Evidence map›Paper›PMID 38507601›Full record

ArticleG3 (Bethesda, Md.)2024

Estimating between-country migration in pneumococcal populations.

Sophie Belman, Henri Pesonen, Nicholas J Croucher, Stephen D Bentley, Jukka Corander

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2024. 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. Review
  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

5 authors.

Sophie BelmanParasites and Microbes, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.ORCID 0000-0002-9778-7174
Henri PesonenOslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, 0372, Norway.ORCID 0000-0003-4500-2926
Nicholas J CroucherMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, White City Campus, Imperial College London, London W12 0BZ, UK.ORCID 0000-0001-6303-8768
Stephen D BentleyParasites and Microbes, Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.ORCID 0000-0001-8094-3751
Jukka CoranderDepartment of Biostatistics, University of Oslo, Oslo, 0372, Norway.ORCID 0000-0002-7752-1942

Funding

Bill and Melinda Gates Foundation OPP1034556Department for International Development MR/R015600/1Medical Research CouncilRoyal Society 104169/Z/14/ASir Henry Dale FellowshipWellcome WT098051Wellcome Sanger InstituteWellcome Trust
6 · The paper itself

Abstract

Streptococcus pneumoniae (the pneumococcus) is a globally distributed, human obligate opportunistic bacterial pathogen which, although often carried commensally, is also a significant cause of invasive disease. Apart from multi-drug resistant and virulent clones, the rate and direction of pneumococcal dissemination between different countries remains largely unknown. The ability for the pneumococcus to take a foothold in a country depends on existing population configuration, the extent of vaccine implementation, as well as human mobility since it is a human obligate bacterium. To shed light on its international movement, we used extensive genome data from the Global Pneumococcal Sequencing project and estimated migration parameters between multiple countries in Africa. Data on allele frequencies of polymorphisms at housekeeping-like loci for multiple different lineages circulating in the populations of South Africa, Malawi, Kenya, and The Gambia were used to calculate the fixation index (Fst) between countries. We then further used these summaries to fit migration coalescent models with the likelihood-free inference algorithms available in the ELFI software package. Synthetic datawere additionally used to validate the inference approach. Our results demonstrate country-pair specific migration patterns and heterogeneity in the extent of migration between different lineages. Our approach demonstrates that coalescent models can be effectively used for inferring migration rates for bacterial species and lineages provided sufficiently granular population genomics surveillance data. Further, it can demonstrate the connectivity of respiratory disease agents between countries to inform intervention policy in the longer term.

Indexed as

Streptococcus pneumoniaeAfricaGene FrequencyHumansKenyaPneumococcal Infectionsapproximate bayesian computation (ABC)bacterial populationsgenomicsmigrationpneumococcus

Identifiers

PMID38507601
PMCPMC11152062

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.