Download SARS Outbreak Study 2

SARS Outbreak Study 2
Step 1: Learning Objectives
A. Describe the four modes of transmission.
B. Distinguish between epidemic, endemic, and pandemic.
C. Formulate hypotheses and design a study to test your hypotheses:
1. Define an incubation period.
- Describe the relationship between the lognormal curve and the incubation period.
- Describe a simple technique for projecting the incubation period.
2. Distinguish between prevalence and incidence.
- Calculate incidence of disease.
3. Calculate the attack rate.
- Define secondary attack rate.
- Describe how change in the definition of the denominator of attack rate can influence
perceived public health importance of the epidemic.
4. Calculate the reproductive rate ( R 0 ).
- Describe components of the reproductive rate.
- Describe how R 0 changes with varying parameters (refer to R 0 = β * c * D).
- Describe how an epidemic can be controlled by manipulating these parameters.
D. Suggest how your findings will refine the previously implemented outbreak control measures from
Study 1.
Step 2: Introduction to the Study
Your internship at the Epiville Department of Health (DOH) has kept you on your toes. A SARS outbreak has been
confirmed in Epiville, a casual agent determined, and active surveillance put in place. Your supervisor asks you to
formulate and test hypotheses so that the outbreak management is optimized.
Step 3: Student Role - Your Plan of Action
You need to gather the following background information found on the various web pages.
- Department of Health
- Epiville Map
- Radio Transcript
Listen to the WEPI1 news report which provides background to your investigation (text of the newscast is available
below):
Interview Transcript
Reporter and Dr. Morrisa Zapp
Reporter: Dear Epiville, today we are privileged to have with us Dr. Morrisa Zapp, one of the senior scientists at the
Department of Health working on SARS outbreak in our area. Dr. Zapp, what can you tell us about progress that has
been made in SARS investigation?
Dr.Zapp: Thank you for having me here today. As many of you know, SARS is a Severe acute respiratory syndrome
(SARS); it is a respiratory illness that has recently been reported in Asia, North America, and Europe, and now it has
made its way to our own Epiville. The Centers for Disease Control and Prevention (CDC) and the World Health
Organization (WHO), as well as local DOHs (Departments of Health) are working hard in this investigation. It is a
relief that causal agent of SARS has been identified. A novel coronavirus is believed to be responsible for the global
epidemic of SARS. The CDC just recently completed the genome sequencing. Moreover, there now exists a
diagnostic test, a special laboratory procedure, which helps clinicians confirm whether someone with respiratory
symptoms really has SARS. Our goal right now is outbreak management and control. One of the reasons why I am
here is that I would like to communicate to you the latest development, which occurred in this investigation. All
individuals suspected of having contact with SARS cases have been isolated and those who were admitted to
hospitals, quarantined. Everyone is on high alert. I would like to stress that we should support our community during
these hard times and those who have SARS are not at fault in any way. Epiville DOH has its own website and
everyone is welcome to access it to learn more about SARS.
Step 4: Study Design
Now you are ready to move forward with data analysis. The goal of data analysis is to extract from the observations
(i.e. data collected) the information necessary for accurate estimation, but prior to that you want to develop
hypotheses. When developing hypotheses you should be asking yourself the following questions:
- Who is at risk of becoming ill?
- What is the disease?
- What are the source of the outbreak and the vehicle of transmission?
- What is the mode of transmission?
ANSWERS
a: Incorrect
While it is correct that the causing agent of the SARS epidemic is coronavirus and the most likely mode of spread of
infection is person-to-person, this answer does not provide information on the control measures which will stop the
outbreak.
b: Correct
Based on what we know about SARS so far, the best formulated hypothesis is one that includes coronavirus as the
most likely agent of infection, spread of SARS via person-to-person and isolation as a measure of control.
c: Incorrect
From the previous SARS epidemic we do not have information that it is transmitted via mosquito bites. while it is
certainly true that airplane travel has played a role in the spread of the SARS epidemic around the globe, it is
unlikely that banning air travel to affected areas will completely stop the epidemic as the epidemic can spread by
many other ways, e.g. local travel by buses and on foot.
d: Incorrect
Symptoms which are characteristic of West Nile virus infection differ from those of SARS infection, and therefore, the
case definition of SARS cannot be met. In addition, the CDC has established that SARS is caused by a virus from
the corona family, not by a West Nile virus. It has also been established that the most likely way of spread of SARS is
person-to-person (which could be an artifact of sexual contact but sexual contact is not necessary to get the
disease).
