dr. jeff zimmerman - developments in infectious disease surveillance

Developments in infectious disease surveillanceM Rotolo, Y Sun, C Wang, LG Giménez-Lirola, R Main, J Zimmerman

Definitions• Surveillance = detection.• Monitor = track changes

over time.• In practice, “surveillance”

and “monitoring” are used interchangeably.

Rodger Paskin. 1999.

Surveillance: Humans• "Representative sampling" described in 1895.

(Kruskal and Mosteller, 1980).

• Normal practice was to sample everybody.

• Lesson from 1948 U.S. presidential election ... use statistically-based sampling. use

CSFV ►

PRV ►xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Surveillance: CSFV

CSFV ►

PRV ►

Surveillance: CSFV

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1959 - Khrushchev, Garst, Lodge

CSFV ►

PRV ►

Surveillance: PRV

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxREPRESENTATIVE

SAMPLING

Surveillance: PRV Official "Random" Samples

• 95/10 (95% probability of detecting 10% infection)

< 100 pigs - test 25100-200 - test 27201-999 - test 28≥1,000 - test 29

• 95/5 (95% probability of detecting 5% infection)

< 100 pigs - test 45100-200 - test 51201-999 - test 57≥1,000 - test 59

• 95/20 sampling: up to 14 head, test all. Over 14 head, test 14

Surveillance: PRV Official "Random" Samples

• 95/10 (95% probability of detecting 10% infection)

< 100 pigs - test 25100-200 - test 27201-999 - test 28≥1,000 - test 29

• 95/5 (95% probability of detecting 5% infection)

< 100 pigs - test 45100-200 - test 51201-999 - test 57≥1,000 - test 59

• 95/20 sampling: up to 14 head, test all. Over 14 head, test 14

Surveillance: PRV

RM Cannon, RT Roe. 1982

Surveillance: PRV

RM Cannon, RT Roe. 1982

WHERE DID THESE TABLES COME FROM?

Based on specific assumptions ...

1. Finite population.2. Binary outcome (yes/no).3. Each observation is independent. 4. Target is randomly distributed

in the population.

If the assumptions hold, sample size (n) can be calculated as ...

𝑛 = ( ^2 ) / (( ^2 ( −1)+ ^2 ))𝑁𝑧 𝑝𝑞 𝐸 𝑁 𝑧 𝑝𝑞• n = Minimum sample size for detection• N = Population size• z = Confidence level (zα/2)• p = Proportion of events in population• q = Proportion of non-events in population• E = Accuracy of sample proportions

Need for evolution of surveillance ...• PROBLEM: Complexity of systems

• 2012: 60% of inventory on farms with ≥ 5,000 head.

• RESPONSE: New sample types• Individual pig samples• Pooled samples• Aggregate samples (OF, air, water,

Swiffers)

Oral fluid samples ...

Collecting oral fluids

Recipe for collecting oral fluids:1. Collect first thing in the

morning (pigs are most active)

2. Use cotton rope3. Adjust rope to pig size 4. Extract fluid from rope5. Pour fluid into a tube chill or

freeze6. Send for testing

ISU - VDL - oral fluid tests:

•2010 - 10,268

•2011 - 32,591

•2012 - 60,034

•2013 - 94,101 •2014 - 146,831

•2015 - 176,167 •2016 - 178,000? new norm?

PCR detection of pathogens in oral fluids

• African swine fever virus• Classical swine fever virus• Foot-and-mouth disease

virus• Influenza viruses• PCV2• Aujeszky’s disease virus

• PEDV• PRRS virus• TTV1 and 2• Erysipelothrix spp.• M. hyorhinis • M. hyosynoviae

Possible oral fluid antibody assays ...• African swine fever virus• Aujeszky's disease virus• Classical swine fever virus• FMD virus• Influenza viruses• PCV2• PEDV• PRRSV

• Actinobacillus pleuropneumoniae

• Erysipelothrix spp.• Salmonella spp. • Lawsonia intracellularis• Any pathogen for which

we have a good serum ELISA

How to collect oral fluid samples in a “statistically valid” surveillance approach?

Statistically valid method to collect OF samples?• Allocation of samples• Number of samples• Frequency of sampling

BARN LEVEL - NOT SITE LEVEL

Statistically valid method to collect OF samples?• Allocation of samples?• Number of samples?

