Evidence map›Paper›PMID 33270798›Full record

ArticlePloS one2020

Changes to the sample design and weighting methods of a public health surveillance system to also include persons not receiving HIV medical care.

Christopher H Johnson, Linda Beer, R Lee Harding, Ronaldo Iachan, Davia Moyse, Adam Lee, Tonja Kyle, Pranesh P Chowdhury, R Luke Shouse

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 44% of its field
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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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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 at 2 institutions in 1 country.

Christopher H JohnsonDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Linda BeerDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.ORCID 0000-0002-5781-8626
R Lee HardingICF International, Inc., Calverton, Maryland, United States of America.
Ronaldo IachanICF International, Inc., Calverton, Maryland, United States of America.
Davia MoyseICF International, Inc., Calverton, Maryland, United States of America.
Adam LeeICF International, Inc., Calverton, Maryland, United States of America.
Tonja KyleICF International, Inc., Calverton, Maryland, United States of America.
Pranesh P ChowdhuryDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
R Luke ShouseDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
ICF International (United States) · USCenters for Disease Control and Prevention · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe Medical Monitoring Project (MMP) is a public health surveillance system that provides representative estimates of the experiences and behaviors of adults with diagnosed HIV in the United States. In 2015, the sample design and frame of MMP changed from a system that only included HIV patients to one that captures the experiences of persons receiving and not receiving HIV care. We describe methods investigated for calculating survey weights, the approach chosen, and the benefits of using a dynamic surveillance registry as a sampling frame.

methodsMMP samples adults with diagnosed HIV from the National HIV Surveillance System, the HIV case surveillance registry for the United States. In the methodological study presented in this manuscript, we compared methods that account for sample design and nonresponse, including weighting class adjustment vs. propensity weighting and a single-stage nonresponse adjustment vs. sequential adjustments for noncontact and nonresponse. We investigated how best to adjust for non-coverage using surveillance data to post-stratify estimates.

resultsAfter assessing these methods, we chose as our preferred procedure weighting class adjustments and a single-stage nonresponse adjustment. Classes were constructed using variables associated with respondents' characteristics and important survey outcomes, chief among them laboratory results available from surveillance that served as a proxy for medical care.

conclusionsMMPs weighting procedures reduced sample bias by leveraging auxiliary information on medical care available from the surveillance registry sampling frame. Expanding MMPs population of focus provides important information on characteristics of persons with diagnosed HIV that complement the information provided by the surveillance registry. MMP methods can be applied to other disease registries or population-monitoring systems when more detailed information is needed for a population, with the detailed information obtained efficiently from a representative sample of the population covered by the registry.

Indexed as

Delivery of Health CarePublic Health SurveillanceAdultFemaleHIV InfectionsHumansMaleMiddle AgedUnited States

Identifiers

PMID33270798
PMCPMC7714102
OpenAlexW3109348209

What OpenQuestion holds

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Registered trials

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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.