Disaster-related Data for Sustainable Development Sendai ...global... · baselines for measuring the global targets of the Sendai Framework. This Summary Report addresses the key

Disaster-related Data forSustainable Development

Sendai FrameworkData Readiness Review 2017

Global Summary Report

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TableofContents

Executivesummary............................................................................................4

Introduction ......................................................................................................7

Chapter1. DataAvailability–findingsfromtheSendaiFrameworkDataReadinessReview.........................................................................9

1.1.Disasterlossdatacollectionatnationallevel–Findings........................10

1.1.1. Availabilityofdisasterlossdata................................................10

1.1.2. Disaggregationofdisasterlossdata..........................................12

1.1.3. Capacityneedstodevelopdisasterlossdata...........................14

1.1.4. Developmentoflossdata-relatedbaselinesfortheSendaiFramework................................................................................15

1.2.DataAvailabilityfortheIndicatorsoftheGlobalTargetsoftheSendaiFrameworkforDisasterRiskReduction..................................................16

Chapter2. Dataquality................................................................................61

2.1.Disasterlossaccounting,geospatialdata,bigdataandstatistics...........62

2.2.Disaster-relatedearthobservationdata.................................................63

2.3.Officialstatisticsanddisaster-relateddatafortheSendaiFrameworkandtheSDGs...........................................................................................65

Chapter3. Dataaccessibility........................................................................67

Chapter4. Applicationofdata.....................................................................69

4.1.Nationalstatisticalofficesandnationaldisasterriskmanagementinstitutions..............................................................................................70

Chapter5. Conclusions.................................................................................73

ANNEX1–ReportingCountries.......................................................................77

SendaiFrameworkDataReadinessReview2017

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Executivesummary

InadoptingtheSendaiFrameworkforDisasterRiskReduction2015–2030,MemberStatescommittedtothesystematicandcyclicalmeasurement,monitoringandreportingofprogress inachievingtheoutcomeandgoaloftheframework.Atthegloballevel,progressistobemeasuredagainstthesevenglobal targets1and associated indicators2. The indicators were developed by the Members andobserversoftheOpen-endedintergovernmentalexpertworkinggrouponindicatorsandterminologyrelatingtodisasterriskreduction(OIEWG),tobeabletocaptureprogressinthepreventionofnew,and the reduction of existing risk, and the strengthening of resilience of persons, businesses,communitiesandcountries.Furthermore,inendorsingtheproposalforaglobalindicatorframeworkforthe2030AgendaforSustainableDevelopment,inwhichwereincludedkeyglobalindicatorsoftheSendaiFramework,MemberStatesplacedthereductionofdisasterriskattheheartofsustainabledevelopment.

EffectivemonitoringofprogressinachievingtheglobaltargetsoftheSendaiFrameworkanddisaster-related SDGs, is predicated on the availability, accessibility, quality and applicability of multipledatasets. Thesedataarecollectedfrommultiplesourcesvianumerousmechanisms, includingbutnot restricted to national disaster loss accounting systems, national statistical systems, householdsurveysandroutineadministrativedata.Qualitativeandquantitativedatawillberequired,andcouldbesupplementedbyEarthobservations(EO)andgeospatialinformation(GI)forexample.

ThefirstcycleofmonitoringprogressinimplementingtheSendaiFramework(whichwillexceptionallycoverthetwobiennia2015-2016and2017-2018)willbelaunchedinearly2018,endinginMarch2019.Feasibilityandqualitywillbedependentupontheavailabilityandaccessibilityoftherequireddata;datathatwillneedtobesufficientlyconsistentandcomparabletoallowmeaningfulmeasurementofprogressand impact. Toassess the current stateofplay, theOIEWGrecommended to conductareviewofthereadinessofcountriestoreportagainsttheglobaltargets.IncontributingtotheReview,87Member States across all regions assessed their stateof readiness tomonitor and report, andspecifically,theavailabilityofnationaldisaster-relateddata,disaster-relateddatagapsandthetypeofresourcesrequiredtofilldatagapsidentified.Italsoassessedcountries’currentabilitytosetupbaselinesformeasuringtheglobaltargetsoftheSendaiFramework.

This SummaryReportaddresses thekey findingsof theSendai FrameworkDataReadinessReview(henceforthreferredtoastheReview),andpresentstheminfourchaptersthatreflectsomeofthekeycharacteristicsofdata.

