Evidence map›Paper›PMID 34433092›Full record

ArticleMethods (San Diego, Calif.)2022

Fuzzy association analysis for identifying climatic and socio-demographic factors impacting the spread of COVID-19.

Sujoy Chatterjee, Deepmala Chakrabarty, Anirban Mukhopadhyay

Abstract read
In one paragraph

Article in Methods (San Diego, Calif.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Sujoy ChatterjeeDepartment of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India.
Deepmala ChakrabartyPrasanta Chandra Mahalanobis Mahavidyalaya, West Bengal State University, India.
Anirban MukhopadhyayDepartment of Computer Science and Engineering, University of Kalyani, India. Electronic address: anirban@klyuniv.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, the whole world witnessed the fatal outbreak of COVID-19 epidemic originating at Wuhan, Hubei province, China, during a mass gathering in a film festival. World Health Organization (WHO) has declared this COVID-19 as a pandemic due to its rapid spread across different countries within a few days. Several research works are being performed to understand the various influential factors responsible for spreading COVID. However, limited studies have been performed on how climatic and socio-demographic conditions may impact the spread of the virus. In this work, we aim to find the relationship of socio-demographic conditions, such as temperature, humidity, and population density of the regions, with the spread of COVID-19. The COVID data for different countries along with the social data are collected. For the experimental purpose, Fuzzy association rule mining is employed to infer the various relationships from the data. Moreover, to examine the seasonal effect, a streaming setting is also considered. The experimental results demonstrate various interesting insights to understand the impact of different factors on spreading COVID-19.

Indexed as

COVID-19DemographyDisease OutbreaksHumansPandemicsSARS-CoV-2Association rule miningClimatic factorsCOVID-19Fuzzy association rulesSocio-demographic factors

Identifiers

PMID34433092
PMCPMC8380196

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.