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Module 7: Outbreak Investigation & Disease Control – Public Health Surveillance

TRANSCRIPT

Slide 1: Introduction

Hello, and welcome to module 7, public health

surveillance. My name is Krissy Simeonsson and

I’m an assistant professor in the Department of

Pediatrics and Public Health at the Brody School

of Medicine.

Slide 2: Acknowledgements

This education module is made possible through

the Centers for Disease Control and Prevention,

and the Association for Prevention Teaching and

Research cooperative agreement. APTR wishes

to acknowledge the following individuals that

developed this module.

Slide 3: Presentation Objectives

Through the course of this presentation we will

start with defining surveillance, then we’ll

discuss some of the uses of surveillance, we’ll

spend some time reviewing notifiable disease

surveillance, and then finally describe some of

surveillance’s limitations.

Developed through the APTR Initiative to Enhance Prevention and Population

Health Education in collaboration with the Brody School of Medicine at East

Carolina University with funding from the Centers for Disease Control and

Prevention

Public Health Surveillance

Developed through the APTR Initiative to Enhance Prevention and Population

Health Education in collaboration with the Brody School of Medicine at East

Carolina University with funding from the Centers for Disease Control and

Prevention

Public Health Surveillance

APTR wishes to acknowledge the following individuals that developed this module:

Kristina Simeonsson, MD, MSPHDepartment of Public Health

Brody School of Medicine at East Carolina University

Julie Daugherty, MPHDepartment of Public Health


This education module is made possible through the Centers for Disease Control and Prevention (CDC) and the

Association for Prevention Teaching and Research (APTR) Cooperative Agreement, No. 5U50CD300860. The module

represents the opinions of the author(s) and does not necessarily represent the views of the Centers for Disease

Control and Prevention or the Association for Prevention Teaching and Research.

APTR wishes to acknowledge the following individuals that developed this module:

Kristina Simeonsson, MD, MSPHDepartment of Public Health


Julie Daugherty, MPHDepartment of Public Health


This education module is made possible through the Centers for Disease Control and Prevention (CDC) and the

Association for Prevention Teaching and Research (APTR) Cooperative Agreement, No. 5U50CD300860. The module

represents the opinions of the author(s) and does not necessarily represent the views of the Centers for Disease

Control and Prevention or the Association for Prevention Teaching and Research.

1. Define surveillance2. Discuss the uses of surveillance3. Review notifiable disease surveillance4. Describe surveillance limitations

1. Define surveillance2. Discuss the uses of surveillance3. Review notifiable disease surveillance4. Describe surveillance limitations


TRANSCRIPT

Slide 4: Surveillance – Information for Action

Surveillance is basically information for action.

This slide displays the 3 public health core

functions, assessment, policy development, and

assurance, which you can see on the outside of

the circle. The multi-colored pieces in the center

represent the 10 Essential Public Health Services.

Surveillance activity occurs as part of the

assessment pieces; monitoring health, and diagnosing and investigating disease, or

health problems. Good surveillance provides data needed to give an accurate

assessment of the status of health in a given population. Good surveillance can also

provide an early warning of disease problems, so immediate control measures can be put

into place. It can also give us information to design and plan public health programs, and

also information to plan and conduct research.

Slide 5: Surveillance

We mentioned previously that surveillance is

information for action, but on this slide a more

formal definition of surveillance is displayed.

Surveillance as defined by the Centers for

Disease Control and Prevention is the ongoing

systematic collection, analysis, and

interpretation of health data, essential to

planning, implementation, and evaluation of public health practice, closely integrated

with the timely dissemination to those who need to know.

Source: http://www.health.gov/phfunctions/public.htmSource: http://www.health.gov/phfunctions/public.htm

The ongoing systematic collection, analysis, and interpretation of health data, essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination to those who need to know.

www.cdc.gov

The ongoing systematic collection, analysis, and interpretation of health data, essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination to those who need to know.

www.cdc.gov


TRANSCRIPT

Slide 6: Sources of Surveillance Data

Where does surveillance data come from? There

are many sources of surveillance data available.

