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Cited by 117Antibiotic Use and ResistanceCOVID-19 and healthcare impactsCOVID-19 Clinical Research Studies

The DOI matches its Crossref record; 52 of the 53 references it cites were found in a registry or an index.

Sales of antibiotics and hydroxychloroquine in India during the COVID-19 epidemic: An interrupted time series analysis

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Sulis, Giorgia, Batomen, Brice, Kotwani, Anita, Pai, Madhukar, Gandra, Sumanth·2021·PLoS Medicine
DOI 10.1371/journal.pmed.1003682PMC PMC8248656
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Abstract

BACKGROUND: We assessed the impact of the coronavirus disease 2019 (COVID-19) epidemic in India on the consumption of antibiotics and hydroxychloroquine (HCQ) in the private sector in 2020 compared to the expected level of use had the epidemic not occurred. METHODS AND FINDINGS: We performed interrupted time series (ITS) analyses of sales volumes reported in standard units (i.e., doses), collected at regular monthly intervals from January 2018 to December 2020 and obtained from IQVIA, India. As children are less prone to develop symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, we hypothesized a predominant increase in non-child-appropriate formulation (non-CAF) sales. COVID-19-attributable changes in the level and trend of monthly sales of total antibiotics, azithromycin, and HCQ were estimated, accounting for seasonality and lockdown period where appropriate. A total of 16,290 million doses of antibiotics were sold in India in 2020, which is slightly less than the amount in 2018 and 2019. However, the proportion of non-CAF antibiotics increased from 72.5% (95% CI: 71.8% to 73.1%) in 2019 to 76.8% (95% CI: 76.2% to 77.5%) in 2020. Our ITS analyses estimated that COVID-19 likely contributed to 216.4 million (95% CI: 68.0 to 364.8 million; P = 0.008) excess doses of non-CAF antibiotics and 38.0 million (95% CI: 26.4 to 49.2 million; P < 0.001) excess doses of non-CAF azithromycin (equivalent to a minimum of 6.2 million azithromycin treatment courses) between June and September 2020, i.e., until the peak of the first epidemic wave, after which a negative change in trend was identified. In March 2020, we estimated a COVID-19-attributable change in level of +11.1 million doses (95% CI: 9.2 to 13.0 million; P < 0.001) for HCQ sales, whereas a weak negative change in monthly trend was found for this drug. Study limitations include the lack of coverage of the public healthcare sector, the inability to distinguish antibiotic and HCQ sales in inpatient versus outpatient care, and the suboptimal number of pre- and post-epidemic data points, which could have prevented an accurate adjustment for seasonal trends despite the robustness of our statistical approaches. CONCLUSIONS: A significant increase in non-CAF antibiotic sales, and particularly azithromycin, occurred during the peak phase of the first COVID-19 epidemic wave in India, indicating the need for urgent antibiotic stewardship measures.

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Crossref · 10.1371/journal.pmed.1003682

