SWAP algorithm validation

SWAPAlgorithmVerificationTestoutbreaklibrary1/7/2016LosAlamosNationalLaboratoryDataDreamers

1

TableofContents

OBJECTIVE 2

EXAMPLESOFTESTOUTBREAKDATAINPUTANDEVALUATIONOFRESULTS 2

TESTOUTBREAKS-DETAILSANDRECOMMENDEDCUTOFFPERCENTAGE 1. Chikungunya 62. Cholera 73. Dengue 84. Ebola 95. FootandmouthDisease 106. Gastroenteritis 11-127. Influenza 138. Leptospirosis 149. Malaria 1510. Measles 1611. Meningococcaldisease 1712. Plague 1813. Q-fever 1914. Tularemia 2015. WestNilevirus 21

2

ObjectiveTheSWAPwebappusesanalgorithmtoassignpercentagesimilarity/matchscores

foruserinputandahistoricaloutbreakfromtheSWAPlibrary.Thisalgorithmrequiresdiseasespecificpropertiesandspecificweightsassociatedwitheachproperty.Outbreaksthatarenotincludedinthelibrarycanbeusedtotestthepropertiesandweightsofadiseasespecificalgorithm.WecollectedinformationfortestoutbreaksanduseditasinputfortheSWAPtoevaluateSWAPoutput.Theexpectedresultforthetestwasthatthetop1-5matchinghistoricaloutbreakswouldhavecasecountsanddurationsthatreflectthescenariointhetestoutbreak.

Wealsoevaluatedalowerlimitorthresholdmatchvalueforeachdiseaseforarelevantmatch.Therelevantmatchcutoffindicatesthepercentagematchbelowwhichthesimilaritiestohistoricoutbreakswerefoundtobe“notrelevant”.However,thisdoesnotmeanallmatchesaboveagivenpercentagewillberelevanttotheuserinputscenario.Forexample,ifthediseasehasacutoffthresholdof70%andthetop5SWAPcontains84-64%matchscore.Theresultsinterpretationmaybeasfollows:outbreakswithscoresbelow70%canbeignored.Afterevaluatinghistoricoutbreaksabove70%,itmaybedeterminedonlytop1andtop2arereasonablematches.Thethirdmatchdespiteamatchscoreof>70%maynotbearelevantmatchduetoimprobablyhighcasenumberand/orduration.Thediseasespecifictablescontainourreasoningfornon-matchingscenarios.Thenotessessionofthetablesarefreetext.

ThisdocumentcontainsuserinputinformationfortestoutbreaksusedforalloftheSWAPdiseases,thesimilarity/matchscorerangeforthetop5matches(inpercentage),thenumberofexpertdeterminedacceptablematchesintop5andthereasoning(notes).Aweblinktothetestoutbreakdatasourceisalsoprovided.

3

Examplesoftestoutbreakdatainputandevaluationofresults Figure1providesanexampleofuserinputquestionsfortheSWAPEbolaalgorithmandthetestoutbreakdetailsaregivenbelow.AsshownbelowtheinformationprovidedinthetablecanbeappliedbyaSWAPusertoreproducetheSWAPoutputLANLanalystsobtained.

SWAPoutputcanthenbecomparedtodatafromatestscenarioiftheinformationisavailable(Figure2).Inthecomparisongivenbelowthe2015EbolaoutbreakinSierraLeoneisexpectedtohave30-60casesandduration8-10weeks.Thetopmatch(74%)isthe1979Sudanoutbreakwith35casesanddurationoftwomonths.Thenexttwooutbreakshaveveryhighcasenumberscomparedto2015scenario.Thistypeofdataallowedatustodeterminealowerlimitforarelevantsimilarityscoreforeachdisease.

4

Table1containsacomparisonofpropertiesoftheBostonChipotleoutbreakcausedbynorovirusinlate2015andtopmatchingSWAPhistoricaloutbreaks.TheSWAPevaluationswereconductedduringday3,day5andday7ofthisunfoldingoutbreakandrangeofsimilarityscoresforthisscenariorangedfrom92-75%.Thedatashowsthatcasecountanddurationforthisoutbreakandthetopmatchinghistoricaloutbreaksareverysimilar.TheseresultsindicatethatSWAPevaluationscanbeperformedassoonassomeinformationoncasecount,timeandpropertiesareavailable.Informationobtainedcanthenbeusedtoenhanceandacceleratetheoutbreakinvestigation. Case

countTimeframe

Sourceofcontamination

Productorsiteevent

season

BostonChipotle

~150 ~10days Notknown Site/event winter

China2010 427 10days Water(norovirusdetectedfromterminalpointofwaterdeliverysystem

