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Description

The OKC-Co Health Department deployed a phased vectorborne response plan to address multiple diseases, including Zika Virus and West Nile Virus. This plan is scalable and flexible, but must necessarily prepare for the worst case scenario. Although not currently a local threat in OKC-Co, Zika virus response planning requires early coordination between state, local and federal agencies in order to mitigate risk to the population. The backbone of the Vectorborne response planning has been proven successful through West Nile Virus response in which Oklahoma has experienced three outbreak seasons: 2003, 2007 and 2012. (OSDH) In 2015, the OKC area experienced a greater than 112% increase in the number of vectors and 18 WNV positive test pools were observed. The heightened number of vectors and positive test pools did not translate to the same escalation in human cases, which demonstrates the strength that Public Health collaboration between surrounding municipalities and community members has on reducing the potential impact of this seasonal epidemic. During the most recent 2017 mosquito season, local code enforcement, city officials and consumer protection deployed a total of 18 CDC Gravid and BG Sentinel traps. The final day of sorting took place during the last week of October, as consistent with the decrease in mosquito numbers. There were 23 trapping and testing weeks with a total of 43,079 mosquitos trapped and 33, 846 mosquitos tested. An average of 66% of all trapped mosquitos were tested each week. The Maximum Likelihood Estimation (MLE) Infection Rate is calculated each week.

Objective: Demonstrate the impact of surveillance and media engagement on Public Health protection during a Vectorborne disease response.Identify surveillance and reporting methods for timely response to positive cases steps.Explore and apply best practices for collaboration with partners and surrounding municipalities in order to reduce disease impact

Submitted by elamb on
Description

In December 2009, Taiwan’s CDC stopped its sentinel physician surveillance system. Currently, infectious disease surveillance systems in Taiwan rely on not only the national notifiable disease surveillance system but also real-time outbreak and disease surveillance (RODS) from emergency rooms, and the outpatient and hospitalization surveillance system from National Health Insurance data. However, the timeliness of data exchange and the number of monitored syndromic groups are limited. The spatial resolution of monitoring units is also too coarse, at the city level. Those systems can capture the epidemic situation at the nationwide level, but have difficulty reflecting the real epidemic situation in communities in a timely manner. Based on past epidemic experience, daily and small area surveillance can detect early aberrations. In addition, emerging infectious diseases do not have typical symptoms at the early stage of an epidemic. Traditional disease-based reporting systems cannot capture this kind of signal. Therefore, we have set up a clinic-based surveillance system to monitor 23 kinds of syndromic groups. Through longitudinal surveillance and sensitive statistical models, the system can automatically remind medical practitioners of the epidemic situation of different syndromic groups, and will help them remain vigilant to susceptible patients. Local health departments can take action based on aberrations to prevent an epidemic from getting worse and to reduce the severity of the infected cases.

Objective: Sentinel physician surveillance in the communities has played an important role in detecting early aberrations in epidemics. The traditional approach is to ask primary care physicians to actively report some diseases such as influenza-like illness (ILI), and hand, foot, and mouth disease (HFMD) to health authorities on a weekly basis. However, this is labor-intensive and time-consuming work. In this study, we try to set up an automatic sentinel surveillance system to detect 23 syndromic groups in the communites.

Submitted by elamb on
Description

Since 2008, drug overdose deaths exceeded the number of motor vehicle traffic-related deaths in Indiana, and the gap continues to widen1. While federal funding opportunities are available for states, it often takes years for best practices to be developed, shared, and published. Similarly, local health departments (LHDs) may experience lengthy delays to receive finalized county health statistics. Indiana collects and stores syndromic emergency department data in the Public Health Emergency Surveillance System (PHESS) and uses the Electronic Surveillance System for the Early Notification of Community-based Epidemics version 1.21 (ESSENCE) to monitor public health events and trends. In July 2017, the Indiana Overdose Surveillance Team (IOST) developed a standard process for monitoring and alerting local health partners of increases in drug overdoses captured in ESSENCE at the county level. ISDH is enhancing these alerts by mapping the data in GIS and providing spatiotemporal data to LHDs to inform more targeted intervention and prevention efforts.

