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© Research
Publication : Epidemiology and infection

Are we modelling the correct dataset? Minimizing false predictions for dengue fever in Thailand

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Epidemiology and infection - 01 Nov 2014

Aguiar M, Paul R, Sakuntabhai A, Stollenwerk N

Link to Pubmed [PMID] – 25267408

Epidemiol. Infect. 2014 Nov;142(11):2447-59

Models describing dengue epidemics are parametrized on disease incidence data and therefore high-quality data are essential. For Thailand, two different sources of long-term dengue data are available, the hard copy data from 1980 to 2005, where hospital admission cases were notified, and the electronic files, from 2003 to the present, where clinically classified forms of disease, i.e. dengue fever, dengue haemorrhagic fever, and dengue shock syndrome, are notified using separate files. The official dengue notification data, provided by the Bureau of Epidemiology, Ministry of Public Health in Thailand, were cross-checked with dengue data used in recent publications, where an inexact continuous time-series was observed to be consistently used since 2003, affecting considerably the model dynamics and its correct application. In this paper, numerical analysis and simulation techniques giving insights on predictability are performed to show the effects of model parametrization by using different datasets.