Evidence map›Paper›PMID 41635214›Full record

ArticlePublic health reports (Washington, D.C. : 1974)2026

Simplifying Public Health Recommendations: Use of a Public CDC Chatbot During the COVID-19 Pandemic, 2022-2024.

François M Castonguay, Melissa H Boyette, Dolly Katz, Tou Fong Lee, Rebecca McDaniel, Palak Patel, W Fred Smith, Peter D Way, Martin I Meltzer

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Public health reports (Washington, D.C. : 1974), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

François M CastonguayModeling Support Team, Contact Tracing and Innovation Section, State, Tribal, Local, and Territorial Task Force, CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.ORCID 0000-0002-0631-6992
Melissa H BoyetteModeling Support Team, Contact Tracing and Innovation Section, State, Tribal, Local, and Territorial Task Force, CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.ORCID 0000-0002-6338-6233
Dolly KatzModeling Support Team, Contact Tracing and Innovation Section, State, Tribal, Local, and Territorial Task Force, CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Tou Fong LeeDivision of Digital Media, Office of Communications, Immediate Office of the Director, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Rebecca McDanielDivision of Digital Media, Office of Communications, Immediate Office of the Director, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Palak PatelDivision of Digital Media, Office of Communications, Immediate Office of the Director, Centers for Disease Control and Prevention, Atlanta, GA, USA.
W Fred SmithDivision of Digital Media, Office of Communications, Immediate Office of the Director, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Peter D WayDivision of Digital Media, Office of Communications, Immediate Office of the Director, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Martin I MeltzerModeling Support Team, Contact Tracing and Innovation Section, State, Tribal, Local, and Territorial Task Force, CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, GA, USA.ORCID 0000-0002-7250-0472

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To help people with COVID-19 and their contacts quickly understand guidelines to prevent transmission, the Centers for Disease Control and Prevention (CDC) developed an interactive calculator that indicated whether and how long to stay home, get tested, wear face masks, and adopt other precautions. The CDC COVID-19 Calculator used a web-based chatbot format that mimicked a 2-person conversation. The calculator had the following design specifications: (1) reach an audience of people with COVID-19 (who tested positive or were symptomatic for COVID-19) and their close contacts and (2) provide an answer to the question "When can I leave home?" in less than 1 minute. To measure the use of the calculator, we analyzed the number of anonymous unique visitors and median visit time. The calculator had approximately 13.6 million visitors by March 1, 2024. The median visit time was 38 seconds, and approximately 65% of visits were via smartphones. The millions of unique visitors to the CDC COVID-19 Calculator demonstrated the usefulness of a conversational chatbot format to provide public health guidance. Future research should assess whether such tools influence behavior.

Indexed as

calculatorchatbotCOVID-19guidelinesinternetisolationpublic healthquarantine

Identifiers

PMID41635214
PMCPMC12872423

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.