{"id":32892,"date":"2020-05-21T13:27:01","date_gmt":"2020-05-21T20:27:01","guid":{"rendered":"http:\/\/blogs.evergreen.edu\/mesweekly\/?p=32892"},"modified":"2020-05-21T13:27:01","modified_gmt":"2020-05-21T20:27:01","slug":"job-covid-19-corps-syndromic-surveillance-epidemiologist-cdc-foundation-shoreline-wa","status":"publish","type":"post","link":"https:\/\/sites.evergreen.edu\/mesweekly\/job-covid-19-corps-syndromic-surveillance-epidemiologist-cdc-foundation-shoreline-wa\/","title":{"rendered":"Job: COVID 19 Corps- Syndromic Surveillance Epidemiologist, CDC Foundation (Shoreline, WA)"},"content":{"rendered":"<p><!--more--><\/p>\n<p>The CDC Foundation helps the Centers for Disease Control and Prevention (CDC) save and improve lives by unleashing the power of collaboration between CDC, philanthropies, corporations, organizations and individuals to protect the health, safety and security of America and the world. The CDC Foundation is the sole entity authorized by Congress to mobilize philanthropic partners and private-sector resources to support CDC\u2019s critical health protection mission. Since 1995, the CDC Foundation has launched approximately 1,000 programs and has served as a strategic partner to CDC during public health emergencies. This is an outstanding opportunity to work with the nation\u2019s lead agency charged with protecting the public&#8217;s health.<\/p>\n<p>Overview<br \/>\nThe CDC Foundation is seeking a Syndromic Surveillance Epidemiologist in Shoreline, WA. This Syndromic Surveillance Epidemiologist role contributes to this mission by performing public health surveillance and enhancing surveillance practice focused on COVID-19. With syndromic surveillance data submitted by hospitals, emergency departments (EDs) and outpatient clinics. These activities improve OCDE and DOH\u2019s capacity to identify COVID-19 disease trends, conduct disease investigations, improve detection of clusters and hot spots, and provide essential information to inform control measures for COVID-19 in Washington State. This work is done to support DOH\u2019s Rapid Health Information NetwOrk (RHINO) and supports the effective use of public health data and surveillance systems supported and utilized by DOH, LHJ, and tribal epidemiologists.<\/p>\n<p>Responsibilities<br \/>\n\u2022 Evaluates and enhances syndromic queries and definitions used to monitor for trends in clinical encounters related to COVID-19 and other associated health conditions<br \/>\n\u2022 Develops processes for the detection of suspected spatial-temporal clusters of COVID-19 in support of outbreak investigation and control efforts<br \/>\n\u2022 Works with investigators and others supporting outbreak response to identify opportunities to leverage syndromic surveillance data to better characterize and respond to issues related to COVID-19, including potential spillover health effects unrelated to direct infections<br \/>\n\u2022 Designs, develops, and produces datasets, reports, and data visualizations to show trends in COVID-19 activity using syndromic surveillance data for use by DOH practitioners, local heath jurisdictions and tribes, and others as needed<br \/>\n\u2022 Assist with efforts to model the COVID-19 outbreak in Washington to better predict geographical spread, severity, impact on persons at increased risk, burden on the healthcare system, and other key factors<br \/>\n\u2022 Develops, validates, and utilizes advanced analytical tools including text mining and machine learning to improve surveillance practice<br \/>\n\u2022 Develop, monitor, and summarize syndromic surveillance indicators for lifting or implementing non-pharmaceutical interventions across the state<br \/>\n\u2022 Use syndromic surveillance data to describe comorbidities and outcomes of COVID-19 cases<br \/>\n\u2022 Develop innovative methods to analyze trends in data given drastic and frequent changes in underlying data<br \/>\n\u2022 Provide support to local health jurisdiction, DOH, and other personnel on appropriate use and interpretation of syndromic surveillance data.<br \/>\n\u2022 Ensures that validated patient visit data for participating ILINet clinics and hospitals are available to CDC. As appropriate, expands participation in ILINet among syndromic surveillance data submitters<br \/>\n\u2022 Extracts and analyzes the syndromic surveillance data that will be used to determine the percentage of visits due to influenza-like illness, and characterizes the population served by each facility<br \/>\n\u2022 Monitors processes that link syndromic surveillance records to case reports of confirmed COVID-19 cases.