Evidence map›Paper›PMID 32994752›Full record

ReviewEnvironment, development and sustainability2021

Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India.

Amit Awasthi, Aditi Sharma, Prabhjot Kaur, Balakrishnaiah Gugamsetty, Akshay Kumar

Abstract readReview
In one paragraph

Review in Environment, development and sustainability, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Retrospection of heatwave and heat index.Theoretical and applied climatology · 2022
    Article
  5. Article
  6. Review
  7. Investigation of the Importance of Climatic Factors in COVID-19 Worldwide Intensity.International journal of environmental research and public health · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Amit AwasthiDepartment of Physics, University of Petroleum and Energy Studies, Dehradun, UK 248007 India.ORCID 0000-0001-8811-2338
Aditi SharmaDepartment of Petroleum Engineering and Earth Sciences, University of Petroleum and Energy Studies, Dehradun, UK India.
Prabhjot KaurDepartment of Computer Science, Uttaranchal University, Dehradun, UK India.
Balakrishnaiah GugamsettyAerosol and Atmospheric Research Laboratory, Department of Physics, Sri Krishnadevaraya University, Anantapur, AP India.
Akshay KumarDepartment of Nanotechnology, Sri Guru Granth Sahib World University Fatehgarh Sahib, Fatehgarh Sahib, Punjab India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus disease is known as COVID-19, which is declared as a pandemic by the World Health Organization during March 2020. In this study, the COVID-19 connection with various weather parameters like temperature, wind speed, and relative humidity is investigated and the future scenario of COVID-19 is predicted based on the Gaussian model (GM). This study is conducted in Delhi, the capital city of India, during the lowest mobility rate due to strict lockdown nationwide for about two months from March 15 to May 17, 2020. Spearman correlation is applied to obtain the interconnection of COVID-19 cases with weather parameters. Based on statistical analysis, this has been observed that the temperature parameter shows a significant positive trend during the period of study. The number of confirmed cases of COVID-19 is fitted with respect to the number of days by using the Gaussian curve and it is estimated on the basis of the model that maximum cases will go up to 123,886 in number. The maximum number of cases will be observed during the range of 166 ± 36 days. It is also estimated by using the width of the fitted GM that it will take minimum of 10 months for the complete recovery from COVID-19. Additionally, the linear regression technique is used to find the trend of COVID-19 cases with temperature and it is estimated that with an increase in temperature by 1 °C, 30 new COVID-19 cases on daily basis will be expected to observe. This study is believed to be a preliminary study and to better understand the concrete relationship of coronavirus, at least one complete cycle is essential to investigate. The laboratory-based study is essential to be done to support the present field-based study. Henceforth, based on preliminary studies, significant inputs are put forth to the research community and government to formulate thoughtful strategies like medical facilities such as ventilators, beds, testing centers, quarantine centers, etc., to curb the effects of COVID-19.

Indexed as

CoronavirusCOVID-19Exposure studiesGaussian modelPandemicWeather parameters

Identifiers

PMID32994752
PMCPMC7515685

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.