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2011 Model Practice Application (Public)
Application Name: 2011 Model Practice Application (Public) : Florida Department of Health in Miami-Dade County : 2009 H1N1 Influenza Surveillance Systems
Applicant Name: Dr. Lillian Rivera, PhD
2009 H1N1 Influenza Surveillance Systems
Miami-Dade County Health Department
2009 H1N1 Influenza Surveillance Systems
Responsiveness and Innovation
On June 11, 2009, the World Health Organization (WHO) declared a global pandemic of 2009 H1N1 Influenza and raised the worldwide alert level to Phase 6. This model practice addressed the public health issue of pandemic flu.
Agency Community Roles
MDCHD was the creator of the two new automated surveillance systems and was the leader in sharing the results of data collected from the systems.
Costs and Expenditures
Miami-Dade County is the largest county in Florida and has a population of 2.4 million, of which 62.5% is Hispanic, 17.6% is White and 19.5% is Black. Over half (50.9%) of the population is foreign-born, a figure higher than any other county in the United States. Additionally, 16.5% of residents are living in poverty. The county also has more than 12 million visitors annually and is a center for international travel. Miami-Dade County Health Department (MDCHD) serves this population and most of our interventions are targeted at all residents and visitors. When 2009 H1N1 Influenza emerged in the United States in April 2009, Miami-Dade County began working with partners in the community to respond to the pandemic. Based on MDCHD overall goal, the Applied Epidemiology and Research Team’s aim was: Goal: To provide on-time scientific information to decision-makers and the community in order to prevent the spread of 2009 H1N1 Influenza in Miami-Dade County Two objectives that aligned with the goal included: 1) To conduct disease surveillance (i.e. morbidity and mortality) among high-risk populations (i.e. hospitalized patients and school-aged children) using innovate reporting systems 2) To educate our partners and the community-at-large about 2009 H1N1 Influenza using data collected from reporting systems As 2009 H1N1 Influenza continued to spread, disease monitoring and surveillance was critical to prevent new cases and outbreaks. The MDCHD Applied Epidemiology and Research Team created 2 automatic report systems; one that analyzes daily emergency department visit trends for influenza-like illness (Hospital Influenza Report System (HIRS)-created June 2009) and the second system signaled alerts based on public school absenteeism data (School Absenteeism System (SABS) -created August 2009). While SABS did not require additional funding, the HIRS system used Centers for Disease Control and Prevention (CDC) Bioterrorism Grant funding. In-kind costs included employee time spent on this project (i.e. 80 total hours to implement system, 1 hour daily to run the report and conduct investigations based on alerts). Reports created by these systems were sent daily to health department officials, schools, hospitals and local government offices. These innovative tools detected influenza outbreaks which were then successfully contained and managed. This experience helped each entity better prepare for future public health emergencies.
Goal: To provide on-time scientific information to decision-makers and the community in order to prevent the spread of 2009 H1N1 Influenza in Miami-Dade County. Three objectives that align with the goal include:
1. Create an innovative alert system using school absenteeism data to detect possible school-based outbreaks of H1N1;
2. Design an automatic daily ILI-related syndromic surveillance report creator that works in conjunction with the current Electronic Surveillance System for the Early Notification of Community Based Epidemics (ESSENCE) data;
3. Educate our partners and the community-at-large about 2009 H1N1 Influenza using data collected from reporting systems
Time is crucial to detect any potential outbreak or event trend during an H1N1 outbreak. Designing an automatic report system using currently available data is convenient and efficient to: 1) understand absenteeism status at different age and school levels as well as possible outbreaks; and 2) review the daily percent of ILI, fever and respiratory ED visit trends by age group or compare the percentage of ILI ED visits by hospital on the same screen. When calculating and creating this report manually, time and manpower costs were considered for a large regional area. We spent 3 weeks to create and test these two report systems and 1 week to train staff. Hospital reports were sent daily for 9 months (June 2009-March 2010). School reports have been distributed since September 2009 and continue to be sent. The time staff spends on these daily activities is between 0.5 and 2 hours. More time is spent investigating when there are alerts that may be caused by potential outbreaks
There is full commitment by the Miami-Dade County Health Department (MDCHD), the Miami-Dade County Public School (MDCPS) District and the local hospitals. For the hospital report system, there are Memorandums of Understanding/Agreement (MOU/A) to utilize the ESSENCE system and there is sufficient support by hospital IT and Infection Control Practitioner (ICP) staff. Although the hospital reports have ceased since the decline of 2009 H1N1 influenza, the practice could be re-established in the event of a future pandemic, either from influenza or any other emerging infectious disease. The school reports have sustainability because there is a strong partnership between the MDCHD and MDCPS. These reports benefit the school district because it is an enhanced level of absentee monitoring.