Chapter1isthemainbodyofthereportandpresentsthefindingsofMemberStatesintermsofdataavailabilitytoreportoneachoftheindicatorsoftheglobaltargetsoftheSendaiFramework.ThefindingsshowedthatwhiledatawasavailableformostcountriesforTargetsAandB(respectively83%and66%ofreportingcountries)withbetween50%and60%beingabletoestablishbaselines,dataaremorelimitedforTargetsCandD. Only37%-55%ofcountriesreporthavingdataoneconomiclossestoproductiveassets, lossesincritical infrastructureandculturalheritage,anddisruptionstohealth,educationandotherbasic services,withbetween29%and33%able todevelopbaselines.

1http://www.preventionweb.net/files/43291_sendaiframeworkfordrren.pdf2http://www.preventionweb.net/files/50683_oiewgreportenglish.pdf


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TargetsE,FandGexhibitwidevariationsindataavailability.From57%to72%fordatapertainingtoearlywarningsystems,riskinformationandpeopleevacuated,to39%to54%ofreportingcountriesfordataonnationalandlocalDRRstrategiesunderTargetE.ThelowestdataavailabilityisobservedfortheindicatorsforTargetF,wherebetween20%and25%ofreportingcountriescitethatdataisavailable.

Ingeneral,withwellestablisheddisasterlossaccountingprotocolsinmanycountries,thelossdataenvironmentisreasonablypopulated,althoughdataaretypicallymoreavailableonphysicaldamageandhumanimpact,andlessavailableoneconomiclosses,lossesofspecificassetsandinfrastructure,culturalheritageanddisruptionstobasicservices.However,itshouldbenotedthatasapproximatelyaquarterofthe98nationaldisasterlossdatabasesavailableinthepublicdomainarenotgovernmentoperated,governmentownershipmaybeanissue.Consequently,absolutedataavailabilitymaybehigher.

DataavailabilitygapsshouldbeaddressedbyMarch2019,ifcountriesaretobeabletoreportagainsttheSendaiFrameworkglobalTargetsasplanned.Thegapsidentifiedarenotrestrictdtodisasterlossdata;statisticaldatasetsarealsoinshortsupply,forexampletobeabletomeasurecertainindicatorsofTargetF.Consequently,countrieswerealsoaskedtoidentifytheresourcesthatwouldberequiredto redress thegaps identified, andqualify their answersusing the three recognized categories forinternational cooperation: financial resources, technology transfer and capacity building. Inmostcases, finance was the resource most frequently cited followed by capacity building and thentechnologytransfer.Therewereexceptionshowever;capacitybuildingwascitedasthemostneededresourcetofillthedatagapformeasuringtheindicatorsonearlywarningsystems.

MoredetailedanalysiscanbefoundinChapter1.

Chapter2addressesaspectsofdataqualitywhichissoessentialtofacilitatingeffectivemonitoring,reportingandinformeddecision-makingforimplementationoftheSendaiFrameworkandtheSDGs,inter alia through the application of commonly agreed methodologies and standards to allowconsistentandcomparabledata.

Theintegrationofdisaster-relateddatawithinnationalstatisticalsystemscanbringqualitydividendsthrough applying the fundamental principles of official statistics, and at the same time, facilitateintegrated reporting to the SDGs and the Sendai Framework using multi-purpose data sources;therebyreducingthereportingburdenonMemberStates.

ConsistentwiththeworkoftheWorkingGrouponGeospatial InformationoftheInter-agencyandExpertGrouponSDGsIndicators(IAEG-SDGs), it isrecommendedthatcountriesexploretheaddedvalueofusingotherdata–includingEO,GIand‘bigdata’–toamplifythequalityandapplicabilityofdisasterlossdataanddisaster-relatedstatistics.Tothisend,theOIEWGinstructedtechnicalworktobeundertakenwithrelevanttechnicalpartners,includingtheinternationalstatisticalcommunity,todevelopguidanceonmethodologiesandstandardsthatwouldenhancedataquality,comparabilityadusability.Thisworkisongoing.

Chapter3examinesdataaccessibility,whichhasbeenidentifiedbyanumberofcountriesasanotherchallengetobeovercomeifcapabilitiesaretobeenhancedandtheefficacyandqualityofmonitoringandreportingistobeoptimised.Datamaybeavailable,butaccesstothedatamaybeimpeded,for


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instance by being subject to a tariff or payment (for which there are no resources). In othercircumstances a lack of access to existing datasets may simply be a function of established(mal)practiceortheabsenceofdata-sharingprotocols,mechanismsandappropriatedatagovernancearrangements.