Step 5: Data Analysis
Now that you have developed your hypothesis, you are ready to test it. The outbreak is best described by an
epidemic time curve . An epidemic time curve is a graph with time on the x-axis and the number of new cases on
the y-axis. An epidemic time curve helps epidemiologists answer several important questions: What was the
type of exposure? What was the route of spread? When were affected persons exposed? What was the incubation
period? In addition to primary cases (persons initially infected from a common source), were there secondary cases
(person-to-person transmission of disease from primary cases to other persons)? In a point source epidemic (cases
originate from common source exposure), the lognormal distribution of cases reflects the incubation period.
Intellectually curious? Lognormal Distribution
The lognormal distribution is frequently used in Biostatistics and Epidemiology. A random variable x is said to have
the lognormal distribution, with parameters µ and σ,
if l n (x) has the normal distribution with mean µ and
standard deviation σ. Log of time distribution of cases (x-axis) turns epicurve into normal distribution with many
valuable statistical properties.
Intellectually curious?
Why should we not combine cases from the Amoy Apartment Complex and the Star Hospital?
We should not combine cases from the Amoy Apartment Complex together with cases from the Star Hospital
because in the Star Hospital there is a secondary wave of transmission while there is no secondary wave of
transmission at the Amoy Apartment Complex.
"Incubation period" is the time interval between exposure to an infectious agent and the appearance of the first signs
or symptoms of disease (Gordis p.20-21). Different diseases have different incubation periods. There is no such
thing as a precise incubation period but rather a range of incubation periods that is characteristic of a particular
disease.
Intellectually curious?
See a list of cases which appeared in the Amoy Apartment Complex and at the Star Hospital .
<PLEASE REFER TO 'APPENDIX A'>
ANSWERS:
a: Incorrect
Incubation period is not a particular number of days but rather a range of days. Please note that there are some
infectious diseases, which may have an incubation period equal to a particular number of days.
b: Incorrect
This is not the correct time interval between exposure to an infectious agent and onset of disease.
c: Incorrect
Same as "a". There is no such thing as a precise incubation period but rather a range of incubation periods.
d: Correct
Persons were first exposed to infection on August 1, 2003 at the luau party at the Amoy Apartment Complex. First
cases appeared 3 days later and the last cases appeared 12 days later, on August 13th. Therefore, the correct
incubation period is from 3 to 12 days."
ANSWERS:
a: Incorrect
There is no such thing as a precise incubation period but rather a range of incubation periods.
b: Incorrect
Personnel of the Star Hospital who were first exposed to the index case on August 3, first developed symptoms 7
days later, on August 10, not 10 days later. Index case was put in isolation on August 7 and last case in the Star
Hospital developed on August 23, which means that the incubation period could not have been more than 17 days.
c: Correct
First case at the Star Hospital appeared 7 days and the last case appeared 20 days after the index case was
hospitalized there.
Investigators of acute disease outbreaks ordinarily use a measure of disease frequency called an attack rate. An
attack rate is really the proportion of exposed persons that becomes ill. There are two types of attack rate: primary
attack rate and secondary attack rate .
An attack rate is also an incidence rate (we discussed this in Study 1 of the SARS exercise). An attack rate is used
when the occurrence of disease among a population at risk increases dramatically over a short period of time.
Secondary attack rate refers to the spread of disease in a family, household, dwelling unit, dormitory, or similar
circumscribed group. The spread of infection from an index case (the initial case, i.e. the case that introduced the
organism into the population) to the attending medical staff is called secondary attack rate. It is a good measure of
person-to-person spread of disease after the disease has been introduced into a population.
ANSWER:
(66/600)*1000=110 per 1000
Note: this is the same answer as what you obtained for the incidence rate calculation.
The secondary attack rate is calculated according to the following equation:
ANSWERS:
((22-1)/(110-1))*1,000=193 per 1,000
When you calculated the attack rate above (or incidence rate), you used number of people at risk who develop a
certain illness as your numerator and total number of people at risk as your denominator. Time is not explicitly
specified in an attack rate. If you want to show what percent of people diagnosed as having a certain disease die
within a certain time after diagnosis, you need to calculate case-fatality ratio. The percentage of the clinically ill
persons who die is called the case-fatality ratio. The higher the case-fatality ratio, the more virulent the infection is.
Case-fatality ratio is an index, which helps to measure virulence of the disease.
ANSWERS:
a: Correct answer: (12/66)*100=18.18%
b: Correct answer: (12/(66-20))*100=26.09
c: Correct answer: (3/22)*100=13.64
d: Correct answer: (3/(22-5))*100=17.64
ANSWERS:
a: Incorrect
a and c (in question 6a) are not better answers because calculating the case-fatality ratio assuming that all those
who are still ill will recover inflates the denominator of case-fatality ratio and produces an underestimate of the casefatality ratio.
b: Correct
b and d (in question 6a) are better answers because calculating the case-fatality ratio using only those cases whose
final outcome is known (died or recovered) before the outbreak is over gives an overestimate. This is a widely used
way of calculating case fatality because it is more conservative to have an overestimate rather than an
underestimate.
