paper-with-me

홈 › Papers

Intermittent Preventive Treatment (IPT): Its role in averting disease-induced mortalities in children and in promoting the spread of antimalarial drug resistance

2017-01-18

We develop a variable population age-structured ODE model to investigate the role of Intermittent Preventive Treatment (IPT) in averting malaria-induced mortalities in children, as well as its related cost in promoting the spread of anti-malarial drug resistance. IPT, a malaria control strategy in which a full curative dose of an antimalarial medication is administered to vulnerable asymptomatic individuals at specified intervals, has been shown to have a positive impact on reducing malaria transmission and deaths in children and pregnant women. However, it can also promote drug resistance spread. Our mathematical model is used to explore IPT effects on drug resistance in holoendemic malaria regions while quantifying the benefits in deaths averted. Our model includes both drug-sensitive and drug-resistant strains of the parasite as well as interactions between human hosts and mosquitoes. The basic reproduction numbers for both strains as well as the invasion reproduction numbers are derived and used to examine the role of IPT on drug resistance. Numerical simulations show the individual and combined effects of IPT and treatment of symptomatic infections on the prevalence levels of both parasite strains and on the number of lives saved. The results suggest that while IPT can indeed save lives, particularly in the high transmission region, certain combinations of drugs used for IPT and drugs used to treat symptomatic infection may result in more deaths when resistant parasite strains are circulating. Moreover, the half-lives of the treatment and IPT drugs used play an important role in the extent to which IPT may influence the rate of spread of the resistant strain. A sensitivity analysis indicates the model outcomes are most sensitive to the reduction factor of transmission for the resistant strain, rate of immunity loss, and the clearance rate of sensitive infections.

📄 PDF Abstract BibTeX arXiv:1701.05210

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Data-Driven Allocation of Preventive Care With Application to Diabetes Mellitus Type II

2023-08-14 · Mathias Kraus, Stefan Feuerriegel, Maytal Saar-Tsechansky

Problem Definition. Increasing costs of healthcare highlight the importance of effective disease prevention. However, decision models for allocating preventive care are lacking. Methodology/Results. In this paper, we dev…

counterfactualCounterfactual InferenceDecision MakingManagement

Optimal Transmission Topology for Facilitating the Growth of Renewable Power Generation

2021-03-29 · Emily Little, Sandrine Bortolotti, Jean-Yves Bourmaud, Efthymios Karangelos 외

Transmission topology control is a tool used by system operators in the role of a control action taken into account as a preventive or corrective action relative to a specific outage or set of outages. However, their inc…

Optimal Control applied to a SEIR model of 2019-nCoV with social distancing

2020-04-19 · medRxiv 2020 4 · Abhishek Mallela1

Does the implementation of social distancing measures have merit in controlling the spread of the novel coronavirus? In this study, we develop a mathematical model to explore the effects of social distancing on new dis…

3D Distance-color-coded Assessment of PCI Stent Apposition via Deep-learning-based Three-dimensional Multi-object Segmentation

2024-10-26 · Xiaoyang Qin, Hao Huang, Shuaichen Lin, Xinhao Zeng 외

Coronary artery disease poses a significant global health challenge, often necessitating percutaneous coronary intervention (PCI) with stent implantation. Assessing stent apposition holds pivotal importance in averting a…

Semantic SegmentationStyle Transfer

Trustworthy Chronic Disease Risk Prediction For Self-Directed Preventive Care via Medical Literature Validation

2025-06-21 · Minh Le, Khoi Ton

Chronic diseases are long-term, manageable, yet typically incurable conditions, highlighting the need for effective preventive strategies. Machine learning has been widely used to assess individual risk for chronic disea…

Disease Prediction