When More Transmission Equals Less Disease: Reconciling the Disconnect between Disease Hotspots and Parasite Transmission

The assumed straightforward connection between transmission intensity and disease occurrence impacts surveillance and control efforts along with statistical methodology, including parameter inference and niche modeling. Many infectious disease systems have the potential for this connection to be more complicated–although demonstrating this in any given disease system has remained elusive. Hemorrhagic disease (HD) is one of the most important diseases of white-tailed deer and is caused by viruses in the Orbivirus genus. Like many infectious diseases, the probability or severity of disease increases with age (after loss of maternal antibodies) and the probability of disease is lower upon re-infection compared to first infection (based on cross-immunity between virus strains). These broad criteria generate a prediction that disease occurrence is maximized at intermediate levels of transmission intensity. Using published US field data, we first fit a statistical model to predict disease occurrence as a function of seroprevalence (a proxy for transmission intensity), demonstrating that states with intermediate seroprevalence have the highest level of case reporting. We subsequently introduce an independently parameterized mechanistic model supporting the theory that high case reporting should come from areas with intermediate levels of transmission. This is the first rigorous demonstration of this phenomenon and illustrates that variation in transmission rate (e.g. along an ecologically-controlled transmission gradient) can create cryptic refuges for infectious diseases.传播强度与疾病发生之间被假定存在的直接关联，会对传染病的监测与防控工作，以及参数推断、生态位建模等统计方法的应用产生影响。诸多传染病系统中，这一关联实则可能更为复杂——但要在任一特定传染病系统中证实这一点，始终难以实现。出血热（Hemorrhagic Disease, HD）是白尾鹿的重要病害之一，其病原体为环状病毒属（Orbivirus）病毒。与多数传染病类似，该病的发生概率或严重程度会随宿主年龄增长而升高（母源抗体消失后），且再次感染时的发病概率相较于初次感染更低，这一现象源于病毒毒株间的交叉免疫。基于上述通用规律，可推导出一项预测：当传播强度处于中等水平时，疾病的发生概率将达到峰值。我们利用已公开的美国野外调查数据，首先构建了以血清阳性率（seroprevalence，作为传播强度的替代指标）为自变量的疾病发生概率预测统计模型，结果显示血清阳性率处于中等水平的州，其报告病例数最多。随后，我们引入了一个独立参数化的机理模型，该模型验证了“高病例报告数应源自传播强度中等的区域”这一理论。本研究首次严谨证实了这一现象，并揭示出传播速率的变异（例如沿生态调控的传播梯度）可为传染病提供隐秘的庇护所。