Intellectually curious?Alternative Ways to Calculate Case Fatality
Survival Analysis as a better alternative for calculating case-fatality ratio. Survival analysis relies on detailed
individual data on the time from illness onset to death or full recovery, or time since illness onset for current cases.
This method yields a more accurate and unbiased estimation of case-fatality ratio.
Step 6: Plan of Action
At this point in the outbreak investigation, your primary concern is to contain its spread. Looking at the very different
experience of the two Epiville hospitals, you see the importance of public health measures which were instituted at
the Epiville General Hospital, where no secondary transmission occurred.
Reproductive rate, R 0 , is one of the most important concepts in infectious disease epidemiology (consult your List of
Infectious Disease Concepts and Terms for information on reproductive rate). R 0 is the number of secondary
infections per 1 infected case. This measure is most useful in determining the outbreak control measures. It is
defined by the following equation:
R0 = β * c * D, where:
β = average probability a contact will be infected over duration of a relationship (depends on the biology and
behavior of infection)
c = average rate of getting into contact (isolation and quarantine minimize this parameter because infectious
persons, as in isolation, and those who are suspected to be infected, are in minimum contact with healthy
individuals)
D = average duration of infectiousness (this parameter represents length of symptomatic disease; we can modify D
by shortening duration of infectiousness. This could be achieved by proper treatment and isolation of cases.)
The epidemic is spreading if R 0 > 1.
For an epidemic to remain endemic, R 0 = 1.
When an epidemic is declining, R 0 < 1.
This equation is used for modeling of infectious diseases (it has been extensively used in HIV/AIDS research).
Through modeling, you can anticipate when the infectious disease will reach its peak and, therefore, take necessary
control measures, such as proper infection control in the hospitals and reduction of contact rates in the population.
You can also learn about the etiologic agent and how transmittable it is.
There are a number of important policy implications derived from this formula:
- Wearing masks
- Closing schools
- Public advisory on attending public gatherings (cinemas were closed in Hong Kong during the SARS
epidemic)
- Precautionary measures at the hospitals (negative pressure wards and properly clothed personnel)
- Travel advisories
Exercise:
The objective of this exercise is to understand how Ro changes with varying of its parameters: β, c, and D
<Please see 'EPIVILLE SITE MAP' on SImulation Site>
Directions For This Exercise:
1. The map, which appears under 08/03/2003, reflects the epidemic outbreak given 66 cases that occurred in Amoy
Apartment Complex and 22 cases of secondary transmission in the Star Hospital. Reproductive rate offers means of
outbreak management.
2. Please click on Map 2. If you compare this map to Map 1, what do you observe?
3. Do you think this is an effective outbreak management?
4 Now click on Map 3, compare this map to Maps 1 and 2, what do you observe?
- Assumptions for Map 2: when R 0 =2.3, our Beta=0.16, c=2, and duration of infectiousness=7 days
- Assumptions for Map 3: when R 0 =0.8, our Beta=0.05, c=2, and duration of infectiousness=7 days
Step 7: Discussion Questions
1. What are the most effective ways of manipulating parameters of reproductive rate equation in order to control an
epidemic?
2. What has the international community learned from the emergence of SARS? (hint: think in terms of emerging
pathogens, world wide traveling, global community, etc.).
3. Are we, as a global community, ready if SARS outbreaks reoccur next year? What do you think should be done to
insure such readiness?
Questions for the Intellectually Curious:
When do you think case-fatality ratio is most meaningful: at the end of the epidemic or while the epidemic is evolving
and why?
What if the index case admitted with SARS to the Star Hospital had been isolated from the very beginning?
New York Times article, May 7, 2003 :
Study in Hong Kong Suggests A Higher Rate Of SARS Death
By LAWRENCE K. ALTMAN
The death rate from SARS may be significantly higher than health officials had thought, up to 55 percent in people
60 and older, and up to 13.2 percent in younger people, the first major epidemiological study of the disease
suggests.
Mortality rates are bound to change somewhat as an epidemic continues. But unless the numbers fall drastically,
SARS would be among infectious diseases with the highest death rates. Until now, fatality rates reported by the
World Health Organization had ranged from 2 percent, when the epidemic was first detected in March, to 7.2 percent.