Objective: This poster presentation shares Indiana's approach of alerting local health departments (LHDs) with near real-time drug overdose data and how this process has been enhanced through mapping and analysis with a geographic information system (GIS).

Submitted by elamb on
Description

Southwest states are prone to wildfires, dust storms, and high winds especially during the monsoon season (June- September). Wildfire smoke is a complex mixture of carbon monoxide, carbon dioxide, water vapor, hydrocarbons, nitrogen, oxides, metals, and particulate matter (PM). Dust storms are made up of aerosols and dust particles varying in size; particles bigger than 10 µm are not breathable, but can damage external organs such as causing skin and eye irritations. Particles smaller than 10 µm are inhalable and often are trapped in the nose, mouth, and upper respiratory tracts, and can cause respiratory disorders such as asthma and pneumonia. Numerous studies have characterized the epidemiological and toxicological impact of exposure to PM in dust or smoke form on human health. All of these environmental conditions can have impacts on cardiovascular conditions such as hypertension and cause respiratory flare ups, especially asthma. Previous studies have shown a relationship between PM exposure and increases in respiratory-related hospital admissions. In an analysis of the health effects of a large wildfire in California in 2008, Reid, et. al, observed a linear increase in risk for asthma hospitalizations (RR=1.07, 95% CI= (1.05, 1.10) per 5 µg/m3 increase) and asthma emergency department visits (RR=1.06, 95% CI=(1.05, 1.07) per 5 µg/m3 increase) with increasing PM2.5 during wildfires. In a study specific to New Mexico, Resnick, et. al, found that smoke from the Wallow fire in Arizona in 2011 impacted the health of New Mexicans, observing increases in emergency department visits for asthma flare-ups in Santa Fe, Espanola, and Albuquerque residents. This current study will evaluate the effectiveness of outreach to asthmatic members during times of poor air quality; informing them of the air quality, instructing them to limit their outdoor activity, and to remind them to carry or access their inhalers or other medical necessities if/when needed.

Objective: To inform asthmatic, health plan patients of air quality conditions in their specific geographic location and to assess if the communication is successful in reducing the number of emergency department visits for asthmatic/respiratory flare ups.

Submitted by elamb on
Description

Surveillance of influenza epidemics is a priority for risk assessment and pandemic preparedness. Mapping epidemics can be challenging because influenza infections are incompletely ascertained, ascertainment can vary spatially, and often a denominator is not available. Rapid, more refined geographic or spatial intelligence could facilitate better preparedness and response.

Objective: Using the epidemic of influenza type A in 2016 in Australia, we demonstrated a simple but statistically sound adaptive method of automatically representing the spatial intensity and evolution of an influenza epidemic that could be applied to a laboratory surveillance count data stream that does not have a denominator.

Submitted by elamb on
Description

Seasonal influenza epidemics are responsible for over 200,000 hospitalizations in the United States per year, and 39,000 of them are in children. In the United States, the Advisory Committee on Immunization Practices guides immunization practices, including influenza vaccination, with recommendations revised on an annual basis. For the 2006–2007 flu season, the Advisory Committee on Immunization Practices recommendations for influenza vaccination began including healthy children aged 24–59 months (two to four years), a shift that added 10.6 million children to the target group.

Canada has a parallel federal organization, the National Advisory Committee on Immunization, which is responsible for guiding the use of vaccines. Recommendations made by the National Advisory Committee on Immunization and the Advisory Committee on Immunization Practices around seasonal influenza vaccination was concordant until the 2006–2007 season. Starting in the 2010–2011 season, the National Advisory Committee on Immunization has further expanded its recommendations to additional pediatric age groups by including two- to four-year-olds for targeted seasonal influenza vaccination.

