![]() ![]() To smooth the data, we used 7-day moving averages in the R(t) estimation. Interpret cautiously for these counties as we are not able to observe the trend over time. Some of the R(t) estimates may be unreliable for counties with “data dumps”. We investigated several options based on the literature and found this choice of distribution and parameters to not affect the results significantly. The generation time estimates were generated using a gamma distribution with mean 3.96 and standard deviation 4.75, based on estimates from Ganyani, et al. R(t) was estimated using the R0 package in R. Hospitals, cities and counties may adjust the availability of hospital beds as cases increase or decrease within their jurisdictions. Any device used to support, assist or control respiration through the application of positive pressure to the airway when delivered via an artificial airway. Ventilator availability: Total number of adult ventilators available, to include adult ventilators that are capable of ventilating a pediatric patient.Hospital, ICU, or surge bed availability must only be reported to the state if they are staffed. Bed availability: Defined as including hospital bed, ICU beds and surge bed availability as reported by the hospitals to the state.Suspected COVID19: 1) patient with respiratory illness AND no other obvious causes AND no travel within 14 days 2) respiratory illness AND has been in contact with a confirmed COVID19 person 3) severe respiratory illness AND requires hospitalization AND no other obvious explanation.COVID19 hospitalization: confirmed PCR or suspected COVID19.To keep reporting consistent throughout the state, DSHS defined key metrics. To systemize reporting, the Hospital Preparedness Program Providers (HPP) created 8 subgroups across Texas in charge of collecting hospital data and reporting to the state. ![]() ![]() On March 24, 2020, all hospitals were mandated to report COVID19 hospitalizations to the state.The models “smooth” the data to account for these outliers, but larger outliers may still have significant influence on analyses. This may be due to retrospective county corrections. There are some situations where the daily cases are negative.This impacts projection, hot spots, and R(t) analyses. ![]() A "data dump" is a large amount of cases counted on one date instead of spread over time. We probably see this, for example, in Anderson county on June 17.
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