Wikipedia Access

Attribute Details
Source Name wiki
Data Source Wikimedia pageviews for health-related Wikipedia articles
Geographic Levels Not applicable (article-based)
Temporal Granularity Hourly, Daily, and Weekly (Epiweek)
Available Articles 54 health-related articles
Reporting Cadence Inactive - No longer updated since 2021w11
Temporal Scope Start 2007w50 (December 9th, 2007)
License CC BY-SA

Overview

This data source measures public interest in health topics by tracking access counts for specific influenza-related articles on English-language Wikipedia. Delphi aggregates these counts from Wikimedia’s public pageview dumps, providing a proxy for information-seeking behavior and public awareness of the flu.

General topics not specific to any particular endpoint are discussed in the API overview. Such topics include: contributing, citing, and data licensing.

Table of contents

  1. Estimation
  2. Limitations
  3. The API
    1. Parameters
      1. Required
        1. Available Articles
          1. Influenza (Flu)
          2. Norovirus (Noro)
          3. Dengue
      2. Optional
    2. Response
  4. Example URLs
    1. Wikipedia Access article “influenza” on 2020w01
    2. Wikipedia Access article “influenza” on date 2020-01-01
  5. Code Samples
    1. Legacy Clients

Estimation

Counts are extracted directly from Wikimedia’s public pageviews dumps.

The available indicators include:

  • count: The number of pageviews for the specific article in the given language and time period.
  • total: The total number of pageviews for all articles in the specified language during the same time period.
  • value: The normalized pageview rate, calculated as (count / total) * 1,000,000 (views per million).

Counts are aggregated by hour and then summed to daily or weekly totals. No smoothing is applied.

Limitations

  • Information-seeking behaviour does not always correlate perfectly with disease incidence.

The API

The base URL is: https://api.delphi.cmu.edu/epidata/wiki/

Parameters

Required

Parameter Description Type
articles articles list of articles
language language (currently en, es, and pt supported) string
dates dates (see Date Formats) list of dates
epiweeks epiweeks (see Date Formats) list of epiweeks
Available Articles

Articles are categorized by the disease or condition they are most closely related to. Note that some articles (like “fever” or “nausea”) may overlap across categories.

Influenza (Flu)
Click to expand
Article Name
amantadine
antiviral_drugs
avian_influenza
canine_influenza
cat_flu
chills
common_cold
cough
equine_influenza
fatigue_(medical)
fever
flu_season
gastroenteritis
headache
hemagglutinin_(influenza)
human_flu
influenza
influenzalike_illness
influenzavirus_a
influenzavirus_c
influenza_a_virus
influenza_a_virus_subtype_h10n7
influenza_a_virus_subtype_h1n1
influenza_a_virus_subtype_h1n2
influenza_a_virus_subtype_h2n2
influenza_a_virus_subtype_h3n2
influenza_a_virus_subtype_h3n8
influenza_a_virus_subtype_h5n1
influenza_a_virus_subtype_h7n2
influenza_a_virus_subtype_h7n3
influenza_a_virus_subtype_h7n7
influenza_a_virus_subtype_h7n9
influenza_a_virus_subtype_h9n2
influenza_b_virus
influenza_pandemic
influenza_prevention
influenza_vaccine
malaise
myalgia
nasal_congestion
nausea
neuraminidase_inhibitor
orthomyxoviridae
oseltamivir
paracetamol
rhinorrhea
rimantadine
shivering
sore_throat
swine_influenza
viral_neuraminidase
viral_pneumonia
vomiting
zanamivir
Norovirus (Noro)
Click to expand
Article Name
abdominal_pain
caliciviridae
dehydration
diarrhea
fecal–oral_route
foodborne_illness
gastroenteritis
intravenous_therapy
leaky_scanning
nausea
norovirus
oral_rehydration_therapy
rotavirus
shellfish
vomiting
Dengue
Click to expand
Article Name
aedes
aedes_aegypti
arthralgia
blood_transfusion
dengue_fever
dengue_vaccine
dengue_virus
diarrhea
exanthem
fever
flavivirus
headache
hematuria
mosquito
mosquito-borne_disease
myalgia
nausea
nosebleed
paracetamol
petechia
rhinitis
thrombocytopenia
vomiting

Optional

Parameter Description Type
hours hours list of hours (0-23)

Notes:

  • Only one of dates and epiweeks is required. If both are provided, epiweeks is ignored.
  • dates, epiweeks, and hours are None by default.
  • language is en by default.

