Imperial College London
Alternate

Professor Nimalan Arinaminpathy (Nim Pathy)

Faculty of Medicine, School of Public Health

Professor in Mathematical Epidemiology
 
 
 
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Contact

 

nim.pathy Website

 
 
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Location

 

Praed StreetSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Fu:2020:10.1186/s12879-020-4914-2,
author = {Fu, H and Lin, H-H and Hallett, TB and Arinaminpathy, N},
doi = {10.1186/s12879-020-4914-2},
journal = {BMC Infectious Diseases},
title = {Explaining age disparities in tuberculosis burden in Taiwan: a modelling study},
url = {http://dx.doi.org/10.1186/s12879-020-4914-2},
volume = {20},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundTuberculosis (TB) burden shows wide disparities across ages in Taiwan. In 2016, the age-specific notification rate in those older than 65 years old was about 100 times as much as in those younger than 15 years old (185.0 vs 1.6 per 100,000 population). Similar patterns are observed in other intermediate TB burden settings. However, driving mechanisms for such age disparities are not clear and may have importance for TB control efforts.MethodsWe hypothesised three mechanisms for the age disparity in TB burden: (i) older age groups bear a higher risk of TB progression due to immune senescence, (ii) elderly cases acquired TB infection during a past period of high transmission, which has since rapidly declined and thus contributes to little recent infections, and (iii) assortative mixing by age allows elders to maintain a higher risk of TB infection, while limiting spillover transmission to younger age groups. We developed a series of dynamic compartmental models to incorporate these mechanisms, individually and in combination. The models were calibrated to the TB notification rates in Taiwan over 1997–2016 and evaluated by goodness-of-fit to the age disparities and the temporal trend in the TB burden, as well as the deviance information criterion (DIC). According to the model performance, we compared contributions of the hypothesised mechanisms.ResultsThe ‘full’ model including all the three hypothesised mechanisms best captured the age disparities and temporal trend of the TB notification rates. However, dropping individual mechanisms from the full model in turn, we found that excluding the mechanism of assortative mixing yielded the least change in goodness-of-fit. In terms of their influence on the TB dynamics, the major contribution of the ‘immune senescence’ and ‘assortative mixing’ mechanisms was to create disparate burden among age groups, while the ‘declining transmission’ mechanism s
AU  - Fu,H
AU  - Lin,H-H
AU  - Hallett,TB
AU  - Arinaminpathy,N
DO  - 10.1186/s12879-020-4914-2
PY  - 2020///
SN  - 1471-2334
TI  - Explaining age disparities in tuberculosis burden in Taiwan: a modelling study
T2  - BMC Infectious Diseases
UR  - http://dx.doi.org/10.1186/s12879-020-4914-2
UR  - http://hdl.handle.net/10044/1/78038
VL  - 20
ER  -
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