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Experimental Human Pneumococcal Carriage
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Approximate likelihood-based estimation method of multiple-type pathogen interactions: An application to longitudinal

Irene Man1,2, Johannes A Bogaards1,3, Kishan Makwana1

  • 1Centre for Infectious Diseases Control, National Institute for Public Health and the Environment, Utrecht, The Netherlands.

Statistics in Medicine
|January 27, 2022
PubMed
Summary
This summary is machine-generated.

New Bayesian methods reveal Streptococcus pneumoniae serotype competition during colonization. Molecular detection data show competition in clearance, though the effect size is small, advancing our understanding of pneumococcal interactions.

Keywords:
Bayesian inferenceStreptococcus pneumoniaeapproximate likelihoodco-carriagelongitudinal datamultiple-type interactions

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Area of Science:

  • Microbiology
  • Epidemiology
  • Biostatistics

Background:

  • Streptococcus pneumoniae serotypes compete during human host colonization.
  • Understanding the mechanisms of pneumococcal between-type competition is incomplete.
  • Molecular detection methods provide more comprehensive co-carriage data than traditional culture methods.

Purpose of the Study:

  • To develop a Bayesian estimation method for inferring between-type interactions from longitudinal carriage data.
  • To enable inference from data with co-carriage of multiple serotypes, common with molecular detection.
  • To address computational challenges of analyzing complex co-carriage data.

Main Methods:

  • Developed a Bayesian estimation method using longitudinal presence/absence data.
  • Employed a multi-state model approximation to handle computational burden.
  • Validated the method on simulated data and incorporated random effects to correct for confounding.
  • Applied the method to empirical data on pneumococcal carriage in infants.

Main Results:

  • The Bayesian method provided unbiased estimates of interaction parameters with short sampling intervals.
  • The ratio of interaction parameters, reflecting total interaction, remained unbiased even with less frequent sampling.
  • New evidence for between-serotype competition in clearance was found in infant carriage data.
  • The identified competition in clearance had a small effect size.

Conclusions:

  • The developed Bayesian method effectively infers pneumococcal serotype interactions from longitudinal molecular data.
  • The study provides new evidence for competition among Streptococcus pneumoniae serotypes during the clearance phase of colonization.
  • Findings contribute to a more complete understanding of the ecological dynamics of pneumococcal colonization.