Fig 1.
Temporal distribution of human brucellosis in Ningxia and China (2007–2022).
(a) Administrative divisions of Ningxia Hui Autonomous Region, China. Map (a) shows the study area and its internal boundaries of five prefecture-level cities in Ningxia. The base map layer was created using data from the Database of Global Administrative Areas (GADM, https://gadm.org), which is available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.; (b) Joinpoint trend analysis of brucellosis incidence in Ningxia; (c) Comparative Trends of Human Brucellosis Incidence (2007-2022).
Fig 2.
Temporal-spatial distribution of brucellosis incidence in Ningxia (2007–2022).
County-level annual incidence rates (per 100,000 population) are categorized into five levels: 0.00–50.00, 50.01–90.00, 90.01–120.00, 120.01–190.00, and 190.01–330.00. Administrative boundaries were obtained from the ‘geoBoundaries-CHN-ADM3_simplified.geojson’ dataset on the Humanitarian Data Exchange (HDX) platform, available directly at: https://data.humdata.org/dataset/geoboundaries-admin-boundaries-for-china/resource/bb2bb8b4-c882-4eb0-93e8-f0ed0e26b740 under a Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/). The map is for illustrative purposes only and does not imply any opinion on legal status.
Table 1.
Results of Spatio-Temporal Scan Analysis of Ningxia Region, 2007-2022.
Table 2.
Joinpoint analysis of brucellosis incidence in notable agglomerations, 2007-2022.
Fig 3.
Livestock stock at the end of the year, Ningxia region, 2007-2022.
Fig 4.
Spearman’s correlation coefficient between socio-economic factors and the incidence of brucellosis in Ningxia region, 2007-2022.
Table 3.
Factor detector results.
Fig 5.
Two-factor enhanced interactions driving brucellosis in Ningxia.
(a) Factor pairs and interaction patterns; (b) Quantified interaction q-values.
Table 4.
Distributed lag nonlinear model (DLNM) regression results.
Fig 6.
Results of a Distributed Lag Nonlinear Model Analyzing the Exposure Effect of Cattle and Sheep Stocking: Changes in Relative Risk (RR) with Standardized Stocking and Lag Time.
Fig 7.
Relative Risk (RR) and 95% Confidence Interval for Immediate Effects of Covariates.