Using Community-Level Prevalence of <i>Loa loa</i> Infection to Predict the Proportion of Highly-Infected Individuals: Statistical Modelling to Support Lymphatic Filariasis and Onchocerciasis Elimination Programs

Lymphatic Filariasis and Onchocerciasis (river blindness) constitute pressing public health issues in tropical regions. Global elimination programs, involving mass drug administration (MDA), have been launched by the World Health Organisation. Although the drugs used are generally well tolerated, individuals who are highly co-infected with Loa loa are at risk of experiencing serious adverse events. Highly infected individuals are more likely to be found in communities with high prevalence. An understanding of the relationship between individual infection and population-level prevalence can therefore inform decisions on whether MDA can be safely administered in an endemic community. Based on Loa loa infection intensity data from individuals in Cameroon, the Republic of the Congo and the Democratic Republic of the Congo we develop a statistical model for the distribution of infection levels in communities. We then use this model to make predictive inferences regarding the proportion of individuals whose parasite count exceeds policy-relevant levels. In particular we show how to exploit the positive correlation between community-level prevalence and intensity of infection in order to predict the proportion of highly infected individuals in a community given only prevalence data from the community in question. The resulting prediction intervals are not substantially wider, and in some cases narrower, than the corresponding binomial confidence intervals obtained from data that include measurements of individual infection levels. Therefore the model developed here facilitates the estimation of the proportion of individuals highly infected with Loa loa using only estimated community level prevalence. It can be used to assess the risk of rolling out MDA in a specific community, or to guide policy decisions.淋巴丝虫病（Lymphatic Filariasis）与盘尾丝虫病（河盲症，Onchocerciasis）是热带地区亟待解决的重大公共卫生问题。世界卫生组织已发起包含大规模药物给药（mass drug administration, MDA）在内的全球消除规划。尽管所用药物总体耐受性良好，但同时高感染罗阿丝虫（Loa loa）的个体存在发生严重不良事件的风险。高感染个体更常出现于感染流行率较高的社区。因此，明晰个体感染水平与群体流行率之间的关联，可为某一流行社区是否可安全开展大规模药物给药提供决策参考。本研究基于喀麦隆、刚果共和国及刚果民主共和国人群的罗阿丝虫感染强度数据，构建了社区内感染水平分布的统计模型。随后利用该模型对寄生虫计数超过政策相关阈值的个体比例开展预测推断。特别地，研究展示了如何利用社区级流行率与感染强度间的正相关关系，仅通过目标社区的流行率数据，即可预测该社区内高感染个体的占比。所得预测区间与包含个体感染水平测量数据的二项式置信区间相比，宽度并未显著增加，部分场景下甚至更窄。因此，本研究所构建的模型可仅通过估算的社区级流行率，实现罗阿丝虫高感染个体占比的估算，可用于评估特定社区开展大规模药物给药的风险，或为政策制定提供指导。