![]() If R t exceeds 1, the number of incident cases will inevitably grow over time, and a large epidemic is possible. The magnitude of R t is a useful indicator for evaluating the risk of an infectious disease and the validity of controlling the epidemic. As an infection is spreading through a population, it is more convenient to work with an effective reproduction number R t, which is defined as the number of secondary infections that arise from a typical primary case. One of the key parameters in epidemic models is the basic reproduction number R 0, defined as the number of secondary infections that arise from a typical primary case in a completely susceptible population. By March 12, 2020, controlling the spread of the epidemic has become a global challenge. Despite this, the epidemic still spread throughout the entire country. However, with the epidemic in Wuhan further expanding, the Chinese Government started to take emergency actions to lock down the Wuhan city on January 23, 2020. At first the local governments did not take effective measures which leaded to local people not paying enough attention to the risk. In December, 2019, a cluster of pneumonia cases in Wuhan, China was caused by a novel coronavirus, the COVID-19. The simulation results predict that China’s epidemic will gradually tend to disappear by May 2020 if the quarantine measures can continue to be executed. By applying these estimated reproduction numbers into the susceptible-infectious-removed epidemic model, we simulate the evolutionary track of the epidemic in China, which is well in accordance with that of the real incident cases. Based on this method, given the mean value and variance of the generation interval, we first determine its probability distribution function and in turn estimate the real-time values of reproduction number of COVID-19 in China. In this letter, given the incomplete information for the generation interval, we propose a maximum entropy method to estimate the reproduction number. ![]() To estimate the reproduction number, the probability distribution function of the generation interval of an infectious disease is required to be available however, this distribution is often unknown. To prevent the expansion of an epidemic, R must be reduced to a level below 1. If it exceeds 1, the number of incident cases will inevitably grow over time, and a large epidemic is possible. The key parameter that characterizes the transmissibility of a disease is the reproduction number R. ![]()
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