• Nenhum resultado encontrado

Snow's case revisited: new tool in geographic profiling of epidemiology

N/A
N/A
Protected

Academic year: 2021

Share "Snow's case revisited: new tool in geographic profiling of epidemiology"

Copied!
4
0
0

Texto

(1)

brazjinfectdis2017;21(1):112–115

w w w . e l s e v ie r . c o m / l o c a t e / b j i d

The

Brazilian

Journal

of

INFECTIOUS

DISEASES

Brief

communication

Snow’s

case

revisited:

new

tool

in

geographic

profiling

of

epidemiology

Alessio

Papini

a,∗

,

Ugo

Santosuosso

b aUniversityofFlorence,DepartmentofBiology,Firenze,Italy

bUniversityofFlorence,DepartmentofClinicalandExperimentalMedicine,Firenze,Italy

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received27July2016 Accepted30September2016 Availableonline9November2016

Keywords: Geographicprofiling Geographicepidemiology Cholera JohnSnow

a

b

s

t

r

a

c

t

GeographicProfilingtechniqueisusedtofindtheoriginofaseriesofcrimes.Themethod wasrecentlyextendedtootherfields.Oneofthebestrenowneddatainepidemiologyisthat byJohnSnowduringanoutburstofcholerainLondon.WewrotePythonscriptstoperform theanalysestoapplytheGeographicProfilingforindividuatingthestartingoriginofan infectionbyusingtheoldSnow’sdataset.Wemodifiedthemethodbyapplyingaweightto eachpointofthemapwherecasesofcholerawerereported.Theweightwasproportional tothenumberofcasesinagivenlocation.

ThismodificationoftheGeographicProfilingmethodallowedtoindividuateinthemap anareaofmaximumprobabilityoftheinfectionsource,whichwasafewmeterswideand includingthehistoricallyknownsourceofcholera,thatisthe“classical”waterpumpat BroadStreet.

Themethodappearstobeausefulcomplementinordertoindividuatethesourceof epidemicswhenavailabledataaboutthecasesoftheinfectionscanbesummarizedona map.

©2016SociedadeBrasileiradeInfectologia.PublishedbyElsevierEditoraLtda.Thisisan openaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/ by-nc-nd/4.0/).

Introduction

GeographicProfiling(GP) isananalytictoolwidelyused in criminologyinordertoidentifyonamap anarea of high-estprobabilityassumedtocontaintheoriginoflinkedevents, typicallycrimesexecutedbyaserialoffender.1Themethod

wasextendedfromcriminologytootherfieldswhereitwas possibletoidentifyaseriesoflinkedeventswhichmighthave

Correspondingauthor.

E-mailaddress:alpapini@unifi.it(A.Papini).

originated from a starting point in the space (represented onatwodimensionalmap).Fieldsofapplicationotherthan criminologyhavebeen:invasionbyalienspecies,2–5

bumble-bees foraging and nest location,6,7 and infectious diseases

targeting.8,9

GP usesthecoordinatesonthemappedevents,creating aprobabilitysurface,theso-calledgeoprofile.1Thegeoprofile

does notindicatetheexact origin ofthe events,but rather prioritizeaseriesofgeographicalpoints,basedonthedata.1

http://dx.doi.org/10.1016/j.bjid.2016.09.010

1413-8670/©2016SociedadeBrasileiradeInfectologia.PublishedbyElsevierEditoraLtda.ThisisanopenaccessarticleundertheCC BY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.0/).