Within our own health department, this practice is sustainable over time because we have 8 dedicated staff assigned to these duties and new employees could be trained if needed. Since the systems are already created, there are no additional costs necessary to run the reports on a daily basis. The only resource that is used is the staff time spent retrieving and sending the reports. Some staff are specifically trained in computer programming for these systems. Therefore, they can troubleshoot if there are any potential malfunctions. It is our hope that these model practices serve as a national example. The Applied Epidemiology and Research Team of the Miami-Dade County Health Department would be eager to share experiences in order to help other counties and states conduct similar surveillance techniques during public health emergencies
Outcome Process Evaluation
The time taken to achieve the practice was approximately 4 weeks. During this time, the Applied Epidemiology Research Team worked on creating the system using Microsoft Access, Statistical Analysis Software 9.13 (SAS), Visual Basic, and ArcGIS 9.3. The school absenteeism system was piloted for a period of 4 weeks to collect sufficient data for comparison while the Hospital Influenza Report System (HIRS) took approximately 2 weeks to pilot the practice. The following primary objectives were evaluated by performance measure, data collection, evaluation and feedback. Objective 1) To conduct disease surveillance (i.e. morbidity and mortality) among high-risk populations (i.e. hospitalized patients and school-aged children) using innovate reporting systems Performance measure Number of schools receiving feedback on influenza related school absenteeism: 415 schools. Number of hospitals participating in HIRS: 21 hospitals Number of reports distributed to partners: The Hospital Influenza Report System (HIRS) was over 150 reports (June 25, 2009-March 28, 2010) and School Absenteeism System (SABS) – over 200 reports (Sept 2009- Present) Number of school outbreaks detected in which prevention measures were implemented: 9 outbreaks. Table: ILI* identified through SABS†, Miami-Dade County, 9/8 – 10/21, 2009 Week Dates Red alert Yellow alert Warning alert # schools with outbreaks identified through SABS # ill identified through SABS 1 9/8-9-11 3 2 17 0 0 2 9/14-9/18 8 2 16 1 27 3 9/21-9/25 9 11 10 2 17 4 9/28-10/02 9 4 7 0 0 5 10/5-10/9 16 4 11 2 7 6 10/12-10/16 16 5 6 1 20 7 10/19-10/21 0 0 0 3 0 Total‡ 61 28 67 9 71 *Influenza-like illness. †School absentee system. ‡ 3 days were excluded due to school closures. On 10/20-21, high schools were excluded for FCAT testing and only elementary schools were counted. Data collection HIRS used the Electronic Surveillance System for the Early Notification of Community Based Epidemics (ESSENCE), which uses de-identified hospital chief complaint data. The report also contained data from lab-confirmed 2009 H1N1 influenza cases reported in the statewide electronic disease reporting system, Merlin. This described the number of hospitalizations and deaths by age group, sex, pregnancy status and race/ethnicity. School Absenteeism System (SABS) collected MDC public school raw data of the number of students absent at each school along with the total population of students enrolled. This data is sent to a MDCHD server which was then transferred into our system in order to create the specialized school absenteeism report. Evaluation We learned that both systems assisted with monitoring disease surveillance among populations and strengthened our relationship with our partners. By the end of flu season, we were able to understand the demographic and geographic trends of influenza and communicate our findings to the community. Feedback Daily reports were uploaded on the MDCHD intranet website. Modifications to the hospital report were made after feedback from the hospitals request for individualized percentages of influenza-like-illness. For schools, many were appreciative when we called to notify them of increases in absenteeism and they said they were more likely to call in the event of a possible outbreak. Communication with the schools helped them improve their own methods for monitoring school absenteeism due to illnesses. Objective 2) To educate our partners and the community-at-large about 2009 H1N1 Influenza using data collected from reporting systems Performance measure Reports from the hospitals and schools were utilized to inform the community in each of the following modes: Number of press conferences: 9 Number of press releases: 95 Number of media calls answered: 1,359 Number of interviews: 156 TV, 44 radio, 45 newspaper Number of town hall meetings: 23 Total number of persons attending town hall meetings: 1,332 Number of community ev