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850 records · Page 48

Epi Archive: automated data collection of notifiable disease data

LANL has built a software program that automatically collects global notifiable disease data—particularly data stored in files—and makes it available and shareable within the Biosurveillance Ecosystem(BSVE) as a new data source. This will improve the prediction and early warning of disease events and other applications. Most countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health as exemplified by the Biosurveillance Ecosystem(BSVE).While most nations do likely store their data in a machine-readable format, the governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues. For example, an attempt by LANL to obtain a weekly version of openly available monthly data, reported by the Australian government, resulted in an onerous bureaucratic reply. The obstacles to obtaining data included: paperwork to request data from each of the Australian states and territories, a long delay to obtain data (up to 3 months) and extensive limitations on the data’s use that prohibit collaboration and sharing. This type of experience when attempting to contact public health departments or ministries of health for data is not uncommon. A survey conducted by LANL of notifiable disease data reporting in 52 countries identified only 10 as being machine-readable and 42 being reported in pdf files on a regular basis. Within the 42 nations that report in pdf files, 32 report in a structured, tabular format and10 in a non-structured way. As a result, LANL has developed a tool-Epi Archive (formerly known as EPIC)-to automatically and continuously collect global notifiable disease data and make it readily accessible. We conducted a survey of the national notifiable disease reporting systems notating how the data is reported in two important dimensions: date standards and case definitions. The development of software to regularly ingests notifiable disease data frand makes this data available involved four main steps scraping, extracting, parsing and persisting. For scraping: we would examine website designs and determine reporting mechanisms for each country/website as well as what varies across the reporting mechanisms. We then designed and wrote code to automate the downloading of report pdf files, for each country. We stored report pdfs along with appropriate metadata for extracting and parsing. For extracting: we developed software that can extract notifiable disease data presented in tabular form from a pdf file. We combined the methodology of figure placement detection with the in-house developed table extraction and annotation heuristics. For parsing: we determined what to extract from each pdf dataset from the survey conducted. We then parsed the extracted data into uniform data structures correctly accommodating the dimensions surveyed and the various human languages. This task involved ingesting notifiable disease data in many disparate formats extracted from pdf files and coalescing the data into a standardized format. For persisting: We then store the data in the Epi Archive PostgreSQL database and make it available through the BSVE. The EpiArchive tool currently contains subnational notifiable disease data from 10 nations. When a user accesses the EpiArchive site, they are prompted with four fields: country, region, disease, and date duration. These fields allow the user to specify the location(down to the state level), the disease of interest, and the duration of interest. Upon form submission, a time series is generated from the users’ specifications. The generated time series can then be downloaded into a csv file if a user is interested in performing personal analysis. Additionally, the data from EpiArchive can be reached through an API. LANL as part of a currently funded DTRA effort so that it will automatically and continuously collect global notifiable disease data—particularly data stored in pdf files—and make it available and shareable within the Biosurveillance Ecosystem (BSVE) as a new data source. This will provide data to analytics and users that will improve the prediction and early warning of disease events and other applications.