This slide is only a partial listing of some of the

sources. We are going to review notifiable

disease surveillance later in the presentation.

But some other sources of data that you may be

familiar with include vital records, such as birth

certificates, and death certificates. Environmental monitoring systems, animal health

data, information provided from individuals, information from laboratories, medical

records at outpatient healthcare facilities, as well as hospitals. Over the counter

medication sales can be a source of data. Registries are sources of data, and finally

surveys. Some examples of surveys are population-based surveys such as the National

Health Interview Survey, and the National Health & Nutrition Examination Survey, or

NHANES. And then there are also provider-based surveys. Some examples of these are

the National Ambulatory Medical Care Survey, and also the National Hospital Discharge

Survey, which looks at ICD-9 codes.

Slide 7: Types of Surveillance

Let’s turn now to talk about different types of

surveillance, and there are three types I would

like to discuss in this presentation. Passive

surveillance, active surveillance, and also

syndromic surveillance.

Notifiable diseases Vital records Environmental monitoring systems Animal health data Individuals Laboratories Medical records Over the counter medication sales Registries Surveys

population-based provider-based

Notifiable diseases Vital records Environmental monitoring systems Animal health data Individuals Laboratories Medical records Over the counter medication sales Registries Surveys

population-based provider-based

Passive

Active

Syndromic

Passive

Active

Syndromic


TRANSCRIPT

Slide 8: Passive Surveillance

Passive surveillance is the most common form of

surveillance and occurs when laboratories,

physicians, or other healthcare providers

regularly report cases or disease to the local

health department. These reports are based on

standard case definitions for a particular disease

or condition. Passive surveillance means that the

healthcare provider or laboratory initiates the forwarding of the data to the health

department.

Slide 9: Active Surveillance

A second form of surveillance is active

surveillance. This occurs when the collection of

data from the lab, physician, or other healthcare

provider is initiated by the health department.

Active surveillance is often used during outbreak

investigations or research studies. Active

surveillance has an advantage over passive

surveillance because it achieves more complete and accurate reporting. However, the

draw-back is that it’s more resource intensive for the public health agency that is

conducting the active surveillance. It costs more, it takes more personnel, and more

time to do active surveillance.

Slide 10: Syndromic Surveillance

A third type of surveillance is syndromic

surveillance. It is defined as the ongoing,

systematic collection, analysis, interpretation,

and application of real-time indicators for

disease that allow for detection before public

health authorities would otherwise identify

them. Syndromic surveillance data are collected

in real time, meaning that the data are automated so that they can be received daily, or

even more frequently. The type of data collected is not actual disease, instead we are

interested in specific indicators of disease. The definition of syndromic surveillance,

you’ve probably noticed is similar in ways to the definition of surveillance in general. It’s

on-going and systematic collection, there’s analysis and interpretation of data, however,

the time component and type of data collected are different from passive, or even

active, surveillance. Some common surveillance syndromes are: gastrointestinal illness,

Laboratories, physicians, or others regularly report cases of disease / death to the local or state health department

Case reports based on a standard case definition of that particular disease

Deaths reported on standard certificate

Laboratories, physicians, or others regularly report cases of disease / death to the local or state health department

Case reports based on a standard case definition of that particular disease

Deaths reported on standard certificate

Local or state health departments initiate the collection of information from laboratories, physicians, health care providers or the general population.

Achieves more complete and accurate reporting

More resource intensive for the public health agency

▪ money

▪ personnel

▪ time

Local or state health departments initiate the collection of information from laboratories, physicians, health care providers or the general population.

Achieves more complete and accurate reporting

More resource intensive for the public health agency

▪ money

▪ personnel

▪ time

The ongoing, systematic collection, analysis, interpretation, and application of real-time indicators for disease that allow for detection before public health authorities would otherwise identify them.

Common surveillance syndromes

Gastrointestinal

Influenza-like illness

Rash and Fever

The ongoing, systematic collection, analysis, interpretation, and application of real-time indicators for disease that allow for detection before public health authorities would otherwise identify them.

Common surveillance syndromes

Gastrointestinal

Influenza-like illness

Rash and Fever


TRANSCRIPT

influenza-like illness, or rash and fever syndrome.