We took advantage of this divergence in policy between two neighboring countries with similar annual seasonal influenza epidemics to try to understand the effects of the

policy change in the United States to expand influenza vaccination coverage to other pediatric populations.

 

Objective

The objective of this study is to estimate the effect of expanding recommendations for routine seasonal influenza vaccination to include 24–59-month-old children.

Submitted by hparton on
Description

Syndromic surveillance systems significantly enhance the ability of Public Health Units to identify, quantify, and respond to disease outbreaks. Existing systems provide excellent classification, identification, and alerting functions, but are limited in the range of statistical and mapping analyses that can be done. Currently available commercial off-the-shelf (COTS) statistical and GIS packages provide a much broader range of analytical and visualization tools, as well as the capacity for automation through user-friendly scripting languages. This study retrospectively evaluates the use of these packages for surveillance using syndromic data collected in Ottawa during the 2009 pH1NI outbreak.

 

Objective

The objective of this study was to create and evaluate a system that uses customized scripts developed for COTS statistical and GIS software to (1) analyze syndromic data and produce regular reports to public health epidemiologists, containing the information they would need to detect and manage an ILI outbreak, and (2) facilitate the generation more detailed analyses relevant to specific situations using these data.

Submitted by hparton on
Description

Influenza-like illness (ILI) data is collected via an Influenza Sentinel Provider Surveillance Network at the state level. Because participation is voluntary, locations of the sentinel providers may not reflect optimal geographic placement. This study analyzes two different geographic placement schemes - a maximal coverage model (MCM) and a K-median model, two location-allocation models commonly used in geographic information systems. The MCM chooses sites in areas with the densest population. The K-median model chooses sites which minimize the average distance traveled by individuals to their nearest site. We have previously shown how a placement model can be used to improve population coverage for ILI surveillance in Iowa when considering the sites recruited by the Iowa Department of Public Health. We extend this work by evaluating different surveillance placement algorithms with respect to outbreak intensity and timing (i.e., being able to capture the start, peak and end of the influenza season).

 

Objective

To evaluate the performance of several sentinel surveillance site placement algorithms for ILI surveillance systems. We explore how these different approaches perform by capturing both the overall intensity and timing of influenza activity in the state of Iowa.

Submitted by elamb on
Description

Detection of the signs of HIV epidemic transition from concentrated to generalized stage is an important issue for many countries including Ukraine. Objective and timely detection of the generalization of HIV epidemic is a significant factor for the development and implementation of appropriate preventive programs. As an additional method for estimating HIV epidemic stage, the spatial analysis of the reported new HIV cases among injection drug use (IDU) and other populations (due to sexual way of transmission) has been recommended. For studying new HIV cases in small societies, Relative Risk (RR) rates are preferred over incidence indicators. Spatial clustering based on the calculation of RR rates allows us to locate the high risk areas of HIV infection with greater accuracy. In our opinion, in the process of epidemic generalization the spatial divergence of epidemic will be observed as well. In particular, clusters with high RR of sexual HIV transmission independent from the clusters with high RR of injection HIV transmission may appear.

Objective

To investigate the utility of spatial analysis in the tracking of the stages of the HIV epidemic at an administrative territory level, using the Odessa region, Ukraine as an example.

Submitted by elamb on
Description

The Armenian landscape is composed of a complex mountainous relief (400-4095 m above sea level) with several landscape-ecological zones. Fauna diversity is conditioned by ecological factors, 13 families of rodents, and 12 types of vectors. Because of these complex ecological features, many diseases remain endemic in the country. For example, approximately 95% of Armenia is a natural focus for tularemia. Rodents (voles/Microtus socialis) play the most important role in the epizotoology of tularemia. Voles inhabit all the landscape-ecological zones 1400-3300 m above sea level. In addition, 80 types of parasite ticks and fleas are found in all ecological zones of Armenia.

Objective

We have applied GIS methodologies to create a retrospective analysis of tularemia outbreaks in the Republic of Armenia.

Submitted by knowledge_repo… on