<br \/>\n\u2022 Compile and summarize data obtained from external data sources to enable more complete description of hospitalization and ventilator status, among other key variables<br \/>\n\u2022 Participates in communicable disease epidemiology preparedness exercises and training.<br \/>\n\u2022 Provides surge capacity for the communicable disease epidemiology office in responding to public health emergencies.<br \/>\n\u2022 Provides on-site or in-office coverage capacity for communicable disease emergency response, including after hours or weekend response<br \/>\n\u2022 Collaborates with the Division of Emergency Preparedness and Response (EPR) and other DOH programs on planning and response for public health emergencies.<br \/>\n\u2022 May serve on DOH emergency response teams including the Epidemiology Response Team<br \/>\n\u2022 Quality Improvement<br \/>\n\u2022 Progress Reporting<br \/>\n\u2022 Local\/State\/National Involvement<br \/>\n\u2022 Participates in workgroups and communities of practice to enhance surveillance practice in Washington and to share lessons learned with other practitioners and jurisdictions<br \/>\n\u2022 Other duties as assigned<\/p>\n<p>Qualifications<br \/>\n\u2022 A Master&#8217;s degree in epidemiology, or a Master&#8217;s degree in public health including 12 graduate quarter hours or equivalent (500 level or above) in epidemiology and 12 graduate quarter hours or equivalent in biostatistics.<br \/>\n\u2022 Prior experience in public health epidemiology research and analysis.<br \/>\n\u2022 Intermediate to advanced proficiency in R programming, especially use of packages in the tidyverse.<br \/>\n\u2022 Experience practicing syndromic surveillance using the ESSENCE platform or similar<br \/>\n\u2022 Experience analyzing and interpreting clinical data especially from hospitals and Emergency Departments<br \/>\n\u2022 Experience with SQL.<br \/>\n\u2022 Experience with Rhapsody<br \/>\n\u2022 Experience working in communicable disease epidemiology<br \/>\n\u2022 Knowledge of Health Level 7 (HL7) messaging<br \/>\n\u2022 Experience with electronic medical record systems and\/or using medical record data<br \/>\n\u2022 Experience developing geospatial visualizations and\/or developing spatial-temporal cluster detection<br \/>\n\u2022 Experience with machine learning including natural language processing<br \/>\n\u2022 Experience preparing effective data visualizations<br \/>\n\u2022 Experience working with stakeholders and\/or customer service background<\/p>\n<p>All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, national origin, age, mental or physical disabilities, veteran status, and all other characteristics protected by law. We comply with all applicable laws including E.O. 11246 and the Vietnam Era Readjustment Assistance Act of 1974 governing employment practices and do not discriminate on the basis of any unlawful criteria in accordance with 41 C.F.R. \u00a7\u00a7 60-300.5(a)(12) and 60-741.5(a)(7). As a federal government contractor, we take affirmative action on behalf of protected veterans.<br \/>\nThe CDC Foundation is a smoke-free environment.<br \/>\nRelocation expenses are not included.<\/p>\n<p>&nbsp;<\/p>\n<p>Find posting and application here:\u00a0<a href=\"https:\/\/www.cdcfoundation.org\/jobs\">https:\/\/www.cdcfoundation.org\/jobs<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":4,"featured_media":23918,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_s2mail":"yes"},"categories":[14,15],"tags":[4,7,13,20],"_links":{"self":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/32892"}],"collection":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/comments?post=32892"}],"version-history":[{"count":0,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/posts\/32892\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/"}],"wp:attachment":[{"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/media?parent=32892"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/categories?post=32892"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.evergreen.edu\/mesweekly\/wp-json\/wp\/v2\/tags?post=32892"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}