{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,8,9]],"date-time":"2022-08-09T04:04:06Z","timestamp":1660017846327},"reference-count":0,"publisher":"University of Illinois Libraries","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["OJPHI"],"abstract":"Abstract \nWhere there is limited access to COVID-19 tests, or where the results of such tests have been delayed or even invalidated (e.g., California and Utah), there is a need for scalable alternative approaches\u2014such as a heuristic model or \u201cpregnancy test for COVID-19\u201d that can factor in the time denominator (i.e., duration of symptoms).\u00a0 This paper asks whether infection among these public health and safety agencies\u00a0is a \"canary in the coal mine,\" litmus\u00a0test, or microcosm (pick your analogy) for the communities in which they operate.\u00a0 Can COVID-19 infection counts and rates be seen \u201cmoving around\u201d communities by examining the virus\u2019s effect on emergency\u00a0responders themselves? \u00a0The troubling question of emergency responders becoming \u201chuman indicator values\u201d is relevant to maintaining the health of Mobile Medicine (EMS and Fire) personnel, as well as Police, who are an under-attended population, because without them our collective resiliency would crash.\u00a0 It has further implications for policies regarding, and investments, in exposure tracking and contact tracing, PPE acquisition, and mental and physical wellness.\u00a0 \n\u00a0 \nDesign:\u00a0 We aggregated data from four (4) different EMS documentation systems across twelve (12) states using the MEDIVIEW BEACON Prehospital Health Information Exchange.\u00a0 We then outputted lists of charts containing critical ICD-10 values that had been identified by the WHO, the CDC, and the Los Angeles County Fire Dept. as inclusion criteria for possible signs, symptoms, and clinical impressions of COVID-19. \n\u00a0 \nResults:\u00a0 Three important results emergency from this study: (1) a demonstration of frequent exposure to possible COVID-19 infection among Mobile Medical (EMS & Fire) care providers in the states whose data were included; (2) a demonstration of the nervousness of the general population, given that calls for help due to possible COVID-19 based on symptomology exceeded the number of responses with a correlating \u201cprovider impression\u201d after an informed clinical assessment; and (3) that this study was empowered by a public-private partnerships between a technology startup and numerous public health and public safety agencies, offers a template for success in rapidly implementing research and development collaborations. \n\u00a0 \nLimitations:\u00a0 This study incorporates data from only (a) twelve (12) states, and (b) four (4) Mobile Medical documentation systems.\u00a0 We sought to combat these limitations by ensuring that our sample crosses agencies types, geographies, population demographics, and municipal environments (i.e., rural vs. urban). \n\u00a0 \nConclusions:\u00a0 Other studies have noted that EMS agencies are tasked with transporting the \u201csickest of the sick.\u201d\u00a0 We found that PPE is particularly essential where the frequency of encounters between potentially\u2014or actually\u2014infected patients is high, because from Los Angeles County to rural Texas, without sufficient protection, public health and public safety agencies have become microcosms of the communities they are meant to protect.\u00a0 Indeed, data from the first six months of the pandemic in the U.S.A. show that intra-departmental spread is one of (if not the) riskiest sources of infection among Mobile Medical professionals.<\/jats:p>","DOI":"10.5210\/ojphi.v13i1.11484","type":"journal-article","created":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T20:50:20Z","timestamp":1617396620000},"source":"Crossref","is-referenced-by-count":0,"title":["COVID-19 Exposure Tracking Within Public Health & Safety Enterprises:"],"prefix":"10.5210","volume":"13","author":[{"given":"Jonathon","family":"Feit","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Witt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"3470","published-online":{"date-parts":[[2021,3,21]]},"container-title":["Online Journal of Public Health Informatics"],"original-title":[],"link":[{"URL":"https:\/\/journals.uic.edu\/ojs\/index.php\/ojphi\/article\/download\/11484\/10088","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.uic.edu\/ojs\/index.php\/ojphi\/article\/download\/11484\/10088","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,8]],"date-time":"2022-08-08T19:53:49Z","timestamp":1659988429000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.uic.edu\/ojs\/index.php\/ojphi\/article\/view\/11484"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,21]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,4,2]]}},"URL":"https:\/\/doi.org\/10.5210\/ojphi.v13i1.11484","relation":{},"ISSN":["1947-2579"],"issn-type":[{"value":"1947-2579","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,21]]}}}