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Quantification of Rotavirus Diarrheal Risk Due to Hydroclimatic Extremes Over South Asia: Prospects of Satellite‐Based Observations in Detecting Outbreaks

机译:轮状病毒腹泻风险的定量分析在南亚地区的极端气候条件下:监测暴发的卫星观测的前景。

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Rotavirus is the most common cause of diarrheal disease among children under 5. Especially in South Asia, rotavirus remains the leading cause of mortality in children due to diarrhea. As climatic extremes and safe water availability significantly influence diarrheal disease impacts in human populations, hydroclimatic information can be a potential tool for disease preparedness. In this study, we conducted a multivariate temporal and spatial assessment of 34 climate indices calculated from ground and satellite Earth observations to examine the role of temperature and rainfall extremes on the seasonality of rotavirus transmission in Bangladesh. We extracted rainfall data from the Global Precipitation Measurement and temperature data from the Moderate Resolution Imaging Spectroradiometer sensors to validate the analyses and explore the potential of a satellite‐based seasonal forecasting model. Our analyses found that the number of rainy days and nighttime temperature range from 16°C to 21°C are particularly influential on the winter transmission cycle of rotavirus. The lower number of wet days with suitable cold temperatures for an extended time accelerates the onset and intensity of the outbreaks. Temporal analysis over Dhaka also suggested that water logging during monsoon precipitation influences rotavirus outbreaks during a summer transmission cycle. The proposed model shows lag components, which allowed us to forecast the disease outbreaks 1 to 2 months in advance. The satellite data‐driven forecasts also effectively captured the increased vulnerability of dry‐cold regions of the country, compared to the wet‐warm regions.
机译:轮状病毒是5岁以下儿童腹泻病的最常见原因,尤其是在南亚,轮状病毒仍然是腹泻导致儿童死亡的主要原因。由于极端的气候和安全的水供应会严重影响人类腹泻病的影响,因此水文气候信息可能成为疾病预防的潜在工具。在这项研究中,我们对从地面和卫星地球观测结果得出的34个气候指数进行了多元时空评估,以检验温度和降雨量极端值对孟加拉国轮状病毒传播季节性的影响。我们从全球降水量测量中提取降雨数据,从中分辨率成像光谱仪中提取温度数据,以验证分析结果并探索基于卫星的季节预报模型的潜力。我们的分析发现,雨天和夜间温度范围从16°C到21°C,对轮状病毒的冬季传播周期尤其有影响。在适当的低温下持续较长时间的较少的湿润天数会加快爆发的发作和强度。达卡的时间分析还表明,季风降水期间的水淹影响了夏季传播周期中轮状病毒的爆发。所提出的模型显示了滞后成分,这使我们能够提前1到2个月预测疾病暴发。与湿热地区相比,卫星数据驱动的预测还有效地捕获了该国干冷地区日益增加的脆弱性。

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