(2)

brazj infect dis.2017;21(1):112–115

113

Thegeoprofilewillprovideonthemapadecreasingprobability densityoffindingthesourceoftheeventsdrawnonthemap.1

Themodeldoesnotsearchsimplythegeographical cen-terofthe events,but instead it considersadistance-decay function,suchthattheprobabilityofaneventwillbelower byincreasingthe distancefromthe centeroforigin;and a bufferzone,withinwhichtheprobabilityofanevent tends tozero.1Thedistance-decayfunctionisrelatedto

maximiz-ingparsimonyinmovement,ineconomicalandenergyterms. Surprisingly,thesefunctionsrevealedtobefoundnotonlyfor humans(criminals),butalsoevenforinvasive(nothuman) species2,3andinfectiousdiseases.8–10

Theneedforanalyticaltoolstorecognizethesourceofthe spreadingof“something”(generallyathreat)hasalwaysbeen animportanttask.11Oneofthebestknowncasesis,in

epi-demiology,thatofcholeraoutbreakinLondon,1854,studied byJohnSnow12andwidelycitedasaseminalworkinspatial

epidemiology13[13andreferencestherein].Dr.Snowtagged

thecholeracasesandthewaterpumpsonthemapof Lon-donandsearchedforthearea withthehighestnumber of cases,sodiscoveringthattheoriginoftheoutbreak(the so-calledfocus ofinfection) wasa contaminated waterpump inBroadStreet.ThetaggedcholeracasesdrawnbySnowon themap ofLondon canbeconvertedinadatasetof coor-dinates,thatwasalreadyusedbyLeComberet al.8 totest

theGPmethodfortargetinginfectiousdiseases.LeComber etal.8wereabletomarkarestrictedareainthemapof

Lon-doncontainingthefamouswaterpumpofBroadStreet(see Fig.1CandDintheirarticle).Theseauthorsusedasinputdata theindividualaddresseswherecaseofdeathsduetocholera hadoccurred,thatis321addresses,whilethetotalnumber ofcasesamountedto575,sincemorethanonecasemight haveoccurredatthesameaddress.LeComberet al.8used

thisapproach“toavoidthepossibleproblemofspatial tempo-ralnon-independenceduetosecondaryinfectionsatagiven address”.Ourapproachincluded,instead,allcasesassigning aweighttoeachpoint(addresses)proportionaltothenumber ofcases.Weoverlookedpossiblesecondaryhuman-to-human contagions, since cholera should not easily transmit from person-to-person,whileitstransmissionisknowntobemore food-orwater-born.14 Forthisreason,weinterpretedmore

thanonecaseinthesameaddressasindependenteventsand hencesummable.

Therefore,hereweproposeanewmethodofapplyingGP inwhichadifferentweightisassignedtoeachpointofthe mapproportionallytothenumberofcasesoccurredineach point.

Methods

The data about the positions of cases on the map were acquiredwith Neuronmorpho(http://www.southampton.ac. uk/∼dales/morpho/),apluginofImageJ(NationalInstituteof Health;http://rsb.info.nih.gov/ij/),thatcanreadamap posi-tion with amouse click, building a csv filecontaining the coordinatespointbypoint.Weightswereaddedmanually.Our methodcalculatestheGPbyweightingeachpointofthemap indirectproportionalitywiththenumberofcasesoccurredin agivenpointofthemap.Thatis,somepointsofthemapare

moreimportantthanothers.Thedatawereanalyzedwitha Pythonscript(Geoprof3.0.2.py).

CrucialfortheGPanalysisistheassignmentofthevalues

B,correspondingtotheradiusofthebufferzone.2Inour

anal-ysisweusedB=30,correspondingtoabufferzoneof30pixels (about15monourmap),thatisquitesmall,withrespectto other GPanalysesinotherfields,suchasthose onmalaria casesinCairo.9WeevaluatedmoreBvalues,calculatingthe

impactontheanalysis.TheGPtechniqueisdescribedindetail inPapinietal.3ThevariableB(thebufferzone)isofcourse

dependentonthemapmagnificationandonthemap resolu-tion,sinceBisexpressedinpixels,whiletheactualmeaningof thebufferzonecanbeunderstoodonlyifexpressedinmeters orkm.

The Python scripts were written by the authors and can be retrieved from the site www.unifi.it/caryologia/ PapiniPrograms.html.ThescriptswereexecutedwithPython 2.7.3 (http://www.python.org/), running in Ubuntu 12.04 LTSoperatingsystem, kernel2.6.32.ThePython(>=2.6 ver-sion)programsneedNumPy(http://www.numpy.org/),SciPy (http://www.scipy.org/), Matplotlib (http://matplotlib.org/), Scikit-learn (http://scikit-learn.org), and Python Image Library – PIL – (http://www.pythonware.com/products/pil/) librariesinstalled.Anoteaboutthesoftwareisprovidedas

Supplementarymaterial(SoftwareUsesupplementary.pdf).