Chapter 4 outlines aspects of the application of disaster-related data in policy and investmentdecision-making.Growingpoliticalcommitmentandleadershipbygovernmentstoimproveevidence-based disaster risk management and disaster-related statistics, and ensure that data are madeavailable to the appropriate institutions / individualswith the level of detail needed for decision-making,willbringdividendsnotonlyinincreaseddataaccessibility,butalsoinitsapplicationinpolicyaction.Dataprovidersshouldbesuretoinvestappropriatelyinidentifyingandengagingdatauserssoastobeabletoeffectivelydriveaction

ThepotentialthateffectivecollaborationbetweenNationalDisasterManagementAgencies(NDMAs)andNationalStatisticalOffices(NSOs)offers,isconsiderable.However,inmanycasesthiswillrequirechallenges in information exchange and coordination to be overcome. Factors that include forexample:traditionalinstitutionalstructuresandmandates;commonbaselines;capacitiestomutuallysupportandcomplementrespectivedataandinformationsets;orinformationsharingprotocolsetc..

Inconclusion,anyofthedata-relatedchallengesoutlinedinthisreportarehinderingthecapacityofcountriestomeaningfullymonitor,measureandmanagedisasterriskandlosses.Indifferentcountrycontexts data capacity needs to be addressed comprehensively, by expanding data availability, indevelopingnewdatawhereitdoesnotexist,bycreatingcommonmethodologiesandstandardsforenhanceddataquality,bycreatingcommondatasharingplatformsandprotocolstoenhancedataaccessibilityandapplicability,andsometimesbybreakingdowninstitutionalbarriers.

Suchactionwillneedtobeundertakeninacoordinatedmannertoallowthedevelopmentofconsistentandcomparabledataatthenational,sub-national,aswellasthegloballevels.Theneedforcollectiveeffortinenhancingaspectsofdataavailability,accessibilityandquality,hasbeenrecognizedbyanumberofkeycommunities–includingthenationalstatisticaloffices,andnationalmappingandgeo-informationagencies.

A Global Partnership for Disaster-related Data for Sustainable Development would facilitate acollaborative,multi-stakeholdereffort (bringingtogethergovernments, internationalorganizations,the private sector, civil society groups, and the statistics and data communities), to optimize andoperationalize existing and future disaster-related data in support of national and sub-nationaldisasterriskreductioneffortsandthemeasurementoftheglobaltargetsoftheSendaiFrameworkforDisasterRiskReductionandthe2030AgendaforSustainableDevelopment.

Itisexpectedthatupondraftingthetermsofreferenceforthepartnership,collaboratingentitieswillusetheinformationprovidedbythe87MemberStatescontributingtotheSendaiFrameworkDataReadinessReview2017toformulatethestrategyandpriorityactionstosupportenhancedmonitoring,reportingandrisk-informeddecision-making.


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Introduction

87countriesrespondedtothe2017DataReadinessReview

At the request of the Open-ended intergovernmental expert working group on indicators andterminologyrelatingtodisasterriskreduction(OIEWG),theUNISDRrolledouttheSendaiFrameworkDataReadinessReview(henceforthreferredtoastheReview)inFebruary2017.Asof20April2017,ithadreceivedtheinputsof87countrieswiththefollowingregionaldistribution:

▫ Africa–10▫ Americas–17▫ ArabStates–10

▫ Asia–17▫ Europe–26▫ Pacific–7

IncontributingtotheReview,MemberStatesassessedtheirstateofreadinesstomonitorandreporton the indicators measuring the global targets of the Sendai Framework, and specifically, theavailability of national disaster-related data, disaster-related data gaps and the type of resourcesrequiredtofilldatagapsidentified.Italsoassessedcountries’currentabilitytosetupbaselinesformeasuringtheglobaltargetsoftheSendaiFramework.TheresultsofthisassessmentarecapturedinChapter1.

InthecourseoftheReview,additionalinformationwasprovidedwithrespecttodataquality,dataaccessibility,andtheapplicationofdata.TheseelementsarecapturedinChapters2to4.


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Chapter1. DataAvailability–findingsfromtheSendaiFrameworkDataReadinessReview

Thischapterformsthemainbodyofthereportandisdividedintotwosections:

Section1:generalfindingsfromtheReviewwithregardtodisasterlossdatacollection.

