Time series analysis of human and bovine brucellosis in South Korea from 2005 to 2010

Lee, Hu Suk; Her, Moon; Levine, Michael A.; Moore, George E.

doi:10.1016/j.prevetmed.2012.12.003

Cited by 46 publications

(44 citation statements)

References 18 publications

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“…The white noise test of residuals was also performed according to the autocorrelation plot residuals graph. 28 The forecasting ability of the model was tested by the goodness of fit between the observed and expected numbers of bacillary dysentery cases 23,28,29 using the mean standard error (MSE), 30 …”

Section: Methodsmentioning

confidence: 99%

Meteorological Variables and Bacillary Dysentery Cases in Changsha City, China

Gao¹,

Zhang²,

Ding³

et al. 2014

The American Society of Tropical Medicine and Hygiene

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Abstract. This study aimed to investigate the association between meteorological-related risk factors and bacillary dysentery in a subtropical inland Chinese area: Changsha City. The cross-correlation analysis and the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model were used to quantify the relationship between meteorological factors and the incidence of bacillary dysentery. Monthly mean temperature, mean relative humidity, mean air pressure, mean maximum temperature, and mean minimum temperature were significantly correlated with the number of bacillary dysentery cases with a 1-month lagged effect. The ARIMAX models suggested that a 1 C rise in mean temperature, mean maximum temperature, and mean minimum temperature might lead to 14.8%, 12.9%, and 15.5% increases in the incidence of bacillary dysentery disease, respectively. Temperature could be used as a forecast factor for the increase of bacillary dysentery in Changsha. More public health actions should be taken to prevent the increase of bacillary dysentery disease with consideration of local climate conditions, especially temperature.

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Section: Methodsmentioning

confidence: 99%

Meteorological Variables and Bacillary Dysentery Cases in Changsha City, China

Gao¹,

Zhang²,

Ding³

et al. 2014

The American Society of Tropical Medicine and Hygiene

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“…A reduction of human brucellosis cases was nearly immediately achieved by reducing bovine brucellosis in South Korea (95).…”

Section: Zoonotic Brucellosismentioning

confidence: 99%

The quest for a true One Health perspective of brucellosis

Godfroid¹,

DeBolle²,

Roop³

et al. 2014

Rev. Sci. Tech. OIE

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SummaryOne Health is an interdisciplinary collaboration that aims at mitigating risks to human health arising from microorganisms present in non-human animal species, which have the potential to be transmitted and cause disease in humans. Different degrees of scientific collaboration and sectoral integration are needed for different types of zoonotic diseases, depending on the health and associated economic gains that can be expected from a One Health approach. Indeed, mitigating zoonotic risks related to emerging diseases with pandemic potential is different from mitigating risks related to endemic zoonotic diseases like brucellosis. Likewise, management of brucellosis at the wildlife-livestock interface in wildlife conservation areas is in essence different from mitigating transmission of a given Brucella species within its preferential host species, which in turn is different from mitigating the spillover of a given Brucella species to non-preferential host species, humans included. Brucellosis economic models often oversimplify and/or wrongly assess transmission between reservoir hosts and spillover hosts. Moreover, they may not properly value non-market outcomes, such as avoidance of human disease, consumer confidence and conservation biology issues. As a result, uncertainty is such that the economic predictions of these models can be questionable. Therefore, understanding the infection biology of Brucella species is a prerequisite. This paper reviews and highlights important features of the infection biology of Brucella species and the changing epidemiology of brucellosis that need to be integrated into a true One Health perspective of brucellosis.

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“…Recently, researchers are interested in forecasting the incidence of infectious disease, using the liner time series forecasting models such as seasonal auto-regressive integrated moving average (ARIMA) models [26]–[30]. However, most real time series always contain nonlinear structures, from which liner models cannot yield adequate results [31].…”

Section: Introductionmentioning

confidence: 99%

Application of a New Hybrid Model with Seasonal Auto-Regressive Integrated Moving Average (ARIMA) and Nonlinear Auto-Regressive Neural Network (NARNN) in Forecasting Incidence Cases of HFMD in Shenzhen, China

Zhou

Tan

et al. 2014

PLoS ONE

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BackgroundOutbreaks of hand-foot-mouth disease (HFMD) have been reported for many times in Asia during the last decades. This emerging disease has drawn worldwide attention and vigilance. Nowadays, the prevention and control of HFMD has become an imperative issue in China. Early detection and response will be helpful before it happening, using modern information technology during the epidemic.MethodIn this paper, a hybrid model combining seasonal auto-regressive integrated moving average (ARIMA) model and nonlinear auto-regressive neural network (NARNN) is proposed to predict the expected incidence cases from December 2012 to May 2013, using the retrospective observations obtained from China Information System for Disease Control and Prevention from January 2008 to November 2012.ResultsThe best-fitted hybrid model was combined with seasonal ARIMA and NARNN with 15 hidden units and 5 delays. The hybrid model makes the good forecasting performance and estimates the expected incidence cases from December 2012 to May 2013, which are respectively −965.03, −1879.58, 4138.26, 1858.17, 4061.86 and 6163.16 with an obviously increasing trend.ConclusionThe model proposed in this paper can predict the incidence trend of HFMD effectively, which could be helpful to policy makers. The usefulness of expected cases of HFMD perform not only in detecting outbreaks or providing probability statements, but also in providing decision makers with a probable trend of the variability of future observations that contains both historical and recent information.

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Time series analysis of human and bovine brucellosis in South Korea from 2005 to 2010

Cited by 46 publications

References 18 publications

Meteorological Variables and Bacillary Dysentery Cases in Changsha City, China

Meteorological Variables and Bacillary Dysentery Cases in Changsha City, China

The quest for a true One Health perspective of brucellosis

Application of a New Hybrid Model with Seasonal Auto-Regressive Integrated Moving Average (ARIMA) and Nonlinear Auto-Regressive Neural Network (NARNN) in Forecasting Incidence Cases of HFMD in Shenzhen, China

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