ebola and influenza perception & reality - university of...

Background Influenza burden Transmissibility What is controllable? Conclusions

Ebola and Influenza — Perception & reality

Dennis Chao

Vaccine and Infectious Disease DivisionFred Hutchinson Cancer Research Center

February 26, 2015

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Ebola cases the United States

year

19

76

20

14

0

1

2

Cases from transmission in the USA

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Ebola outbreaks since 1976

start of outbreak (year)

1976

1979

1994

1995

1996

2000

2001

2002

2003

2004

2007

2008

2012

2013

2014

0

5000

10000

15000

20000

25000

Cases

Deaths

data from http://en.wikipedia.org/wiki/List_of_Ebola_outbreaks, downloaded Feb 24, 2015

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Influenza deaths in the United States

start of season (year)

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

0

10000

20000

30000

40000

50000 estimated deaths (USA)

recorded deaths (USA)

Data from: Doshi. Trends in Recorded Influenza Mortality: United States, 1900–2004. Am J Public Health. 2008 May;98(5):939-45

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Ebola vs influenza

Ebola Influenzatransmission route blood, feces, vomit airborne

transmissibility high (in some settings) moderatecase fatality 50–70% 0.001–2%

annual cases hundreds hundreds of millions?

start of outbreak (year)

19

76

19

79

19

94

19

95

19

96

20

00

20

01

20

02

20

03

20

04

20

07

20

08

20

12

20

13

20

14

0

5000

10000

15000

20000

25000

Cases

Deaths

start of season (year)

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

0

10000

20000

30000

40000

50000 estimated deaths (USA)

recorded deaths (USA)

annual deaths tens hundreds of thousands?

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How do we count cases?

Active

Door-to-door or telephonesurveys, contact tracing

(Can be) accurate, ex-pensive

Passive

Hospital and death records,internet search, medical-related purchase histories

Can miss mild cases,hard to extrapolate

Surveillance systems combine active and passive approaches tomeasure populations.

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How do we count ebola cases?

Ebola cases in Liberia. London School of Hygiene & Tropical Medicine.http://ntncmch.github.io/ebola/liberia_sitrep.html

• Hospitals and clinics (should) report how many seek care for ebola.• But not everyone seeks care at medical facilities.• Underreporting may be as high as 50% in the current ebola

epidemic.• Estimating the number of cases may require comparing different

data sources (hospitalization vs death reports), activesurveillance in remote communities, and/or mathematicalmodeling.

Since ebola symptoms are severe, it is easier to count cases.8 / 34


How do we count influenza cases?

Active

Door-to-door or telephonesurveys, contact tracing

(Can be) accurate, ex-pensive

Passive

Hospital and death records,internet search, medical-related purchase histories

Can miss mild cases,hard to extrapolate

How good is this for influenza?

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Influenza-related deaths

http://www.cdc.gov/flu/weekly

Monitor “excess” pneumonia and influenza deaths in a sampleof hospitals. Elderly influenza cases have higher mortality thanyounger cases.

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Influenza-like illness


ILI is defined as fever (temperature of 100◦F [37.8◦C] or greater)and a cough and/or a sore throat without a KNOWN cause otherthan influenza.

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Confirmed influenza infections


Some influenza patient samples are tested in the lab.

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How do we count influenza cases?

Reed, Angulo, Swerdlow, Lipsitch, Meltzer, Jernigan, Finelli. Estimates of theprevalence of pandemic (H1N1) 2009, United States, April–July 2009. Emerg In-fect Dis. 2009 Dec;15(12):2004–7.

• As many as 140 influenzaillnesses for every labora-tory confirmed case.

Each level in the pyramid can introduce error and uncertainty.

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How transmissible are pathogens?

R0 = 2.0

• R0 is popular measure of transmis-sibility.

• R0 is the number of people that atypical infected person infects in afully susceptible population.

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How transmissible are pathogens?

R0 = 2.0

pathogen R0

Influenza 1.1–2.0Ebola 1.7–2.0SARS 2.7

Smallpox 3Rubella 6–7

Measles 7–12

Disease can spread exponentially.

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How does vaccination reduce transmission?

• Individual-level benefit:Vaccination reduces the chancesof infection.

• Population-level benefit:Vaccination reduces the numberof people a person can infect.

• If infected people infect less than1 other on average (R0<1), out-breaks will not occur.

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How many people do we need to vaccinate?

