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Current Mathematical Models for Analyzing Anti-Malarial Antibody Data with an Eye to Malaria Elimination and Eradication

机译:当前以消除疟疾和消除疟疾为目标分析抗疟疾抗体数据的数学模型

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摘要

The last decade has witnessed a steady reduction of the malaria burden worldwide. With various countries targeting disease elimination in the near future, the popular parasite infection or entomological inoculation rates are becoming less and less informative of the underlying malaria burden due to a reduced number of infected individuals or mosquitoes at the time of sampling. To overcome such problem, alternative measures based on antibodies against specific malaria antigens have gained recent interest in malaria epidemiology due to the possibility of estimating past disease exposure in absence of infected individuals. This paper aims then to review current mathematical models and corresponding statistical approaches used in antibody data analysis. The application of these models is illustrated with three data sets from Equatorial Guinea, Brazilian Amazonia region, and western Kenyan highlands. A brief discussion is also carried out on the future challenges of using these models in the context of malaria elimination.
机译:过去十年见证了全世界疟疾负担的稳定减少。由于各个国家在不久的将来都致力于消除疾病,流行的寄生虫感染或昆虫学接种率正由于越来越少的采样时被感染个体或蚊子的数量而对潜在的疟疾负担提供越来越少的信息。为了克服该问题,由于可以在没有感染个体的情况下估计过去的疾病暴露可能性,因此基于针对特定疟疾抗原的抗体的替代措施在疟疾流行病学上已引起了人们的兴趣。然后,本文旨在综述抗体数据分析中使用的当前数学模型和相应的统计方法。赤道几内亚,巴西亚马逊地区和肯尼亚西部高地的三个数据集说明了这些模型的应用。还简要讨论了在消除疟疾的背景下使用这些模型的未来挑战。

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