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Methods for Rapid Mobility Estimation to Support Outbreak Response.

ABSTRACT: When pressed for time, outbreak investigators often use homogeneous mixing models to model infectious diseases in data-poor regions. But recent outbreaks such as the 2014 Ebola outbreak in West Africa have shown the limitations of this approach in an era of increasing urbanization and connectivity. Both outbreak detection and predictive modeling depend on realistic estimates of human and disease mobility, but these data are difficult to acquire in a timely manner. This is especially true when dealing with an emerging outbreak in an under-resourced nation. Weighted travel networks with realistic estimates for population flows are often proprietary, expensive, or nonexistent. Here we propose a method for rapidly generating a mobility model from open-source data. As an example, we use road and river network data, along with population estimates, to construct a realistic model of human movement between health zones in the Democratic Republic of the Congo (DRC). Using these mobility data, we then fit an epidemic model to real-world surveillance data from the recent Ebola outbreak in the Nord Kivu region of the DRC to illustrate a potential use of the generated mobility estimation. In addition to providing a way for rapid risk estimation, this approach brings together novel techniques to merge diverse GIS datasets that can then be used to address issues that pertain to public health and global health security.

SUBMITTER: Telionis PA

PROVIDER: S-EPMC7047125 | biostudies-literature | 2020 Jan/Feb

REPOSITORIES: biostudies-literature

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Methods for Rapid Mobility Estimation to Support Outbreak Response.

Telionis Pyrros A PA Corbett Patrick P Venkatramanan Srinivasan S Lewis Bryan B

Health security 20200101 1

When pressed for time, outbreak investigators often use homogeneous mixing models to model infectious diseases in data-poor regions. But recent outbreaks such as the 2014 Ebola outbreak in West Africa have shown the limitations of this approach in an era of increasing urbanization and connectivity. Both outbreak detection and predictive modeling depend on realistic estimates of human and disease mobility, but these data are difficult to acquire in a timely manner. This is especially true when de ...[more]

PMID: 32078419

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Project description:The global cerebral metabolic rate of oxygen (CMRO2), which reflects metabolic activity of the brain under various physiologic conditions, can be quantified using a method, referred to as 'OxFlow', which simultaneously measures hemoglobin oxygen saturation in a draining vein (Yv) and total cerebral blood flow (tCBF). Conventional OxFlow (Conv-OxFlow) entails four interleaves incorporated in a single pulse sequence - two for phase-contrast based measurement of tCBF in the supplying arteries of the neck, and two to measure the intra- to extravascular phase difference in the superior sagittal sinus to derive Yv [Jain et al., JCBFM 2010]. However, this approach limits achievable temporal resolution thus precluding capture of rapid changes of brain metabolic states such as the response to apneic stimuli. Here, we developed a time-efficient, multiplexed OxFlow method and evaluated its potential for measuring dynamic alterations in global CMRO2 during a breath-hold challenge. Two different implementations of multiplexed OxFlow were investigated: 1) simultaneous-echo-refocusing based OxFlow (SER-OxFlow) and 2) simultaneous-multi-slice imaging-based dual-band OxFlow (DB-OxFlow). The two sequences were implemented on 3T scanners (Siemens TIM Trio and Prisma) and their performance was evaluated in comparison to Conv-OxFlow in ten healthy subjects for baseline CMRO2 quantification. Comparison of measured parameters (Yv, tCBF, CMRO2) revealed no significant bias of SER-OxFlow and DB-OxFlow, with respect to the reference Conv-OxFlow while improving temporal resolution two-fold (12.5 versus 25s). Further acceleration shortened scan time to 8 and 6s for SER and DB-OxFlow, respectively, for time-resolved CMRO2 measurement. The two sequences were able of capturing smooth transitions of Yv, tCBF, and CMRO2 over the time course consisting of 30s of normal breathing, 30s of volitional apnea, and 90s of recovery. While both SER- and DB-OxFlow techniques provide significantly improved temporal resolution (by a factor of 3 - 4 relative to Conv-OxFlow), DB-OxFlow was found to be superior for the study of short physiologic stimuli.

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Methods for Rapid Mobility Estimation to Support Outbreak Response.

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Methods for Rapid Mobility Estimation to Support Outbreak Response.

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