Fig.1–Resultsobtainedbyconsideringonlytheaddresses

onthemapasdatasets.Noweightisassignedtoeach

(3)

114

braz j infect dis.2017;21(1):112–115

Results

and

discussion

Fig. 1 shows the results obtained by considering only the addressesonthemapasdatasets,correspondingtothe anal-ysisbyLeComberetal.,9thatis,noweightwasassignedtoan

addressonthebasisofthenumberofrecordedcases.InFig.2

weshowtheGPanalysiswithweightsassignedtoeachpoint ofthemaponthebasisofthenumberofcases.Theresult isquitestriking,sincetheredarea,representingtheareaof themapwiththepointswith95%ofhighestprobability com-prisedthepumpofBroadStreet.Thisareawasabout30min diameter.Withrespecttothemethodthatdoesnotconsider thenumberofcasesasweights(showninFig.1),thetotalarea ofhighestprobabilityofthepresenceofthesourcewashence muchsmaller.

Countingthepixelswithhighestprobabilityoffindingthe sourceof the crimes, we found that the red pixels (those withhighestprobability)decreasedsubstantiallypassingfrom consideringonlytheaddressestousingthewholedataset withweights,that isfrom 36533to10068 (visiblefrom the reductionindimensionoftheredareafromFig.1toFig.2).

Fig.2–GPanalysiswithweightsassignedtoeachpointof

themaponthebasisofthenumberofcholeracases.The

redarea(thatwithhighestprobabilitytofindtheinfection

source)isonlyabout30mindiameteranditcomprisesthe

famouspumpofBroadStreet.

Calculatingeachcaseasasinglepoint,alsoiflocatedinthe samepositiononthemap(thatisatthesameaddress), pro-ducedanareaofredpixelsonlyslightlyhigherwithrespect totheuseofweights(datanotshown).

Calculatingthedistanceonthemap,theGPanalysiswith weightsproducedanareaofmaximumprobabilityoffinding thesourceofabout30mindiameter,whichcontainsthewell knownsourceofcholeracasesinLondon,thatisthefamous pumpofBroadStreetrecognizedbySnow.12Thisresultshows

thattheuseofweightsproportionaltothenumberofcases ineachaddress largelyincreasetheprecisionofthe analy-sis,thatis,itreducestheareaofmaximumprobabilitywhere tolookforthesourcewithrespecttootherGPtechniquesas thoseemployedbyLeComberetal.9andVerityetal.11

Conclusion

Theweightedgeoprofilingcanbeausefulmethodtoidentify acenteroforiginofanoutbreakofadisease,incaseswhen morecasesofinfectioncanbefoundinthesamepointofthe map(normallycorrespondingtoaresidence),largelyreducing theprioritypointsandhenceshowingthehighestprecisionin delimitingthesourcesearcharea.

Theuseofweightsformorecasesofinfectionsatthesame address,canbeagoodchoiceonlyincaseswheresecondary person-to-personinfectionscanbeconsiderednotprobable (asitislikelythecaseofcholera),otherwise,asstatedbyLe Comberetal.9itisnecessarytouseasinputdataeachaddress

(pointonthemap)aspointswiththesameweight=1.

Funding

FinancialsupportbytheItalianMinistryofResearch(MUR), FondidiAteneo.

Conflicts

of

interest

Theauthorsdeclarenoconflictsofinterest.

Appendix

A.

Supplementary

data

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/ j.bjid.2016.09.010.

r

e

f

e

r

e

n

c

e

s

1.RossmoDK.Geographicprofiling.BocaRaton,FL:CRCPress; 2000.

2.StevensonMD,RossmoDK,KnellRJ,LeComberSC. Geographicprofilingasanovelspatialtoolfortargetingthe controlofinvasivespecies.Ecography.2012;35:1–12.

