Forecasting antimicrobial resistance in China using a hybrid ARIMA-GM(1,1) model.

OBJECTIVE

To evaluate the application value of the ARIMA-GM(1,1) combined model in predicting the resistance rates of key drug-resistant bacteria in China, providing a scientific basis for optimizing antimicrobial management strategies.

METHODS

Based on data from the China Antibacterial Resistance Surveillance Network from 2014 to 2023, we selected six types of key drug-resistant bacteria, including methicillin-resistant Staphylococcus aureus (MRSA) and cefotaxime/ceftriaxone-resistant Klebsiella pneumoniae (CTX/CRO-R-KP), to construct the ARIMA-GM(1,1) combined model. The model performance was evaluated using five metrics: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and R, and the resistance rate trends for 2024-2028 were predicted.

RESULTS

The model exhibited strong predictive performance, with MSE, RMSE, MAE, and MAPE below 10 for all six strains, and R values exceeding 0.8 for five strains. Projected resistance rates for 2024 are as follows: MRSA at 27.46% (95% CI: 26.90%-28.02%), CTX/CRO-R-KP at 26.47% (25.81%-27.12%), CRKP at 9.87% (8.99%-10.74%), and CRPA at 15.17% (14.10%-16.24%). By 2028, these rates are expected to decrease to 24.05% (22.81%-25.29%), 22.30% (20.82%-23.77%), 7.58% (6.53%-8.63%), and 11.01% (8.61%-13.40%) (all P < 0.05). For 2024, resistance rates for CREC and CRAB are projected to be 1.63% (1.58%-1.68%) and 53.33% (51.37%-55.28%), respectively, with continued decline expected by 2028.

CONCLUSION

The ARIMA-GM(1,1) model has been statistically validated in predicting the resistance rates of MRSA, CTX/CRO-R-KP, CRKP, and CRPA, indicating a significant downward trend driven by the National Action Plan for Curbing Bacterial Drug Resistance (2016-2020). While effective in capturing temporal dynamics, future research should integrate antibiotic usage data and other influencing factors for more targeted interventions.