59 BASIC BIOLOGICAL SCIENCES↗

Remediation Guidance for Major Airports after a Bioterrorist Attack

This document provides general guidelines for airport managers, local officials, and other stakeholders for developing a response and recovery plan for a major airport following the release of a biological warfare agent, with specific guidance for remediation. San Francisco International Airport was selected as the example airport during development of the guidance to illustrate specific details. The spore-forming bacterium Bacillus anthracis was selected as the biological agent of primary concern because it is the most difficult of known bioterrorism agents to inactivate and is considered to be one of the agents most likely to be used as a biological weapon. The focus of the guidance is on cleanup and disposal activities associated with the Characterization, Decontamination, and Clearance Phases that are defined herein. Activities associated with the Notification and First-Response Phases are brieÀy discussed in Appendixes A and B, respectively. In addition to the main text of this Remediation Guidance document and associated appendixes, a data supplement was developed specifically for San Francisco International Airport. Requests for the data supplement must be made directly to the Emergency Planning Operations Division of San Francisco International Airport. This document does not describe public health responses to release of a biological warfare agent. If laboratory analytical results confirm the presence of a biological agent, the responsible public health agency involved in the response will commence appropriate public health actions, such as treatment (CDC 2004) and decontamination of potentially contaminated individuals, distribution of prophylaxis, and medical examinations. See the Centers for Disease Control and Prevention web site for more information on emergency public health responses (http://www.bt.cdc.gov/). Effective communication with the media and the public is an essential component of airport remediation and recovery. Whereas such communication is beyond the scope of this document, many helpful resources are available. (See Section 1.1 for more information.) The concept of operations described in this document for cleanup of a Bacillus anthracis release at a major airport conforms to the National Response Framework (NRF) (DHS 2008) and implementation of the National Incident Management System (NIMS 2004). In most cases, a Unified Command would be formed to direct the cleanup process jointly and to take ultimate responsibility for all cleanup decisions. The Unified Command would likely include the Airport Manager or Airport Emergency Operations Manager, representatives from state and local public health and emergency management agencies, and Federal agencies, such as the U.S. Environmental Protection Agency. The Unified Command and Incident Command Staff would ideally be co-located in an Incident Command Post in an uncontaminated area of the airport. If a release is large or complex, co-location of all key players may not be possible. If a major incident is declared, a Principal Federal Official may be appointed by the Department of Homeland Security to facilitate Federal support to the Unified Command. In some facilities and jurisdictions, additional response plans or procedures (such as BioWatch or other emergency response plans, procedures, or protocols) may govern notification and first response. Facility personnel, responders, and emergency management coordinators should be aware of all applicable plans and procedures and how to implement them. Cleanups following the anthrax attacks of 2001 in the U.S. pre-dated the NRF and NIMS and did not make use of a NIMS Incident Command System as we know it today. Most Incident Commanders for the larger of those cleanups chose to convene a Technical Working Group (TWG) of multi-agency, multi-disciplinary, outside experts to advise in developing sampling and decontamination plans. Most of the Incident Commanders also convened a separate Environmental Clearance Committee (ECC) to independently review pre- and post decontamination sampling data as well as data on decontamination parameters, to evaluate whether the decontamination was effective, and to add credibility regarding a decision that decontaminated areas may be reoccupied. Use of such specialized technical expertise is strongly recommended, although it would now operate within the construct of the NIMS Incident Command System. The TWG, if convened, would act in an advisory capacity to the Environmental Unit within the Planning Section. Likewise, the ECC, if convened, would provide independent peer review of products and recommendations by the Environmental Unit. For maximum impartiality, the ECC could also provide recommendations directly to the Unified Command. Cleanup activities commence with site characterization. The principal goal of characterization is to define the extent of contamination and to gather information needed to design the decontamination approach. Initial sampling data collected by first responders are assessed to approximate the location(s) of contamination. Confirmation of the agent type and viability is obtained from a Laboratory Response Network laboratory. Additional characterization data are collected to determine the extent of contamination and where decontamination actions are needed. Areas suspected of being contaminated are contained and isolated to the degree possible to prevent further movement of an agent to uncontaminated areas or the environment, and to reduce the potential for future exposure from the agent or fumigant, if fumigation is needed. Agent air monitoring in areas adjacent to the contained contamination zones is done to ensure the protection of remediation personnel and to monitor any release from the contained zones. Various sampling approaches are considered. For example, wipe samples can be used to sample hard, nonporous surfaces. Swab samples can be used to sample nooks, crannies, joints, and seams. Appendix I is a template for preparing an incident-specific, operational characterization plan. Upon completion of the characterization plan, an internal review is initiated. Upon approval of the plan by the Unified Command, characterization commences. The Site Safety Officer develops a Health and Safety Plan to ensure that coordinated health and safety measures are in place for all responding personnel. This plan describes physical, chemical, and biological hazards at the site, personal protective equipment, personal decontamination procedures, and emergency procedures to be used by sampling and remediation personnel. An incident-specific Remediation Action Plan is developed, which describes the decontamination methods to be used and other details, including waste disposal. Under NIMS, this overall plan, as well as other plans described below, are implemented through a series of standardized, shorter-term Incident Action Plans, which describe specific activities that will take place during a shift or a day. The template in Appendix J is designed to facilitate preparation of the Remediation Action Plan. If fumigation will be done, a Sampling and Analysis Plan will be needed, as well as an Ambient Air Monitoring Plan, which can be a component of the Remediation Action Plan. These three plans are needed to obtain a crisis exemption from the U.S. Environmental Protection Agency for authorized use of an unregistered sterilant or pesticide during cleanup. If pesticide products become registered for inactivation of B. anthracis in the future, the three plans will likely be required by the product’s labeling, but the plans would no longer be submitted to the U.S. Environmental Protection Agency for approval; rather, the Incident Commander would approve them. If fumigation is used, an Emergency Response Plan is also recommended, although such a plan is not required for a crisis exemption. For some nonpersistent biological warfare agents, natural attenuation may be an adequate decontamination option. In cases where contamination is not extensive or an agent is not persistent, application of surface decontaminants or other methods of medical infection control may be effective. For extensive contamination by persistent agents, such as Bacillus anthracis, fumigation may be necessary. In those cases, the Decontamination Phase commences with source reduction, such as pre-cleaning surfaces to reduce the contaminant load. To expedite cleanup and prevent costs from escalating unnecessarily, a cost–benefit analysis should be incorporated in the decision process related to retention versus disposal of facility items and materials. Certain materials and structural components can be decontaminated for reuse, but it may not be feasible or cost-effective to decontaminate other items. Those items must be pre-treated, packaged (with the package decontaminated externally), and removed for disposal as waste. Site preparation includes sealing openings to prevent leaks and setting up equipment. Decontamination reagents and delivery systems are selected, and pre-testing all systems is done before carrying out chemical treatment(s). The important choice of decontamination technologies depends on characteristics of the agent, the nature and extent of contamination, and other site parameters identified during characterization. Decontamination-related decisions can have a major impact on waste-disposal costs, and it is necessary to develop a disposal plan that identifies a means of disposal, necessary approvals, transportation, and other details. A clearance strategy is developed to ensure that after decontamination, the risk of exposure to residual contamination is negligible. A clearance sampling plan is developed, which sets clearance criteria, specifies how to determine whether the criteria have been met, and describes how and where to collect clearance samples after decontamination. In most cases, clearance sampling includes both surface and aggressive air samples. Appendix K is a clearance plan template that identifies the types of required information. To determine whether the decontaminated area may be reoccupied, the Environmental Unit (and the ECC separately, if one is convened) evaluates the results of clearance samples. For the anthrax incidents to date, and given methods that have been used, cleanup was considered successful only when there was no growth of B. anthracis cultured from any environmental samples taken after decontamination. Other factors that will be considered include the decontamination process parameters (e.g., temperature, relative humidity, decontaminant concentration, and contact time) and the results from post-decontamination culture of biological indicators that may have been used during fumigation or sterilization processes. From such an evaluation the Environmental Unit or ECC, or both, recommend whether the area may be reoccupied, or whether further decontamination is necessary. The UC makes the final decision that a facility is appropriately decontaminated for reoccupancy. The facility owner or responsible public health agency makes the final decision to reopen a decontaminated facility. A theme that is emphasized throughout this document is that many activities can greatly reduce the time required to restore airport operations if those activities are conducted prior to an actual release of biological warfare agent. A summary of specific resources (such as Federal, state, and local agency contacts; contractors; prospective team members; subject-matter experts; laboratory facilities; and other entities) that should be identified in advance by airport officials is provided in each pertinent section of this document, and summary contact lists of such resources are provided in Appendix L. A summary of overall pre-planning actions that should be completed by airport officials is presented at the end of this document.

