Evidence map›Paper›PMID 34218496›Full record

ArticleHealth economics2021

Income gradient of pharmaceutical panic buying at the outbreak of the COVID-19 pandemic.

Péter Elek, Anikó Bíró, Petra Fadgyas-Freyler

Abstract read
In one paragraph

Article in Health economics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Household Pharmaceutical Waste Disposal as a Global Problem-A Review.International journal of environmental research and public health · 2022
    Review
  7. Article
  8. Article
  9. Article
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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.

Péter ElekCentre for Economic and Regional Studies, Budapest, Hungary.ORCID 0000-0001-6196-0767
Anikó BíróCentre for Economic and Regional Studies, Budapest, Hungary.ORCID 0000-0002-4833-4224
Petra Fadgyas-FreylerNational Health Insurance Fund Administration, Budapest, Hungary.ORCID 0000-0002-0858-8924

Funding

Hungarian Academy of Sciences János Bolyai Research ScholarshipMagyar Tudományos Akadémia "Lendület" research programme (no. LP2018-2/2018)Magyar Tudományos Akadémia "Lendület" research programme (no. LP2018-2/2018)OTKA (National Research, Development and Innovation Fund) research grant no. 134573.
6 · The paper itself

Abstract

We analyze the timing, magnitude, and income dependence of pharmaceutical panic buying around the outbreak of the COVID-19 pandemic in Hungary. We use district-level monthly and daily administrative data on detailed categories of pharmaceutical purchases, merge them to income statistics, and estimate multilevel panel models. Our main results are as follows. First, the days of therapy (DOT) of pharmaceutical purchases increased by more than 30% in March 2020, when major lockdown measures were announced. This pattern holds for almost all categories of pharmaceuticals. Second, shortly after the panic reactions, the aggregate amount of pharmaceutical purchases returned to their preshock levels; however, the frequency of pharmacy visits decreased. Third, the panic buying reaction was significantly stronger in richer geographical areas, where-according to the daily data-people also reacted earlier to the pandemic-related news. Overall, the results suggest that panic buying of pharmaceuticals can have detrimental effects on vulnerable populations.

Indexed as

COVID-19Pharmaceutical PreparationsPharmacyCommunicable Disease ControlHumansPandemicsSARS-CoV-2Pharmaceutical PreparationsCOVID-19inequalitypanic buyingpharmaceutical demand

Identifiers

PMID34218496
PMCPMC8420393

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.