Given the task definition and input, reply with output. In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Background: The outbreak of the 2019 novel coronavirus has attracted global attention. In the early stage of the outbreak, the most important question concerns some meaningful milepost moments, including (1) the time when the number of daily confirmed cases decreases, (2) the time when the number of daily confirmed cases becomes smaller than that of the daily removed (recovered and death), (3) the time when the number of daily confirmed cases becomes zero, and (4) the time when the number of patients treated in hospital is zero, which indicates the end of the epidemic. Intuitively, the former two can be regarded as two important turning points which indicate the alleviation of epidemic to some extent, while the latter two as two "zero" points, respectively. Unfortunately, it is extremely difficult to make right and precise prediction due to the limited amount of available data at a early stage of the outbreak. Method: To address it, in this paper, we propose a flexible framework incorporating the effectiveness of the government control to forecast the whole process of a new unknown infectious disease in its early-outbreak. Specially, we first establish the iconic indicators to characterize the extent of epidemic spread, yielding four periods of the whole process corresponding to the four meaningful milepost moments: two turning points and two "zero" points. Then we develop the tracking and forecasting procedure with mild and reasonable assumption. Finally we apply it to analyze and evaluate the COVID-19 using the public available data for mainland China beyond Hubei Province from the China Centers for Disease Control (CDC) during the period of Jan 29th, 2020, to Feb 29th, 2020, which shows the effectiveness of the proposed procedure. Results: Results show that our model can clearly outline the development of the epidemic at a very early stage. The first prediction results on Jan 29th reveal that the first and second milepost moments
Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19