When will the coronavirus end? Are the current precautionary measures effective? To answer these questions it is important to forecast regularly and accurately the spread of COVID-19 infections. Different time series forecasting models have been applied in the literature to tackle the pandemic situation. The current research efforts developed few of these models and validates its accuracy for selected countries. It becomes difficult to draw an objective comparison between the performance of these models at a global scale. This is because, the time series trend for the infection differs between the countries depending on the strategies adopted by the healthcare organizations to decrease the spread. Consequently, it is important to develop a tailored model for a country that allows healthcare organizations to better judge the effect of the undertaken precautionary measures, and provision more efficiently the needed resources to face this disease. This paper addresses this void. We develop and compare the performance of the time series models in the literature in terms of root mean squared error and mean absolute percentage error.

冠状病毒什么时候结束？当前的预防措施是否有效？要回答这些问题，定期且准确地预测COVID-19感染的传播非常重要。在文献中已经采用了不同的时间序列预测模型来应对大流行情况。当前的研究工作很少开发这些模型，并验证了所选国家/地区的准确性。在全球范围内，很难对这些模型的性能进行客观的比较。这是因为，不同国家之间的感染时间序列趋势会有所不同，具体取决于医疗机构采取的减少传播的策略。所以，重要的是要为一个国家量身定制一个模型，使医疗机构能够更好地判断所采取的预防措施的效果，并更有效地提供应对这种疾病所需的资源。本文解决了这个空白。我们根据均方根误差和绝对绝对百分比误差来开发和比较文献中时间序列模型的性能。