Abstract
Where 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—such as a heuristic model or “pregnancy test for COVID-19” that can factor in the time denominator (i.e., duration of symptoms). This paper asks whether infection among these public health and safety agencies is a \"canary in the coal mine,\" litmus test, or microcosm (pick your analogy) for the communities in which they operate. Can COVID-19 infection counts and rates be seen “moving around” communities by examining the virus’s effect on emergency responders themselves? The troubling question of emergency responders becoming “human indicator values” 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. It has further implications for policies regarding, and investments, in exposure tracking and contact tracing, PPE acquisition, and mental and physical wellness.
Design: We aggregated data from four (4) different EMS documentation systems across twelve (12) states using the MEDIVIEW BEACON Prehospital Health Information Exchange. 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.
Results: 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 “provider impression” 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.
Limitations: This study incorporates data from only (a) twelve (12) states, and (b) four (4) Mobile Medical documentation systems. 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).
Conclusions: Other studies have noted that EMS agencies are tasked with transporting the “sickest of the sick.” We found that PPE is particularly essential where the frequency of encounters between potentially—or actually—infected 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. 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.