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Mortality Surveillance

Surveillance of deaths due to influenza and pneumonia using death records has the potential to be a relatively inexpensive and quick approach to tracking and detecting influenza and respiratory illness outbreaks; however, presently such a system does not exist because of the time delays in processing death records: in Utah, as is similar elsewhere in the United States, coded death certificate data are typically not available for at least 1–3 months after the date of death, and coded national vital statistics data are not available until after 2–3 years.

Objective

This poster presents the rationale for designing a real-time surveillance system, based on mortality data, using grid and natural language processing tools that will address the current barrier that coded death certificate data not being available for several months. To develop a public health tool that delivers a timely surveillance system for influenza and pneumonia, we integrated death certificates from the Utah Department of Health, analytical grid services, and natural language processing tools to monitor levels of mortality. This example demonstrates how local, state, and national authorities can automate their influenza and pneumonia surveillance system, and expand the number of reporting cities.

Referenced File
Submitted by uysz on

Drug overdose mortality is a growing problem in the United States. In 2017 alone over 72,000 deaths were attributed to drug overdose, most of which were caused by fentanyl and fentanyl analogs (synthetic opioids). While nearly every community has seen an increase in drug overdose, there is considerable variation in the degree of increase in specific communities. The Harris County community, which includes the City of Houston, has not seen the massive spikes observed in some communities, such as West Virginia, Kentucky, and Ohio. However, the situation in Harris County is complicated in mortality and drug use. From 2010 - 2016 Harris County has seen a fairly stable overdose-related mortality count, ranging from 450 - 618 deaths per year. Of concern, the last two years, 2015-2016, suggest a sharp increase has occurred. Another complexity is that Harris County drug related deaths seem to be largely from polysubstance abuse. Deaths attributed to cocaine, methamphetamine, and benzodiazipine all have risen in the past few years. Deaths associated with methamphetamine have risen from approximately 20 per year in 2010 - 2012 to 119 in 2016. This 6-fold increase is alarming and suggests a large-scale public health response is needed.

Objective: In this session, we will explore the results of a descriptive analysis of all drug overdose mortality data collected by the Harris County Medical Examiner's Office and how that data can be used to inform public health action.

Submitted by elamb on

In 2004, Sante publique France, the French Public Health Agency set up a reactive all-cause mortality surveillance based on the administrative part of the death certificate, in the final objectives 1/ to detect unexpected or usual variations in mortality and 2/ to provide a first evaluation of mortality impact of events. In 2007, an Electronic Death Registration System (EDRS) was implemented, enabling electronic transmission of the medical causes of death to the agency in real-time. To date, 12% of the mortality is registered electronically. A pilot study demonstrated that these data were valuable for a reactive mortality surveillance system based on causes of death. A strategy has thus been developed for the analysis in routine of the medical causes of death with the objectives of early detection of expected and unexpected outbreaks and reactive evaluation of their impact. This system will allow approaching the cause accountability when an excess death will be observed.

Objective: The aim of this study is to present the syndromic groups that will be routinely monitored for the reactive mortality surveillance based on free-text medical causes of death.

Submitted by elamb on

Accurately assigning causes or contributing causes to deaths remains a universal challenge, especially in the elderly with underlying disease. Cause of death statistics commonly record the underlying cause of death, and influenza deaths in winter are often attributed to underlying circulatory disorders. Estimating the number of deaths attributable to influenza is, therefore, usually performed using statistical models. These regression models (usually linear or poisson regression are applied) are flexible and can be built to incorporate trends in addition to influenza virus activity such as surveillance data on other viruses, bacteria, pure seasonal trends and temperature trends.

 

Objective

Mortality exhibits clear seasonality mainly caused by an increase in deaths in the elderly in winter. As there may be substantial hidden mortality for a number of common pathogens, we estimated the number of elderly deaths attributable to common seasonal viruses and bacteria for which robust weekly laboratory surveillance data were available.

Referenced File
Submitted by hparton on

The 122 Cities Mortality Reporting System (CMRS) has been used for pneumonia and influenza monitoring in the U.S. since the early 20th century. The 122 CMRS is regarded as the timeliest source of mortality data, with the majority of deaths being reported to the system within two weeks. However, while it excels at timeliness it lacks detail, accuracy and completeness. Deaths are counted during the week that the death certificate was filed and not during the week in which the death occurred and the system only covers approximately 25% of the U.S. population. Also, while the standard case definition for 122 CMRS is a death in which pneumonia or influenza is listed anywhere on the death certificate; not all sites follow this definition (i.e. some sites only use pneumonia or influenza listed only as the underlying cause of death) [1]. 

Objective

To increase the accuracy, completeness, and detail of data as well as decrease the resources needed to conduct pneumonia and influenza mortality surveillance in the U.S.

Submitted by elamb on
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