Modeling analysis of COVID-19 based on morbidity data in Anhui, China.

Since the first case of coronavirus disease (COVID-19) in Wuhan Hubei, China, was reported in December 2019, COVID-19 has spread rapidly across the country and overseas. The first case in Anhui, a province of China, was reported on January 10, 2020. In the field of infectious diseases, modeling, evaluating and predicting the rate of disease transmission is very important for epidemic prevention and control. Different intervention measures have been implemented starting from different time nodes in the country and Anhui, the epidemic may be divided into three stages for January 10 to February 11, 2020, namely. We adopted interrupted time series method and develop an SEI/QR model to analyse the data. Our results displayed that the lockdown of Wuhan implemented on January 23, 2020 reduced the contact rate of epidemic transmission in Anhui province by 48.37%, and centralized quarantine management policy for close contacts in Anhui reduced the contact rate by an additional 36.97%. At the same time, the estimated basic reproduction number gradually decreased from the initial 2.9764 to 0.8667 and then to 0.5725. We conclude that the Wuhan lockdown and the centralized quarantine management policy in Anhui played a crucial role in the timely and effective mitigation of the epidemic in Anhui. One merit of this work is the adoption of morbidity data which may reflect the epidemic more accurately and promptly. Our estimated parameters are largely in line with the World Health Organization estimates and previous studies.

Comparative study of SARIMA and NARX models in predicting the incidence of schistosomiasis in China.

In this paper, based on the data of the incidence of schistosomiasis in China from January 2011 to May 2018 we establish SARIMA model and NARX model. These two models are used to predict the incidence of schistosomiasis in China from June 2018 to September 2018. By comparing the mean square error and the mean absolute error of two sets of predicted values, the results show that the NARX model is better and it has an e ective forecasting precision to incidence of schistosomiasis. Then according to the results, a mixed model called NARX-SARIMA model is used to predict the incidence future trends and make a comparison with the two model. The mixed model has a better application based on its good fitting capability.

Parameter estimation of modeling schistosomiasis transmission for four provinces in China.

According to monitoring data of Anhui, Jiangxi, Hubei, Jiangsu Provinces, in this paper the transmission of schistosomiasis is studied based on Barbour's mathematical model. The values of the basic reproduction number and key parameters are obtained with two methods. The first method is to calculate directly by using parameter values in references. The second one is to estimate parameter values by the methods of noise measurement and data smoothing and then to obtain new values of basic reproduction number. Comparing these two methods, we found the second method is good to fit the data. This parameter values can be used as reference values in other provinces. Finally, some numerical simulations are carried out to discuss the development trend of prevalence of humans and snails in each province. It is found that schistosomiasis in four provinces is expected to be eliminated with the improvement or maintenance of the standards of prevention and control. Furthermore, the time needed is different in the different four provinces.