Bosomprah Samuel
Department of Biostatistics, School of Public Health, University of Ghana, Legon, Accra, Ghana.
Malar J. 2014 Jan 8;13:12. doi: 10.1186/1475-2875-13-12.
Malaria transmission intensity is traditionally estimated from entomological studies as the entomological inoculation rate (EIR), but this is labour intensive and also raises sampling issues due to the large variation from house to house. Incidence of malaria in the control group of a trial or in a cohort study can be used but is difficult to interpret and to compare between different places and between age groups because of differences in levels of acquired immunity. The reversible catalytic model has been developed to estimate malaria transmission intensity using age-stratified serological data. However, the limitation of this model is that it does not allow for persons to have their seropositivity boosted by exposure while they are already seropositive. The aim of this paper is to develop superinfection mathematical models that allow for antibody response to be boosted by exposure.
The superinfection models were fitted to age-stratified serological data using maximum likelihood method.
The results showed that estimates of seroconversion rate were higher using the superinfection model than catalytic model. This difference was milder when the level of transmission was lower. This suggests that the catalytic model is underestimating the transmission intensity by up to 31%. The duration of seropositivity is shorter with superinfection model, but still seems too long.
The model is important because it can produce more realistic estimates of the duration of seropositivity. This is analogous to Dietz model, which allowed for superinfection and produced more realistic estimates of the duration of infection as compared to the original Ross-MacDonald malaria model, which also ignores superinfection.
疟疾传播强度传统上是通过昆虫学研究以昆虫接种率（EIR）来估计的，但这需要大量人力，而且由于不同房屋之间差异很大，还存在抽样问题。试验对照组或队列研究中的疟疾发病率可以使用，但由于获得性免疫水平的差异，很难解释和比较不同地点以及不同年龄组之间的情况。可逆催化模型已被开发出来，用于利用年龄分层的血清学数据估计疟疾传播强度。然而，该模型的局限性在于，它不考虑个体在已经血清阳性时因接触而使血清阳性率提高的情况。本文的目的是开发允许因接触而增强抗体反应的重复感染数学模型。
使用最大似然法将重复感染模型拟合到年龄分层的血清学数据。
结果表明，使用重复感染模型得到的血清转化率估计值高于催化模型。当传播水平较低时，这种差异较小。这表明催化模型对传播强度的估计低估了高达31%。重复感染模型下血清阳性持续时间较短，但似乎仍然过长。
该模型很重要，因为它可以对血清阳性持续时间做出更现实的估计。这类似于迪茨模型，该模型考虑了重复感染，与同样忽略重复感染的原始罗斯 - 麦克唐纳疟疾模型相比，可以对感染持续时间做出更现实的估计。