59 BASIC BIOLOGICAL SCIENCES↗

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence↗

A precise measurement of the jet energy scale derived from single-particle measurements and in situ techniques in proton–proton collisions at $\sqrt{s}=$ 13 TeV with the ATLAS detector

The jet energy calibration and its uncertainties are derived from measurements of the calorimeter response to single particles in both data and Monte Carlo simulation using proton–proton collisions at $\sqrt{s} = 13$ TeV collected with the ATLAS detector during Run 2 at the Large Hadron Collider. The jet calibration uncertainty for anti-$k_T$ jets with a jet radius parameter of R$_\textrm{jet} = 0.4$ and in the central jet rapidity region is about 2.5% for transverse momenta ($p_{\text {T}}$) of 20 $\text {GeV}$ , about 0.5% for $p_{\text {T}} = 300$ GeV and 0.7% for $p_{\text {T}} = 4$ TeV . Excellent agreement is found with earlier determinations obtained from -balance based in situ methods ($Z/\gamma$ +jets). The combination of these two independent methods results in the most precise jet energy measurement achieved so far with the ATLAS detector with a relative uncertainty of 0.3% at $p_\textrm{T} = 300$ GeV and 0.6% at 4 TeV. The jet energy calibration is also derived with the single-particle calorimeter response measurements separately for quark- and gluon-induced jets and furthermore for jets with R jet varying from 0.2 to 1.0 retaining the correlations between these measurements. Differences between inclusive jets and jets from boosted top-quark decays, with and without grooming the soft jet constituents, are also studied.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