Abstract:
Coronavirus Disease-2019 (COVID-19) started in Wuhan province of China in November 2019 and within a short
time, it was declared as a worldwide pandemic by World Health Organisation due to the very fast worldwide
spread of the virus. There are a few studies that look for the correlation with infected individuals and different
environmental parameters using early data of COVID-19 but there is no study so far that deals with the variation
of effective reproduction number and environmental factors. Effective reproduction number is the driving
parameter of the spread of a pandemic and it is important to study the effect of various environmental factors on
effective reproduction number to understand the effect of those factors on the spread of the virus. We have used
time-dependent models to investigate the variation of different time-dependent driving parameters of COVID-19
like effective reproduction number and contact rate using data from India as a test case. India is a large population
country that is highly affected due to the COVID-19 pandemic and has a wide span of different temperature
and humidity regions and is ideal for such study. We have studied the impact of temperature and humidity on the
spread of the virus of different Indian states using time-dependent epidemiological models SIRD, and SEIRD for a
long time scale. We have used a linear regression method to look for any dependency between the effective
reproduction number with the relative humidity, absolute humidity, and temperature. The effective reproduction
number shows a negative correlation with both relative and absolute humidity for most of the Indian states,
which are statistically significant. This implies that relative and absolute humidity may have an important role in
the variation of effective reproduction number. Most of the states (six out of ten) show a positive correlation
while two (out of ten) show a negative correlation between effective reproduction number and average air
temperature for both SIRD and SEIRD models.