Section2:findingsondataavailabilityforspecificindicators.

Where datawere assumed to be inconsistent or scarce, questionswere added so as to allow anassessmentofdataavailabilityandsources thatcouldserveasaproxy for the indicator. Thishasbecomecommonpracticeineffortssupportingthedevelopmentofmanyofthe98existingnationaldisasterlossaccountingsystems3.

Dataavailability

The availability of data was requested for two time periods, current availability and the periodbetween2005–2015.ThelatterrepresentstheimplementationperiodoftheHyogoFrameworkforActionfromwhichthebaselinefortheSendaiFrameworkforDisasterRiskReductiontargetsA-D,andpotentiallysomeoftheindicatorsoftargetF,willbeconstructed.Dataavailabilityisbeingmeasuredintermsofnumberofcountriesthathaveatleast1datapointbyregion.

87of the193UNMember States responded to theReview. The indicators recommendedby theOIEWG were endorsed in UNGeneral Assembly Resolution A/RES/71/276 on 2 February 2017,whereupontheReviewwaslaunchedsoastobeabletopresenttheresultsattheGlobalPlatformforDisaster Risk Reduction. At 45% of all Member States, this is an excellent response given thetimeframesrequiredforfeedback,andtheresultsprovideauseful,representativeperspectiveonthestateofreadinessofMemberStatestoreportagainstboththeSendaiFrameworkandtheSDGs.

Thosecountriesstillwishingtoconductthereadinessreviewmaydosothroughoutthesecondhalfof 2017, facilitating preparation for monitoring and reporting and in so doing providing a morecomprehensiverepresentationofthestateofreadiness.

Disaggregation

Paragraph19(g)oftheSendaiFrameworkcallsforspecificattentiontofactorssuchasincome,sex,ageanddisability indisaster risk reduction. Furthermore, theOIEWGrecognized thecollectionofdisaggregateddataas instrumental to theeffective implementationof theSendai Frameworkandrelevant disaster risk-related targets of the Sustainable Development Goals. At the same time,recognizingthedifferentcapacitiesofMemberStateswithregardtodatacollectionandreporting,andtheneedforindicatorstobeusablebyallMemberStatesinordertobeconsideredglobal,theOIEWGnotedthatdatadisaggregationmightnotbeimmediatelyfeasibleacrossallMemberStates.

Althoughnotarequirement,theOIEWGencouragedMemberStatestocommenceor,asappropriate,furtherenhancethecollectionofdataondisasterlossdisaggregatedbyincome,sex,ageanddisability,with the engagement of the national statistical offices and in accordance with the FundamentalPrinciplesofOfficial Statistics, and to start reportingdisaggregateddata. It alsocalled foractionsundertargetFoftheSendaiFrameworktostrengthennationalcapacitiestodoso.

3includingthoseemployingtheDesinventarmethodology–http://Desinventar.net/index_www.html


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1.1. Disasterlossdatacollectionatnationallevel–Findings

1.1.1. AvailabilityofdisasterlossdataDisasterlossdatawillbeusedbycountriestoreportagainstallindicatorsoftheglobaltargetsA-DoftheSendaiFramework,aswellasthedisaster-relatedtargetsofSDGs1,11and13(seeChapter2),andthereforecomprisethebackboneofmonitoringprogress intargetandgoalachievement. TheReviewfoundthat60%ofreportingcountrieshaveanationaldatabaseforcollectingdisasterlosses,and of the 87 respondents, 26 countries reported that they useDesinventar4 . DesInventar is aconceptual and methodological tool for the generation of National Disaster Inventories and theconstructionofdatabasesofdamage,lossesandtheeffectsofdisasters;itissupportedbyUNISDR,UNDP,theEuropeanCommissionandothertechnicalpartners.

Countrieswithnationaldisasterlossdatabasesoperatedbygovernment(ingreen);countrieswithout(orange);noresponse(grey)

Acommonmethodologyforlossdatacollectionisthepreconditionforthecomparisonofmonitoringresultsbetweencountries.Itallowsforthedevelopmentofdisaster-relatedstatistics,andintegratedreportingforboththeSendaiFrameworkandtheSDGs.

