Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhua Road, 230601, Anhui, Hefei, China.
School of Global Health, Chinese Centre for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China.
BMC Public Health. 2024 Mar 4;24(1):695. doi: 10.1186/s12889-024-18239-w.
Anhui Province is currently facing an increase in imported malaria cases as a result of globalization and international travel. In response, Anhui Province has implemented a comprehensive adaptive framework to effectively address this threat.
This study collected surveillance data from 2012 to 2022 in Anhui Province. Descriptive statistics were used to analyze the epidemiological characteristics of imported malaria cases. Additionally, multivariate logistic regression was employed to identify factors associated with severe malaria. Documents were reviewed to document the evolution of the adaptive framework designed to combat imported malaria. The effectiveness of the adaptive framework was evaluated based on the rates of timely medical visits, timely diagnosis, and species identification.
During the study period, a total of 1008 imported malaria cases were reported across 77 out of 105 counties in Anhui Province, representing a coverage of 73.33%. It was found that 10.52% of imported cases went undiagnosed for more than seven days after onset. The multivariate analysis revealed several potential risk factors for severe malaria, including increasing age (OR = 1.049, 95%CI:1.015-1.083), occupation (waitperson vs. worker, OR = 2.698, 95%CI:1.054-6.906), a longer time interval between onset and the initial medical visit (OR = 1.061, 95%CI:1.011-1.114), and misdiagnosis during the first medical visit (OR = 5.167, 95%CI:2.535-10.533). Following the implementation of the adaptive framework, the rates of timely medical visits, timely diagnosis, and species identification reached 100.00%, 78.57%, and 100.00%, respectively.
Anhui Province has successfully developed and implemented an adaptive framework for addressing imported malaria, focusing on robust surveillance, prompt diagnosis, and standardized treatment. The experiences gained from this initiative can serve as a valuable reference for other non-endemic areas.
安徽省目前正面临全球化和国际旅行导致的输入性疟疾病例增加的问题。为此，安徽省实施了全面的适应性框架，以有效应对这一威胁。
本研究收集了 2012 年至 2022 年安徽省的监测数据。采用描述性统计方法分析输入性疟疾病例的流行病学特征。此外，还采用多变量逻辑回归分析方法确定与重症疟疾相关的因素。通过文献回顾记录了针对输入性疟疾设计的适应性框架的演变。根据及时就医、及时诊断和物种鉴定的比例评估适应性框架的有效性。
在研究期间，安徽省 105 个县中的 77 个县共报告了 1008 例输入性疟疾病例，覆盖了 73.33%。结果发现，10.52%的输入性疟疾病例在发病后超过 7 天未被诊断。多变量分析显示，重症疟疾的几个潜在危险因素包括年龄增加（OR=1.049，95%CI：1.015-1.083）、职业（服务员与工人，OR=2.698，95%CI：1.054-6.906）、发病到首次就医的时间间隔较长（OR=1.061，95%CI：1.011-1.114）和首次就医时误诊（OR=5.167，95%CI：2.535-10.533）。实施适应性框架后，及时就医、及时诊断和物种鉴定的比例分别达到 100.00%、78.57%和 100.00%。
安徽省成功开发并实施了针对输入性疟疾的适应性框架，重点关注了强有力的监测、及时诊断和标准化治疗。该倡议的经验可为其他非疟疾流行地区提供有价值的参考。