R0=2.0 pathogen R or R0



Measles 7–12

(assuming a perfect vaccine)

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50% for R0=2.0 pathogen R or R0



Measles 7–12


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Measles 7–12


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67% for R0=3.0 pathogen R or R0



Measles 7–12


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Measles 7–12


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87.5% for R0=8.0 pathogen R or R0



Measles 7–12


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Critical vaccination fraction

R

cri

tica

l va

ccin

atio

n f

ractio

n

1 3 5 7 9

0.0

0.2

0.4

0.6

0.8

1.0

VE=100%

VE=80%VE=60%

• The critical vaccination fraction is the proportion of the populationthat needs to be vaccinated to prevent outbreaks.

• Basically, vaccinate enough to drive R0 below 1.• The critical vaccination fraction depends on R0 and the vaccine

efficacy, VE:1−1/R0

VE 23 / 34


Measles vaccination coverage around the world

Measles by the numbers: A race to eradication. Nature 518:148–149. 2015. Annotation added by Dennis.

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Local MMR vaccination coverage

https://data.kingcounty.gov/dataset/Kindergarten-MMR-Vaccine-Coverage/kbfa-mvcb

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How long does it take to infect someone else?

Field Epidemiology Manual. https://wiki.ecdc.europa.eu/fem

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Transmissibility + speed can be used to model outbreaks

S I R

I γβ

dSdt

= −βSI

dIdt

= βSI − γI

dRdt

= γI William Kermack Anderson McKendrick1898–1970 1876–1943

Calculus is often used to model epidemic dynamics.

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Simple epidemic dynamics

Time in days

Infe

cte

d

0 20 40 60 80 100 120 140

0

100

200

300

400

500

600

Epidemic dynamics of a simple mathematical model.

pathogen R0 or R serial intervalInfluenza 1.1–1.5 3.4 days

Ebola 1.83 15.3 daysSARS 2.7 6 days

Measles 7.7 14 days

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What outbreaks are containable?

Field Epidemiology Manual. https://wiki.ecdc.europa.eu/fem

Influenza: Many asymptomaticbut infectious cases. Shortgeneration time.Ebola: Cases are not veryinfectious until late. Longergeneration time. Clinical diseaseis debilitating.SARS: Most cases are symp-tomatic. Little transmissionbefore symptoms appear.Measles: Highly transmissible.Vaccination is very effective.HIV: Highly infectious beforesymptoms appear.

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Projecting the ebola epidemic with models

Ebola Cases Could Reach 1.4 Million Within Four Months, C.D.C.Estimates. New York Times. September 2014.

Meltzer, Atkins, Santibanez, Knust, Petersen, Ervin, Nichol, Damon,Washington. Estimating the Future Number of Cases in the EbolaEpidemic — Liberia and Sierra Leone, 2014–2015. MMWR SurveillSumm 63:1–14. 2014.

With initial R0 and generation time estimates, one can forecastepidemic spread.

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(Over-) estimating Ebola

Models overestimate Ebola cases. November 2014.Ending the Ebola Outbreak. New York Times. February 2015.

Projections may assume that the epidemic will maintain its initialcourse.

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Ebola transmission in hospitals and funerals

Faye, Boëlle, Heleze, Faye, Loucoubar, Magassouba, Soropogui,Keita, Gakou, Bah, Koivogui, Sall, Cauchemez. Chains of trans-mission and control of Ebola virus disease in Conakry, Guinea, in2014: an observational study. Lancet Infect Dis. In press.

• “Ebola virus disease who werenot health-care workers infecteda mean of 2·3 people (95% CI1.6–3.2): 1.4 (0.9–2.2) in thecommunity, 0.4 (0.1–0.9) in hos-pitals, and 0.5 (0.2-1.0) at funer-als.”

• “After the implementation of in-fection control in April, the repro-duction number in hospitals andat funerals reduced to lower than0.1.”

• “In the community, the repro-duction number dropped by 50%for patients that were admittedto hospital, but remained un-changed for those that were not.”

Behaviors change and authorities take action during largeoutbreaks.

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Summary and conclusions

• Epidemiologists design surveillance systems to detect and quantifyinfectious disease transmission.

• Mathematical modelers use these data for projections and toestimate the impact of interventions.

• Early projections may be inaccurate, but can be useful. Oneshould not extrapolate trends too far into the future.

• It is hard to predict behavioral responses to epidemics. Fear (orlack of fear) can have a large effect.

• Someone else needs to communicate infectious disease risk topolicymakers and the general public.

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Thank you!

Boukan Kare, Haiti.Photo by D. Chao

[email protected]

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