Response

Field Description Type
result result code: 1 = success, 2 = too many results, -2 = no results integer
epidata list of results array of objects
epidata[].article Wikipedia article name string
epidata[].count article-specific pageview count for the requested period/hours integer
epidata[].total total Wikipedia pageviews for the specified language (e.g., all English Wikipedia traffic) over the same period/hours integer
epidata[].hour hour (0-23) of access (-1 if not filtering by hour) integer
epidata[].date date (yyyy-MM-dd) string
epidata[].epiweek epiweek integer
epidata[].value normalized pageview count (pageviews per million total language traffic): (count / total) * 10^6 float
message success or error message string

Example URLs

Wikipedia Access article “influenza” on 2020w01

https://api.delphi.cmu.edu/epidata/wiki/?language=en&articles=influenza&epiweeks=202001

{
  "result": 1,
  "epidata": [
    {
      "article": "influenza",
      "count": 6516,
      "total": 663604044,
      "hour": -1,
      "epiweek": 202001,
      "value": 9.81910834
    }
  ],
  "message": "success"
}

Wikipedia Access article “influenza” on date 2020-01-01

https://api.delphi.cmu.edu/epidata/wiki/?language=en&articles=influenza&dates=20200101

{
  "result": 1,
  "epidata": [
    {
      "article": "influenza",
      "date": "2020-01-01",
      "count": 676,
      "total": 82359844,
      "hour": -1,
      "value": 8.20788344
    }
  ],
  "message": "success"
}

Code Samples

Libraries are available for R and Python. The following samples show how to import the library and fetch Wikipedia Access data for article “influenza” in English for epiweeks 202001-202010 (10 weeks total) and hours 0 and 12.

Install the package using pip:

pip install -e "git+https://github.com/cmu-delphi/epidatpy.git#egg=epidatpy"

# Import
from epidatpy import CovidcastEpidata, EpiDataContext, EpiRange
# Fetch data
epidata = EpiDataContext()
res = epidata.pub_wiki(articles=['influenza'], time_values=EpiRange(202001, 202010), time_type='week', language='en', hours=[0, 12])
print(res)

library(epidatr)
# Fetch data
res <- pub_wiki(articles = "influenza", time_values = epirange(202001, 202010),
                time_type = "week", language = "en", hours = c(0, 12))
print(res)

Legacy Clients

We recommend using the modern client libraries mentioned above. Legacy clients are also available for Python, R, and JavaScript.

Optionally install the package using pip(env):

pip install delphi-epidata

Otherwise, place delphi_epidata.py from this repo next to your python script.

# Import
from delphi_epidata import Epidata
# Fetch data
res = Epidata.wiki(['influenza'], Epidata.range(202001, 202010), {'time_type': 'week', 'language': 'en', 'hours': [0, 12]})
print(res['result'], res['message'], len(res['epidata']))

Place delphi_epidata.R from this repo next to your R script.

source("delphi_epidata.R")
# Fetch data
res <- Epidata$wiki(articles = list("influenza"), time_values = Epidata$range(202001, 202010), time_type = "week", options = list(language = "en", hours = list(0, 12)))
print(res$message)
print(length(res$epidata))

<!-- Imports -->
<script src="delphi_epidata.js"></script>
<!-- Fetch data -->
<script>
  EpidataAsync.wiki('influenza', EpidataAsync.range(202001, 202010), {time_type: 'week', language: 'en', hours: [0, 12]}).then((res) => {
    console.log(res.result, res.message, res.epidata != null ? res.epidata.length : 0);
  });
</script>