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巴布亚新几内亚利希尔岛雅司病消除的常微分方程模型。

An ODE model of yaws elimination in Lihir Island, Papua New Guinea.

作者信息

Kimball Presley, Levenson Jacob, Moore Amy, Rychtar Jan, Taylor Dewey

机构信息

Department of Mathematics, Creighton University, Omaha, NE, United States of America.

Department of Mathematics, Washington and Lee University, Lexington, VA, United States of America.

出版信息

PeerJ. 2022 Mar 17;10:e13018. doi: 10.7717/peerj.13018. eCollection 2022.

DOI:10.7717/peerj.13018
PMID:35317072
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8934533/
Abstract

Yaws is a chronic infection that affects mainly the skin, bone and cartilage and spreads mostly between children. The new approval of a medication as treatment in 2012 has revived eradication efforts and now only few known localized foci of infection remain. The World Health Organization strategy mandates an initial round of total community treatment (TCT) with single-dose azithromycin followed either by further TCT or by total targeted treatment (TTT), an active case-finding and treatment of cases and their contacts. We develop the compartmental ODE model of yaws transmission and treatment for these scenarios. We solve for disease-free and endemic equilibria and also perform the stability analysis. We calibrate the model and validate its predictions on the data from Lihir Island in Papua New Guinea. We demonstrate that TTT strategy is efficient in preventing outbreaks but, due to the presence of asymptomatic latent cases, TTT will not eliminate yaws within a reasonable time frame. To achieve the 2030 eradication target, TCT should be applied instead.

摘要

雅司病是一种主要影响皮肤、骨骼和软骨的慢性感染,主要在儿童之间传播。2012年一种药物获批用于治疗,这使得根除工作得以重启,目前仅剩下少数已知的局部感染病灶。世界卫生组织的策略要求首轮进行单剂量阿奇霉素的社区全覆盖治疗(TCT),随后可进行进一步的TCT或全面目标治疗(TTT),即主动查找病例并对病例及其接触者进行治疗。我们针对这些情况建立了雅司病传播和治疗的房室常微分方程模型。我们求解了无病平衡点和地方病平衡点,并进行了稳定性分析。我们对模型进行校准,并根据巴布亚新几内亚利希尔岛的数据验证其预测结果。我们证明,TTT策略在预防疫情爆发方面是有效的,但由于存在无症状潜伏病例,TTT无法在合理时间内消除雅司病。为实现2030年的根除目标,应改用TCT。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/a91c54e4562e/peerj-10-13018-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/e09f642395d1/peerj-10-13018-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/1e3503a2c6ad/peerj-10-13018-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/8c25d0c3b3f0/peerj-10-13018-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/2d1894750366/peerj-10-13018-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/74a78bb445c6/peerj-10-13018-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/a91c54e4562e/peerj-10-13018-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/e09f642395d1/peerj-10-13018-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/a9a3b73f5cfd/peerj-10-13018-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/d19af69a5ebf/peerj-10-13018-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/1e3503a2c6ad/peerj-10-13018-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/8c25d0c3b3f0/peerj-10-13018-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/2d1894750366/peerj-10-13018-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/74a78bb445c6/peerj-10-13018-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c62/8934533/a91c54e4562e/peerj-10-13018-g008.jpg

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