21 countries reported that they use a methodology other than DesInventar to collect loss data;representing24%ofcountriesparticipatingintheReview.TheDesInventarrepositorycontainsdatafor98countries,andafurther11countriesaredevelopingsuchdatabases. Therefore,60%ofUNMemberStatesproducelossdatausingastandardizedandcomparablemethodologythatcanbeusedinthereportingoflossindicators.Infact,lossdataexistsinthisrepositoryfor34ofthe87countriesthat respondedto theReview. Thediscrepancywith thenumberofcountries that reportedusingDesInventarmaybeattributedtothenatureofthesampleparticipatingintheReview.Itmayalsobeindicativeofthe issueofownershipofnational lossdatabycountries–someofthe lossdatasetscurrently stored inDesinventararenotbeingdevelopedandupdatedbynational institutionswith

4http://Desinventar.net/index_www.html


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responsibilitiesfordisasterriskreduction,butbynon-governmententities.Forexample,thisisthecaseinthreeCaribbeancountrieswherethisisbeingundertakenbytheUnitedNationssystem;byinter-governmentalorganizationsinsixcountriesinthePacific;orbyresearchorganizationsand/oracademic institutions, in Mexico, Colombia and Guatemala for example. In some cases, theseinstitutionsareresponsibleforthemonitoringofprogressagainsttheSendaiFramework;andinmanycaseswereresponsibleforHFAmonitoring.

TheReviewaskedcountryfocalpointsifthey‘collectnationaldisasterlossdata’,andnotifthey‘haveaccesstonationaldisasterlossdata’.Themodestpercentageofcountriesindicatingthatthey‘collectnational disaster loss data’ could also be indicative of progress that is still required in theinstitutionalization of disaster loss accounting, and promoting ownership of such data. This hasconsequences for the accessibility to, and application of, disaster loss data by disaster riskmanagement agencies and other relevant government institutions, that go beyond issues ofavailability.Suchgapsmaybeaddressedbysupportingthestrengtheningofcountries’capabilitiestocollectdisasterlossdata,andthroughtheinstitutionalisationofavailabledisasterlossdatabases.

ThemajorityofcountriescitedtheMinistryofInterior,thecivilprotectionorthedisastermanagementagencyas responsible for thecollectionofdisaster lossdataat thenational level.However,manyotherinstitutionswerecitedintheproductionofdisaster-relateddata,rangingfromsectorallineministries(agriculture,infrastructure,waterortransport),orfromtheemergencyservices(fire,policeetc.)tothenationalstatisticaloffices(NSO).Itistobenotedthatresearch,academicinstitutionsandthink tanks, which lead loss data collection in a number of countries using Desinventar, find nomention.

Acomparativereviewof57disasterlossdatabasesconductedbytheUNDPBureauforCrisisPreventionandRecoveryin2013foundthat80%wereusingDesInventar,ofwhich77%werehostedbygovernments,andtheremaining23% were hosted by NGO’s, research centres, universities and otherconsortia.Thestudyalsofoundthatwhencomparinggovernmentandnon-government hosting arrangements for loss databases, in general thenon-governmental hosting arrangements led to higher accessibility, continuityanduseofthedatabases‡.Thereportfoundthattheapplicationoflossdataforpolicydevelopmentandanalysiswashigher inthecaseofgovernmenthosteddatabases,whileapplicationforresearchishigherinthecaseofnon-governmenthosteddatabases–findingsthatappeartobereflectedintheresultsoftheReview.

‡AComparativeReviewofCountry-LevelandRegionalDisasterLossandDamageDatabases.UNDP.BureauforCrisisPreventionandRecovery.2013


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1.1.2. Disaggregationofdisasterlossdata

Disaggregated loss data is of particular importance, not least in pursuing Priority 1 of the SendaiFramework “understanding disaster risk” which recognises that it is important “to enhance thedevelopment and dissemination of science-based methodologies and tools to record and sharedisasterlossesandrelevantdisaggregateddataandstatistics[…]“.

Bycollectingdataassociatedwithspecifichazardswithspecificgeographicalfootprints,countriescanbetter understand their impact,which in turn can steer the development and implementation ofefficientriskmanagementandriskmitigationmeasures.

Almost98%ofthecountriesreportingthattheyarecollectingdisasterlossdata,dosobygeographiclocationandevent; 94%disaggregatedisaster lossdatabyhazard type. Of thosecountries thatreportedtotheReview,thepercentagesthatdisaggregatedisasterlossdataareasfollows.

