Statistical and network analysis of 1212 COVID-19 patients in Henan, China

Abstract Background COVID-19 is spreading quickly all over the world. Publicly released data for 1212 COVID-19 patients in Henan of China was analyzed in this paper. Methods Various statistical and network analysis methods were employed. Results We found that COVID-19 patients show gender (55% vs 45%) and age (81% aged between 21 and 60) preferences, possible causes were explored; The estimated average, mode and median incubation periods are 7.4, 4 and 7 days; Incubation periods of 92% patients were no more than 14 days; The epidemic in Henan has undergone three stages and showed high correlations with the numbers of patients recently return from Wuhan; Network analysis revealed that 208 cases were clustering infected and various people's Hospitals are the main force in treating COVID-19. Conclusions The incubation period was statistical estimated and the proposed state transition diagram can well explore the epidemic stages of emerging infectious disease. We suggest that though the quarantine measures are gradually at work, strong measures might be still needed for a period of time, since ∼7.45% patients may have very long incubation periods. Migrant workers or college students are with high risk. State transition diagram can help us to recognize the time-phased nature of epidemic. Our investigations have implications for the prevention and control of COVID-19 in other regions of the world.