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Social network analysis reveals the failure of between-farm movement restrictions to reduce Salmonella transmission

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Abstract

An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella (S.) Dublin, which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-year period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modelling approach. The analysis revealed similar network trends for non-infected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control programme. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre-and post-movement measures within a 1-month time-window may help reduce S. Dublin spread.
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Social network analysis reveals the failure of between-farm movement restrictions 1
to reduce Salmonella transmission 2
3
4
B. Conrady1,2*, E.H. Dervic2,3, P. Klimek2,3,4, L. Pedersen1,5, M. Merhi Reimert1, P. 5
Rasmussen1, O.O. Apenteng1, and L.R. Nielsen1 6
7
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ABSTRACT 18
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
2
INTRODUCTION 38
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
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MATERIAL AND METHODS 114
Data 115
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
5
Network analysis and association of S. Dublin infections with ca9le movements 157
and local transmissions 158
159
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
6
Modelling of S. Dublin spread on ca9le movement networks 199
!200
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
7
RESULTS 238
Movements, infections and production categories of Danish ca9le farms 239
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8
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
9
Association of S. Dublin infections with ca9le movements and local transmissions 306
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10
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
11
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
12
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h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
13
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1#7#14!*+!#)7-&*)(#)'%1!%)/!%)-(%1!(*7#(#)'!4$&#%/!(#39%)-4(4Z c9-4!4'H/.!/#(*)4'&%'#4!9*`!%)!509
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+*&(H1%'#!$*1-3-#4!%-(#/!%'!&#/H3-):!'9#!4$&#%/!*+!%!/-4#%4#!'9%'!'9&#%'#)4!9H(%)!%)/!%)-(%1!9#%1'9Z 511
c9-4!`*&D!-11H4'&%'#4!9*`!H4#+H1!-)4-:9'!-)'*!'9#!3*)'%3'!$%a#&)4!*+!3%a1#!$*$H1%'-*)4!3%)!E#!*E'%-)#/!512
h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
14
E.!3*(E-)-):!3%a1#!(*7#(#)'!%)/!$%'9*:#)!4H&7#-11%)3#!/%'%!`9-1#!3*)4-/#&-):!(*7#(#)'bE%4#/!%)/!513
