用于西尼罗河病毒预测的虫媒病毒绘图和预测 (ArboMAP) 系统

IF 2.5 Q2 HEALTH CARE SCIENCES & SERVICES
Dawn M. Nekorchuk, Anita Bharadwaja, Sean Simonson, Emma Ortega, Caio M B França, Emily Dinh, Rebecca Reik, Rachel Burkholder, Michael C Wimberly
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引用次数: 0

摘要

西尼罗河病毒(WNV)是美国最常见的蚊媒疾病。预测疫情爆发的地点和时间有助于有针对性地开展疾病预防和蚊虫控制活动。我们的目标是开发一款软件(ArboMAP),利用公共卫生监测数据和气象观测数据对 WNV 进行常规预测。 ArboMAP 使用 R 标记脚本进行数据处理、建模和报告生成。开发了一个谷歌地球引擎应用程序,用于汇总和下载气象数据。使用广义相加模型对 WNV 病例进行县级预测。 ArboMAP 最大限度地减少了每周预测所需的人工步骤,生成了对决策者有用的信息,并在多个公共卫生机构进行了测试和实施。 公共卫生部门使用 ArboMAP 对蚊媒疾病风险进行常规预测是可行的,并可付诸实施。 西尼罗河病毒(WNV)是美国最常见的蚊媒疾病。为了降低 WNV 的风险,公共卫生机构分发有关如何避免蚊虫叮咬的信息,并使用杀虫剂来减少传播疾病的蚊虫数量。关于何时何地感染 WNV 风险最高的信息将有助于这些机构有针对性地开展活动,并更有效地利用有限的资源。为了支持这一目标,我们开发了 ArboMAP 软件系统,用于预测人类感染 WNV 疾病的风险。ArboMAP 利用最近的天气信息,结合诱捕蚊子并检测蚊子是否携带 WNV 的数据,来预测未来几周会有多少人感染病例。预测贯穿当前的 WNV 流行季节(通常为 5 月至 9 月),并针对州内的每个县进行预测。该系统以一套免费软件工具的形式实施,可供州、市卫生部门的流行病学家使用。南达科他州、路易斯安那州、俄克拉荷马州和密歇根州公共卫生机构的反馈意见已被纳入该系统,以提高系统的可用性,并设计可视化的预测总结。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Arbovirus Mapping and Prediction (ArboMAP) System for West Nile Virus Forecasting
West Nile virus (WNV) is the most common mosquito-borne disease in the United States. Predicting the location and timing of outbreaks would allow targeting of disease prevention and mosquito control activities. Our objective was to develop software (ArboMAP) for routine WNV forecasting using public health surveillance data and meteorological observations. ArboMAP was implemented using an R markdown script for data processing, modelling, and report generation. A Google Earth Engine application was developed to summarize and download weather data. Generalized additive models were used to make county-level predictions of WNV cases. ArboMAP minimized the number of manual steps required to make weekly forecasts, generated information that was useful for decision makers, and has been tested and implemented in multiple public health institutions. Routine predictions of mosquito-borne disease risk are feasible and can be implemented by public health departments using ArboMAP. West Nile virus (WNV) is the most common mosquito-borne disease in the United States. To reduce the risk of WNV, public health agencies distribute information about how to avoid mosquito bites and use insecticides to reduce the abundances of disease-transmitting mosquitoes. Information about when and where the risk of getting WNV is highest would help these agencies to target their activities and use limited resources more efficiently. To support this goal, we developed the ArboMAP software system for predicting the risk of WNV disease in humans. ArboMAP uses information about recent weather combined with data obtained from trapping mosquitoes and testing them for presence of WNV to predict how many human cases that will occur in future weeks. Predictions extend throughout the current WNV season (typically May-September) and are made for each county within a state. The system is implemented as a set of free software tools that can be used by epidemiologists in state and municipal departments of health. Feedback from public health agencies in South Dakota, Louisiana, Oklahoma, and Michigan has been incorporated to enhance the usability of the system and design visualizations that summarize the forecasts.
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来源期刊
JAMIA Open
JAMIA Open Medicine-Health Informatics
CiteScore
4.10
自引率
4.80%
发文量
102
审稿时长
16 weeks
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