Site(highlylocalized)

winter

Israel1999 164 5days Saladvegetablesservedatamess

Site(occurredin

winter

5

hall+secondaryperson-to-person

amilitarybase)

USATexas1998

125 10days Cookedfoodpreparedbyanillpersonand+sodafountainarea

Site(occurredinmilitarybase)

autumn

Netherlands2009

130 12days water Site(studentsatarecreationalfountain)

summer

Table1:ComparisonofpropertiesforBostonchipotleoutbreaksandtopmatchingSWAPoutbreaks.Alltheoutbreakswerecausedbynorovirus.ThefollowingtablescontaindatausedfromtestoutbreaksforeachdiseaseintheSWAP.ASWAPusercanusethesetablestoruntheSWAP.

6

Disease–Chikungunya

Montpellier,France2014

Guangdong,China2010

Brazil,2015 Florida,USAasofMay5,2015

FrenchPolynesia,2015

Location Montpellier,France

Guangdong,China

Brazil Florida,USA

FrenchPolynesia

Diseasestatus

Non-endemic Non-endemic Non-endemic Non-endemic

Non-endemic

PopulationatRisk

30,000-300,000

79million 200million 20million 300,000

Populationsusceptibility

Naive Naive Naive Naive Notnaive

Humandevelopmentindex

>0.8 0.719 0.744 0.914 Lessthan0.8

Outbreaktiming

Notsummer Notsummer Summer Notsummer

Summer

Casenumber 8 20 114confirmed6000suspected

21 70,000cases

Durationinformation

2015-07-01to2015-07-26

2015-07-01to2015-07-15

20-25weektimeline

5months 6months

link http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=21108

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3309566/

Pleasesearchthetitle.Itdownloadsapdffile.NumberofReportedCasesofChikungunyaFeverintheAmericas,byCountryorTerritory2015(toweeknoted)EpidemiologicalWeek/EW29(Updatedasof24July2015)

http://www.cdc.gov/chikungunya/pdfs/2015Table1-050515.pdf

http://www.radionz.co.nz/international/pacific-news/269097/french-polynesia-chikungunya-outbreak-over

Rangefortop5

87-69% 98-64% 75-61% 92-63% 67-51%

7

matches

Numberofexpertacceptablematchesintop5

Top4Toponeisaverygoodmatch.

Top3 Top4 Top2 The1stoneand4thone.Reasonfortop1&4beingbettermatch-locationcharacteristichavehighermatchtotestscenario

Notes Cutoffat70% Cutoffat70%

Recommendedlowerlimitforarelevantmatch–70%

8

Disease–Cholera Nigeria2015 Myanmar2014 Malawi

09/10PNG09-10 Haiti2015

location Bayelsa,Nigeria Myanmar,southOkkalapatownship

Malawi PapuaNewGuinea

Haiti

DiseaseStatus

Endemic endemic endemic Non-endemic

endemic

Populationatrisk

1million 200,000 16million 7million 10million

Casenumber 23 234/380testedpositive

250 250 4000

Durationinformation

December24–January28

September27–October8

1months 3months 1month(beginningoftheoutbreak)

link http://allafrica.com/stories/201501281403.html

http://www.mmtimes.com/index.php/national-news/11951-hundreds-infected-in-cholera-outbreak.html

http://www.who.int/cholera/countries/MalawiCountryProfile2010.pdf?ua

=1

http://www.who.int/cholera/countries/PapuaNewGuineaCountryProfile2010.pdf?ua=1

http://www.haitilibre.com/en/news-13483-haiti-cholera-20-communes-on-red-alert.html