Deaths,missing,injuredorillattributedtodisasters:

▫ 90% of countries disaggregate by hazard type, location and event (consistent with theDesinventarapproachtodisasterlossaccounting)

▫ Between57%and66%ofcountriesdisaggregatebyageandsex,whichalthoughnotrequiredfortheSendaiFramework,isarequirementforreportingontheSDGs

▫ 28%to31%disaggregatebydisability(alsoarequirementforreportingontheSDGs)▫ 12%to15%ofcountriesdisaggregatebyincomegroups

Number of peoplewhose dwellings were damaged; number of dwellings destroyed; livelihoodsdisruptedordestroyed;economiclosstohousingsector;damagedordestroyedcriticalinfrastructure;number of health and educational facilities damaged and destroyed; number of disruptions toeducationalservices:

▫ 87%to98%ofcountriesdisaggregatebyevent,locationandhazardtype▫ Between42%and60%disaggregatebyageandsex(arequirementforreportingontheSDGs)▫ 28%to34%(56%forlivelihoods)disaggregatebydisability(alsoarequirementforreporting

ontheSDGs)▫ 12%to17%(23%forlivelihoods)disaggregatebyincomegroups

Damagedanddestroyedheritage;disruptionstootherbasicservices:

▫ 84%ofcountriesdisaggregatedisasterlossdatabyhazardtype,locationandevent


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Over90%ofcountriescurrentlycollectdatadisaggregatedbyhydrologicalandmeteorologicalhazardtypes, and over 80% of countries collect data on geophysical hazards; these are the three mostcommonlyavailablecategories.Between68%and76%ofcountriesalsodisaggregatebyman-made,climatological, environmental and technological hazards. Approximately 20% of countriesdisaggregatebyotherhazardtypes.

38%ofreportingcountriesindicatedthattheirlossdataiscurrentlypublicallyavailable,while17%ofcountriesreportedthattheirlossdataisnotpublicallyavailable.45%ofcountriesdidnotrespond.

Disaster loss data is collected for events of all scales, including small-scale disasters, by 45% ofcountriesparticipatingintheReview;10%ofreportingcountriesdonot,and45%didnotrespond.Although theSendaiFramework stresses the importanceof consideringall scalesofdisasters, thisimpliesthatformanyofthereportingcountries,the“extensiverisklayer”remainslargelyinvisible.

AsrevealedintheGlobalAssessmentReportonDisasterRiskReduction(GAR)²,themajorityofdamageandlossesincurredsince1990havebeenassociatedwithdisastersrelatedtoextensiverisk. Ingoingunrecorded,direct economic losses attributed to disasters have been grosslyunderestimated. GAR15 highlights that a more accurate estimationshould value direct economic losses at around 60% higher than thosereportedinternationally.²http://www.preventionweb.net/english/hyogo/gar/


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1.1.3. Capacityneedstodevelopdisasterlossdata

94%ofthosecountrieswhicharenotcurrentlycollectingdisasterlossdata,indicatedthattheyrequirethe capacities to do so. 77% and 72% of countries indicate respectively the need for financialresources,andtechnologytransfer.

Allcountriesreportingthattheydonotcurrentlycollectdisasterlossdatadeclaredtheirintentiontostartdatacollectionbetweennowand2018.

52countriesdidnot reporton the resources required tobeable to collectdisaster lossdata; thisequates to thenumberof countries participating in theReview that reportedhavingdisaster lossdatabases.


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1.1.4. Developmentoflossdata-relatedbaselinesfortheSendaiFramework

ThebaselinefortheSendaiFrameworkforDRRglobaltargetsA–Distheaverageofdisasterlossdatarecords between 2005 and 2015 – the implementation period of the HFA. Currently 41% of thecountriesparticipating in theReview reportedhaving lossdata records covering theentireperiod2005-2015.14%ofreportingcountriesreportedthattheydidnothavethatdatarequiredtoestablishabaseline,and45%didnotrespond.

Countrieswithnationaldisaster lossdatabases covering theperiod2005-2015,operatedbygovernment (ingreen);countrieswithout(orange);noresponse(grey)


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1.2. DataAvailabilityfortheIndicatorsoftheGlobalTargetsoftheSendaiFrameworkforDisasterRiskReduction

Global targetA: Substantially reduce global disastermortality by 2030, aiming to loweraverageper100,000globalmortalitybetween2020-2030comparedwith2005-2015.

