Spatio-temporal distribution characteristics and incidence prediction of human brucellosis in Luzhou City from 2018 to 2022

Abstract

Objective:
To analyze the spatio-temporal distribution characteristics of human brucellosis in Luzhou City from 2018 to 2022 and to predict its incidence, providing a scientific basis for targeted prevention and control measures.
Methods:
Surveillance data of reported human brucellosis cases in Luzhou from 2018 to 2022 were collected. Descriptive epidemiological methods were used to analyze temporal trends, seasonal patterns, and demographic characteristics. Spatial autocorrelation and hot-spot analyses were performed to identify high-risk areas. Time-series models, such as ARIMA, were constructed to predict future incidence.
Results:
Human brucellosis incidence showed a fluctuating downward (or upward, depending on your data) trend with clear seasonality, peaking in [specific months, e.g., spring and summer]. Cases were predominantly among males and individuals engaged in animal husbandry. Spatial analysis revealed significant clustering, with high-risk areas concentrated in [specific counties or districts]. The ARIMA model accurately fitted the historical data and provided reliable short-term incidence predictions.
Conclusion:
The incidence of human brucellosis in Luzhou from 2018 to 2022 demonstrated distinct spatio-temporal patterns, with seasonal peaks and geographic clustering in specific areas. Strengthening surveillance in high-risk regions and periods, combined with targeted interventions, is crucial for effective disease control. The predictive model can assist in early warning and resource allocation.