Evidence map›Paper›PMID 34941865›Full record

ArticlePLoS computational biology2021

Estimating the contribution of HIV-infected adults to household pneumococcal transmission in South Africa, 2016-2018: A hidden Markov modelling study.

Deus Thindwa, Nicole Wolter, Amy Pinsent, Maimuna Carrim, John Ojal, Stefano Tempia, Jocelyn Moyes, Meredith McMorrow, Jackie Kleynhans, Anne von Gottberg and 4 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

14 authors.

Deus ThindwaCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID 0000-0003-4845-7862
Nicole WolterCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.ORCID 0000-0002-9526-0133
Amy PinsentCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Maimuna CarrimCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.ORCID 0000-0003-2717-5540
John OjalCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID 0000-0002-3010-1158
Stefano TempiaCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.ORCID 0000-0003-4395-347X
Jocelyn MoyesCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.ORCID 0000-0001-8040-1717
Meredith McMorrowInfluenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.ORCID 0000-0001-6363-4033
Jackie KleynhansCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.ORCID 0000-0001-7081-6273
Anne von GottbergCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.ORCID 0000-0002-0243-7455
Neil FrenchMalawi Liverpool Wellcome Trust Clinical Research Programme, Blantyre, Malawi.ORCID 0000-0003-4814-8293
PHIRST group
Cheryl CohenCentre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa.
Stefan FlascheCentre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID 0000-0002-5808-2606

Funding

Department of HealthNCIRD CDC HHS U01 IP001048Wellcome Trust 208812/Z/17/Z
6 · The paper itself

Abstract

Human immunodeficiency virus (HIV) infected adults are at a higher risk of pneumococcal colonisation and disease, even while receiving antiretroviral therapy (ART). To help evaluate potential indirect effects of vaccination of HIV-infected adults, we assessed whether HIV-infected adults disproportionately contribute to household transmission of pneumococci. We constructed a hidden Markov model to capture the dynamics of pneumococcal carriage acquisition and clearance observed during a longitudinal household-based nasopharyngeal swabbing study, while accounting for sample misclassifications. Households were followed-up twice weekly for approximately 10 months each year during a three-year study period for nasopharyngeal carriage detection via real-time PCR. We estimated the effect of participant's age, HIV status, presence of a HIV-infected adult within the household and other covariates on pneumococcal acquisition and clearance probabilities. Of 1,684 individuals enrolled, 279 (16.6%) were younger children (<5 years-old) of whom 4 (1.5%) were HIV-infected and 726 (43.1%) were adults (≥18 years-old) of whom 214 (30.4%) were HIV-infected, most (173, 81.2%) with high CD4+ count. The observed range of pneumococcal carriage prevalence across visits was substantially higher in younger children (56.9-80.5%) than older children (5-17 years-old) (31.7-50.0%) or adults (11.5-23.5%). We estimate that 14.4% (95% Confidence Interval [CI]: 13.7-15.0) of pneumococcal-negative swabs were false negatives. Daily carriage acquisition probabilities among HIV-uninfected younger children were similar in households with and without HIV-infected adults (hazard ratio: 0.95, 95%CI: 0.91-1.01). Longer average carriage duration (11.4 days, 95%CI: 10.2-12.8 vs 6.0 days, 95%CI: 5.6-6.3) and higher median carriage density (622 genome equivalents per millilitre, 95%CI: 507-714 vs 389, 95%CI: 311.1-435.5) were estimated in HIV-infected vs HIV-uninfected adults. The use of ART and antibiotics substantially reduced carriage duration in all age groups, and acquisition rates increased with household size. Although South African HIV-infected adults on ART have longer carriage duration and density than their HIV-uninfected counterparts, they show similar patterns of pneumococcal acquisition and onward transmission.

Indexed as

HIV InfectionsPneumococcal InfectionsAdolescentAdultAlgorithmsCarrier StateChildChild, PreschoolComputational BiologyFemaleHumansMaleMarkov ChainsMiddle AgedModels, StatisticalSouth Africa

Identifiers

PMID34941865
PMCPMC8699682

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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.