Abstract: Science of the Total Environment 729 (2020) 138705 Contents lists available at ScienceDirect Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv Investigation of effective climatology parameters on COVID-19 outbreak in Iran Mohsen Ahmadi a, Abbas Sharifi b,⁎, Shadi Dorosti a, Saeid Jafarzadeh Ghoushchi a, Negar Ghanbari c a b c Department of Industrial Engineering, Urmia University of Technology (UUT), P.O. Box: 57166-419, Urmia, Iran Department of Mechanical Engineering, Urmia University of Technology (UUT), P.O. Box: 57166-419, Urmia, Iran Faculty of Medicine, Tabriz University of Medical Science, P.O. Box: 51666-16471, Tabriz, Iran H I G H L I G H T S G R A P H I C A L A B S T R A C T • Geographical and Climatological parameter is assessed to study COVID-19 outbreak. • Population density, intra-provincial movement have a direct relationship with the infection rate. • Humidity has a reverse relationship within the virus outbreak speed. • The outbreak at low speed of the wind is remarkable. • Solar radiation threats the virus's survival. a r t i c l e i n f o Article history: Received 6 April 2020 Received in revised form 13 April 2020 Accepted 13 April 2020 Available online 17 April 2020 Editor: Jianmin Chen Keywords: COVID-19 Climate Iran Outbreak Sensitivity analysis a b s t r a c t SARS CoV-2 (COVID-19) Coronavirus cases are confirmed throughout the world and millions of people are being put into quarantine. A better understanding of the effective parameters in infection spreading can bring about a logical measurement toward COVID-19. The effect of climatic factors on spreading of COVID-19 can play an important role in the new Coronavirus outbreak. In this study, the main parameters, including the number of infected people with COVID-19, population density, intra-provincial movement, and infection days to end of the study period, average temperature, average precipitation, humidity, wind speed, and average solar radiation investigated to understand how can these parameters effects on COVID-19 spreading in Iran? The Partial correlation coefficient (PCC) and Sobol’-Jansen methods are used for analyzing the effect and correlation of variables with the COVID-19 spreading rate. The result of sensitivity analysis shows that the population density, intraprovincial movement have a direct relationship with the infection outbreak. Conversely, areas with low values of wind speed, humidity, and solar radiation exposure to a high rate of infection that support the virus's survival. The provinces such as Tehran, Mazandaran, Alborz, Gilan, and Qom are more susceptible to infection because of high population density, intra-provincial movements and high humidity rate in comparison with Southern provinces. © 2020 Published by Elsevier B.V. ⁎ Corresponding author at: 5716693188. E-mail addresses: Mohsen.Ahmadi@ine.uut.ac.ir (M. Ahmadi), Abbas.Sharifi@mee.uut.ac.ir (A. Sharifi), Shadi.Dorosti@gmail.com (S. Dorosti), S.Jafarzadeh@uut.ac.ir (S. Jafarzadeh Ghoushchi), Negaringhanbari@gmail.com (N. Ghanbari). https://doi.org/10.1016/j.scitotenv.2020.138705 0048-9697/© 2020 Published by Elsevier B.V. 2 M. Ahmadi et al. / Science of the Total Environment 729 (2020) 138705