High Mean Water Vapour Pressure Promotes the Transmission of Bacillary Dysentery

Bacillary dysentery is an infectious disease caused by Shigella dysenteriae, which has a seasonal distribution. External environmental factors, including climate, play a significant role in its transmission. This paper identifies climate-related risk factors and their role in bacillary dysentery transmission. Harbin, in northeast China, with a temperate climate, and Quzhou, in southern China, with a subtropical climate, are chosen as the study locations. The least absolute shrinkage and selectionator operator is applied to select relevant climate factors involved in the transmission of bacillary dysentery. Based on the selected relevant climate factors and incidence rates, an AutoRegressive Integrated Moving Average (ARIMA) model is established successfully as a time series prediction model. The numerical results demonstrate that the mean water vapour pressure over the previous month results in a high relative risk for bacillary dysentery transmission in both cities, and the ARIMA model can successfully perform such a prediction. These results provide better explanations for the relationship between climate factors and bacillary dysentery transmission than those put forth in other studies that use only correlation coefficients or fitting models. The findings in this paper demonstrate that the mean water vapour pressure over the previous month is an important predictor for the transmission of bacillary dysentery.

[1]  S. Hales,et al.  Climate change and human health: present and future risks , 2006, The Lancet.

[2]  J. Contreras,et al.  ARIMA Models to Predict Next-Day Electricity Prices , 2002, IEEE Power Engineering Review.

[3]  J. Hiller,et al.  Projected Years Lost due to Disabilities (YLDs) for bacillary dysentery related to increased temperature in temperate and subtropical cities of China. , 2012, Journal of environmental monitoring : JEM.

[4]  B G Armstrong,et al.  The effect of temperature on food poisoning: a time-series analysis of salmonellosis in ten European countries , 2004, Epidemiology and Infection.

[5]  M. Watarai,et al.  vacC, a virulence-associated chromosomal locus of Shigella flexneri, is homologous to tgt, a gene encoding tRNA-guanine transglycosylase (Tgt) of Escherichia coli K-12 , 1994, Journal of bacteriology.

[6]  Ying Zhang,et al.  Climate variations and bacillary dysentery in northern and southern cities of China. , 2007, The Journal of infection.

[7]  Feng Chen,et al.  Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China , 2014, PloS one.

[8]  Gillian Hall,et al.  Does Ambient Temperature Affect Foodborne Disease? , 2004, Epidemiology.

[9]  C. Sasakawa,et al.  Transcriptional control of the invasion regulatory gene virB of Shigella flexneri: activation by virF and repression by H-NS , 1993, Journal of bacteriology.

[10]  Hanʾguk Misaengmul Hakhoe,et al.  The journal of microbiology , 1995 .

[11]  D. M. Allen Mean Square Error of Prediction as a Criterion for Selecting Variables , 1971 .

[12]  Erik W. Kolstad,et al.  Uncertainties Associated with Quantifying Climate Change Impacts on Human Health: A Case Study for Diarrhea , 2010, Environmental health perspectives.

[13]  J. Contreras,et al.  ARIMA models to predict next-day electricity prices , 2002 .

[14]  S J O'Brien,et al.  Temperature dependence of reported Campylobacter infection in England, 1989–1999 , 2005, Epidemiology and Infection.

[15]  E. Ziegel Forecasting and Time Series: An Applied Approach , 2000 .

[16]  A Hagihara,et al.  Effects of weather variability on infectious gastroenteritis , 2009, Epidemiology and Infection.

[17]  Naiqing Zhao,et al.  Applied Mixed Generalized Additive Model to Assess the Effect of Temperature on the Incidence of Bacillary Dysentery and Its Forecast , 2013, PloS one.

[18]  B. Menne,et al.  Climate change and infectious diseases in Europe , 2010 .

[19]  Eduardo Gotuzzo,et al.  Environmental temperature, cholera, and acute diarrhoea in adults in Lima, Peru. , 2004, Journal of health, population, and nutrition.

[20]  R. Tibshirani The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.

[21]  P Weinstein,et al.  The influence of climate variation and change on diarrheal disease in the Pacific Islands. , 2001, Environmental health perspectives.