"piecewise exponential survival model"

Field data• 3 wean-to-finish barns on one site• 36 pens per barn (~25 pigs per pen)• Sampling from the end of the first

week placed + weekly for 8 weeks (9 samplings in total)

Field data• ~972 oral fluid samples

• 3 barns x 36 pens x 9 samplings = 972• All samples randomized and then tested• PRRSV RT-PCRs were used in the analysis

Dufr

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, Pol

son,

Hol

ck, R

ober

ts.

2003

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Dufr

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son,

Hol

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2003

PRR

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"Groups with an initial prevalence of 8% took 5 weeks to reach 100% prevalence." Dr. John Roberts - analysis of field data

PR

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"Groups with an initial prevalence of 8% took 5 weeks to reach 100% prevalence." Dr. John Roberts - analysis of field data

How to collect oral fluid samples in a “statistically valid” approach?

Statistically valid method to collect OF samples?• Allocation of samples?• Number of samples?

"piecewise exponential survival model"

"Allocation" of samples?

"Fixed" spatial samplingEquidistant spacing in

buildings and/or spaces.

Random samplingSimple random sampling

(random.org).

Caution! Complex data!Do not worry about the details.

Remember the concepts.

Prob

abili

ty o

f det

ectio

n:

1) p

reva

lenc

e 2

) no

sam

ples

3)

sam

ple

allo

catio

n

Prob

abili

ty o

f det

ectio

n:

1) p

reva

lenc

e 2

) no

sam

ples

3)

sam

ple

allo

catio

n

Statistical analysis: fixed spatial sampling was EQUAL OR BETTER than random

samling

Dete

ction

by

prev

alen

ce

(100

% d

x se

, 100

% d

x sp

• Easily understood and applied• Widely used, e.g., forestry and

environmental sciences.• "Systematic sampling is more precise than simple

random sampling when spatial autocorrelation is present and the sampling effort is equal." (Aune-Lundberg and Strand, 2014)

Systematic spatial sampling

Poster 23. Rotolo et al. Spatialautocorrelation and implications for oral

fluid based PRRSV surveillance.&

Tuesday 8:00 am CRWAD

Detection on a site depends on the number of barns sampled!

Probability of detection (P) as a function of the number of barns on the site P = (1 - (1 - p)n) n = number of barns sampled

Probability (p) of detection (one barn)

XXXXXXXXXXXXX

Probability (p) of detection (one barn)

Probability of detection (site)

XXXXXXXXXXXXX

Fixed spatial sampling also works for monitoring

Fixed spatial sampling works for monitoring …

10 sites x 6 pens in each barn x sampling each2 weeks for 18 weeks.

0

0.5

1

1.5

2

2.5

3

3.5

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 10

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 5

0.000.501.001.502.002.503.003.504.004.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 9

P

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 6

P

P

P

P

P

P

0

0.5

1

1.5

2

2.5

3

3.5

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 10

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 5

0.000.501.001.502.002.503.003.504.004.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 9

P

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 6

P

P

P

P

P

P

Results (averages)ELISA S/P values

RT-PCR positives (P)

0

0.5

1

1.5

2

2.5

3

3.5

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 10

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 5

0.000.501.001.502.002.503.003.504.004.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 9

P

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 6

P

P

P

P

P

P

0

0.5

1

1.5

2

2.5

3

3.5

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 10

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 5

0.000.501.001.502.002.503.003.504.004.50

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 9

P

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 2 4 6 8 10 12 14 16 18

Mea

n S/

P ra

tio

Week of Growout

Barn 6

P

P

P

P

P

P

The results are logical and easy to understand because they reflect the pigs' response to infection over time

Results (averages)ELISA S/P values

RT-PCR positives (P)

This exmple used PRRSV PCRs, but the model applies to any pathogen / assay combination.

1. Sampling recommendations should apply to any oral fluid-based test.

2. Use fixed spatial allocation3. Works for either detection

(surveillance) or monitoring4. Approach compatible with

regional disease control projects.

CONCLUSIONS - Oral fluid surveillance

Improving our response to swine health challenges

M Rotolo, Y Sun, C Wang, LG Giménez-Lirola, R Main, J Zimmerman

jjzimm@iastate.edu

Thank you.Questions?