IndicatorA2:Numberofdeathsattributedtodisasters,per100,000population

DataavailabilityIndicatorA-2(Mortality)5

Currentdataavailability:Datafor‘numberofdeathsattributedtodisasters,per100,000population’arecurrentlyavailable in72countries(representing83%ofreportingcountries). 10%ofreportingcountriesindicatedthattheydonotcollectthenumberofdeathsand7%didnotrespond.

Baselinedevelopment:52countries(representing60%ofreportingcountries)reportedhavingdatatocovertheentireperiod2005-2015.

Resourcesneededtocollectdata:Financialresources–90%ofreportingcountries;Capacity–80%;andTechnologytransfer–60%.Notethatonly11%ofreportingcountriesrespondedtothisquestion.

5Thelegendappliestoallsubsequentillustrationsofgeographicaldistributionbyindicator


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IndicatorA3:Numberofmissingpersonsattributedtodisasters,per100,000population

DataavailabilityIndicatorA-3(Missing)

Currentdataavailability: Datafor ‘numberofmissingpersonsattributedtodisasters,per100,000population’arecurrentlyavailablein61countries(representing70%ofreportingcountries).21%ofreportingcountriesindicatedthattheydonotcollectthenumberofmissingpersonsand9%didnotrespond.



SummaryTargetA

OfthosecountriesthatreportedtotheReview,thepercentagesthatcollectdataareasfollows:

▫ 83%onhumandeathsattributedtodisasters▫ 70%onpeoplemissingattributedtodisasters.

Relativetotheindicatorsunderothertargets,TargetAexhibitsthehighestpercentageofcountrieswithdatacurrentlyavailable.50-60%ofthecountriesreportingintheReviewareabletodevelopabaselinewithexisting2005-2015data.


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Global target B: Substantially reduce the number of affected people globally by 2030,aimingtoloweraverageglobalfigureper100,000between2020-2030comparedwith2005-2015.

IndicatorB2:Numberofinjuredorillpeopleattributedtodisasters,per100,000population

DataavailabilityIndicatorB-2(Injured/Ill)

Currentdataavailability:Datafor‘numberofinjuredorillpeopleattributedtodisasters,per100,000population’arecurrentlyavailablein61countries(representing70%ofreportingcountries).19%ofreportingcountriesindicatedthattheydonotcollectthenumberofinjuredorillpeopleand10%didnotrespond.




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IndicatorB3:Numberofpeoplewhosedamageddwellingswereattributedtodisasters

DataavailabilityIndicatorB-3(Dwellingsdamaged)

Currentdataavailability:Datafor‘numberofpeoplewhosedwellingsweredamagedattributedtodisasters’arecurrentlyavailablein57countries(representing65%ofreportingcountries). 25%ofreportingcountriesthattheydonotcollectthenumberofpeoplewhosedwellingsweredamagedand10%didnotrespond.



AlternativedataforindicatorB3.

B3a:Numberofdwellingsthatweredamagedattributedtodisasters

Currentdataavailability:Datafor‘numberofdwellingsthatweredamagedattributedtodisasters’arecurrentlyavailable in60countries(representing69%ofreportingcountries). 20%ofreportingcountriesindicatedthattheydonotcollectthenumberofdwellingsthatweredamagedand11%didnotrespond.


MetadataforB3a(andB4a)


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B3b:Officialstatisticaldatasourceprovidingnumberofpeopleperhousehold

Current data availability: Official statistics providing the ‘number of people per household’ arecurrently available in 59 countries (representing 68% of reporting countries). 21% of reportingcountriesindicatedthatthisisnotavailablefromofficialstatisticsand12%didnotrespond.

IndicatorB4:Numberofpeoplewhosedestroyeddwellingswereattributedtodisasters

DataavailabilityIndicatorB-4(Dwellingsdestroyed)

Currentdataavailability:Datafor‘numberofpeoplewhosedwellingsweredestroyedattributedtodisasters’arecurrentlyavailablein50countries(representing57%ofreportingcountries). 31%ofreportingcountries indicatedthattheydonotcollectthenumberofpeoplewhosedwellingsweredestroyedand12%didnotrespond.



AlternativedataforindicatorB4:

B4a:Numberofdwellingsthatweredestroyedattributedtodisasters

Currentdataavailability:Datafor‘numberofpeoplewhosedwellingsweredestroyedattributedtodisasters’arecurrentlyavailablein60countries(representing69%ofreportingcountries). 20%ofreportingcountriesindicatedthattheydonotcollectthenumberofdwellingsdestroyedand11%didnotanswer.



