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

被引:14
作者
Aguiar, M. [1 ]
Paul, R. [2 ]
Sakuntabhai, A. [2 ]
Stollenwerk, N. [1 ]
机构
[1] Univ Lisbon, Ctr Matemat & Aplicacoes Fundamentais, P-1649003 Lisbon, Portugal
[2] Inst Pasteur, Funct Genet Infect Dis Unit, Paris, France
关键词
Data analysis; dengue fever; multi-strain model; parameter estimation; predictability; HEMORRHAGIC-FEVER; EPIDEMIOLOGY; TRANSMISSION; PATHOGENICITY; ENHANCEMENT; PERSISTENCE; INFECTION; DYNAMICS; DISEASE;
D O I
10.1017/S0950268813003348
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:2447 / 2459
页数:13
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