1*3%1!'&%)4(-44-*)!$%'9`%.4Z!c9#!&#4H1'4!4H::#4'!'9%'5!-)!%//-'-*)!'*!&%)D-):!+%&(4!-)!'#&(4!*+!)#'`*&D!514
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+*3H4!*)!$&#b%)/!$*4'b(*7#(#)'!(#%4H&#4!`-'9-)!%!@b(*)'9!`-)/*`Z!c9H45!`#!4H::#4'!'9%'!3H&&#)'!516
4H&7#-11%)3#!%)/!3*)'&*1!(#%4H&#4!3*H1/!E#!%/%$'#/!'*!+*3H4!*)!&#/H3-):!'9#!&-4D!*+!(*7-):!-)+#3'#/!517
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$&#7%1#)3#! *+! -)+#3'#/! +%&(45! %)/! #-'9#&! (*&#! &#4'&-3'-7#! (*7#(#)'! &#4'&-3'-*)4! ^3H&&#)'1.! (%-)1.!519
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(-'-:%'-*)! (#%4H&#4! 4H39! %4! %)-(%1! *&! %)-(%1! :&*H$! '#4'-):! %)/S*&! hH%&%)'-)#! *+! (*7#/! %)-(%14!521
`-'9-)!%!@b(*)'9!`-)/*`!'*!9#1$! &#/H3#!'9#!(*7#(#)'b&#1%'#/!4$&#%/!*+! 2Z!"HE1-)!E#'`##)!+%&(4Z!522
c9#4#! %/%$'%'-*)4!'*! 3H&&#)'! $&*:&%((#4! `*H1/! 1-D#1.! 9#1$! '*! &#/H3#! '9#! (*7#(#)'b&#1%'#/!523
'&%)4(-44-*)!*+!S.!"HE1-)!E#'`##)!+%&(4Z!524
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CONCLUSIONS!527
c9#!4'&*):#4'!$&#/-3'-7#!+%3'*&!+*&!+%&(4!E#3*(-):!-)+#3'#/!`%4!'9#-&!3%a1#!(*7#(#)'!%3'-7-'-#4!528
-)!'9#!$&#7-*H4!(*)'95!`-'9!'`-3#!'9#!#d#3'!*+!1*3%1!'&%)4(-44-*)Z!c9#!4-(H1%'-*)!(*/#1!-)/-3%'#/!%)!529
#)/#(-3!SZ!"HE1-)!*33H&&#)3#5!`-'9!$#%D4!-)!*H'E&#%D!$&*E%E-1-'-#4!%)/!4-]#4!%&*H)/!*E4#&7#/!3%a1#!530
(*7#(#)'!%3'-7-'-#4Z! c9#&#+*&#5!`#!4H::#4'!'9%'! 3H&&#)'! 4H&7#-11%)3#!%)/!3*)'&*1!(#%4H&#4!3*H1/!E#!531
%/%$'#/!'*!+*3H4!*)!&#/H3-):!'9#!&-4D!*+!(*7-):!-)+#3'#/!3%a1#!E#'`##)!+%&(4!E.!-($1#(#)'-):!(*&#!532
+*3H4#/! `-'9-)b9#&/! 3*)'&*1! (#%4H&#4! '*! &#/H3#! '9#! $&#7%1#)3#! *+! -)+#3'#/! +%&(45! %)/! #-'9#&! (*&#!533
&#4'&-3'-7#! (*7#(#)'! &#4'&-3'-*)4! ^3H&&#)'1.! (%-)1.! &#1#7%)'! +*&! (H1'-b4-'#! EH4-)#44! 4'&H3'H&#4! %)/!534
'9#&#+*&#!/-s3H1'!'*!-($1#(#)'_5!$&#b(*7#(#)'!(-'-:%'-*)!(#%4H&#4!4H39!%4!%)-(%1!*&!%)-(%1!:&*H$!535
'#4'-):!%)/S*&!hH%&%)'-)#!*+!(*7#/!%)-(%14!`-'9-)!%!@b(*)'9!`-)/*`!'*!9#1$!&#/H3#!'9#!(*7#(#)'b536
&#1%'#/!4$&#%/!*+!2Z!"HE1-)!E#'`##)!+%&(4Z 537
538
539
h-ps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4674114
15
REFERENCES 540
541
01E#&'5!rZ5!GZ!I#*):5!%)/!0Zf!X%&%Eƒ4-Z!PBBBZ!Q&&*&!%)/!%a%3D!'*1#&%)3#!*+!3*($1#F!)#'`*&D4!!542
U%'H&#5!\BkZ!543
X%>%&/-5!RZ5!0Z!X%&&%'5!fZ!2%7-)-5!%)/!,Z!8*1-]]%Z!PB@PZ!l$'-(-]-):!4H&7#-11%)3#!+*&!1-7#4'*3D!/-4#%4#!!544
4$&#%/-):!'9&*H:9!%)-(%1!(*7#(#)'4Z!IZ!rZ!2*3Z!N)'#&+%3#Z!M5!P?@\P?PTZ!545
XQj!)*Z!@APL!PPS@PSPB@BZ!X#D#)/':<&#14#!*(!4%1(*)#11%!9*4!D7„:!(Z(Z!07%-1%E1#!%'W!!546
9a$4WSS```Z:**:1#Z3*(SH&1…4%v-†&3'v>†hv†#4&3v4†4*H&3#v`#E†3/v†7#/vB80N‡`A0I%93547
jQ`>‡ˆ%.jB'j00F600000G‡00000‡0:†H&1v9a$4iL0iPCiPC```Z&#'4-)+*&(%'-*548
)Z/DiPC%$-iPC$/+iPC@LTPM@†$4-:v0l7,%`@4c2-%]Q/@O\7l/(A‰7f-l†H4'v@kM@AATA?B549
\AB?\L†*$-v?MMA?\\M!^%33#44#/!*)W!@B!0H:H4'!PBPL_!550
X-:&%4bR*H1-)5!OZ5!jZ!X%&+*/5!2Z!O*&'#)4#)5!%)/!OZ!;&#-)#&Z!PBBAZ!r#1%'-*)49-$!*+!'&%/#!$%a#&)4!*+!'9#!!551