Slide 11: Ideal Surveillance System

What are the key features of an ideal

surveillance system? We want the system to be

simple, which means it’s easy to participate in

and the daily operation of it is not too

cumbersome. It also needs to be timely, data

that’s not available when we need it, is not

helpful for planning or response. It needs to be

representative, which means that a surveillance system needs to collect data that’s

representative of the population that we’re following. It needs to be flexible, which

means at certain times, such as outbreak situations, you need to be able to ramp it up,

but then in times when there are not a lot of cases you need to be able to scale back. It

needs to be sensitive and have strong predictive value, which we’ll talk about in the next

few slides. It certainly needs to be acceptable. Both the public and healthcare providers

need to feel like what they’re doing makes sense, and that it’s not too intrusive. And

finally, an ideal surveillance system needs to be cost effective.

Slide 12: Ideal Surveillance System

So in the next few slides we’re going to spend a

little bit more time talking about these two

characteristics (Sensitive and Strong Predictive

Value) of an ideal surveillance system.

Simple Timely Representative Flexible Sensitive Strong predictive value Acceptable

public

health care providers Cost-effective


public

health care providers Cost-effective


public

health care providers Cost effective


public

health care providers Cost effective


TRANSCRIPT

Slide 13: Ideal Surveillance System – Sensitivity

and Predictive Value

For an ideal surveillance system to be sensitive,

we want it to not miss many cases. We want to

have few, if any, missed cases of the disease

we’re trying to track. We increase the sensitivity

of a surveillance system by having very broad

case definitions, which means that we capture

cases that may not actually be cases by only have a few characteristics that we’re looking

for, for each disease. Clearly, the problem with that is there will be cases counted that

might not actually be true cases of disease. But if you really are trying to catch every

case out there, and not miss any then we have to have a sensitive surveillance system.

The flip side of that is positive predictive value of a surveillance system. All case reports

that we are receiving for a disease or illness meet the case definition; we can feel fairly

certain that any cases we’re capturing in our system truly represent cases. We can

increase the predictive value of a surveillance system by adopting a more restrictive case

definition: individuals have to match more characteristics of a disease to be counted as a

case. There is a balance, or a trade-off, between sensitivity and predictive value of a

surveillance system.

Slide 12: Uses of Public Health Surveillance

Next we’re going to talk a little bit about the uses

of public health surveillance. Public health

surveillance can be used to estimate the

magnitude of a health problem; it can help us

determine the geographic distribution of an

illness. It helps to portray the natural history of a

disease, is it on the rise, is it on the decline? It

helps us detect epidemics, or define problems in the community. It can help us generate

hypotheses, and stimulate research. It helps us evaluate our control measures. We can

monitor changes in infectious agents, for examples whether certain bacteria are

becoming more resistant to some of the antibiotics that are in use. Surveillance helps us

detect changes in health practices; are more people getting screened in a community, or

are less people, and what are the barriers? Finally, surveillance can help us facilitate

planning.

Sensitivity

Few if any missed cases

Increase by having broad case definitions

Positive predictive value

Almost all case reports received for illnesses meet the surveillance case definition

Increase by adopting a more restrictive case definition

Hopkins, R. 2005

Sensitivity

Few if any missed cases

Increase by having broad case definitions

Positive predictive value

Almost all case reports received for illnesses meet the surveillance case definition

Increase by adopting a more restrictive case definition

Hopkins, R. 2005

Estimate magnitude of the problem Determine geographic distribution of illness Portray the natural history of a disease Detect epidemics / define a problem Generate hypotheses, stimulate research Evaluate control measures Monitor changes in infectious agents Detect changes in health practices Facilitate planning

http://www.cdc.gov/osels/ph_surveillance/nndss/phs/overview.htm


http://www.cdc.gov/osels/ph_surveillance/nndss/phs/overview.htm


TRANSCRIPT


Let’s follow with a few examples. The first

example is going to illustrate how surveillance

helps us estimate the magnitude of a problem,

and also at the same time determine the

geographic distribution of illness.

