infectious disease epidemiology how do we use...

Infectious Disease Epidemiology How do we use statistics?

Laura MacDougall

BC Centre for Disease Control SFU, Stat 305, April 5, 2012

Epidemiology

•  “The study of the distribution and determinants of disease in (human) populations; its application to control health problems” Last, 2001

•  Components of ID epidemiology – Surveillance – Outbreak investigation – Research

Surveillance

Surveillance framework Collection, analysis, interpretation and dissemination of data that leads to action to prevent and control disease

Collection

Analysis

Interpretation Dissemination

Action

Data sources •  Reportable diseases •  Laboratories •  Administrative data

–  Physician billings – Hospitalisations

•  Clinical data –  Clinics or emergency

dpt •  Vital statistics

–  Births – Deaths

•  Hospitals, health facilities

•  Schools, daycares, workplace

•  Surveys •  Immunization

registries •  Vaccine-associated

adverse reaction data

Data collected •  Person

–  Demographics (age, sex, ethnicity) –  Clinical (symptoms, lab data)

•  Place –  Residence –  Exposure

•  Time –  Onset→specimen collection→diagnosis →reported

•  Exposures/risk factors –  Travel, food history, sexual practices, immunization

history…

Automatic aberration detection

•  Automatic detection of statistically significant change in distribution of disease (i.e. outbreak)

•  Methods –  Identify electronic retrospective data to forecast

expected numbers –  Select a method (e.g. time series, regression,

CUSUM) to adjust for trends, seasons, past outbreaks and develop model

–  Determine alert threshold –  Apply model to prospective data –  Identify and interpret signals detected

Automatic aberration detection example

BCCDC 2007

Outbreak Response

A family cluster is detected…

•  Onset February 20/03 •  5/6 symptomatic

–  2 hospitalized –  3 lab confirmed

•  Food history: –  Frozen chicken

nuggets –  French toast

An outbreak?

Incidence of S. Heidelberg in 2003 vs. 5 year average (1998-2002 )

0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10 11 12

5 YR AVE 2003

No.

cas

es

Week

Methods

•  Case-control study –  Cases

•  Lab confirmed January 1 – April 1, 2003 •  10 cases only ; 1 case per household •  Recall period – 7 days prior to onset

–  Controls •  1:1 age matched: 0-6, 7-17, 18+ •  Forward digit dialing •  Recall period – 7 days prior to interview

Risk Factors

*For one case, no information on strip exposure was provided.

Exposure MOR 95% CI # cases exposed*

# controls exposed

Nuggets alone 2 0.29 < OR < 22.11 4/20 4/18Strips alone undefined 6/19 0/18Nuggets + strips 8 1.07 < OR < 354.98 13/19 4/18Nuggets + strips (excl. restaurant i.e. McDonalds)

11 1.60 < OR < 473.47 13/19 1/18

No other risk factor significant

L. MacDougall, M. Fyfe et al. J Food Prot. 2004 Jun;67(6):1111-5

Consumer attitudes + beliefs

•  Considered product pre-cooked – 1/3 cases, 1/3 controls

•  27% always or sometimes used microwave

•  35% washed hands less frequently after handling nuggets vs. raw chicken

•  37% re-packaged their strips – Of these, only 26% kept cooking instructions

L. MacDougall, M. Fyfe et al. J Food Prot. 2004 Jun;67(6):1111-5

Conclusion

•  Frozen chicken nuggets/strips are a risk factor for S. Heidelberg infection

•  Contributes significantly to the baseline (non-outbreak) rate of infection in BC

•  Labels must be changed to clearly identify nuggets/strips as a raw product

•  Consumer education required

Actions taken

•  Local press release to consumers – CFIA and BCCDC

•  Labelling changes! Before

After

Research

A Cryptic Story

5

•  An increase in the number of animal and human cryptococcosis noted in 2001

•  Clinical symptoms: prolonged cough, sharp chest pain, unexplained shortness of breath, severe headache, fever, night sweats, weight loss; skin lesions (animals)

•  Profiles of human cases did not fit the traditional understanding of cryptococcosis

•  All cases resided on or had visited Vancouver Island prior to the onset of illness

Emergence of C. gattii on VI

Fyfe CCDR 2008

Hospitalizations for cryptococcal infection in HIV-negative patients by location of treatment, BC 1995-2004

0

5

10

15

20

25

30

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

MainlandIsland

(N=158)

Fyfe CCDR 2008

Cryptococcus isolates by serotype, BC, 1987-2000

0

2

4

6

8

10

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

Num

ber o

f iso

late

s

BDA

(N=36)

Emergence of C. gattii on VI

Risk factors? •  Case control study

–  30 cases from 1999-2001 –  Matched to 2 controls by sex –  Controls required recent normal CXR –  Standard questionnaire administered

•  Population control study –  218 cases from 1999-2007 –  Compared to population data

•  Age and sex distribution (BC Statistics) •  Smoking prevalence (Canadian Community Health Survey) •  Cancer prevalence (BC Cancer Agency) •  HIV, COPD prevalence (published data)

MacDougall EID, 2011 Feb;17(2):193-9

Risk factors (results) Risk factor Case control study

mOR (95%CI) Case vs. population control

prevalence (p-value)

Age > 50y Not significant 72.4% vs. 31.3% (p<0.001)

Male sex Not evaluated 55.8% vs. 49.6% (p=0.198)

Smoking 1.18 (0.44-3.20) 41.9% vs. 17.8% (p<0.001)

Systemic steroid use 8.1 (1.7-37.8) Not evaluated

Chronic lung disease 3.2 (1.1-9.5) 4.1% vs. 8.0% (p=0.090)

Cancer 2.0 (0.6-6.1) 24.7% vs. 3.6% (p<0.001)

HIV infection Not evaluated 3.7% vs 0.2% (p<0.001)

MacDougall EID, 2011 Feb;17(2):193-9

Study Objective

To delineate the geographic areas where Cryptococcus gattii is currently established and forecast areas that could support Cryptococcus gattii in the future for targeted public health messaging of Cryptococcus gattii risk and prioritization of environmental sampling

S. Mak, MSc thesis, 2009

GARP Animal

Human

Environmental

Elevation

Aspect

Slope

Biogeoclimatic

January Temp (x3)

July Temp (x3)

Precipitation (x3)

Soil (x2)

Determine significant variables

Methodology and Data

Resulting models


Conclusion (1)

•  Suitable ecological niche for Cryptococcus gattii is

available on the BC mainland

•  Cryptococcus gattii distribution in BC associated with

areas having >1oC January average temperature and

<770m elevation (mean = 100m)

•  Animal distribution of cryptococcosis corresponds

directly with human distribution


Conclusion (2)

•  Ecological niche modeling of Cryptococcus gattii

produced very accurate predictions (>98% accuracy)

•  The ecological niche model based on environmental

sampling data produced the most conservative forecast

•  Environmental sampling for Cryptococcus gattii in

geographic locations identified as “optimal” ecological

niche areas are currently underway


Summary

•  Both simple and complex statistics are useful in communicable disease epidemiology

•  Are important for surveillance, outbreak response and research

•  Used to: –  Identify outbreaks – Examine risk factors – Persuade policy makers and the public

infectious disease epidemiology how do we use...

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