Evidence map›Paper›PMID 31190073›Full record

ArticleThe Journal of infectious diseases2019

High Genetic Diversity of Plasmodium falciparum in the Low-Transmission Setting of the Kingdom of Eswatini.

Michelle E Roh, Sofonias K Tessema, Maxwell Murphy, Nomcebo Nhlabathi, Nomcebo Mkhonta, Sibonakaliso Vilakati, Nyasatu Ntshalintshali, Manik Saini, Gugu Maphalala, Anna Chen and 6 more

Abstract read
In one paragraph

Article in The Journal of infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
–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

50 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Genetic metrics decodeFrontiers in genetics · 2026
    Article
  4. Genetic Diversity ofTropical medicine and infectious disease · 2025
    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

16 authors.

Michelle E RohMalaria Elimination Initiative, Institute of Global Health Sciences, University of California, San Francisco.
Sofonias K TessemaDivision of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco.
Maxwell MurphyDivision of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco.
Nomcebo NhlabathiNational Malaria Programme, Ministry of Health, Manzini.
Nomcebo MkhontaNational Malaria Programme, Ministry of Health, Manzini.
Sibonakaliso VilakatiNational Malaria Programme, Ministry of Health, Manzini.
Nyasatu NtshalintshaliClinton Health Access Initiative, Mbabane, Eswatini.
Manik SainiClinton Health Access Initiative, Mbabane, Eswatini.
Gugu MaphalalaMinistry of Health, Mbabane, Eswatini.
Anna ChenDivision of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco.
Jordan WilheimDivision of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco.
Lisa PrachMalaria Elimination Initiative, Institute of Global Health Sciences, University of California, San Francisco.
Roly GoslingMalaria Elimination Initiative, Institute of Global Health Sciences, University of California, San Francisco.
Simon KuneneMinistry of Health, Mbabane, Eswatini.
Michelle S HsiangMalaria Elimination Initiative, Institute of Global Health Sciences, University of California, San Francisco.
Bryan GreenhouseDivision of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California, San Francisco.

Funding

Evaluating Re-active Surveillance Strategies for Malaria Elimination in SwazilandK23AI101012 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI HSIANG, MICHELLE SANG · 2012 to 2016
$657k
NIAID NIH HHS K23 AI101012
6 · The paper itself

Abstract

backgroundTo better understand transmission dynamics, we characterized Plasmodium falciparum genetic diversity in Eswatini, where transmission is low and sustained by importation.

methodsTwenty-six P. falciparum microsatellites were genotyped in 66% of confirmed cases (2014-2016; N = 582). Population and within-host diversity were used to characterize differences between imported and locally acquired infections. Logistic regression was used to assess the added value of diversity metrics to classify imported and local infections beyond epidemiology data alone.

resultsParasite population in Eswatini was highly diverse (expected heterozygosity [HE] = 0.75) and complex: 67% polyclonal infections, mean multiplicity of infection (MOI) 2.2, and mean within-host infection fixation index (FWS) 0.84. Imported cases had comparable diversity to local cases but exhibited higher MOI (2.4 vs 2.0; P = .004) and lower mean FWS (0.82 vs 0.85; P = .03). Addition of MOI and FWS to multivariate analyses did not increase discrimination between imported and local infections.

conclusionsIn contrast to the common perception that P. falciparum diversity declines with decreasing transmission intensity, Eswatini isolates exhibited high parasite diversity consistent with high rates of malaria importation and limited local transmission. Estimates of malaria transmission intensity from genetic data need to consider the effect of importation, especially as countries near elimination.

Indexed as

Communicable Diseases, ImportedDNA, ProtozoanEpidemiological MonitoringEswatiniGenetic VariationGenome, ProtozoanHumansIncidenceMalaria, FalciparumMicrosatellite RepeatsPlasmodium falciparumDNA, ProtozoanEswatinimalariamalaria eliminationmicrosatellite genotypingparasite diversitypopulation geneticsSwazilandtransmission intensity

Identifiers

PMID31190073
PMCPMC6743842

What OpenQuestion holds

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LicenceCC BY
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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.