Rangefortop5matches

94-78 90-64 83-77% 71-68% 72-67%


Top5 Top2 Top4Lastone

casecountabittoohigh

Top2 Top3

Notes Onlybeginningofoutbreakinfois

Cutoffvalue75% Cutoff70%

Cutoff70%

9

available

http://www.who.int/cholera/countries/en/

Recommendedcutoffmatch–70%

10

Disease–Dengue Singapore2015 TamilNadu,

India2015Cambodia2015 Belize2015 Brazil2014

Location Singapore TN,India Cambodia Belize Brazil

Maxpptn 11in 1 5.9 4 4

Casenumber

1463,99in7thweek 95 2688 110 200,000

Durationinformation

7weeks 1month 6months 16weeks

15weeks

link https://www.moh.gov.sg/content/dam/moh_web/Statistics/Infectious_Diseases_Bulletin/2015/February/2015_week_07.pdf

http://www.todayonline.com/singapore/53-year-old-woman-first-dengue-death-spore-year

http://zeenews.india.com/news/health/health-news/9-die-of-dengue-in-tirunelveli-zone-this-month_1537402.html

http://www.khmertimeskh.com/news/13682/cambodia-reports-sharp-rise-in-dengue-fever-cases-in-1st-half-of-2015/

http://www.paho.org/hq/index.php?option=com_topics&view=article&id=1&Itemid=40734

(clickon2015)

http://portalsaude.saude.gov.br/images/pdf/2014/maio/29/BE-2014-45--4--semana-15.pdf

Rangefortop5matches

98-78% 66-44% 84-61% 71-40% 66-48%


Top4Lastonecumulativecasecountistoohigh.

None Top3Last2cumulativecasecounttoohigh.

Top1 None.Thisisasecondyearhighratescenario

Notes Possiblecutoffat80%

ThereisfloodinginTNcurrently,anunusual

Possiblecutoffat70%

Possiblecutoffat70%

11

situation.

Changingrainfallchangesmatchesabit

Recommendedcutoffmatch–70%

12

DiseaseEbola Guinea2015 Liberia2015 SierraLeone

2015Guinea2015

Location Guinea Monrovia,Liberia SierraLeone Guinea

Populationatrisk 12million 400,000 6million 12million

Physiciandensity 0.1 0.014 .022 0.1

HistoryofEbola yes yes yes yes

Contactwithbushmeatorbats

no No no no

Casenumberanddurationinformation

5oneday,27cumulative(timeperiodnotgiven

Tried5inonedayand27in2weeksand1month

6caseintwomonths,threecaseinpastweek

12in1weekand45in1month(answersonthewebsite

13in1week

47inonemonth(extendeddataisavailableonthelink)

link http://www.reuters.com/article/2015/05/15/us-health-ebola-guinea-idUSKBN0O01M220150515

http://www.usatoday.com/story/news/world/2015/07/15/ebola-liberia-epidemic-sierra-leone-guinea/30183429/

http://apps.who.int/ebola/current-situation/ebola-situation-report-5-august-2015



Rangefortop5matches

69-62%for1dayand2weeks,79-67%for1months

79-66% 73-58% 1week72-59%

1month–72-67%


Top1 Possibly4(2ndoneisnotcorrect)

Top1Otherscumulativecasecounttoohigh.

13in1week–Top1

47in1month–Onlyonefromthetop5.BothscenariosmatchtoSudan1979.

13

Cumulativecasecounttoohighfornon-matchingoutbreaks

Notes Thisisacountrythatisrecoveringfromepidemic.

Postoutbreakrecoveryperiod

possiblecutoffat70%

Iamnotsureaboutamatchcutoff.

14

DiseaseFMD Jinning

township,Kinmencounty,China2015

Bahrain2015 Israel2013

Botswana2015

Location Jinningtownship,Kinmencounty,China

Bahrain Israel Botswana

Animalidentifier

cattle cattle cattle cattle

Cattledensity High(176) Low(Ithink) low high

Swinedensity low low low low

Infectedpremises

1case176susceptible

13 1(1village)

1

Durationinformation

1monthApril13–May1

Feb23toMarch16

1week 26/07/2015-31/07/2015

links http://www.oie.int/wahis_2/public/wahid.php/Reviewreport/Review?pop=1&reportid=17682

http://www.gulf-daily-news.com/NewsDetails.aspx?storyid=398212

http://www.oie.int/wahis_2/public/wahid.php/Reviewreport/Review?page_refer=MapFullEventReport&reportid=14420

http://www.oie.int/wahis_2/public/wahid.php/Reviewreport/Review?page_refer=MapFullEventReport&reportid=18268

Rangefortop5matches

77-65% 92-67% 96-75% 96-71%

Numberofreasonablematchesintop

Top5 Top5 Top5 Top5

15

5

Notes

Acceptabletohavea70%matchcutoff.

