论文标题
沟通的像素化：可视化疾病风险和其他空间连续图的不确定性
Pixelate to communicate: visualising uncertainty in maps of disease risk and other spatial continua
论文作者
论文摘要
长期以来，地图已被用来可视化空间变量的估计值，特别是疾病负担和风险。使用地统计学模型做出的预测通常在空间上变化。但是，这种不确定性很难用估计本身映射，因此通常不包括在内，从而产生了对疾病负担或其他重要变量的潜在误导性的确定性。为了解决这个问题，我们建议通过改变像素大小来同时可视化预测及其在单个地图中相关的不确定性。我们使用疟疾发病率的例子说明了我们的方法，但是该方法可以应用于与相关不确定性的任何空间连续性的预测。
Maps have long been been used to visualise estimates of spatial variables, in particular disease burden and risk. Predictions made using a geostatistical model have uncertainty that typically varies spatially. However, this uncertainty is difficult to map with the estimate itself and is often not included as a result, thereby generating a potentially misleading sense of certainty about disease burden or other important variables. To remedy this, we propose simultaneously visualising predictions and their associated uncertainty within a single map by varying pixel size. We illustrate our approach using examples of malaria incidence, but the method could be applied to predictions of any spatial continua with associated uncertainty.
