Evidence map›Paper›PMID 35154804›Full record

ArticleDigital health

A pilot study using financial transactions' spatial information to define high-risk neighborhoods and distribution pattern of COVID-19.

Esmaeil Mohammadi, Mehrdad Azmin, Nima Fattahi, Erfan Ghasemi, Sina Azadnajafabad, Negar Rezaei, Mohammad-Mahdi Rashidi, Mohammad Keykhaei, Hossein Zokaei, Nazila Rezaei and 5 more

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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

15 authors.

Esmaeil MohammadiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mehrdad AzminNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Nima FattahiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Erfan GhasemiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Sina AzadnajafabadNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Negar RezaeiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad-Mahdi RashidiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad KeykhaeiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Hossein ZokaeiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Nazila RezaeiNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Rosa HaghshenasNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Farzad KavehCenter for Communicable Diseases Control, Ministry of Health & Medical Education, Tehran, Iran.
Erfan PakatchianNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Hamidreza JamshidiResearch Institute for Endocrine Sciences, School of Medicine, Department of Pharmacology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farshad FarzadfarNon-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0001-8288-4046

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDevelopment of surveillance systems based on big data sources with spatial information is necessitated more than ever during this pandemic. Here, we present our pilot results of a new technique for the incorporation of spatial information of transactions and a vital registry of COVID-19 to evaluate the disease spread.

methodsWe merged two databases of laboratory-confirmed national COVID-19 registry of Iran and financial transactions of point-of-sale devices from February to March 2020 as our training data sources. Spatial information was used for the visualization of maps and movements of sick individuals. We used the point-of-sale devices-related guild to check for the dynamics of financial transactions and effectiveness of quarantines.

findingsIn the study period, 174,428 confirmed cases were in the COVID-19 registry with accompanying transactions information. In total, 13,924,982 financial transactions were performed by them, with a mean of 1.2 per day for each person. All guilds had a decreasing pattern of "risky" transactions except for grocery stores and pharmacies. The latter showed a decreasing pattern by impose of lockdowns. Different cities were the hotspot of disease transmission as many "high-risk" transactions were performed in them, among which Tehran (mainly its central neighborhoods) and southern cities of Lake Urmia predominated. Lockdowns indicated that the disease gradually became less transmissible.

interpretationFinancial transactions can be readily used for epidemics surveillance. Semi real-time results of such iterations can be informative for policy makers, guild owners, and general population to prepare safer commuting and merchandise spaces.

Indexed as

COVID-19epidemicspandemicsurveillancetransactions

Identifiers

PMID35154804
PMCPMC8832127

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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.