中国输入性疟疾国际移民劳工的延迟就医。

Delayed care-seeking in international migrant workers with imported malaria in China.

机构信息

Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu Province, 225009, China.

National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, 214064, China.

出版信息

J Travel Med. 2024 Apr 6;31(3). doi: 10.1093/jtm/taae021.

DOI:10.1093/jtm/taae021

PMID:38335249

Abstract

BACKGROUND

Imported malaria cases continue to pose major challenges in China as well as in other countries that have achieved elimination. Early diagnosis and treatment of each imported malaria case is the key to successfully maintaining malaria elimination success. This study aimed to build an easy-to-use predictive nomogram to predict and intervene against delayed care-seeking among international migrant workers with imported malaria.

METHODS

A prediction model was built based on cases with imported malaria from 2012 to 2019, in Jiangsu Province, China. Routine surveillance information (e.g. sex, age, symptoms, origin country and length of stay abroad), data on the place of initial care-seeking and the gross domestic product (GDP) of the destination city were extracted. Multivariate logistic regression was performed to identify independent predictors and a nomogram was established to predict the risk of delayed care-seeking. The discrimination and calibration of the nomogram was performed using area under the curve and calibration plots. In addition, four machine learning models were used to make a comparison.

RESULTS

Of 2255 patients with imported malaria, 636 (28.2%) sought care within 24 h after symptom onset, and 577 (25.6%) sought care 3 days after symptom onset. Development of symptoms before entry into China, initial care-seeking from superior healthcare facilities and a higher GDP level of the destination city were significantly associated with delayed care-seeking among migrant workers with imported malaria. Based on these independent risk factors, an easy-to-use and intuitive nomogram was established. The calibration curves of the nomogram showed good consistency.

CONCLUSIONS

The tool provides public health practitioners with a method for the early detection of delayed care-seeking risk among international migrant workers with imported malaria, which may be of significance in improving post-travel healthcare for labour migrants, reducing the risk of severe malaria, preventing malaria reintroduction and sustaining achievements in malaria elimination.

摘要

背景

在中国和其他已消除疟疾的国家，输入性疟疾病例仍然构成重大挑战。每个输入性疟疾病例的早期诊断和治疗是成功维持消除疟疾成功的关键。本研究旨在构建一个易于使用的预测列线图，以预测和干预国际移民工人中输入性疟疾的延迟就医。

方法

基于 2012 年至 2019 年中国江苏省输入性疟疾病例，建立预测模型。提取常规监测信息（如性别、年龄、症状、来源国和在国外停留时间）、首次就诊地点和目的地城市国内生产总值（GDP）数据。采用多变量逻辑回归分析确定独立预测因素，并建立列线图预测延迟就医的风险。使用曲线下面积和校准图对列线图的区分度和校准度进行评估。此外，还使用了四种机器学习模型进行比较。

结果

在 2255 例输入性疟疾病例中，636 例（28.2%）在症状出现后 24 小时内就诊，577 例（25.6%）在症状出现后 3 天就诊。入境前出现症状、首次就诊于上级医疗机构和目的地城市 GDP 水平较高与输入性疟疾病例移民工人的延迟就医显著相关。基于这些独立的风险因素，建立了一个易于使用和直观的列线图。列线图的校准曲线显示出良好的一致性。