"%)-49!4`-)#!-)/H4'&.!%)-(%1!(*7#(#)'4!)#'`*&D!'*!$*'#)'-%1!/-4#%4#!4$&#%/Z!R&#7!,#'!O#/Z!552
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X•a)#&5!jZ5!IZ!j&-#'#&5!0Z!c&%H14#)5!%)/!NZ!c&%H14#)Z!PB@LZ!Qs3-#)'!N)'#&&H$'-*)!*+!N)+#3'-*)!89%-)4!E.!!555
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0
50
100
A B C D
Infection Category
Number of months
1000
2000
5000
10000
20000
2010 2015 2020
Time
Number of farms
Infection Category
A
B
C
D
A
0
50
100
Production Category
Number of months
500
1000
2000
5000
2010 2015 2020
Time
Number of farms
Production Category
Beef large
Beef small
Dairy
Heifer
Other large
Other small
Slaughter Calve Large
Slaughter Calve Small
B
Infection Category A Infection Category B
Infection Category C Infection Category D
Production Category Beef large
Beef small
Dairy
Heifer
Other large
Other small
Slaughter Calve Large
Slaughter Calve Small
0
5
10
15
20
25
2010 2015 2020
Date
Percentage
Bornholm
Zealand
Funen
Jutland South
Jutland SouthWest
Jutland CentralWest
Jutland Ost
Jutland Central
Himmerland
Jutland North
Total Denmark
AB
2010
2011
2012
45%
95%
48%
88%
Years
C
=Negative
=Positive
=Unknown
=Likely negative
A. Negative B. Positive
C. Unknown D. Likely negative
22
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Next month
Next two months
Next three months
Next four months
Next five months
Next six months
Local Movement Local Movement Local Movement Local Movement Local Movement Local Movement
1.00
1.25
1.50
1.75
2.00
Odds Ratio with 95% CI
Exposure to local or cattle movement transmissions
24
755
!756
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25
Supplementary information
Social network analysis reveals the failure of between-farm movement restrictions
to reduce Salmonella transmission
B. Conrady1,2*, E.H. Dervic2,3, P. Klimek2,3,4, L. Pedersen1,5, M. Merhi Reimert1, P.
Rasmussen1, O.O. Apenteng1, L.R. Nielsen1
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(updated in BEK
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+11!=.62#6%.%3!0&':#=2.&3!9&'!7'96@='62'&':!96:!3=91':!<>!(!3296:9&:!:'?#92#.6A!V#$6#E=96='!6#?'9%)!!nnn!0!o!UAUU(]!!nn!0!o!UAU(]!!n!0!o!UAUXA!
1!L6M6.56!p!K&.:%=2#.6!=92'$.&#'3!9&'!7#33#6$!8.&!09&2#=%19&!7.6243A!
41
C-:H&#!2@W!O%$!*+!S.!"HE1-)!9-:9!%)/!1*`!$&#7%1#)3#!%&#%4!-)!"#)(%&DZ!X#'`##)!E*'9!&#:-*)4!^9-:9!1
%)/!1*`_5!(*7#(#)'!&#4'&-3'-*)4!`#&#!-($1#(#)'#/!^&#+#&&#/!'*!%4!&#:-*)%1-4%'-*)_Z!c9#!(%$!49*`4!'9#!2
1%4'!4'%'H4!*+!'9#!&#:-*)%1-4%'-*)Z!!3
4
5
Areas with high prevalence
Areas with low prevalence
42
C-:H&#!2PW!89%):#4!*+!'9#!$&*/H3'-*)!4.4'#(!+*&!'9&##!&%)/*(1.!4#1#3'#/!9*1/-):4!%33*&/-):!'*!*s3-%1!
&#3*&/4!+&*(!'9#!"%)-49!9*1/-):!&#:-4'&.Z C*&!#F%($1#5!9*1/-):!P!39%):#/!-'4!$&*/H3'-*)!'.$#!+&*(!%!
/%-&.!$&*/H3#&!'*!%!41%H:9'#&9*H4#!%)/!'9#)!'*!%!(#/-3%1!+%3-1-'.5!%11!`-'9-)!*)#!.#%&Z!
!
