Force of infection of Helicobacter pylori in Mexico: evidence from a national survey using a hierarchical Bayesian model

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Alarid-Escudero F, Enns EA, MacLehose R, Parsonnet J, Torres J, Kuntz KM. Force of infection of H. pylori in Mexico: Evidence from a national survey using a hierarchical Bayesian model. Epidemiology and Infection, 2018;146(8):961-9.

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BibTex

@article{alarid2018force,
  title={Force of infection of Helicobacter pylori in Mexico: evidence from a national survey using a hierarchical Bayesian model},
  author={Alarid-Escudero, F and Enns, EA and MacLehose, RF and Parsonnet, J and Torres, J and Kuntz, KM},
  journal={Epidemiology \& Infection},
  volume={146},
  number={8},
  pages={961--969},
  year={2018},
  publisher={Cambridge University Press}
}

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EndNote

%0 Journal Article
%T Force of infection of Helicobacter pylori in Mexico: evidence from a national survey using a hierarchical Bayesian model
%A Alarid-Escudero, F
%A Enns, EA
%A MacLehose, RF
%A Parsonnet, J
%A Torres, J
%A Kuntz, KM
%J Epidemiology & Infection
%V 146
%N 8
%P 961-969
%@ 0950-2688
%D 2018
%I Cambridge University Press

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RefMan

TY  - JOUR
T1  - Force of infection of Helicobacter pylori in Mexico: evidence from a national survey using a hierarchical Bayesian model
A1  - Alarid-Escudero, F
A1  - Enns, EA
A1  - MacLehose, RF
A1  - Parsonnet, J
A1  - Torres, J
A1  - Kuntz, KM
JO  - Epidemiology & Infection
VL  - 146
IS  - 8
SP  - 961
EP  - 969
SN  - 0950-2688
Y1  - 2018
PB  - Cambridge University Press
ER  - 

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Abstract

 

Background

Helicobacter pylori (H. pylori) is present in the stomach of half of the world’s population. The force of infection describes the rate at which susceptibles acquire infection. In this article, we estimated the age-specific force of infection of H. pylori in Mexico.

 

Methods

Data came from a national H. pylori seroepidemiology survey collected in Mexico in 1987–88. We modelled the number of individuals with H. pylori at a given age as a binomial random variable. We assumed that the cumulative risk of infection by a given age follows a modified exponential catalytic model, allowing some fraction of the population to remain uninfected.

 

Results

The cumulative risk of infection was modelled for each state in Mexico and were shrunk towards the overall national cumulative risk curve using Bayesian hierarchical models. The proportion of the population that can be infected (i.e. susceptible population) is 85.9% (95% credible interval (CR) 84.3%–87.5%). The constant rate of infection per year of age among the susceptible population is 0.092 (95% CR 0.084–0.100). The estimated force of infection was highest at birth 0.079 (95% CR 0.071–0.087) decreasing to zero as age increases.

 

Conclusions

This Bayesian hierarchical model allows stable estimation of state-specific force of infection by pooling information between the states, resulting in more realistic estimates.