An attraction-repulsion point process model for respiratory syncytial virus infections

Joshua Goldstein, Murali Haran, Ivan Simeonov, John Fricks, Francesca Chiaromonte

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

How is the progression of a virus influenced by properties intrinsic to individual cells? We address this question by studying the susceptibility of cells infected with two strains of the human respiratory syncytial virus (RSV-A and RSV-B) in an in vitro experiment. Spatial patterns of infected cells give us insight into how local conditions influence susceptibility to the virus. We observe a complicated attraction and repulsion behavior, a tendency for infected cells to lump together or remain apart. We develop a new spatial point process model to describe this behavior. Inference on spatial point processes is difficult because the likelihood functions of these models contain intractable normalizing constants; we adapt an MCMC algorithm called double Metropolis-Hastings to overcome this computational challenge. Our methods are computationally efficient even for large point patterns consisting of over 10,000 points. We illustrate the application of our model and inferential approach to simulated data examples and fit our model to various RSV experiments. Because our model parameters are easy to interpret, we are able to draw meaningful scientific conclusions from the fitted models.

Original languageEnglish (US)
Pages (from-to)376-385
Number of pages10
JournalBiometrics
Volume71
Issue number2
DOIs
StatePublished - Jun 1 2015
Externally publishedYes

Fingerprint

Respiratory Syncytial Virus Infections
Point Process
Viruses
Process Model
Virus
Infection
viruses
Spatial Point Process
infection
Cell
Susceptibility
Human respiratory syncytial virus
Likelihood Functions
MCMC Algorithm
Normalizing Constant
Metropolis-Hastings
Model
cells
Spatial Pattern
Likelihood Function

Keywords

  • Intractable normalizing constant
  • Markov chain Monte Carlo
  • Spatial point process
  • Virus infections

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

An attraction-repulsion point process model for respiratory syncytial virus infections. / Goldstein, Joshua; Haran, Murali; Simeonov, Ivan; Fricks, John; Chiaromonte, Francesca.

In: Biometrics, Vol. 71, No. 2, 01.06.2015, p. 376-385.

Research output: Contribution to journalArticle

Goldstein, J, Haran, M, Simeonov, I, Fricks, J & Chiaromonte, F 2015, 'An attraction-repulsion point process model for respiratory syncytial virus infections', Biometrics, vol. 71, no. 2, pp. 376-385. https://doi.org/10.1111/biom.12267
Goldstein, Joshua ; Haran, Murali ; Simeonov, Ivan ; Fricks, John ; Chiaromonte, Francesca. / An attraction-repulsion point process model for respiratory syncytial virus infections. In: Biometrics. 2015 ; Vol. 71, No. 2. pp. 376-385.
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