Processing facilities
Tra de comp any
Hobby farm
Medical facilities
Meat, in general
Meat, Organic
Meat, young animals
Cooling facilities
Milk production
Milk, organic
Milk, young animals
Slautherhouse
20202010 2015 2010 2015 2020 2010 2015 2020
Yea r
Proportion of holding types
Farm 1 Farm 2 Farm 3
Processing facilities
Tra de com pa ny
Hobby farm
Medical facilities
Meat, in general
Meat, Organic
Meat, young animals
Cooling facilities
Milk production
Milk, organic
Milk, young animals
Slautherhouse
20202010 2015 2010 2015 2020 2010 2015 2020
Yea r
Proportion of holding types
Farm 1 Farm 2 Farm 3
Holding 1Holding 2Holding 3
43
C-:H&#!2LW!R&*$*&'-*)!*+!(*7#(#)'4!E#'`##)!/-d#&#)'!&#:-*)4!%)/!$&*7-)3#4!%)/!-)+#3'-*)!3%'#:*&-#4!1
*7#&!%!@Bb.#%&!$#&-*/!-)!"#)(%&DZ!^0_!O*7#(#)'4!E#'`##)!/-d#&#)'!&#:-*)4Z!^X_!O*7#(#)'4!E#'`##)!2
/-d#&#)'!$&*7-)3#4Z!^8_!O*7#(#)'4!*+!S. "HE1-)!b)#:%'-7#!+%&(4!%'!'9#!$&*7-)3#!1#7#1Z!^"_!O*7#(#)'4!3
*+!S. "HE1-)!b$*4-'-7#!+%&(4!%'!'9#!$&*7-)3#!1#7#1Z!c9#!3*1*&#/!1-)#4!-)!'9#!3-&31#!&#$&#4#)'!(*7#(#)'4!4
%44-:)#/!'*!4$#3-o3!&#:-*)4!*&!$&*7-)3#4!%)/!'9#!'9-3D)#44!*+!'9#!1-)#4!&#$&#4#)'4!'9#!$&*$*&'-*)!*+!'*'%1!5
(*7#(#)'4!%a&-EH'%E1#!'*!#%39!(*7#(#)'Z!U*'#!'9%'!'9#!*&-:-)!%)/!/#4'-)%'-*)!`#&#!`-'9-)!'9#!4%(#!6
&#:-*)!+*&!%!1%&:#!$&*$*&'-*)!*+!3%a1#!(*7#(#)'45!^mi!`-'9-)n_Z!c9#!$#&3#)'%:#!*+!'*'%1!(*7#(#)'4!7
%44-:)#/!'*!&#:-*)4!*&!$&*7-)3#4!-4!49*`)!-)!'9#!4hH%&#!E&%3D#'4!%1*):!'9#!*H'#&!&-):Z!C*&!#F%($1#5!^0_!8
49*`4!'9%'! TTi!*+! '9#!'*'%1! 3%a1#! (*7#(#)'4! *&-:-)%'#/!+&*(! 2*H'9#&)!"#)(%&D5! `9-1#!P\i! `#&#!9
`-'9-)!'9#!4%(#!&#:-*)!%)/!@Ai!`#&#!+&*(!2*H'9#&)!"#)(%&D!'*!8#)'&%1!IH'1%)/Z!10
11
12
The capital
Central Jutland
Northern Jutland
Zealand
Southern Denmark
Bornholm
City Copenhagen
Funen
Copenhagen area
Northern Jutland
North Zealand
Eastern Jutland
East Zealand
South Jutland
West and South Zealand
West Jutland
Bornholm
City Copenhagen
Funen
Copenhagen area
Northern Jutland
North Zealand
Eastern Jutland
East Zealand
South Jutland
West and South Zealand
West Jutland
Bornholm
City Copenhagen
Funen
Copenhagen area
Northern Jutland
North Zealand
Eastern Jutland
East Zealand
South Jutland
West and South Zealand
West Jutland
AB
CD
24% within
1.7% within
14% within
17% within
17
Central Jutland [23]
Northern Jutland [17]
Zealand [4]
Southern Denmark [55]
North Zealand [0.4]
Eastern Jutland [5.3]
Northern Jutland [16.7]
East Zealand [0.1]
South Jutland [48]
West and South Zealand [4]
West Jutland [18]
Copenhagen [0.1]
Funen [6.9]
Bornholm [0.5]
The captial [1]
14% within
16% within
9% within
8.7
North Zealand [0.4%]
North Zealand [0.1]
Eastern Jutland [3.7]
Northern Jutland [16.3]
East Zealand [0.1]
South Jutland [54.5]
West and South Zealand [2.5]
West Jutland [17]
Copenhagen [0.1]
Funen [5.3]
Bornholm [0.4]
17% within
14% within
17% within
9.9
7.2
5.8
North Zealand [0.6]
Eastern Jutland [6.8]
Northern Jutland [16.7]
East Zealand [0.2]
South Jutland [42.4]
West and South Zealand [5.6]
West Jutland [18.6]
Copenhagen [0.1]
Funen [8.3]
Bornholm [0.7]
4.1
5.1
7.6
9.6% within
14.5% within
14% within
2.3
2.9% within
3.8
5.6
2.8% within
1.8% within
7.3
4.7
1.2% within
1.5% within
0.8% within
4
6
6
3.8
3.5
5
6.7
4.9
2.2
2.2% within
2.1% within
44
C-:H&#!2\W!^0_!O%$!*+!3%a1#!+%&(!1*3%'-*)4!-)!"#)(%&D!-)!I%)H%&.!PB@B!%)/!I%)H%&.!PBPBZ!^X_!O%$!*+!
