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Data

Share of children with symptoms of a respiratory infection who received antibiotics

See all data and research on:
Antibiotics & Antibiotic Resistance

About this data

Share of children with symptoms of a respiratory infection who received antibiotics
The caregiver reported share of children under five years old, with symptoms of lower respiratory tract infection, who received antibiotics for this illness.
Source
Browne AJ et al. (2021) – processed by Our World in Data
Last updated
October 9, 2024
Date range
2000–2018
Unit
%

Related research and writing

Antibiotics and Antibiotic Resistance

Saloni Dattani, Fiona Spooner, Hannah Ritchie, and Max Roser

Sources and processing

This data is based on the following sources

Browne AJ et al. – Global Research on Antimicrobial Resistance (GRAM) - children

The Global Research on Antimicrobial Resistance (GRAM) Project is a partnership between the University of Oxford and the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, to provide rigorous quantitative estimates of antimicrobial resistance (AMR) burden; to increase global-, regional-, and country-level awareness of AMR; to boost surveillance efforts, particularly in low and middle income countries (LMICs); and, to promote the rational use of antimicrobials worldwide.

Retrieved on
October 9, 2024
Retrieved from
https://www.tropicalmedicine.ox.ac.uk/gram/research/visualisation-app-antibiotic-usage-and-consumption
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Browne AJ, Chipeta MG, Haines-Woodhouse G, et al. Global antibiotic consumption and usage in humans, 2000 to 2018: a spatial modelling study. Lancet Planetary Health 2021.

The Global Research on Antimicrobial Resistance (GRAM) Project is a partnership between the University of Oxford and the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, to provide rigorous quantitative estimates of antimicrobial resistance (AMR) burden; to increase global-, regional-, and country-level awareness of AMR; to boost surveillance efforts, particularly in low and middle income countries (LMICs); and, to promote the rational use of antimicrobials worldwide.

Retrieved on
October 9, 2024
Retrieved from
https://www.tropicalmedicine.ox.ac.uk/gram/research/visualisation-app-antibiotic-usage-and-consumption
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Browne AJ, Chipeta MG, Haines-Woodhouse G, et al. Global antibiotic consumption and usage in humans, 2000 to 2018: a spatial modelling study. Lancet Planetary Health 2021.

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All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

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  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
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Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Share of children with symptoms of a respiratory infection who received antibiotics”, part of the following publication: Saloni Dattani, Fiona Spooner, Hannah Ritchie, and Max Roser (2024) - “Antibiotics and Antibiotic Resistance”. Data adapted from Browne AJ et al.. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/antibiotic-usage-in-children.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Browne AJ et al. (2021) – processed by Our World in Data

Full citation

Browne AJ et al. (2021) – processed by Our World in Data. “Share of children with symptoms of a respiratory infection who received antibiotics” [dataset]. Browne AJ et al., “Global Research on Antimicrobial Resistance (GRAM) - children” [original data]. Retrieved March 31, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/antibiotic-usage-in-children.html (archived on March 4, 2026).

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Data API

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Data URL (CSV format)
https://ourworldindata.org/grapher/antibiotic-usage-in-children.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/antibiotic-usage-in-children.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/antibiotic-usage-in-children.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/antibiotic-usage-in-children.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/antibiotic-usage-in-children.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/antibiotic-usage-in-children.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/antibiotic-usage-in-children.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/antibiotic-usage-in-children.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear