This syndrome was developed for enhanced surveillance during a 2017 U.S. President rally in Phoenix, Arizona. Terms were included based on events at previous rallies in other cities. The query was created using chief complaint field in NSSP ESSENCE.
Kumar Rasneet
This syndrome was developed for enhanced surveillance during the National Collegiate Athletic Association Final Four games and related events in Maricopa County in 2017. In addition to the Final four games, Maricopa County hosted several related events including a multi day music festival and Fan Fest. The query was developed in NSSP ESSENCE using chief complaint terms for the events, venues, participating teams, and performing artists
This syndrome was created as a part of the Arboviral Syndromic Surveillance Project in Arizona, which includes bi-weekly monitoring of syndromic data to enhance traditional arboviral surveillance. The syndrome was developed using BioSense 2.0 phpMyAdmin and later transitioned to ESSENCE. The syndrome queries chief complaint and discharge diagnosis code
This syndrome was created as a part of the Arboviral Syndromic Surveillance Project in Arizona, which includes bi-weekly monitoring of syndromic data to enhance traditional arboviral surveillance. The syndrome was developed using BioSense 2.0 phpMyAdmin and later transitioned to ESSENCE. The syndrome queries chief complaint and discharge diagnosis code
This syndrome was created as a part of the Arizona Arboviral Syndrome Surveillance Project, which includes bi-weekly monitoring of syndromic data to enhance traditional surveillance. The syndrome was initially created using BioSesne 2.0 phpMyAdmin and later transitioned to ESSENCE.
This syndrome was created using BioSense 2.0 phpMyAdmin and later transitioned to ESSENCE. The syndrome queries chief complaint and discharge diagnosis fields. The Maricopa County data include emergency room and inpatient visits.
In general, data from public health surveillance can be used for short- and long-term planning and response through retrospective data analysis of trends over time or specific events. Combining health outcome data (e.g., hospitalizations or deaths) with environmental and socio-demographic information also provides a more complete picture of most vulnerable populations. Using syndromic surveillance systems for climate and health surveillance offers the unique opportunity to help quantify and track in near-real time the burden of disease from climate and weather impacts.
This definition is based the following document created by the CSTE Heat Workgroup: Heat-related Illness Syndrome Query: A guidance Document for Implementing Heat-related Illness Syndromic Surveillance in Public Health Practice (attached). The query is built using chief complaint and discharge diagnosis. It is also available in the CC and DD category in NSSP ESSENCE.