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Abstract
Background The epidemic caused by SARS-CoV-2 was first reported in Wuhan, China, and now is spreading worldwide. The Chinese government responded to this epidemic with multiple public health policies including locking down the city of Wuhan, establishing multiple temporary hospitals, and prohibiting public gathering events. Here, we constructed a new real-time status dynamic model of SEIO (MH) to reveal the influence of national public health policies and to model the epidemic in Wuhan.
Methods A real-time status dynamic model was proposed to model the population of Wuhan in status Susceptible (S), Exposed (E), Infected with symptoms (I), with Medical care (M), and Out of the system (O) daily. Model parameters were fitted according to the daily report of new infections from Jan. 27th, 2020 to Feb. 2nd, 2020. Using the fitted parameters, the epidemic under different conditions was simulated and compared with the current situation.
Finding According to our study, the first patient is most likely appeared on Nov. 29th, 2019. There had already been 4,153 infected people and 6,536 exposed ones with the basic reproduction number R_0 of 2.65 before lockdown, whereas R_0 dropped to 1.98 for the first 30 days after the lockdown. The peak point is Feb. 17th, 2020 with 24,115 infected people and the end point is Jun. 17th, 2020. In total, 77,453 people will be infected. If lockdown imposed 7 days earlier, the total number of infected people would be 21,508, while delaying the lockdown by 1-6 days would expand the infection scale 1.23 to 4.94 times. A delay for 7 days would make the epidemic finally out of control. Doubling the number of beds in hospitals would decrease the total infections by 28%, and further investment in bed numbers would yield a diminishing return. Last, public gathering events that increased the transmission parameter by 5% in one single day would increase 4,243 infected people eventually.
Interpretation Our model forecasted that the peak time in Wuhan was Feb. 17th, 2020 and the epidemic in Wuhan is now under control. The outbreak of SARS-CoV-2 is currently a global public health threat for all nations. Multiple countries including South Korea, Japan, Iran, Italy, and the United States are suffering from SARS-CoV-2. Our study, which simulated the epidemic in Wuhan, the first city in the world fighting against SARS-CoV-2, may provide useful guidance for other countries in dealing with similar situations.
Background The epidemic caused by SARS-CoV-2 was first reported in Wuhan, China, and now is spreading worldwide. The Chinese government responded to this epidemic with multiple public health policies including locking down the city of Wuhan, establishing multiple temporary hospitals, and prohibiting public gathering events. Here, we constructed a new real-time status dynamic model of SEIO (MH) to reveal the influence of national public health policies and to model the epidemic in Wuhan.
Methods A real-time status dynamic model was proposed to model the population of Wuhan in status Susceptible (S), Exposed (E), Infected with symptoms (I), with Medical care (M), and Out of the system (O) daily. Model parameters were fitted according to the daily report of new infections from Jan. 27th, 2020 to Feb. 2nd, 2020. Using the fitted parameters, the epidemic under different conditions was simulated and compared with the current situation.
Finding According to our study, the first patient is most likely appeared on Nov. 29th, 2019. There had already been 4,153 infected people and 6,536 exposed ones with the basic reproduction number R_0 of 2.65 before lockdown, whereas R_0 dropped to 1.98 for the first 30 days after the lockdown. The peak point is Feb. 17th, 2020 with 24,115 infected people and the end point is Jun. 17th, 2020. In total, 77,453 people will be infected. If lockdown imposed 7 days earlier, the total number of infected people would be 21,508, while delaying the lockdown by 1-6 days would expand the infection scale 1.23 to 4.94 times. A delay for 7 days would make the epidemic finally out of control. Doubling the number of beds in hospitals would decrease the total infections by 28%, and further investment in bed numbers would yield a diminishing return. Last, public gathering events that increased the transmission parameter by 5% in one single day would increase 4,243 infected people eventually.
Interpretation Our model forecasted that the peak time in Wuhan was Feb. 17th, 2020 and the epidemic in Wuhan is now under control. The outbreak of SARS-CoV-2 is currently a global public health threat for all nations. Multiple countries including South Korea, Japan, Iran, Italy, and the United States are suffering from SARS-CoV-2. Our study, which simulated the epidemic in Wuhan, the first city in the world fighting against SARS-CoV-2, may provide useful guidance for other countries in dealing with similar situations.