Evidence map›Paper›PMID 38802749›Full record

ArticleBMC medical research methodology2024

CalScope: methodology and lessons learned for conducting a remote statewide SARS-CoV-2 seroprevalence study in California using an at-home dried blood spot collection kit and online survey.

Esther Lim, Megha L Mehrotra, Katherine Lamba, Amanda Kamali, Kristina W Lai, Erika Meza, Stephanie Bertsch-Merbach, Irvin Szeto, Catherine Ley, Andrew B Martin and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Supporting rapid innovation in research data capture and management: the REDCap external module framework.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
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

19 authors.

Esther LimCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA. esther.lim@cdph.ca.gov.
Megha L MehrotraCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
Katherine LambaCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
Amanda KamaliCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
Kristina W LaiCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
Erika MezaCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
Stephanie Bertsch-MerbachCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
Irvin SzetoResearch IT, School of Medicine, Stanford University, Palo Alto, CA, USA.
Catherine LeyDepartment of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Andrew B MartinResearch IT, School of Medicine, Stanford University, Palo Alto, CA, USA.
Julie ParsonnetDepartment of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Peter RobinsonEnable Biosciences, South San Francisco, CA, USA.
David GebhartEnable Biosciences, South San Francisco, CA, USA.
Noemi FonsecaEnable Biosciences, South San Francisco, CA, USA.
Cheng-Ting TsaiEnable Biosciences, South San Francisco, CA, USA.
David SeftelEnable Biosciences, South San Francisco, CA, USA.
Allyx NicoliciCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
David MeltonCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.
Seema JainCalifornia Department of Public Health, Epidemiology, Surveillance, and Modeling Section, COVID-19 Response, Richmond, CA, USA.

Funding

Spectrum Stanford Center for clinical and Translational Research and EducationUL1TR001085 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$37.1M
ACL HHS U01CK000539CDC HHS 6NU50CK000539NCATS NIH HHS UL1 TR001085NCEZID CDC HHS U01 CK000539
6 · The paper itself

Abstract

backgroundTo describe the methodology for conducting the CalScope study, a remote, population-based survey launched by the California Department of Public Health (CDPH) to estimate SARS-CoV-2 seroprevalence and understand COVID-19 disease burden in California.

methodsBetween April 2021 and August 2022, 666,857 randomly selected households were invited by mail to complete an online survey and at-home test kit for up to one adult and one child. A gift card was given for each completed survey and test kit. Multiple customized REDCap databases were used to create a data system which provided task automation and scalable data management through API integrations. Support infrastructure was developed to manage follow-up for participant questions and a communications plan was used for outreach through local partners.

resultsAcross 3 waves, 32,671 out of 666,857 (4.9%) households registered, 6.3% by phone using an interactive voice response (IVR) system and 95.7% in English. Overall, 25,488 (78.0%) households completed surveys, while 23,396 (71.6%) households returned blood samples for testing. Support requests (n = 5,807) received through the web-based form (36.3%), by email (34.1%), and voicemail (29.7%) were mostly concerned with the test kit (31.6%), test result (26.8%), and gift card (21.3%).

conclusionsEnsuring a well-integrated and scalable data system, responsive support infrastructure for participant follow-up, and appropriate academic and local health department partnerships for study management and communication allowed for successful rollout of a large population-based survey. Remote data collection utilizing online surveys and at-home test kits can complement routine surveillance data for a state health department.

Indexed as

COVID-19Dried Blood Spot TestingSARS-CoV-2AdolescentAdultCaliforniaChildFemaleHumansMaleMiddle AgedSeroepidemiologic StudiesSurveys and QuestionnairesAt home testingHealth DepartmentPopulation-based surveillanceRemoteSARS-CoV-2

Identifiers

PMID38802749
PMCPMC11131314

What OpenQuestion 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 OpenQuestion graph.