Evidence map›Paper›PMID 34166310›Full record

ArticleJournal of acquired immune deficiency syndromes (1999)2021

Data Architecture to Support Real-Time Data Analytics for the Population-Based HIV Impact Assessments.

Melissa Metz, Rebecca Smith, Rick Mitchell, Yen T Duong, Kristin Brown, Steve Kinchen, Kiwon Lee, Francis M Ogollah, Tafadzwa Dzinamarira, Vusumuzi Maliwa and 5 more

Abstract read
In one paragraph

Article in Journal of acquired immune deficiency syndromes (1999), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

15 authors.

Melissa MetzICAP at Columbia University, New York, NY.
Rebecca SmithICAP at Columbia University, New York, NY.
Rick MitchellICAP at Columbia University, New York, NY.
Yen T DuongICAP at Columbia University, New York, NY.
Kristin BrownDivision of Global HIV and TB, Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, GA; and.
Steve KinchenDivision of Global HIV and TB, Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, GA; and.
Kiwon LeeICAP at Columbia University, New York, NY.
Francis M OgollahICAP at Columbia University, New York, NY.
Tafadzwa DzinamariraICAP at Columbia University, New York, NY.
Vusumuzi MaliwaICAP at Columbia University, New York, NY.
Carole MooreDivision of Global HIV and TB, Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, GA; and.
Hetal PatelDivision of Global HIV and TB, Center for Global Health, U.S. Centers for Disease Control and Prevention, Atlanta, GA; and.
Hannah ChungICAP at Columbia University, New York, NY.
Helecks MtengoICAP at Columbia University, New York, NY.
Suzue SaitoICAP at Columbia University, New York, NY.

Funding

CGH CDC HHS U2G GH000994CGH CDC HHS U2G GH001226PEPFAR
6 · The paper itself

Abstract

BACKGROUND AND

settingElectronic data capture facilitates timely use of data. Population-based HIV impact assessments (PHIAs) were led by host governments, with funding from the President's Emergency Plan for AIDS Relief, technical assistance from the Centers for Disease Control, and implementation support from ICAP at Columbia University. We described data architectures, code-based processes, and resulting data volume and quality for 14 national PHIA surveys with concurrent timelines and varied country-level data governance (2015-2020).

methodsPHIA project data were collected through tablets, point-of-care and laboratory testing instruments, and inventory management systems, using open-source software, vendor solutions, and custom-built software. Data were securely uploaded to the PHIA data warehouse daily or weekly and then used to populate survey-monitoring dashboards and return timely laboratory-based test results on an ongoing basis. Automated data processing allowed timely reporting of survey results.

resultsFourteen data architectures were successfully established, and data from more than 450,000 participants in 30,000 files across 13 countries with completed PHIAs, and blood draws producing approximately 6000 aliquots each week per country, were securely collected, transmitted, and processed by 17 full-time equivalent staff. More than 25,600 viral load results were returned to clinics of participants' choice. Data cleaning was not needed for 98.5% of household and 99.2% of individual questionnaires.

conclusionThe PHIA data architecture permitted secure, simultaneous collection and transmission of high-quality interview and biomarker data across multiple countries, quick turnaround time of laboratory-based biomarker results, and rapid dissemination of survey outcomes to guide President's Emergency Plan for AIDS Relief epidemic control.

Indexed as

Health SurveysHIV-1Anti-HIV AgentsData ScienceDeveloping CountriesEpidemiological MonitoringHIV InfectionsHumansInternational CooperationSpecimen HandlingViral LoadAnti-HIV Agents

Identifiers

PMID34166310
PMCPMC10897861

What OpenQuestion holds

Textmetadata
LicenceTDM
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.