^43&%(E1#/_!3%a1#!+%&(4!^)*/#4_!*)1.!`-'9!3%a1#!(*7#(#)'!&#3*&/4!-)!I%)H%&.!PB@B!%)/!I%)H%&.!PBPBZ!
f-)D4!E#'`##)!)*/#4!&#$&#4#)'!'9#!'&%/#!(*7#(#)'4!%)/!'9#-&!'9-3D)#44!&#$&#4#)'4!'9#!)H(E#&!*+!3%a1#!
'&%/#/!-)!I%)H%&.!4'&%'-o#/!+*&!'9#!.#%&!PB@B!%)/!PBPBZ!8*1*H&4!&#$&#4#)'!-)+#3'-*)!3%'#:*&-#4!%)/!'9#!
4-]#!*+!%!$*-)'!&#$&#4#)'4!'9#!9#&/!4-]#Z!!
Size
0
500
1000
1500
2000
Infection Category
A
B
C
D
012010
Size
0
1000
2000
3000
Infection Category
A
B
C
D
012020
Size
0
500
1000
1500
2000
Infection Category
A
B
C
D
012010
Size
0
1000
2000
3000
Infection Category
A
B
C
D
012020
Size
0
500
1000
1500
2000
Infection Category
A
B
C
D
012010
Size
0
1000
2000
3000
Infection Category
A
B
C
D
012020
Size
0
500
1000
1500
2000
Infection Category
A
B
C
D
012010
Size
0
1000
2000
3000
Infection Category
A
B
C
D
012020
A
B
Size
0
500
1000
1500
2000
Infection Category
A
B
C
D
012010
Size
0
1000
2000
3000
Infection Category
A
B
C
D
012020
01-2010 01-2020
01-2010 01-2020 Negative
Positive
Unknown
Unlikely negative
45
C-:H&#!2TW!0$$%&#)'!$&#7%1#)3#!*+!S.!"HE1-)!-)!/%-&.!+%&(4!*7#&!'9#!@Bb.#%&!$#&-*/5!4'&%'-o#/!E.!"%)-49!
&#:-*)4!%)/!%::&#:%'#/!%'!'9#!)%'-*)%1!1#7#1Z!
0
5
10
15
20
25
2010 2015 2020
Date
Percentage
Bornholm
Zealand
Funen
Jutland South
Jutland SouthWest
Jutland CentralWest
Jutland Ost
Jutland Central
Himmerland
Jutland North
Total Denmark
46
C-:H&#!2kW!U#'`*&D!$&*$#&'-#4!*+!)*)b-)+#3'#/!+%&(4!%)/!S. "HE1-)!-)+#3'#/!+%&(4!'*:#'9#&W!^0_!c*'%1!1
)H(E#&!*+!+%&(4!'9%'!%&#!'&%/-):Z!^X_!07#&%:#!/#:&##Z!^8_!07#&%:#!$%'9!1#):'9Z!^"_!X#'`##))#44Z!^Q_!2
"#)4-'.Z!^C_!O*/H1%&-'.Z!^;_!8*($*)#)'Z!^G_!81*4#)#44Z!3
!4
5
4000
5000
6000
7000
2010 2015 2020
Time
Number of farms
in the network
A
3.2
3.4
3.6
3.8
4.0
2010 2015 2020
Time
Degree
B
6
7
8
2010 2015 2020
Time
Average
path length
C
3000
4000
5000
6000
2010 2015 2020
Time
Betweenness
D
0.00025
0.00030
0.00035
0.00040
0.00045
0.00050
2010 2015 2020
Time
Density
E
0.675
0.700
0.725
0.750
0.775
2010 2015 2020
Time
Modularity
F
1000
1500
2000
2010 2015 2020
Time
Component
component_weak component_strong
G
0.25
0.30
0.35
0.40
2010 2015 2020
Time
Closeness
closeness closeness_in closeness_out
H
47
C-:H&#!2AW!"#:&##!/-4'&-EH'-*)4!*+!'9#!"%)-49!3%a1#!'&%/#!)#'`*&D!+*&!'9#!.#%&!PBPB!%3&*44!4#1#3'!(*)'94!6
&#$&#4#)'#/!*)!%!1*:b1*:!43%1#W!^0_!I%)H%&.5!^X_!C#E&H%&.!%)/!^8_!O%&39Z!011!*'9#&!(*)'94!%)/!.#%&4!7
+&*(!PB@B!'*!PBPB!%&#!%7%-1%E1#!H$*)!&#hH#4'Z!c9#!/#:&##!/-4'&-EH'-*)!`%4!oa#/!E.!%!$*`#&!1%`!H4-):!8
