Abstract:

Objective To establish ascariasis transmission mathematical models and apply them to predict field status. Methods Cuiping District in Sichuan Province, Jinxian County in Jiangxi Province and Yueyang County in Hunan Province were selected as the investigation sites. The Ascaris lumbricoides infection rates and mean worm burdens of baseline, 1 month and 1 year later after deworming were acquired by field surveys. The transmission models on population dynamics, distribution and infection rate were developed. The model parameters obtained through the field data were substituted into models to predict the infection lev? el one year after deworming. The predicted values were compared with the actual survey data, and the sensitivity analysis was per? formed to analyze factors related to the chemotherapy measures. Results The infection rates of Cuiping, Jinxian and Yueyang at baseline were 28.79%, 20.35% and 20.72%, respectively, with mean worm burdens of 1.32, 0.65 and 0.48, respectively. Those one year after chemotherapy were 30.10%, 7.51% and 0.94%, respectively, with mean worm burdens of 1.04, 0.56 and 0.34, respective? ly. The predict values were all in the range of the 95% confidence interval of the actual values. The sensitivity analysis showed that the treatment coverage rate and the treatment frequency were the important factors influencing the disease benefits (infection rate and mean worm burden). Conclusions The ascariasis transmission mathematical models have been established which fit the ac? tual field data well. Therefore, they can provide theoretical basis for setting ascariasis control specifications and optimizing the con? trol strategies.

Key words: Ascariasis, Ascaris lumbricoides, Mathematical model, Transmission, Population dynamics, Distribution

摘要：

目的 目的 建立我国蛔虫病传播数学模型并用于现场预测。方法 方法 选择四川翠屏、 江西进贤和湖南岳阳3个调查点，通过现场调查获取基线、 服药后1月和1年后人群蛔虫感染率及平均虫负荷， 构建蛔虫种群动力学、 分布及感染率等传播数学模型。由现场数据获得模型参数， 代入模型后预测1年后的感染水平， 与实际调查数据比较， 针对与药物驱虫措施相关的因素进行敏感性分析。结果 结果 翠屏、 进贤、 岳阳3个调查点蛔虫基线感染率分别为28.79%、 20.35%和20.72%， 平均虫负荷分别为1.32、 0.65和0.48， 药物驱虫后1年感染率分别为30.10%、 7.51%和0.94%， 平均虫负荷分别为1.04、 0.56和 0.34。服药1年后感染率和平均虫负荷均在实际观察值的95%可信区间内。敏感性分析结果显示服药覆盖率和治疗频次是影响疾病收益 （平均虫负荷、 感染率） 的重要因素。结论 结论 本研究建立的蛔虫病传播数学模型较好地拟合了现场数据，可为制定蛔虫病控制规范和优化防治策略提供理论依据。

关键词: 蛔虫病, 蛔虫, 数学模型, 传播, 种群动力学, 分布