Investigation of effective climatology parameters on COVID-19 outbreak in Iran
(چکیده مقاله) :
Abstract :
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, intra-provincial 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.
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, intra-provincial 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.
(توضیحات تکمیلی) :
(توضیحات تکمیلی) :
Description :
مقاله ISI انگلیسی اصلی
سال انتشار: 2020
فایل ISI انگلیسی اصلی ، با فرمت Pdf
تعداد صفحات فایل ISI انگلیسی اصلی: 22 صفحه
سال انتشار: 2020
فایل ISI انگلیسی اصلی ، با فرمت Pdf
تعداد صفحات فایل ISI انگلیسی اصلی: 22 صفحه
Authors / Descriptions(نویسندگان/توضیحات): سال انتشار 2020 \ مقاله ISI انگلیسی اصلی \ نویسندگان: Mohsen Ahmadi, Abbas Sharifi, Shadi Dorosti, Saeid Jafarzadeh Ghoushchi, Negar Ghanbari
Sent date(تاریخ ارسال) :
1399/01/29 | 4/17/2020
Number of visits(تعداد بازدید):
871
Key words (کلمات کلیدی):
COVID-19, Climate, Iran, Outbreak, Sensitivity analysis.
Number of pages(تعداد صفحات) :
22
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