16

Diseasefamily_Gastroenteritis

pathogen E.coli E.coli Salmonella Salmonella norovirus Salmonella

Location USA2014 USA2013 UK2014 UK

Sourceofcontamination

Rawclover Cookedfood eggs WatermelonfromBrazil

Frozenstrawberries

Persontoperson

Productorsite/event

product product product product product Site/event

season Spring winter summer December Autumn Autumn

military No No No No

Casenumber 19forall(10fortillMay10th

11,35total 55 22 40(300in10days)

14

Durationinformation

April29–May20

Dec30–Jan30(lastcaseApril10

May21-June30

Oct30-Nov30th

3days 1week

link http://www.cdc.gov/ecoli/2014/O121-05-14/index.html

http://www.cdc.gov/ecoli/2013/O121-03-13/index.html

http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=21098



http://www.clickondetroit.com/news/14-patients-diagnosed-with-salmonella-at-henry-ford-hospital/35566506

Rangefortop5matches

96-78% 97-78% 92-72% 86-77% 77-73%for3day

79-68%for10day

98-83%

Numberofexpertacceptable

Top4.Lastonecasecounttoo

4matches.Oneand4onthemark.Lastone

All5 All5 All5ifusing10

Possibly4,thoughnotthe

17

matchesintop5

high. toohighcasecount

daysvalue top1match

Notes IdentifiedE.coliaspathogen.Possiblecutoffat80%

IdentifiedpathogenasE.coli.Possiblecutoffat80%

PathogenidentifiedasSalmonella

Pathogen–SalmonellaorE.coli

PathogennarrowedtoE.coliornorovirusbutneeded10daydata

PathogenidentifiedwronglyasNorovirusorShigella.Wedon’thavehospitalassourceatthemoment

70-80%matchrequiredforpathogenidentification

Applyingthistoreallifesituation-BostonChipotleoutbreak

80overtheweekend(Dec5-7)

100casesbyWednesday(Dec9th)

141casesbyFriday(Dec11)

StooltestsforNorovirusandE.coliwereinprogressonDecember8

th

morning.EarlylabtestsreportedpresenceofnorovirusonWednesdayDecember9

th.On

December11thlabresults

confirmedtheabsenceofotherbacterialpathogen(Bostonpublichealthcommission).

Note: NorovirusChina2010,Netherlands-2009andcampylobacteriosisoutbreakswerecausedbywaterbasedcontamination.

18

Disease-influenzaID Argentina

2009NewZealand2009

Cambodia2013

Zhejiang,China2013

UnitedStates2011

Location Argentina NewZealand Cambodia Zhejiang,China

UnitedStates

Strain H1N1 H1N1 H5N1 H7N9 H3N2v

Persontoperson

Yes Yes no Yes no

Casenumber 7,173confirmed(811,940Influenza-likecases)

3086confirmed

26 40 12

Durationinformation

May16–August232009

April28–August212009

February1–Dec102013

March9–April172013

August17–December232011

link http://www.flu.gov/pandemic/global/final.pdf

http://www.flu.gov/pandemic/global/final.pdf

http://www.who.int/influenza/human_animal_interface/H5N1_cumulative_table_archives/en/

http://www.who.int/influenza/human_animal_interface/influenza_h7n9/ChinaH7N9JointMissionReport2013u.pdf?ua=1

http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6051a4.htm

Rangefortop5matches

75-68% 83-71% 100-81% 80-71% 80-77%


Top4 Top5 Top5 Top5 Top5

Notes TheyareallH1N1

Allmatchestonovelinfluenza



19

Note:weonlyhave5seasonalinfluenza

Cutoffmatchof70%isreasonable.

Disease–Leptospirosis Maharashtra,

India2015Florida,USA2005

Manila,Philippines2009

Karnataka,India2011

Location Maharashtra Florida Manila Karnataka

HDI medium Veryhigh medium medium

Contactwithwater

Heavyrainfall swimming

rain yes

Floodingorpopulationdisplacement

yes no

yes no

Casenumber 130 44in1month

12in3weeks

300 100(estimatedpeak)totalcasesin2weeks286

Durationinformation

Startofmonsoon(June)tomid-September

1OctobertoNov19 4days

link http://www.dnaindia.com/mumbai/report-19-die-due-to-leptospirosis-this-year-2125261

http://cid.oxfordjournals.org/content/50/6/843.full.pdf+html

http://reliefweb.int/sites/reliefweb.int/files/resources/D87F541373D245BC4925767A000C5761-Full_Report.pdf

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC33

http://www.scopus.com/record/display.url?eid=2-s2.0-84930817082&origin=inward&txGid=8F21F1C0A98CEB873852A4C8F44CD289.aqHV

20

10081/

0EoE4xlIF3hgVWgA%3a1

Rangefortop5matches

67-57% 73-66% 88-66% 73-69%


Top3. Top3 Top4Oneofthe66%isOK,butotherisnotduetohighcasenumber.