The new findings come from a statistical analysis of 1,425 patients suspected of having SARS who were admitted to
Hong Kong hospitals from Feb. 20 to April 15. Over all, their mortality rate was estimated to be as high as 19.9
percent. By contrast, the influenza pandemic of 1918, which killed tens of millions of people worldwide, had an
estimated mortality rate, over all, of 1 percent or less.
But calculating mortality rates for newly emerging diseases is a notoriously difficult challenge for epidemiologists,
especially if there is no definitive diagnostic test, as is the case with severe acute respiratory syndrome.
It is possible, for example, that some people infected with the virus believed to cause the disease never fall ill, or
develop symptoms so mild that they do not seek medical assistance. If that is the case, mortality rates could be much
lower.
The research, led by Dr. Roy M. Anderson and Dr. Christl A. Donnelly, both of Imperial College in London, is to be
reported in Saturday's issue of The Lancet, the British-based medical journal. Its editors posted the report on the
journal's Web site, www.thelancet.com, yesterday, citing its public health importance.
The principal authors of the study -- from Imperial College, the University of Hong Kong, the Chinese University of
Hong Kong and the Hong Kong health department -- said their findings underscored that SARS was a serious threat
to the public and that health officials and workers must act to contain it.
The authors credited Hong Kong's efforts to reduce the time from the onset of symptoms to the isolating of patients in
hospitals as an important step in controlling the disease.
Reducing the time did not affect the course of the illness in individual patients, they said, but expediting the isolation
process reduced the period when patients could transmit the virus to others.
Yesterday, the W.H.O. said the number of new SARS cases in Hong Kong had steadily declined, which they said
suggested that the outbreak there had reached a peak. So far, Hong Kong has reported 1,646 probable cases and
193 deaths, which would mean that the death rate is 11.7 percent.
But death rates calculated from this kind of data -- what epidemiologists call case-fatality rates -- can underestimate
actual mortality rates, in part because they do not take into account patients who remain ill, some of whom may die.
By contrast, the authors of the new study arrived at their figures by studying people admitted to Hong Kong hospitals
each week. They began their analysis with patients admitted in the week after Feb. 26; until then there were too few
to make statistically significant calculations, they said. Their analysis ends with patients admitted in the week ended
April 15. For those admitted later, they said, "too little time has elapsed" after the onset to allow analysis of mortality
rates.
In an interview, Dr. Michael T. Osterholm, an expert on infectious disease now at the University of Minnesota, said
that the Lancet study "looks solid and provides an important source of information about the evolving epidemic."
"Anyone who tries to make a point of precision right now about case-fatality rates does not understand them," he
said.
Dr. Klaus Stohr, the scientific director of the SARS investigation for the W.H.O., said in an interview that the agency
was reviewing the new data and the statistical models used to obtain it.
"The case-fatality rate can be calculated in many ways and can depend on various scenarios," Dr. Stohr said. Data
that the W.H.O. has received from Hong Kong officials suggests a death rate closer to 15 percent than 20 percent.
Dr. Stohr said he wished the W.H.O. had received the new data sooner. He said it had been available for more than
a week by the time it was posted.
Dr. Stohr said that earlier receipt of the data could have helped in the evaluation of another finding in the study -- the
time between exposure to the virus and the onset of symptoms, or the incubation period. The study estimated it to be
6.4 days. But other statistical calculations based on a small number of patients in the study showed that the
incubation period could be as long as 14.22 days.
The figure is important because health officials use it to determine how long people exposed to the virus must
remain quarantined. Also, as a rule of thumb, health officials double the estimated incubation period to determine
when they can declare an outbreak over in a certain area.
Health officials have been using 10 days as the longest incubation period and so have used a 20-day period as the
criterion for declaring an area to be no longer affected by SARS. But a 14.22-day figure could mean lengthening the
quarantine period and the criterion for declaring an outbreak over.
Dr. Stohr said that if the data concerning the longer incubation period held up in further analysis, the W.H.O. might
change its recommendations for quarantine.
The authors said it might turn out that the incubation period depended on where the SARS virus entered the body.
Health officials say that most cases result from the spread of droplets from coughs and sneezes. The SARS virus can
survive on surfaces for up to four days, and although scientists have not proved that transmission has occurred
through such contamination, Hong Kong officials suspect that a big outbreak at an apartment complex there was
spread through sewage.
In conducting the Lancet study, the researchers used different statistical methods to calculate the case-fatality rate
over the first nine weeks of the epidemic in Hong Kong.
By one method, they found that the case-fatality rate, among those admitted to hospitals, was 43.3 percent among
patients 60 and older and 13.2 percent among those less than 60.
Using another method, they found the case-fatality rates to be 55 percent among those 60 and older and 6.8 percent
in those younger than 60.
