Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA.
Epidemiol Infect. 2012 Jul;140(7):1236-43. doi: 10.1017/S0950268811001919. Epub 2011 Sep 19.
Studies of temporal and spatial patterns of diarrhoeal disease can suggest putative aetiological agents and environmental or socioeconomic drivers. Here, the seasonal patterns of monthly acute diarrhoeal morbidity in Thailand, where diarrhoeal morbidity is increasing, are explored. Climatic data (2003-2006) and Thai Ministry of Health annual reports (2003-2009) were used to construct a spatially weighted panel regression model. Seasonal patterns of diarrhoeal disease were generally bimodal with aetiological agents peaking at different times of the year. There is a strong association between daily mean temperature and precipitation and the incidence of hospitalization due to acute diarrhoea in Thailand leading to a distinct spatial pattern in the seasonal pattern of diarrhoea. Model performance varied across the country in relation to per capita GDP and population density. While climatic factors are likely to drive the general pattern of diarrhoeal disease in Thailand, the seasonality of diarrhoeal disease is dampened in affluent urban populations.
研究腹泻病的时间和空间模式可以提示可能的病因和环境或社会经济驱动因素。在这里，我们探讨了腹泻发病率不断上升的泰国的月度急性腹泻发病率的季节性模式。我们使用气候数据（2003-2006 年）和泰国卫生部年度报告（2003-2009 年）构建了一个空间加权面板回归模型。腹泻病的季节性模式通常呈双峰型，病因在一年中的不同时间达到高峰。在泰国，日平均温度和降水与因急性腹泻住院的发生率之间存在很强的关联，导致腹泻的季节性模式具有明显的空间模式。与人均国内生产总值和人口密度有关，模型在全国范围内的性能有所不同。虽然气候因素可能会驱动泰国腹泻病的总体模式，但在富裕的城市人群中，腹泻病的季节性有所减弱。