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Figures

Fig 1 Trend in sales volumes of total antibiotics, azithromycin, doxycycline, faropenem, and HCQ in India from January 2018 to December 2020. CAF, non-CAF, and total sales are presented in the graphs, as relevant. Data on antibiotics are inclusive of azithromycin. HCQ and faropenem are only shown as non-CAFs because CAFs are not available for these drugs. As only a very small proportion of doxycycline is sold as CAF, this is omitted in the graph. CAF, child appropriate formulations; HCQ, hydroxychloroquine, SU, standard unit.
Fig 1 Trend in sales volumes of total antibiotics, azithromycin, doxycycline, faropenem, and HCQ in India from January 2018 to December 2020. CAF, non-CAF, and total sales are presented in the graphs, as relevant. Data on antibiotics are inclusive of azithromycin. HCQ and faropenem are only shown as non-CAFs because CAFs are not available for these drugs. As only a very small proportion of doxycycline is sold as CAF, this is omitted in the graph. CAF, child appropriate formulations; HCQ, hydroxychloroquine, SU, standard unit.CC BY · PubMed Central
Fig 2 Relationship between new COVID-19 cases per 100,000 (cumulative rate per month) and national sales volumes of antibiotics, azithromycin, doxycycline, faropenem, and HCQ from January to December 2020. CAF, non-CAF, and total sales are reported. Data on antibiotics are inclusive of azithromycin. HCQ and faropenem are only shown as non-CAFs because CAFs are not available for these drugs. As only a very small proportion of doxycycline is sold as CAF, this is omitted in the graph. CAF, child-appropriate formulation; HCQ, hydroxychloroquine, SU, standard unit.
Fig 2 Relationship between new COVID-19 cases per 100,000 (cumulative rate per month) and national sales volumes of antibiotics, azithromycin, doxycycline, faropenem, and HCQ from January to December 2020. CAF, non-CAF, and total sales are reported. Data on antibiotics are inclusive of azithromycin. HCQ and faropenem are only shown as non-CAFs because CAFs are not available for these drugs. As only a very small proportion of doxycycline is sold as CAF, this is omitted in the graph. CAF, child-appropriate formulation; HCQ, hydroxychloroquine, SU, standard unit.CC BY · PubMed Central
Fig 3 Relationship between new COVID-19 cases per 100,000 (cumulative rate per month) and azithromycin sales volumes per 100,000 population (only non-child-appropriate formulations) in 10 states of India from January to September 2020. States with the highest rates of detected COVID-19 cases are shown on the left side of the graph, whereas states with the lowest rates of detected COVID-19 cases are on the right.
Fig 3 Relationship between new COVID-19 cases per 100,000 (cumulative rate per month) and azithromycin sales volumes per 100,000 population (only non-child-appropriate formulations) in 10 states of India from January to September 2020. States with the highest rates of detected COVID-19 cases are shown on the left side of the graph, whereas states with the lowest rates of detected COVID-19 cases are on the right.CC BY · PubMed Central
Fig 4 Results of segmented regression analysis for monthly sales volumes of non-CAF antibiotics, azithromycin, and HCQ between January 2018 and December 2020.
Fig 4 Results of segmented regression analysis for monthly sales volumes of non-CAF antibiotics, azithromycin, and HCQ between January 2018 and December 2020.CC BY · PubMed Central

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Citations

Cites

Research works printed but not linked: 10

  1. R Nieuwlaat, 2021, COVID-19 and antimicrobial resistance: parallel and interacting health emergencies, Clin Infect Dis, 72, 1657
  2. Indian Council of Medical Research, 2019, Treatment guidelines for antimicrobial use in common syndromes
  3. Directorate of National Vector Borne Disease Control Programme, 2013, National drug policy on malaria
  4. World Health Organization, 2020, Clinical management of COVID-19. Interim guidance—27 May 2020
  5. PRS Legislative Research, 2020, COVID-19: details on cases
  6. National Commission on Population, 2019, Population projections for India and States, 2011–2036: report of the Technical Group on population projections
  7. WHO Collaborating Centre for Drug Statistics Methodology, 2021, ATC/DDD index 2021
  8. Centers for Disease Control and Prevention, 2020, COVID data tracker: demographic trends of COVID-19 cases and deaths in the US reported to CDC
  9. Directorate General of Health Services, 2020, Clinical management protocol: COVID-19
  10. Department of Health and Family Welfare, 2020, Notification. The Gazette of India: extraordinary

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Metadata

Authors
Sulis, G., Batomen, B., Kotwani, A., Pai, M., & Gandra, S.
Affiliations
  • McGill University (CA)
  • University of Toronto (CA)
  • University of Delhi (IN)
  • Washington University in St. Louis (US)
Corresponding author
Gandra, Sumanth
ORCID
Venue
PLoS Medicine
Publisher
Public Library of Science (PLoS)
Published
2021-07-01
Volume
18
Issue
7
Pages
e1003682
ISSN
  • 1549-1277 (ISSN-L)
  • 1549-1676
DOI
10.1371/journal.pmed.1003682
PMC
PMC8248656
OpenAlex
W3175638899
Cited by
117
References
53
Citations by year
2026: 5 · 2025: 11 · 2024: 15 · 2023: 37 · 2022: 37 · 2021: 12
FWCI
14.63
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Imperial College London
  • University of California, San Francisco
  • School of Public Health, Imperial College London
  • School of Medicine, University of California, San Francisco
Topics
  • Health Sciences › Medicine › Infectious Diseases › Antibiotic Use and Resistance
  • Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Keywords
COVID-19 pandemic, antibiotic sales, hydroxychloroquine, azithromycin, India, lockdown, inappropriate antibiotic use, SARS-CoV-2
MeSH terms
COVID-19, SARS-CoV-2, COVID-19 Drug Treatment, Anti-Bacterial Agents, Commerce, Drug Compounding, Drug Utilization, Humans, Hydroxychloroquine, India, Pandemics, Interrupted Time Series Analysis

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