A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model.

Kentaro Iwata,Chisato Miyakoshi

doi:10.3390/jcm9040944

Abstract

Ongoing outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of new patients continues to increase. Even though it began to spread to many other parts of the world, such as other Asian countries, the Americas, Europe, and the Middle East, the impact of secondary outbreaks caused by exported cases outside China remains unclear. We conducted simulations to estimate the impact of potential secondary outbreaks in a community outside China. Simulations using stochastic SEIR model were conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in the total number of persons recovered or removed to be 997 (95% CrI 990–1000) at day 100 and a maximum number of symptomatic infectious patients per day of 335 (95% CrI 232–478). Calculated mean basic reproductive number (R0) was 6.5 (Interquartile range, IQR 5.6–7.2). However, better case scenarios with different parameters led to no secondary cases. Altering parameters, especially time to hospital visit. could change the impact of a secondary outbreak. With these multiple scenarios with different parameters, healthcare professionals might be able to better prepare for this viral infection.

Highlights

An outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of the newly reported cases continues to increase
While we do not know the extent of transmissibility of this virus precisely, and do not know how serious these impacts of secondary human to human transmission outside China could be, we developed a mathematical model and simulated the possibility and the risk of secondary outbreak caused by 2019-nCoV outside China, in a developed country with a relatively good infectious diseases reporting system and infection prevention practices
With the best-case scenario where β was 0.01–0.02, δ was 1/4–1/2, and ν was 1/2–1, a secondary outbreak did not occur, and the total number of recovered or removed patients was 1 (95% credible intervals (CrI) 1–1) at day 100 and maximum number of symptomatic infectious patients per day was 0.2 (95% CrI 0–0.3) (Figure 2)

Summary

Introduction

An outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of the newly reported cases continues to increase. More than 90,000 cases were reported globally, and about 3000 of them have died as of this writing (4 March 2020) [1] This virus was believed to be transmitted from some wild animals to humans, and human to human transmission was limited or nonexistent [2], but it turned out that human to human transmission occurs, resulting in thousands of patients in China. As of this writing, more than 10,000 confirmed cases were reported outside of mainland China, found in 72 different countries [1]. While we do not know the extent of transmissibility of this virus precisely, and do not know how serious these impacts of secondary human to human transmission outside China could be, we developed a mathematical model and simulated the possibility and the risk of secondary outbreak caused by 2019-nCoV outside China, in a developed country with a relatively good infectious diseases reporting system and infection prevention practices

Experimental Section

Results

Discussion

Conclusions

Coronavirus