Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA 24060, USA.
Instituto de Virología, Instituto Nacional de Tecnología Agropecuaria (INTA), Castelar 1712, Argentina.
Viruses. 2020 Aug 28;12(9):955. doi: 10.3390/v12090955.
Human noroviruses (HuNoVs) are the leading causative agents of epidemic and sporadic acute gastroenteritis that affect people of all ages worldwide. However, very few dose-response studies have been carried out to determine the median infectious dose of HuNoVs. In this study, we evaluated the median infectious dose (ID) and diarrhea dose (DD) of the GII.4/2003 variant of HuNoV (Cin-2) in the gnotobiotic pig model of HuNoV infection and disease. Using various mathematical approaches (Reed-Muench, Dragstedt-Behrens, Spearman-Karber, exponential, approximate beta-Poisson dose-response models, and area under the curve methods), we estimated the ID and DD to be between 2400-3400 RNA copies, and 21,000-38,000 RNA copies, respectively. Contemporary dose-response models offer greater flexibility and accuracy in estimating ID. In contrast to classical methods of endpoint estimation, dose-response modelling allows seamless analyses of data that may include inconsistent dilution factors between doses or numbers of subjects per dose group, or small numbers of subjects. Although this investigation is consistent with state-of-the-art ID determinations and offers an advancement in clinical data analysis, it is important to underscore that such analyses remain confounded by pathogen aggregation. Regardless, challenging virus strain ID determination is crucial for identifying the true infectiousness of HuNoVs and for the accurate evaluation of protective efficacies in pre-clinical studies of therapeutics, vaccines and other prophylactics using this reliable animal model.
人类诺如病毒(HuNoVs)是导致全球各年龄段人群暴发和散发急性胃肠炎的主要病原体。然而,仅有少数剂量-反应研究用于确定 HuNoVs 的中位感染剂量。在本研究中,我们在 HuNoV 感染和疾病的无菌猪模型中评估了 GII.4/2003 变异型 HuNoV(Cin-2)的中位感染剂量(ID)和腹泻剂量(DD)。我们使用了各种数学方法(Reed-Muench、Dragstedt-Behrens、Spearman-Karber、指数、近似β-Poisson 剂量反应模型和曲线下面积方法),估计 ID 和 DD 分别为 2400-3400 RNA 拷贝和 21,000-38,000 RNA 拷贝。当代剂量反应模型在估计 ID 方面具有更大的灵活性和准确性。与终点估计的经典方法相比,剂量反应建模允许无缝分析数据,这些数据可能包括剂量之间不一致的稀释因素或每个剂量组的受试者数量,或者受试者数量较少。尽管这项研究与最先进的 ID 确定一致,并为临床数据分析提供了进展,但重要的是要强调,此类分析仍然受到病原体聚集的影响。无论如何,挑战病毒株 ID 确定对于确定 HuNoVs 的真实传染性以及在使用这种可靠动物模型的治疗、疫苗和其他预防措施的临床前研究中准确评估保护效力至关重要。