Slide 14: Incidence of Chlamydia

This data is looking at the incidence of chlamydia

among women in the United States in the year

2009. It gives us incidence by state and shows us

right away the magnitude of the problem, in the

sense that chlamydia is very common. We have

geographic distribution as well, by showing the

states that are highlighted or shaded in dark blue

clearly have, a higher incidence of chlamydia than other states.


The next example is the use of public health

surveillance to detect epidemics.



http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5853a1.htmhttp://www.cdc.gov/mmwr/preview/mmwrhtml/mm5853a1.htm




TRANSCRIPT

Slide 16: Botulism

This is data from the CDC from 2002, looking at

botulism that was responsible for foodborne

outbreaks over a 20-year period, from 1982 to

2002. There are definite peaks in the number of

cases of botulism, and there are labels showing

which ones were related to foodborne

outbreaks.


Finally, the last example is how public health

surveillance can help us evaluate our control

measures.

Slide 18: Cases of Varicella or Chicken Pox

This figure is a line graph that is showing the

number of cases of varicella or chicken pox in 4

states from 1993 to 2009. On the y-axis we have

the number of cases in thousands of chicken pox.

On the x-axis we have the period of time from

1993 to 2009. What you see overall is a steady

decline in the number of cases of chicken pox,

but this data also shows us that licensing of varicella vaccine in the mid-90s was followed

by a steady decline in the number of cases of chicken pox. Then in 2006 a second dose of

varicella vaccine was recommended, and you can see from 2006 to 2009 there was a

decline in the number of cases.

BOTULISM, Foodborne OutbreakReported cases, by year, United States, 1982-2002

Source: CDC. Summary of notifiable diseases. 2002.

Data from the annual survey of State Epidemiologist and Directors of State Public Health Laboratories..

BOTULISM, Foodborne OutbreakReported cases, by year, United States, 1982-2002

Source: CDC. Summary of notifiable diseases. 2002.

Data from the annual survey of State Epidemiologist and Directors of State Public Health Laboratories..



Varicella (ChickenPox). Number of reported cases ---Illinois, Michigan, Texas, and West Virginia*, 1993--2009

www.cdc.gov/mmwr/preview/mmwrhtml/mm5853a1.htm

Varicella (ChickenPox). Number of reported cases ---Illinois, Michigan, Texas, and West Virginia*, 1993--2009

www.cdc.gov/mmwr/preview/mmwrhtml/mm5853a1.htm


TRANSCRIPT

Slide 19: Notifiable Disease Surveillance

We are going to turn now to notifiable disease

reporting. It has been said that no health

department can effectively prevent or control

disease without knowledge of when, where, and

under what conditions cases are occurring.

Public health agencies monitor diseases and

conditions of importance by designating them as

notifiable. The foundation of notifiable disease surveillance is the state and local

application of the National Notifiable Disease Surveillance System. A list of nationally

notifiable diseases is available at the Centers for Disease Control and Prevention website.

You will find that most of the diseases are infectious in nature, but there are some that

are non-infectious, and I’ve listed some of the examples here. Cancer, elevated blood

lead levels, and pesticide-related illness are just some examples of conditions that are

reportable, but are non-infectious.

Slide 20: National Notifiable Disease

Surveillance System (NNDSS)

The National Notifiable Disease Surveillance

System is a system for passing reports from local

and state public health agencies through to the

CDC. There is a role for the Council and State

and Territorial Epidemiologists (CSTE) who work

closely with the CDC in revising the list of

nationally notifiable disease every year. The CDC keeps a list of disease and laboratory

findings of public health interest, and also with support from the CSTE, maintains case

definitions for their surveillance. The CDC also works to disseminate surveillance data

back to healthcare providers. They do this through the Morbidity and Mortality Weekly

Report (MMWR). They also publish an Annual summary of Notifiable Diseases.

