Effect of weather on COVID-19 spread in the US : A prediction model for India in 2020
Copyright © 2020 Elsevier B.V. All rights reserved..
The effect of weather on COVID-19 spread is poorly understood. Recently, few studies have claimed that warm weather can possibly slowdown the global pandemic, which has already affected over 1.6 million people worldwide. Clarification of such relationships in the worst affected country, the US, can be immensely beneficial to understand the role of weather in transmission of the disease in the highly populated countries, such as India. We collected the daily data of new cases in 50 US states between Jan 1-Apr 9, 2020 and also the corresponding weather information (i.e., temperature (T) and absolute humidity (AH)). Distribution modeling of new cases across AH and T, helped identify the narrow and vulnerable AH range. We validated the results for 10-day intervals against monthly observations, and also worldwide trends. The results were used to predict Indian regions which would be vulnerable to weather based spread in upcoming months of 2020. COVID-19 spread in the US is significant for states with 4 < AH < 6 g/m3 and number of new cases > 10,000, irrespective of the chosen time intervals for study parameters. These trends are consistent with worldwide observations, but do not correlate well with India so far possibly due the total cases reported per interval < 10,000. The results clarify the relationship between weather parameters and COVID-19 spread. The vulnerable weather parameters will help classify the risky geographic areas in different countries. Specifically, with further reporting of new cases in India, prediction of states with high risk of weather based spread will be apparent.
| Errataetall: |
ErratumIn: Sci Total Environ. 2020 Dec 15;748:142577. - PMID 33036768 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:728 |
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| Enthalten in: |
The Science of the total environment - 728(2020) vom: 01. Aug., Seite 138860 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Gupta, Sonal [VerfasserIn] |
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Date Completed 24.06.2020 Date Revised 10.01.2021 published: Print-Electronic ErratumIn: Sci Total Environ. 2020 Dec 15;748:142577. - PMID 33036768 Citation Status MEDLINE |
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| doi: |
10.1016/j.scitotenv.2020.138860 |
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| PPN (Katalog-ID): |
NLM309182670 |
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| 520 | |a The effect of weather on COVID-19 spread is poorly understood. Recently, few studies have claimed that warm weather can possibly slowdown the global pandemic, which has already affected over 1.6 million people worldwide. Clarification of such relationships in the worst affected country, the US, can be immensely beneficial to understand the role of weather in transmission of the disease in the highly populated countries, such as India. We collected the daily data of new cases in 50 US states between Jan 1-Apr 9, 2020 and also the corresponding weather information (i.e., temperature (T) and absolute humidity (AH)). Distribution modeling of new cases across AH and T, helped identify the narrow and vulnerable AH range. We validated the results for 10-day intervals against monthly observations, and also worldwide trends. The results were used to predict Indian regions which would be vulnerable to weather based spread in upcoming months of 2020. COVID-19 spread in the US is significant for states with 4 < AH < 6 g/m3 and number of new cases > 10,000, irrespective of the chosen time intervals for study parameters. These trends are consistent with worldwide observations, but do not correlate well with India so far possibly due the total cases reported per interval < 10,000. The results clarify the relationship between weather parameters and COVID-19 spread. The vulnerable weather parameters will help classify the risky geographic areas in different countries. Specifically, with further reporting of new cases in India, prediction of states with high risk of weather based spread will be apparent | ||
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| 700 | 1 | |a Chanda, Arnab |e verfasserin |4 aut | |
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