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Fig. 5 | Infectious Diseases of Poverty

Fig. 5

From: Driving role of climatic and socioenvironmental factors on human brucellosis in China: machine-learning-based predictive analyses

Fig. 5

Predicted MAI of brucellosis in a Baicheng (in Northeast China), b Datong (in Central China), c Jinchang (in Western China), and d Zhangjiakou (in Eastern China) based on SARIMAX model. The four prefecture-level cities in the figure are the cities with the highest average incidence of brucellosis among the four major economic regions in China that are used as typical data for analysis. The data from 2015 to 2019 was used as the model training set, and the data from 2020 was the prediction set. The black line represents the data as a comparison in the prediction set. The colored lines represent the SARIMAX results after different climatic data are input as exogenous variables

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