Top3.

Notes Cutoff65% cutoffat70%

Cutoffat70%


21

Disease–Malaria PuertoRicoUSA

2015Venezuela2014

Madagascar2015

Goa,India2015

location PuertoRico,USA Venezuela201

Madagascar Goa

Populationatrisk 4million 31million 24million 1.8million

Casesperthousand

Lessthan1 Morethan1 Morethan1 Lessthan1

Casenumber 3 1000(week44hasanswers)

200,000 650

Durationinformation

Onemonth Week1of2014

5months 4months

link http://promedmail.org/direct.php?id=20150720.3524406

http://www.mpps.gob.ve/index.php?option=com_phocadownload&view=category&id=43:ano2014&Itemid=915

http://www.lexpressmada.com/blog/actualites/paludisme-le-bilan-salourdit-36369/

http://timesofindia.indiatimes.com/city/goa/Mapusa-witnessing-an-increase-in-malaria-cases/articleshow/47650415.cms

Rangefortop5matches

80-76% 61-53% 75-42% 75-66%


1sttwo80&78%matcheshavecasecountin10s.Nextthreehascasecountin100s.All5matchesarereasonable.

All5havethepotentialtobecorrect.1sttwoare60Klastthree600Krange

1sttwocutoffat50%

All5seemsreasonable

Notes Bothsetsofscenariosarereasonableoutcomesbasedoncontrolmeasures

Thisisverybadoutbreakwithprobablycumulative

22

implemented case100-200K

Thematchesforthesetestoutbreaksareoverallalittlelow.Thelibraryistooinclusive,sogettingtestoutbreakswasdifficult.

23

Disease–MeaslesID Denmark2013 Denmark2014 Bosniaand

Herzegovina2014-2015

Congo2015

Populationatrisk

5.6million 5.6million 3.8million 71million,Kataga5million

Countryimmunization%

90 90 89 77

Affectedregion%

90 90 89 77(kataga51%)

Casenumber 9 18 106 20,000

Durationinformation

5weeks 8weeks 5weeks 6months




http://www.msf.org/article/drc-katanga-measles-epidemic-keeps-worsening

Rangefortop5matches

95-85% 88-79% 94-81% 85-66%


Top1.Casenumbersabittoohighfor3outof5.

Top1.4outof5outbreakssamebutslightlydifferentorderforDenmark2013and2014tests

Top5#1isaverygoodmatchforcasecountaswellastime

Top4

Notes Cutoffat70%

24


25

Disease-MeningococcalID UK2000 Sudan2006 Nigeria2015 USA2013-14 Niger2015

Location UnitedKingdom

Sudan Nigeria PrincetonUniversity,US

Niger

Diseasestatus Non-endemic Non-endemic Endemic Non-endemic Endemic

strain WandA A C B C

Fatality 18.2% 6.9% 7.7% 11.1% 6.9%

Casenumber 22 231 652 9 5855

Durationinformation

March21–April112000

September1-November82006

January26–March52015

March2013–March2014

January1–May102015

link http://www.who.int/csr/don/2000_04_11/en/;http://www.who.int/csr/don/2000_04_21b/en/

http://www.who.int/csr/don/2006_11_21/en/

http://www.who.int/csr/don/13-march-2015-nigeria/en/

http://www.nfid.org/idinfo/meningitis/meningococcal-b-college-outbreaks.html

http://www.who.int/mediacentre/news/situation-assessments/meningitis-niger/en/

Rangefortop5matches

79-41% 71-64% 71-64% 69-31% 74-60%


Top2 Top5 Top2 Top2 4and5seemtobebestmatchforcasecountandtime

Notes Cutoffat70% Cutoffat60% Lowerscoreduetostrainnotmatching.


