Modeling COVID-19 epidemic in Heilongjiang province, China
Autor
Sun, Tingzhe
Wang, Yan
Institución
Resumen
The Coronavirus Disease 2019 (COVID-19) surges worldwide. However, massive imported patients especially into Heilongjiang Province in China recently have been an alert for local COVID-19 outbreak. We
collected data from January 23 to March 25 from Heilongjiang province and trained an ordinary differential equation model to fit the epidemic data. We extended the simulation using this trained model to
characterize the effect of an imported ‘escaper’. We showed that an imported ‘escaper’ was responsible
for the newly confirmed COVID-19 infections from Apr 9 to Apr 19 in Heilongjiang province. Stochastic simulations further showed that significantly increased local contacts among imported ‘escaper’, its
epidemiologically associated cases and susceptible populations greatly contributed to the local outbreak
of COVID-19. Meanwhile, we further found that the reported number of asymptomatic patients was
markedly lower than model predictions implying a large asymptomatic pool which was not identified.
We further forecasted the effect of implementing strong interventions immediately to impede COVID-19
outbreak for Heilongjiang province. Implementation of stronger interventions to lower mutual contacts
could accelerate the complete recovery from coronavirus infections in Heilongjiang province. Collectively,
our model has characterized the epidemic of COVID-19 in Heilongjiang province and implied that strongly
controlled measured should be taken for infected and asymptomatic patients to minimize total infections.