Evidence map›Paper›PMID 41379607›Full record

ArticleEmerging infectious diseases2025

Community-Driven, Text Message-Based COVID-19 Surveillance System, Los Angeles County, California, USA, 2020-2024.

Jordan B Braunfeld, Elizabeth Traub, Howard Chiou, Aryana T Amoon, Christina Collins, Allison Joyce, Justin Buendia, Prabhu Gounder, Annabelle de St Maurice

Abstract read
In one paragraph

Article in Emerging infectious diseases, 2025. 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.

Jordan B Braunfeld
Elizabeth Traub
Howard Chiou
Aryana T Amoon
Christina Collins
Allison Joyce
Justin Buendia
Prabhu Gounder
Annabelle de St Maurice

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Respiratory virus indicators were unreliable at the onset of the COVID-19 pandemic when testing availability was limited and residents with mild symptoms were advised to avoid unnecessary medical care. The Los Angeles County Department of Public Health (Los Angeles, California, USA) developed Angelenos in Action (AiA), a text message-based community syndromic surveillance system to monitor respiratory illness trends. Approximately 17,000 unique participants responded >1 time; 43% of participants continue to regularly respond to the survey. We assessed AiA's performance by measuring correlation coefficients with reported COVID-19 case counts (0.975), sentinel laboratory SARS-CoV-2 test positivity rate (0.762), and wastewater SARS-CoV-2 concentrations (0.861). AiA performed strongly against 3 comparator surveillance methods and correlated particularly well with raw case counts. A moderate correlation was also noted between influenza test positivity rate and AiA data, indicating the system has potential to detect respiratory illness besides COVID-19.

Indexed as

COVID-19Text MessagingHumansLos AngelesPublic Health SurveillanceSARS-CoV-2CaliforniaCOVID-19influenzarespiratory infectionsSARS-CoV-2SurveillanceUnited Statesviruses

Identifiers

PMID41379607
PMCPMC12704538

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.