26

Disease–PlagueID USA2015 Madagascar2015 Zambia2015

location SantaFe Madagascar Zambia

Mortality 25%,low high low

Plaguetype

septicemic pneumonic bubonic

season fall Rainyseason AprilinZambia,Rainyseason

Casenumber

2inSantaFe,4inNM

14cases,10death 13cases,3deaths

Durationinformation

3monthsor1month

17Aug-27Aug 3monthsor1month

link http://nmhealth.org/news/disease/2015/9/?view=313

http://who.int/csr/don/06-september-2015-plague/en/

http://outbreaknewstoday.com/plague-outbreak-kills-three-in-zambia-24623/

Rangefortop5matches

SantaFe-50-44%

NMscore63-51%

87-52% 81-53%


None Top3&5thThefourthmatchisverydifferentintermsofcasecountandtimefromother4.

Threemonthslooksbettermatches

Notes Possiblecutoffat65-70%

27

Cutoffmatchof65-70%isreasonable.

28

DiseaseQ-feverID USA2011 UK,

Scotland2006

Baranya,Hungary2013

Bavaria,Germany2014

Location USA(WA,MT) UK,Scotland Baranya,Hungary Bavaria,Germany

Pop.atrisk ~100,000 300(meatplant)

396,633 12.6million

Farm/herdproximity

<5km NO(questionable)

<5km 5km-20km

season summer summer Summer Spring

Casenumber

11 24 70 12

Durationinformation

June-July 1month April–July2013 Jan–April2014

link http://www.capitalpress.com/content/mw-Q-fever-070111

http://www.documents.hps.scot.nhs.uk/ewr/pdf2006/0629.pdf


http://promedmail.org/direct.php?id=20140511.2464862

Rangefortop5matches

75-62% 92-64% 82-63% 88-51%


Top2.Casecountseemstoohighforall,buttimeisgoodmatchfortop2.

Top5 Top1matchesbothcasecountandtimeframe.Others–eithercasecountortimedoesn’tmatch.Historicepidemicpredictsshorterduration.

Top3

29

Notes 70%cutoffmostlikelyfitsbest.Morecasesareexpected


30

Disease-Tularemia USA2015 USA2015 Spain2014 Russia2014

Location SouthDakota,US

Colorado,US Spain Russia

Season summer summer summer Latesummer

Endemicityandruralvs.urban

Endemic,rural Endemic,rural Endemic,rural Endemic,rural

Type Ulceroglandularandrespiratory

Casenumber

7 16 12 7

Durationinformation

June-July2015 June2015 August2014(1month)1

Sept.2014

link http://outbreaknewstoday.com/tularemia-sickens-7-in-south-dakota-since-june-30075/

http://outbreaknewstoday.com/colorado-tularemia-5-cases-reported-in-weld-county-89951/

http://promedmail.org/direct.php?id=20140815.2684689

http://outbreaknewstoday.com/tularemia-outbreak-reported-in-russia-34925/

Rangefortop5matches

82-63% 75-66% 90-69% 76-63%


Top2 Top2 Top1Thefirstonelooksverygood.Othersseemtofalltotwocategorieswithloworhighercasecount.Bothmightbepossible

Notsure.Casecountsagainfallintotwocategories

Notes 70%cutoff Cutoff70%

31

Itriedtocharacterizetularemiatypebasedonmatches,butthelibraryistoolimitedtoachievethis.70%cutoffseemreasonableinsometestscenarios.Othersitistoodifficulttodetermine.

32

Disease–WestNilevirus Greece2012 USA2014 NewMexico

2015Ontario2014

Location Greece LosAngeles,CA,USA

NewMexico Ontario

Outbreaktiming

Nottailend Tailend Tailend Tailend

Ruralorurban urban urban rural rural

Climate,precipitation,temperature

csa csb Bsh Dfc

Casenumber 18csinthreeweeks

55 11 20

Durationinformation

80casesin3months

4weeks 4months 4months


http://www.publichealth.lacounty.gov/acd/docs/West%20Nile/WNVepi2014.pdf

http://www.cdc.gov/westnile/statsmaps/preliminarymapsdata/histatedate.html

http://healthycanadians.gc.ca/diseases-conditions-maladies-affections/disease-maladie/west-nile-nil-occidental/surveillance-eng.php

Rangefortop5matches

95-77%,91-77%

80-67% 74-48% 68-52%


Top5 Top5 Top1 Top1.Forotherscasecountistoohigh

Notes Fouroutbreaksarecommonforthescenarios

70%cutoff

Cutoffmatchof65-70%isreasonable.

33

Documents

SWAP algorithm validation