Foundation is state and local application of the reportable disease surveillance system known as National Notifiable Disease Surveillance System (NNDSS)

Infectious reportable diseases

Noninfectious reportable diseases

▪ Cancer

▪ Elevated blood lead levels

▪ Pesticide-related illness

Foundation is state and local application of the reportable disease surveillance system known as National Notifiable Disease Surveillance System (NNDSS)

Infectious reportable diseases

Noninfectious reportable diseases

▪ Cancer

▪ Elevated blood lead levels

▪ Pesticide-related illness

System for passing reports from the local to state health departments, and then on to CDC

Role of the Council of State and Territorial Epidemiologists (CSTE)

List of disease and laboratory findings of public health interest

Case definitions for their surveillance

Dissemination of surveillance data

Morbidity and Mortality Weekly Report (MMWR)

MMWR Annual Summary of Notifiable Diseases

System for passing reports from the local to state health departments, and then on to CDC

Role of the Council of State and Territorial Epidemiologists (CSTE)

List of disease and laboratory findings of public health interest

Case definitions for their surveillance

Dissemination of surveillance data

Morbidity and Mortality Weekly Report (MMWR)



TRANSCRIPT

Slide 21: Case Definitions

This is an example of a case definition that you

can find at the CDC website. This is the 2011

case definition for hepatitis A, which is a

nationally notifiable disease. The case definition

includes a clinical component, a laboratory

component, and an epidemiologic component,

(often used during outbreak investigations).

Slide 22: MMWR Annual Summary of Notifiable

Diseases

The CDC disseminates surveillance data back to

providers. More detailed information is

published in the MMWR Annual Summary of

Notifiable Diseases. In this publication, data for

all reportable or notifiable diseases are

published, along with a brief summary of the

year’s activity and information on recent case definitions. At the end of the report are

summary tables and maps. This is an example of a map showing the rate of newly

reported AIDS cases per 100,000 people in the United States in 2002. The information

from the CDC is invaluable source for learning about and understanding the broad scope

of disease surveillance around the country. It also allows healthcare professionals and

public health officials to see what’s going on in their own state, as well as other states

around them. Finally, the publication of these reports shows the collaborative nature of

surveillance. Without the work of healthcare providers and local health departments

these data would not be available.

Uniform criteria for reporting cases

Clinical, Laboratory, Epidemiologic

http://www.cdc.gov/osels/ph_surveillance/nndss/casedef/hepatitisacurrent.htm

Uniform criteria for reporting cases

Clinical, Laboratory, Epidemiologic

http://www.cdc.gov/osels/ph_surveillance/nndss/casedef/hepatitisacurrent.htm


http://www.cdc.gov/mmwr/PDF/wk/mm5754.pdf


http://www.cdc.gov/mmwr/PDF/wk/mm5754.pdf


TRANSCRIPT

Slide 23: State Participation in NNDSS

State participation in the National Notifiable

Disease Surveillance System is voluntary. There is

not a legal requirement that states have to

participate in this system; however, all states

choose to participate. Reporting of notifiable

disease is mandated at the state level and the list

of diseases varies by state. Reportable

conditions are determined by laws and regulations of each state and jurisdiction. Some

conditions deemed nationally notifiable might not be reportable in certain states or

jurisdictions. It’s important as a healthcare provider to know what the list of diseases

that are notifiable, are in the states that you’re practicing in.

Slide 24: Example of Physician Report –

Hepatitis B

The next few slides are going to highlight

examples of healthcare providers who did their

part in surveillance and reported a notifiable

disease to their local health department. The

first is an example of a physician who reported a

case of hepatitis B to the local health

department. This case of acute hepatitis B was in a resident of a long-term care facility,

who was admitted to the hospital with hepatitis B. After the physician made the report

for this one case, the health department nurse remembered that there were several

other cases of acute hepatitis B that had occurred recently at the same long-term care

facility. An investigation was begun, and an unsuspected outbreak was discovered at the

long-term care facility.