%!(%F-(H(!1-D#1-9**/!%$$&*%39Z!C*&!#%39!(*)'95!'9#!#F$*)#)'!*+!'9#!oa#/!$*`#&!1%`!/-4'&-EH'-*)5!9
(-)-(H(! 7%1H#! +&*(! `9-39! '9#! $*`#&! 1%`! /-4'&-EH'-*)! `%4! oa#/5! 1*:b1-D#1-9**/! *+! '9#! oa#/!10
$%&%(#'#&45!j*1(*:*&*7b2(-&)*7!'#4'!4'%'-4'-35!'9#!oa#/!/-4'&-EH'-*)!`-'9!'9#!-)$H'!7#3'*&5!%)/!'9#!$b11
7%1H#!*+!'9#!j*1(*:*&*7b2(-&)*7b'#4'!%&#!3%13H1%'#/!%)/!49*`)!E#1*`!#%39!$1*'Z!c9#!#F$*)#)'4!*+!'9#!12
oa#/!$*`#&!1%`!/-4'&-EH'-*)4!`#&#!7#&.!4-(-1%&!%3&*44!(*)'94!%)/!.#%&4!%)/!&%):#/!E#'`##)!@ZMbLZLZ!!13
!14
15
16
17
18
A)
B)
C)
48
C-:H&#!2?W! c9#!*//4! &%'-*!*+! SZ!"HE1-)! -)+#3'-*)! /H#!'*! 1*3%1! ^&%/-H4!*+! T! D(_!%)/! 3%a1#!(*7#(#)'!19
'&%)4(-44-*)45!%3&*44!(*)'94!*)#!'9&*H:9!4-F!E%4#/!*)!/%'%!*+!$&#7-*H4!^0_!Pb(*)'945!^X_!Lb(*)'94!20
%)/!^8_!\b(*)'94Z!0/>H4'#/!+*&!+%&(!4-]#5!3%a1#!(*7#(#)'!(*)'95!$&*/H3'-*)!3%'#:*&.!*+!+%&(4!%)/!21
'*'%1!)#-:9E*H&9**/!^'*'%1!)H(E#&!*+!+%&(4!-)!%!&%/-H4!*+!T!D(!%&*H)/!'9#!-)+#3'#/!+%&(_Z!U*'#!'9%'!22
1*3%1! '&%)4(-44-*)4! -)31H/#/! %11! $&#(-4#4! ^-Z#Z5! -)31H/-):! +%&(4! `-'9*H'! 3%a1#! (*7#(#)'4! '*! *'9#&!23
$&#(-4#4_Z!24
!25
26
Next month
Next two months
Next three months
Next four months
Next five months
Next six months
Local Movement Local Movement Local Movement Local Movement Local Movement Local Movement
1.00
1.25
1.50
1.75
2.00
Odds Ratio with 95% CI
a)
Next month
Next two months
Next three months
Next four months
Next five months
Next six months
Local Trading Local Trading Local Trading Local Trading Local Trading Local Trading
1.2
1.5
1.8
2.1
Exposure to local and trading transmission
Odds Ratio with 95% CI *
Salmonella Dublin Infection in
* Adjusted for farm size, month, production category, and total neighborhood ( number of farms in the range of 5km)
Odds Ratio with 95% CI
b)
Local Movement Local Movement Local Movement Local Movement Local Movement Local Movement
Next month
Next two months
Next three months
Next four months
Next five months
Next six months
Local Trading Local Trading Local Trading Local Trading Local Trading Local Trading
1.2
1.5
1.8
2.1
Exposure to local and trading transmission
Odds Ratio with 95% CI *
Salmonella Dublin Infection in
Odds Ratio with 95% CI
Local Movement Local Movement Local Movement Local Movement Local Movement Local Movement
c)
Exposure to local or cattle movement transmissions
ResearchGate has not been able to resolve any citations for this publication.
ResearchGate has not been able to resolve any references for this publication.