundy M, Wang X, et al. The temporal association of introducing and lifting non-pharmaceutical interventions with the time-varying reproduction number (R) of SARS-CoV-2: a modelling study across 131 countries. The Lancet Infectious Diseases. 2020;S1473309920307854.

Rader B, Scarpino SV, Nande A, Hill AL, Adlam B, Reiner RC, et al. Crowding and the shape of COVID-19 epidemics. Nat Med. 2020;26:1829–34.

Cacciapaglia G, Cot C, Sannino F. Second wave COVID-19 pandemics in Europe: a temporal playbook. Sci Rep. 2020;10:15514.

Yap TF, Liu Z, Shveda RA, Preston DJ. A predictive model of the temperature-dependent inactivation of coronaviruses. Appl Phys Lett. 2020;117:060601.

Schuit M, Ratnesar-Shumate S, Yolitz J, Williams G, Weaver W, Green B, et al. Airborne SARS-CoV-2 Is Rapidly Inactivated by Simulated Sunlight. The Journal of Infectious Diseases. 2020;222:564–71.

Goh GK-M, Dunker AK, Foster JA, Uversky VN. Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids. Microb Pathog. 2020;144:104177.

Bashir MF, Ma B, Bilal, Komal B, Bashir MA, Tan D, et al. Correlation between climate indicators and COVID-19 pandemic in New York, USA. Science of The Total Environment. 2020;728:138835.

Ma Y, Zhao Y, Liu J, He X, Wang B, Fu S, et al. Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China. Science of The Total Environment. 2020;724:138226.

Tosepu R, Gunawan J, Effendy DS, Ahmad LOAI, Lestari H, Bahar H, et al. Correlation between weather and Covid-19 pandemic in Jakarta, Indonesia. Science of The Total Environment. 2020;725:138436.

Isaia G, Diémoz H, Maluta F, Fountoulakis I, Ceccon D, di Sarra A, et al. Does solar ultraviolet radiation play a role in COVID-19 infection and deaths? An environmental ecological study in Italy. Sci Total Environ. 2020;143757.

Carlson CJ, Gomez ACR, Bansal S, Ryan SJ. Misconceptions about weather and seasonality must not misguide COVID-19 response. Nat Commun. 2020;11:4312.

Cori A, Ferguson NM, Fraser C, Cauchemez S. A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics. American Journal of Epidemiology. 2013;178:1505–12.

Guzzetta G, Merler S. Stime della trasmissibilità di SARS-CoV-2 in Italia [Internet]. 2020. Available from: https://www.epicentro.iss.it/coronavirus/open-data/rt.pdf

Zempila M-M, van Geffen JHGM, Taylor M, Fountoulakis I, Koukouli M-E, van Weele M, et al. TEMIS UV product validation using NILU-UV ground-based measurements in Thessaloniki, Greece. Atmos Chem Phys. 2017;17:7157–74.

The Royal Society. Reproduction number (R) and growth rate (r) of the COVID-19 epidemic in the UK: methods of estimation, data sources, causes of heterogeneity, and use as a guide in policy formulation [Internet]. Available from: https://royalsociety.org/-/media/policy/projects/set-c/set-covid-19-R-estimates.pdf?la=en-GB&hash=FDFFC11968E5D247D8FF641930680BD6 (accessed December 20, 2020).

The Johns Hopkins Coronavirus Resource Center (CRC) [Internet]. Available from: https://coronavirus.jhu.edu/map.html (accessed December 20, 2020).

Mallapaty S. Why COVID outbreaks look set to worsen this winter. Nature. 2020;586:653–653.

Carleton T, Cornetet J, Huybers P, Meng KC, Proctor J. Global evidence for ultraviolet radiation decreasing COVID-19 growth rates. Proc Natl Acad Sci USA. 2021;118:e2012370118.

Herman J, Biegel B, Huang L. Inactivation times from 290 to 315 nm UVB in sunlight for SARS coronaviruses CoV and CoV-2 using OMI satellite data for the sunlit Earth. Air Qual Atmos Health [Internet]. 2020 [cited 2021 Jan 21]; Available from: http://link.springer.com/10.1007/s11869-020-00927-2

Ratnesar-Shumate S, Williams G, Green B, Krause M, Holland B, Wood S, et al. Simulated Sunlight Rapidly Inactivates SARS-CoV-2 on Surfaces. The Journal of Infectious Diseases. 2020;222:214–22.

Prietl B, Treiber G, Pieber T, Amrein K. Vitamin D and Immune Function. Nutrients. 2013;5:2502–21.

Sehra ST, Salciccioli JD, Wiebe DJ, Fundin S, Baker JF. Maximum Daily Temperature, Precipitation, Ultraviolet Light, and Rates of Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 in the United States. Clinical Infectious Diseases. 2020;ciaa681.

Cacho PM, Hernández JL, López-Hoyos M, Martínez-Taboada VM. Can climatic factors explain the differences in COVID-19 incidence and severity across the Spanish regions?: An ecological study. Environ Health. 2020;19:106.

Kraemer MUG, Yang C-H, Gutierrez B, Wu C-H, Klein B, Pigott DM, et al. The effect of human mobility and control measures on the COVID-19 epidemic in China. Science. 2020;368:493–7.

Sulyok M, Walker M. Community movement and COVID-19: a global study using Google’s Community Mobility Reports. Epidemiol Infect. 2020;148:e284.

Adam D. A guide to R — the pandemic’s misunderstood metric. Nature. 2020;583:346–8.


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Evaluation of the combined effect of mobility and seasonality on the COVID-19 pandemic: a Lombardy-based study. Acta Biomed [Internet]. 2022 Aug. 31 [cited 2024 Jun. 23];93(4):e2022212. Available from: https://mattioli1885journals.com/index.php/actabiomedica/article/view/12645