Division of Infectious Diseases, Wadsworth Center, New York State Department of Health, Albany, New York, United States of America.
Department of Atmospheric and Environmental Sciences, University at Albany, Albany, New York, United States of America.
PLoS Negl Trop Dis. 2021 Sep 9;15(9):e0009653. doi: 10.1371/journal.pntd.0009653. eCollection 2021 Sep.
West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m-km, days-weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.
西尼罗河病毒（WNV）是一种分布广泛的蚊媒病毒，对公共健康构成了极大的威胁。WNV 人类病例和蚊子感染模式在空间和时间上存在差异。许多统计模型已经被开发出来，以理解和预测 WNV 的地理和时间动态。然而，这些建模工作是相互独立的，很少进行模型比较，也没有一致的验证。在本文中，我们描述了一个框架，以统一和规范全国范围内的 WNV 建模工作。本综述从美国不同地区积极开展研究的研究小组中征集了 WNV 风险、检测或预警模型。共选择并描述了 13 个模型。比较了每个模型的时空尺度，以指导蚊子和病毒监测的时间和地点，支持蚊子媒介控制决策，并在多个决策尺度上协助开展公共卫生宣传活动。我们的总体目标是弥合模型开发（通常作为学术活动进行）与实际模型应用（发生在州、部落、地方或地区公共卫生和蚊虫控制机构层面）之间的现有差距。拟议的模型评估和比较框架有助于澄清单个模型在决策中的价值，并确定每个模型的适当时间和空间范围。这种定性评估清楚地确定了将模型与应用决策联系起来的差距，并为模型的定量比较奠定了基础。具体而言，虽然已经开发了许多粗粒度的模型（县分辨率或更大），但最需要的是细粒度的短期规划模型（m-km，天-周），而这类模型仍然稀缺。我们进一步建议量化每个决策的信息价值，以确定最需要模型输入的决策。