Hepatitis B

These cases ended up being part of a larger study

that looked at the transmission of hepatitis B

virus among people undergoing blood glucose

monitoring in long-term care facilities

Reporting by states to the CDC is voluntary Reporting mandated at state level

state legislation or regulation

Variation in the lists of reportable diseases exists between states

Reporting by states to the CDC is voluntary Reporting mandated at state level

state legislation or regulation

Variation in the lists of reportable diseases exists between states

Resident of long-term care facility hospitalized with acute hepatitis B

Physician reports case to local health department (LHD)

▪ LHD nurse remembers several other cases of acute hepatitis B at same facility in past year

▪ Unsuspected outbreak of acute hepatitis B was discovered in the facility

Resident of long-term care facility hospitalized with acute hepatitis B

Physician reports case to local health department (LHD)

▪ LHD nurse remembers several other cases of acute hepatitis B at same facility in past year

▪ Unsuspected outbreak of acute hepatitis B was discovered in the facility

MMWR, March 11, 2005 / 54(09);220-223MMWR, March 11, 2005 / 54(09);220-223


TRANSCRIPT


Listeriosis

Another example is a health care provider who

reported a case of listeriosis to their local health

department. This was a pediatrician who

attended a delivery of a stillborn infant. The

physician reported this case to the local health

department and because of this case report and

further investigation, the health department discovered an outbreak of listeriosis,

identified among Hispanic females with 12 cases identified over four months. There

were five stillbirths associated with this outbreak, three premature births and two

newborns who were infected with listeriosis. A case control study was performed to

discover what the source of the exposure was for all of these cases.


Listeriosis

Investigators found that the source of the

outbreak of Listeriosis was associated with

homemade Mexican style cheese or queso

fresco.


Listeriosis

This is one of the samples that was tested during

this outbreak investigation. Again this outbreak

was initially identified because a healthcare

provider had reported the disease to the local

health department.

Stillborn infant delivered at hospital diagnosed with listeriosis

Physician reports case to LHD

▪ Outbreak of listeriosis was identified among Hispanic females with 12 cases identified over 4 month period

5 stillbirths

3 premature births

2 infected newborns

▪ Case-control study identified common source of exposure

Stillborn infant delivered at hospital diagnosed with listeriosis

Physician reports case to LHD

▪ Outbreak of listeriosis was identified among Hispanic females with 12 cases identified over 4 month period

5 stillbirths

3 premature births

2 infected newborns

▪ Case-control study identified common source of exposure

MMWR, July 06, 2001 / 50(26);560-2MMWR, July 06, 2001 / 50(26);560-2

Used with permission from Robert E. WhitwamUsed with permission from Robert E. Whitwam


TRANSCRIPT

Slide 29: Limitations of Surveillance

With all systems and programs there are

limitations. Some of the limitations of

surveillance systems are listed here. We’re

always dealing with incomplete data. There's

overwhelming volumes of data sometimes

coming in from a variety of sources which makes

the organization and management of all that

data complicated. With the continuing advancement of information technology, there's

uneven application of surveillance. Some jurisdictions still have paper-based reporting,

where case reports are completed on paper and mailed in or faxed. There is a transition

over to electronic reporting or internet-based reporting. So we're in a period of

transition with an uneven application of the information technology; two systems trying

to merge together. Timeliness is an issue, how fast can we get the data that we need?

Completeness of the data that's being reported is another issue. Sometimes cases aren’t

reported at all and sometimes the cases that are reported have data that's missing.

Trying to improve all of these areas are challenges that public health agencies face on a

daily basis.

Slide 30: Burden of Illness Pyramid

The burden of illness pyramid depicted here is a

model for understanding foodborne disease

reporting. This illustrates steps that must occur

for an episode of illness in the population to be

registered in a surveillance database. Starting

from the bottom of the pyramid, the areas in

yellow, shows that some members of the general

population can be exposed to an organism, but not all of them will become ill. The next

line of the pyramid represents people who do become ill. In the pink portion of the

pyramid, a percentage of people who become ill will seek care, and of those that do seek

care, in a proportion of them a specimen will be obtained. Then in the purple portion of

the pyramid some of those lab tests will be submitted for the organism of interest and

the laboratory will confirm a case. Only a small proportion of those will be reported to

the health department, which represents that very small section at the top of the

pyramid in green. You can get data on foodborne illnesses in other ways; surveillance is

really just the tip of the iceberg in terms of diseases that are reported to the health

department. There are surveys that are done at the laboratory level to look at what lab

tests are positive. Active surveillance can involve a physician survey targeting that pink

portion of the pyramid, where you can actually ask healthcare providers if they've seen a

