2026-10-12T12:43:55Z https://www.scidb.cn/oai

10.57760/sciencedb.012rm 2026-09-23T19:49:04Z

2026-09-23 Code and Aggregate Data for "Resurging Human Brucellosis despite Strengthened Control in a Semi-Arid Pastoral County of Xinjiang, China: Disentangling Case Detection from Transmission and Identifying Cost-Saving One Health Interventions" doi:10.57760/sciencedb.012rm en This dataset contains all materials required to reproduce the study "Resurging Human Brucellosis despite Strengthened Control in a Semi-Arid Pastoral County of Xinjiang, China: Disentangling Case Detection from Transmission and Identifying Cost-Saving One Health Interventions." It comprises: (1) de-identified aggregate data — monthly and annual (2016–2023) admission counts for human brucellosis from the county-designated referral hospital (June 2014–June 2024) and township-level case distribution (townships pseudonymized with letter codes A–O); (2) Python source code — a deterministic sheep–environment–human compartmental transmission model, an approximate Bayesian computation (ABC) calibration routine, 10-year projections of eight intervention scenarios (S0–S7) with a double-ledger (human plus livestock) economic evaluation, and scripts reproducing Figures 1–4; (3) model outputs — posterior parameter draws, scenario comparison results, and all figures. Individual-level hospital records are not included, in compliance with Chinese infectious-disease data regulations, and the county identity is anonymized as in the manuscript. Requirements: Python 3.9+ with NumPy, SciPy, pandas, and matplotlib. To reproduce all results, run run_calibration.py, run_scenarios.py, and make_figures.py in sequence from the src/ directory; the full pipeline takes approximately 1–2 minutes. brucellosis; zoonosis; transmission dynamics model; approximate Bayesian computation; economic evaluation of interventions; One Health; Xinjiang; China 高翔 PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank