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2.2. Cross‐correlation analysis

KB Kantha Rao Bhimala
GP Gopal Krishna Patra
RM Rajasekhar Mopuri
SM Srinivasa Rao Mutheneni
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To understand the weather impact on COVID‐19 cases, the cross‐correlation analysis was carried out to identify the similarities between the lagged meteorological parameters (X) and daily count of COVID‐19 cases (Y) for different states in India during the period 1 April to 31 July 2020. The cross‐correlation coefficients analysis helps identify whether the antecedent (lagged) meteorological parameters are useful predictors for modelling the COVID‐19 cases over different states in India. The cross‐correlation coefficient values are computed as:

where t, d, N represent the time in days, lag in days (0–14), and the total number of days (122) in time series data, respectively.

Copyright and License information:  ©2021 Wiley‐VCH GmbH
This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

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