Chemotherapy-based Control of Ascariasis and Hookworm in Highly Endemic Areas of China: Field Observations and a Modeling Analysis
doi: 10.3967/0895-3988.2012.03.004
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Key words:
- Ascariosis /
- Hookworm /
- Chemotherapy /
- Field survey /
- Mathematical modeling
Abstract: Objective Our objective was to systematically evaluate chemotherapy-based control of ascariasis and hookworm infection and make predictions of the effectiveness of repeated mass treatment at different levels of coverage in highly endemic areas of China.Methods Field surveys were carried out to acquire the ascariasis and hookworm prevalence and intensity (mean worm burden) at baseline,one month and one year later.We calculated model parameters based on the survey data,then incorporated them into a quantitative framework to predict the prevalence and intensity one year later.Sensitivity analyses were performed to assess the influence of the chemotherapy measures on prevalence and intensity,and model simulations were performed to evaluate the feasibility of achieving the proposed transmission control criteria under different chemotherapy measures.Results The predicted prevalence and intensity one year from baseline were within the 95% confidence interval of actual values.As treatment frequency or coverage increased,the prevalence and intensity decreased.Model simulations show that many rounds of treatment are needed to maintain the prevalence at a low level in highly endemic areas of China.Conclusion We should select different combinations of treatment frequency,coverage and drug efficacy according to available resources and practical attainable conditions.Mathematical modeling could be used to help optimize the chemotherapeutic scheme aiming at specific parasitic species and areas,and to direct the establishment of soil-transmitted helminthiasis control criteria in China.
Citation: | WANG Jun, LI Hua Zhong, CHEN Ying Dan, LIU Chang Hua, TANG Lin Hua. Chemotherapy-based Control of Ascariasis and Hookworm in Highly Endemic Areas of China: Field Observations and a Modeling Analysis[J]. Biomedical and Environmental Sciences, 2012, 25(3): 272-281. doi: 10.3967/0895-3988.2012.03.004 |