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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
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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
esne
, Pol
son,
Hol
ck, R
ober
ts.
2003
PRR
S Co
mpe
ndiu
m (2
nd e
ditio
n).
Dufr
esne
, Pol
son,
Hol
ck, R
ober
ts.
2003
PRR
S Co
mpe
ndiu
m (2
nd e
ditio
n).
"Groups with an initial prevalence of 8% took 5 weeks to reach 100% prevalence." Dr. John Roberts - analysis of field data
PR
RS
V R
T-P
CR
ora
l flu
id te
stin
g re
sults
by
barn
PR
RS
V R
T-P
CR
ora
l flu
id te
stin
g re
sults
by
barn
"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
Thank you.Questions?