论文标题
基于天气启发的合奏基于COVID-19
Weather-inspired ensemble-based probabilistic prediction of COVID-19
论文作者
论文摘要
这项工作的目的是使用受概率天气预测系统启发的预测方法来预测从观察到的数据开始的covid-19的传播。 结果表明，这种方法对中国有效：在第25天，我们可以很好地预测未来35天的结果。同样的方法已应用于意大利和韩国，并且在这项工作中包括了即将到来的几周的预测。对于意大利，基于收集到今天（3月24日）的数据的预测表明，观察到的病例的数量可能会从当前价值69,176，到101K-180K之间，而50％的概率在110k-135k之间。对于韩国，这表明观察到的病例的数量可能会从目前的9,018（截至3月23日）增加到8,500至9,300之间的值，其中50％的概率在8,700至8,900之间。 最后，我们建议概率疾病预测系统是可能的，可以根据天气预报的关键思想和方法发展。访问熟练的每日最新预测可以帮助您更好地了解如何管理诸如Covid-19之类的疾病的传播。
The objective of this work is to predict the spread of COVID-19 starting from observed data, using a forecast method inspired by probabilistic weather prediction systems operational today. Results show that this method works well for China: on day 25 we could have predicted well the outcome for the next 35 days. The same method has been applied to Italy and South Korea, and forecasts for the forthcoming weeks are included in this work. For Italy, forecasts based on data collected up to today (24 March) indicate that number of observed cases could grow from the current value of 69,176, to between 101k-180k, with a 50% probability of being between 110k-135k. For South Korea, it suggests that the number of observed cases could grow from the current value of 9,018 (as of the 23rd of March), to values between 8,500 and 9,300, with a 50% probability of being between 8,700 and 8,900. We conclude by suggesting that probabilistic disease prediction systems are possible and could be developed following key ideas and methods from weather forecasting. Having access to skilful daily updated forecasts could help taking better informed decisions on how to manage the spread of diseases such as COVID-19.