Incomplete data Overwhelming volumes of data from a variety of

sources make management complex Uneven application of information technology

Paper versus electronic reporting Timeliness

Reporting time requirement

Reporting burden Completeness

Unreported cases

Incomplete reports

Incomplete data Overwhelming volumes of data from a variety of

sources make management complex Uneven application of information technology

Paper versus electronic reporting Timeliness

Reporting time requirement

Reporting burden Completeness

Unreported cases

Incomplete reports

CDC’s Burden of Illness Pyramid: Underascertainment of Foodborne Illness in Notifiable Diseases Surveillance

Source: Adapted from Centers for Disease Control and Prevention, “FoodNet Surveillance - Burden of Illness Pyramid.” http://www.cdc.gov/foodnet/surveillance_pages/burden_pyramid.htm. Accessed October 3, 2011.

CDC’s Burden of Illness Pyramid: Underascertainment of Foodborne Illness in Notifiable Diseases Surveillance

Source: Adapted from Centers for Disease Control and Prevention, “FoodNet Surveillance - Burden of Illness Pyramid.” http://www.cdc.gov/foodnet/surveillance_pages/burden_pyramid.htm. Accessed October 3, 2011.


TRANSCRIPT

certain number of people with a constellation of signs and symptoms. And finally at the

bottom of the pyramid you can perform population surveys, were you interview a whole

group of people to find out about common exposures and also what group of people

became ill even if they didn’t seek care. So the surveillance data, the Notifiable Disease

Surveillance really is the top of the pyramid or the tip of iceberg. And that’s the take

home point when you're reviewing surveillance data, to realize that the number of cases

reported for any specific condition is always going to be an underestimation of the actual

number of cases out there.

Slide 31: Limitations of Surveillance – Shigella

This is a similar example of the pyramid. This

was from a 1977 article by Rosenberg, which

talked about cases of shigella. He found in his

study that for every 100 people infected with

shigella about 3/4 of them or 76 would be

symptomatic. 28 would go to a healthcare

provider for evaluation, only nine of those 28

would have stool cultures submitted for testing, seven would have positive results, six of

the cases of confirmed shigella would be reported to the local health department, and

only five would actually be reported to the CDC. So out of 100 people infected with

shigella, it's estimated that only five are reported to the CDC.

Slide 32: Reasons for Failure to Report

In a 2002 study by Doyle et. al, the authors

looked at some of the reasons why healthcare

providers fail to report. Oftentimes it's a lack of

awareness or knowledge of what conditions

need to be reported. A lot of providers don't

know that it's a legal requirement for them to

report. They may not understand the process if

they have a disease they need to report: who do they report it to? Oftentimes there's an

assumption that someone else will take care of it, it’s someone else's job to report.

Occasionally providers don't report on purpose or intentionally because they want to

protect patient privacy. Finally it's been found that insufficient reward or insufficient

penalty are reasons why providers wouldn’t report.

100 persons infected with shigella 76 symptomatic 28 consulted a healthcare provider 9 submitted stool cultures 7 had positive results 6 reported to the local health department 5 reported nationally to CDC

Rosenberg et al, 1977

100 persons infected with shigella 76 symptomatic 28 consulted a healthcare provider 9 submitted stool cultures 7 had positive results 6 reported to the local health department 5 reported nationally to CDC

Rosenberg et al, 1977

1. Lack of awareness of legal requirement2. Lack if knowledge of which conditions are

reportable3. Lack of knowledge of how or to whom to report4. Assumption that someone else will report the case5. Intentional failure to report to protect patient

privacy6. Insufficient reward for reporting7. Insufficient penalty for not reporting

Doyle et al, 2002

1. Lack of awareness of legal requirement2. Lack if knowledge of which conditions are

reportable3. Lack of knowledge of how or to whom to report4. Assumption that someone else will report the case5. Intentional failure to report to protect patient

privacy6. Insufficient reward for reporting7. Insufficient penalty for not reporting

Doyle et al, 2002


TRANSCRIPT

Slide 33: Limitations of Syndromic Surveillance

I wanted to mention limitations of syndromic

surveillance as well. We’ve mentiond that

syndromic surveillance certainly has advantages

over passive surveillance because it's real time

data, it’s automated, it's coming in quickly. But

syndromic surveillance systems are costly and

they require resources to bring together all of

the different syndromic data from hospitals, ambulance transport, poison control

centers, and even school absenteeism as part of the syndromic surveillance system.