3.PapiniA,MostiS,SantosuossoU.Trackingtheoriginofthe invadingCaulerpa(Caulerpales,Chlorophyta)withgeographic profiling,acriminologicaltechniqueforakilleralga.Biol Invasions.2013;15:1613–21.

(4)

brazj infect dis.2017;21(1):112–115

115

4. CiniA,AnforaG,Escudero-ColomarLA,etal.Trackingthe invasionofthealienfruitpestDrosophilasuzukiiinEurope.J PestSci.2014;87:559–66.

5. SantosuossoU,PapiniA.MethodsforGeographicProfilingof biologicalinvasionswithmultipleoriginsites.IntJEnviron SciTechnol.2016;13:2037–44.

6. RaineNE,RossmoDK,LeComberSC.Geographicprofiling appliedtotestingmodelsofbumble-beeforaging.JRSoc Interface.2009;6:307–19.

7. Suzuki-OhnoY,InoueMN,OhnoK.Applyinggeographic profilingusedinthefieldofcriminologyforpredictingthe nestlocationsofbumblebees.JTheorBiol.2010;265:211–7.

8. LeComberSC,RossmoDK,HassanAN,FullerDO,BeierJC. Geographicprofilingasanovelspatialtoolfortargeting infectiousdiseasecontrol.IntJHealthGeogr.2011;10:35.

9. SmithCM,DownsSH,MitchellA,HaywardAC,FryH,Le ComberSC.Spatialtargetingforbovinetuberculosiscontrol:

canthelocationsofinfectedcattlebeusedtofindinfected badgers?PLOSONE.2015;10:e0142710.

10.LeComberSC,StevensonMD.FromJacktheRipperto epidemiologyandecology.TrendsEcolEvol.2012;27:307–8.

11.VerityR,StevensonMD,RossmoKD,NicholsRA,LeComber SC.Spatialtargetingofinfectiousdiseasecontrol:identifying multiple,unknownsources.MethodsEcolEvol.2014;5:647–55.

12.SnowJ.Snowoncholera.AreprintoftwopapersbyJohn Snoe,MD,togetherwithabiographicalmemoirbyBW Richardson,MD,andanintroductionbyWadeHampton Frost.NewYork:TheCommonwealthFund;1936.

13.ShiodeN,ShiodeS,Rod-ThatcherE,RanaS,Vinten-Johansen P.Themortalityratesandthespace-timepatternsofJohn Snow’scholeraepidemicmap.IntJHealthGeogr.2015;14:21.

14.SackDA,SackRB,NairGB,SiddiqueAK.Cholera.Lancet. 2004;363:223–33.

Referências

Documentos relacionados

The probability of attending school four our group of interest in this region increased by 6.5 percentage points after the expansion of the Bolsa Família program in 2007 and

Ao Dr Oliver Duenisch pelos contatos feitos e orientação de língua estrangeira Ao Dr Agenor Maccari pela ajuda na viabilização da área do experimento de campo Ao Dr Rudi Arno

Ousasse apontar algumas hipóteses para a solução desse problema público a partir do exposto dos autores usados como base para fundamentação teórica, da análise dos dados

Cette liste des formes les moins employées des chansons (par rapport aux autres émetteurs, bien entendu) suffit à faire apparaitre l’énorme décalage qui les sépare des autres

The fourth generation of sinkholes is connected with the older Đulin ponor-Medvedica cave system and collects the water which appears deeper in the cave as permanent

The irregular pisoids from Perlova cave have rough outer surface, no nuclei, subtle and irregular lamination and no corrosional surfaces in their internal structure (Figure

i) A condutividade da matriz vítrea diminui com o aumento do tempo de tratamento térmico (Fig.. 241 pequena quantidade de cristais existentes na amostra já provoca um efeito

didático e resolva as ​listas de exercícios (disponíveis no ​Classroom​) referentes às obras de Carlos Drummond de Andrade, João Guimarães Rosa, Machado de Assis,