Monitoring the 2016 LA County Sand Fire with Multiple Early Detection Systems
Authors: Viola Rachel , Luarca Monica Z. , Kajita Emily , Lim Michael , Hwang Bessie 
Published: May 2017

ObjectiveTo detect increases in health complaints resulting from the July2016 Sand Fire near Santa Clarita, CA using syndromic surveillanceand complementary systems.IntroductionOn July 22, 2016, the Sand Fire began burning in the Santa ClaritaValley of Los Angeles County (LAC), CA. This urban-adjacentwildfire breached the city limits of Santa Clarita (population 180,000).Fueled by record heat and an ongoing exceptional drought, the SandFire burned over 40,000 acres in 13 days1and caused a large increasein the air concentration of fine particulate matter2. The syndromicsurveillance team was tasked with reporting on possible health effectsfrom the fire. Fire, asthma, and heat related data were monitoreduntil the fire was reported as 98% contained. The team prepared anddistributed a daily special summary report to key stakeholders in theLAC Department of Public Health.MethodsEmergency department (ED) data were queried for cases relatedto fire, asthma, cardiac events, eye irritation, heat, and total volume.These queries consisted of key word searches within chief complaint(CC), diagnosis and triage note data fields. Queries were conductedon all participating syndromic EDs in LAC, and also restricted to nineEDs closest to the fire. The resulting line lists were reviewed dailyto rule out visits that were unrelated to the Sand Fire. The fire querywas refined periodically with additional exclusion terms. Complaintsrelated to asthma were tallied in a second query. In order to assessheat-related ED visits and temperature trends, existing queries andreport templates were modified to focus on the nine fire-area EDs.Local temperatures were taken from the Weather Undergroundwebsite. Complementary systems were also monitored, includingover-the-counter medication sales and nurse hotline call data. Trendgraphs for hospital admissions and ED visits were produced daily toassess volume from 19 Reddinet participating hospitals. In additionto internal data sources, the South Coast Air Quality ManagementDistrict website was checked daily to monitor air quality in the SantaClarita Valley.ResultsThere were 48 syndromic ED patient records with direct mention ofthe fire in LAC’s syndromic hospitals in 13 days. Of these, 26 did notinclude asthma, and 32 came from the nine hospitals in the Sand Fireregion; 32 were identified from the CC, six by diagnosis and ten bytriage note. Despite an increase in fire-related visits, overall trends inED data were not affected; no increase was found for cardiac events,eye irritation, heat-related illness or total volume. Asthma visitsincreased at the time of the fire, which correlates with a sharp increasein the concentration of fine particulate matter in the Santa ClaritaValley following the start of the fire2. However, these increases wereno higher than other peaks observed in previous months3. No increasesin calls to a nurse hotline or over-the-counter medication sales wereobserved. Among Reddinet hospitals, admissions increased slightlybut ED visits remained unchanged.ConclusionsFor the Sand Fire, ED volume alone was not enough to estimatethe subsequent health effects on residents of LAC; instead a specificfire query was needed. Several factors could explain why overalltrends were not affected. In a region where air quality is alreadycompromised, it is challenging to distinguish between asthmaincreases from air pollution from those exacerbated by wildfiresmoke. It is also likely that residents heeded warnings about air qualityduring active fires, thus reducing their outdoor exposure. Althoughthe majority of cases were identified using the CC field, additionaldata fields such as triage notes available from some hospitals improvethe ability to elicit fire related visits. Regardless of the challengespresented in measuring health effects related to wildfires, syndromicsurveillance and complementary systems continue to be the primarytools for near real-time assessments in LAC.