Dr. Anderson and his team said it would be important to learn whether public health interventions, including news
reports, encouraged infected individuals to report their symptoms quickly.
"The epidemic has demonstrated the need," he said, "for communication of risk which will inform and warn the
public, in a way which will improve personal protection, without inducing high levels of anxiety and fear, as an
essential part of epidemic control. A change in risk perception would potentially lead to an increase in early reporting
of symptoms as well as improvements in hygiene and prevention of transmission."
Copyright 2003 The New York Times
APPENDIX A
Star Hospital
Patient
Sex
Age
Date of Onset
1
F
45
8/10/03
2
M
46
8/11/03
3
F
25
8/12/03
4
F
50
8/13/03
5
M
28
8/13/03
6
M
27
8/13/03
7
M
29
8/13/03
8
M
30
8/14/03
9
F
28
8/14/03
10
F
40
8/14/03
11
F
28
8/14/03
12
F
26
8/15/03
13
F
27
8/15/03
14
F
39
8/15/03
15
M
19
8/15/03
16
M
23
8/15/03
17
M
35
8/15/03
18
F
22
8/16/03
19
F
30
8/16/03
20
F
32
8/17/03
21
F
22
8/20/03
22
M
42
8/23/03
Date of Onset
No of Patients
8/10/03
1
8/11/03
1
8/12/03
1
8/13/03
4
8/14/03
4
8/15/03
6
8/16/03
2
8/17/03
1
8/20/03
1
8/23/03
1
Total
22
Amoy Apartment Complex
Patient
Sex
Attended the Party
Age
Date of Onset
1*
M
Yes
70
8/3/03
2
F
Yes
77
8/3/03
3
F
Yes
63
8/3/03
4
F
Yes
5
8/3/03
5
F
Yes
7
8/3/03
6
F
Yes
68
8/3/03
7
F
Yes
69
8/3/03
8
F
Yes
45
8/3/03
9
F
Yes
2
8/4/03
10
F
Yes
73
8/4/03
11
F
Yes
24
8/4/03
12
F
Yes
26
8/4/03
13
F
Yes
28
8/4/03
14
F
Yes
30
8/4/03
15
F
Yes
3
8/4/03
16
F
Yes
58
8/4/03
17
F
Yes
76
8/5/03
18
F
Yes
52
8/5/03
19
F
Yes
51
8/5/03
20
F
Yes
53
8/5/03
21
F
Yes
42
8/5/03
22
F
Yes
43
8/5/03
23
F
Yes
21
8/5/03
24
F
Yes
35
8/5/03
25
F
Yes
10
8/5/03
26
F
Yes
12
8/6/03
27
F
Yes
14
8/6/03
28
F
Yes
15
8/6/03
29
F
Yes
23
8/6/03
30
F
Yes
62
8/6/03
31
F
Yes
78
8/6/03
32
F
Yes
47
8/6/03
33
F
Yes
58
8/6/03
34
M
Yes
25
8/6/03
35
M
Yes
6
8/7/03
36
M
Yes
9
8/7/03
37
M
Yes
11
8/7/03
38
M
Yes
16
8/7/03
39
M
Yes
17
8/7/03
40
M
Yes
19
8/7/03
41
M
Yes
20
8/7/03
42
M
Yes
22
8/7/03
43
M
Yes
4
8/6/03
44
M
Yes
27
8/6/03
45
M
Yes
29
8/8/03
46
M
Yes
31
8/8/03
47
M
Yes
33
8/8/03
48
M
Yes
37
8/8/03
49
M
Yes
38
8/8/03
50
M
Yes
38
8/8/03
51
M
Yes
40
8/8/03
52
M
Yes
41
8/8/03
53
M
Yes
43
8/9/03
54
M
Yes
44
8/9/03
55
M
Yes
41
8/9/03
56
M
Yes
72
8/9/03
57
M
Yes
31
8/9/03
58
M
Yes
33
8/10/03
59
M
Yes
34
8/10/03
60
M
Yes
36
8/10/03
61
M
Yes
39
8/10/03
62
M
Yes
39
8/12/03
63
M
Yes
46
8/12/03
64
M
Yes
54
8/12/03
65
M
Yes
48
8/12/03
66
M
Yes
49
8/13/03
Date of Onset
No. of Patients
8/3/03
8
8/4/03
8
8/5/03
9
8/6/03
11
8/7/03
8
8/8/03
8
8/9/03
5
8/10/03
4
8/12/03
4
8/13/03
1
Total
66
* case hospitalized at the Star Hospital but is counted in the Amoy
Apartment Complex outbreak
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