Department of Biomedical Sciences, Oregon State University, Corvallis, OR 97331;
Department of Integrative Biology, Oregon State University, Corvallis, OR 97331.
Proc Natl Acad Sci U S A. 2018 Jul 17;115(29):7545-7550. doi: 10.1073/pnas.1801095115. Epub 2018 Jul 2.
Coinfecting parasites and pathogens remain a leading challenge for global public health due to their consequences for individual-level infection risk and disease progression. However, a clear understanding of the population-level consequences of coinfection is lacking. Here, we constructed a model that includes three individual-level effects of coinfection: mortality, fecundity, and transmission. We used the model to investigate how these individual-level consequences of coinfection scale up to produce population-level infection patterns. To parameterize this model, we conducted a 4-y cohort study in African buffalo to estimate the individual-level effects of coinfection with two bacterial pathogens, bovine tuberculosis (bTB) and brucellosis, across a range of demographic and environmental contexts. At the individual level, our empirical results identified bTB as a risk factor for acquiring brucellosis, but we found no association between brucellosis and the risk of acquiring bTB. Both infections were associated with reductions in survival and neither infection was associated with reductions in fecundity. The model reproduced coinfection patterns in the data and predicted opposite impacts of coinfection at individual and population scales: Whereas bTB facilitated brucellosis infection at the individual level, our model predicted the presence of brucellosis to have a strong negative impact on bTB at the population level. In modeled populations where brucellosis was present, the endemic prevalence and basic reproduction number ([Formula: see text]) of bTB were lower than in populations without brucellosis. Therefore, these results provide a data-driven example of competition between coinfecting pathogens that occurs when one pathogen facilitates secondary infections at the individual level.
由于寄生虫和病原体的双重感染会对个体感染风险和疾病进展产生影响，它们仍是全球公共卫生面临的主要挑战。然而，人们对于双重感染的人群层面后果仍缺乏清晰的认识。在这里，我们构建了一个模型，其中包含寄生虫和病原体双重感染的三个个体层面影响：死亡率、繁殖力和传播力。我们使用该模型研究了这些双重感染的个体层面后果如何扩大到产生人群层面的感染模式。为了给这个模型提供参数，我们在非洲水牛中进行了为期 4 年的队列研究，以估计在一系列人口统计学和环境背景下，两种细菌病原体（牛结核病和布鲁氏菌病）的双重感染对个体层面的影响。在个体层面上，我们的实证结果确定了牛结核病是感染布鲁氏菌病的一个风险因素，但我们没有发现布鲁氏菌病与感染牛结核病的风险之间存在关联。这两种感染都与存活率降低有关，而两者都与繁殖力降低无关。该模型再现了数据中的双重感染模式，并预测了个体和人群层面上双重感染的相反影响：虽然牛结核病在个体层面上促进了布鲁氏菌病的感染，但我们的模型预测，布鲁氏菌病的存在会对人群层面上的牛结核病产生强烈的负面影响。在存在布鲁氏菌病的模型人群中，牛结核病的地方性流行率和基本繁殖数 ([Formula: see text]) 低于没有布鲁氏菌病的人群。因此，这些结果提供了一个数据驱动的例子，说明了在个体层面上一种病原体促进二次感染的情况下，同时感染的病原体之间存在竞争。