They require significant staff expertise and dedicated time. We talked early on about an

ideal surveillance system would be simple, but certainly syndromic surveillance requires

staff expertise. Finally formal evaluations of existing syndromic surveillance systems are

incomplete, so the data still out on how well these work in terms of how cost effective

they are. It’s important to keep in mind that syndromic surveillance systems are not

meant to replace regular surveillance systems but rather to enhance the data that we are

already getting from a passive surveillance system.

Slide 34: Limitations of Syndromic Surveillance

Other limitations of syndromic surveillance are

false alarms and failure to detect outbreaks.

False alarms can occur because of non-specific

case definitions. Syndromic surveillance systems

are run off software that recognizes keywords as

part of the syndrome’s case definition (e.g. fever

and rash). This results in many more cases being

picked up that aren’t representative; these are considered false alarms. There can also

be inadequate sensitivity meaning syndromic surveillance is not detecting all outbreaks

or bioterrorism events. This can occur if the outbreak is too small to raise a red flag that

the number of cases has gone beyond a set threshold. Also, if this syndromic

surveillance data are coming from a number of different healthcare facilities across a

state or region, an outbreak can be missed. If a group of people is exposed in one

location but disperses after the event, the cluster may not be evident via syndromic

surveillance.

Costly

Staff expertise required

Formal evaluations of syndromic surveillance systems are incomplete

Costly

Staff expertise required

Formal evaluations of syndromic surveillance systems are incomplete

Inadequate specificity = false alarms Software recognizes key words

Uses resources in investigation

Inadequate sensitivity = failure to detect outbreaks or bioterrorism events Outbreak is too small

Population disperses after exposure, cluster not evident

Inadequate specificity = false alarms Software recognizes key words

Uses resources in investigation

Inadequate sensitivity = failure to detect outbreaks or bioterrorism events Outbreak is too small

Population disperses after exposure, cluster not evident


TRANSCRIPT

Slide 35: Summary

In summary, surveillance data has many practical

uses and is the crux of the public health core

function assessment. Notifiable disease

surveillance is fundamental to prevention and

control efforts in public health. Regardless of

where you practice the list of notifiable diseases

is going to vary by state. Finally we've talked

about limitations in surveillance, but significant improvements are being made in

advancing surveillance and reporting, so stay tuned and make sure you understand your

role in this vital public health function.

Center for Public Health Continuing EducationUniversity at Albany School of Public Health

Department of Community & Family MedicineDuke University School of Medicine

Mike Barry, CAELorrie Basnight, MDNancy Bennett, MD, MSRuth Gaare Bernheim, JD, MPHAmber Berrian, MPHJames Cawley, MPH, PA-CJack Dillenberg, DDS, MPHKristine Gebbie, RN, DrPHAsim Jani, MD, MPH, FACP

Denise Koo, MD, MPHSuzanne Lazorick, MD, MPHRika Maeshiro, MD, MPHDan Mareck, MDSteve McCurdy, MD, MPHSusan M. Meyer, PhDSallie Rixey, MD, MEdNawraz Shawir, MBBS

Surveillance data has many practical uses Notifiable disease surveillance is fundamental to

prevention and control efforts List of notifiable diseases varies by state Significant improvements are being made in

advancing surveillance and reporting

Surveillance data has many practical uses Notifiable disease surveillance is fundamental to

prevention and control efforts List of notifiable diseases varies by state Significant improvements are being made in

advancing surveillance and reporting


TRANSCRIPT

Sharon Hull, MD, MPHPresident

Allison L. LewisExecutive Director

O. Kent Nordvig, MEd

Project Representative

public health surveillance - c.ymcdn.comc.ymcdn.com/sites/ reports based on a standard case...

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