Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Version 1 : Received: 12 February 2020 / Approved: 14 February 2020 / Online: 14 February 2020 (02:34:55 CET)

How to cite: Iwata, K.; Miyakoshi, C. A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model. Preprints 2020, 2020020179. https://doi.org/10.20944/preprints202002.0179.v1 Iwata, K.; Miyakoshi, C. A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model. Preprints 2020, 2020020179. https://doi.org/10.20944/preprints202002.0179.v1

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. On the contrary to ongoing outbreak in China, however, there are limited secondary outbreaks caused by exported case outside the country. We here conducted simulations to estimate the impact of potential secondary outbreaks at a community outside China. Simulations using stochastic SEIR model was conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in total number of persons recovered or removed to be 997 (95% CrI 990-1,000) at day 100 and 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, with good case scenarios with different parameter led to no secondary case. Altering parameters, especially time to hospital visit could change the impact of secondary outbreak. With this multiple scenarios with different parameters, healthcare professionals might be able to prepare for this viral infection better.

Keywords

novel coronavirus; SEIR model; outside China

Subject

Medicine and Pharmacology, Epidemiology and Infectious Diseases

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