Abstract
BackgroundNew emerging diseases are public health concerns in which policy makers have to make decisions in the presence of enormous uncertainty. This is an important challenge in terms of emergency preparation requiring the operation of effective surveillance systems. A key concept to investigate the dynamic of infectious diseases is the basic reproduction number. However it is difficult to be applicable in real situations due to the underlying theoretical assumptions.MethodsIn this paper we propose a robust and flexible methodology for estimating disease strength varying in space and time using an alternative measure of disease transmission within the hierarchical modeling framework. The proposed measure is also extended to allow for incorporating knowledge from related diseases to enhance performance of surveillance system.ResultsA simulation was conducted to examine robustness of the proposed methodology and the simulation results demonstrate that the proposed method allows robust estimation of the disease strength across simulation scenarios. A real data example is provided of an integrative application of Dengue and Zika surveillance in Thailand. The real data example also shows that combining both diseases in an integrated analysis essentially decreases variability of model fitting.ConclusionsThe proposed methodology is robust in several simulated scenarios of spatiotemporal transmission force with computing flexibility and practical benefits. This development has potential for broad applicability as an alternative tool for integrated surveillance of emerging diseases such as Zika.
Highlights
New emerging diseases are public health concerns in which policy makers have to make decisions in the presence of enormous uncertainty
Application to dengue and Zika virus surveillance activities in Thailand Dengue is endemic in Thailand with peak transmission rates occur in the rainy season, between June and September, all across the country, but in northeastern Thailand
Note that the dengue patients included in this analysis were both who diagnosed with Dengue fever (DF) and Dengue hemorrhagic fever (DHF)
Summary
New emerging diseases are public health concerns in which policy makers have to make decisions in the presence of enormous uncertainty This is an important challenge in terms of emergency preparation requiring the operation of effective surveillance systems. A key concept in epidemiology to indicate the scale and speed of spread in a susceptible population is the transmissibility of the infection, Rotejanaprasert et al BMC Medical Research Methodology (2019) 19:200 characterized by the basic reproduction number, R0. This quantity has a definition of longer-term endemicity in a given population (R0 < 1 stops an epidemic) [3]. The basic reproduction number can be useful for understanding the transmissibility of an infectious disease, the methods based on fitting deterministic transmission models are often difficult to use and generalize in practice due to context-specific assumptions which often do not hold [6, 7]
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