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Indicator B5: Number of people whose livelihoods were disrupted or destroyed attributed todisasters

DataavailabilityIndicatorB-5(Livelihoodsdamagedordestroyed)

Currentdataavailability:Datafor‘numberofpeoplewhoselivelihoodsweredisruptedordestroyedattributed to disasters’ are currently available in 34 countries (representing 39% of reportingcountries).49%ofreportingcountriesindicatedthattheydonotcollectthenumberofpeoplewhoselivelihoodsweredisruptedordestroyedand12%didnotrespond.


Resourcesneededtocollectdata:Financialresources–91%ofreportingcountries;Capacity–68%;andTechnologytransfer–81%.Notethat49%ofreportingcountriesrespondedtothisquestion.

AlternativedataforindicatorB5:

B5a:Physicaldamagetotheagriculturalsectorattributedtodisasters

Currentdataavailability:Datafor‘physicaldamagetotheagriculturalsectorattributedtodisasters’arecurrentlyavailable in59countries(representing68%ofreportingcountries). 21%ofreportingcountriesindicatedthattheydonotcollectthephysicaldamagetotheagriculturalsectorand11%didnotrespond.



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B5a1.Numberofhectaresofcroplanddamagedbydisasters

Current data availability: Data for ‘number of hectares on crop land damaged by disasters’ arecurrently available in 55 countries (representing 63% of reporting countries). 5% of reportingcountriesindicatedthattheydonotcollectthenumberofhectaresofcroplanddamagedand32%didnotrespond.

B5a2.Typeofcropsdamagedbydisasters

Currentdataavailability:Datafor‘typeofcropsdamagedbydisasters’arecurrentlyavailablein50countries(representing57%ofreportingcountries).10%ofreportingcountriesindicatedthattheydonotcollectthetypeofcropsdamagedand33%didnotrespond.

B5a3.Numberofhectaresofaquaculturesdamagedbydisasters

Current dataavailability:Data for ‘numberof hectaresof aquaculturesdamagedbydisasters’ arecurrently available in 37 countries (representing 43% of reporting countries). 25% of reportingcountriesindicatedthattheydonotcollectthenumberofhectaresofaquaculturesdamagedand32%didnotrespond.

B5a4.Numberoffishingvesselsdamagedbydisasters(Fisheries)

Currentdataavailability:Data for ‘numberof fishingvesselsdamagedbydisasters (Fisheries)’ arecurrently available in 32 countries (representing 37% of reporting countries). 31% of reportingcountriesindicatedthattheydonotcollectthenumberoffishingvesselsdamagedand32%didnotrespond.

B5a5.Typeoffishingvesselsdamagedbydisasters(Fisheries)

Current data availability: Data for ‘type of fishing vessels damaged by disasters (Fisheries)’ arecurrently available in 26 countries (representing 30% of reporting countries). 38% of reportingcountries indicated that they do not collect the type of fishing vessels damaged and 32%did notrespond.

B5a6.Numberofhectaresofforestsdamagedbydisasters

Currentdataavailability:Datafor‘numberofhectaresofforestsdamagedbydisasters’arecurrentlyavailable in 43 countries (representing 49% of reporting countries). 19% of reporting countriesindicatedthattheydonotcollectthenumberofhectaresofforestsdamagedand32%didnotrespond.

B5a7.Typeofforests(incl.Plantations)damagedbydisasters

Current data availability: Data for ‘type of forests (incl. Plantations) damaged by disasters’ arecurrently available in 39 countries (representing 45% of reporting countries). 23% of reportingcountriesindicatedthattheydonotcollectthetypeofforestsdamagedand32%didnotrespond.


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B5a8.Numberoflivestocklostbydisasters

Currentdataavailability:Datafor‘numberoflivestocklostbydisasters’arecurrentlyavailablein51countries(representing59%ofreportingcountries).9%ofreportingcountriesindicatedthattheydonotcollectthenumberoflivestocklostand32%didnotrespond.

B5a9.Typeoflivestocklostbydisasters

Current dataavailability:Data for ‘typeof livestock lost bydisasters’ are currently available in 49countries(representing56%ofreportingcountries).12%ofreportingcountriesindicatedthattheydonotcollectthetypeofforestsdamagedand32%didnotrespond.

SummaryTargetB


▫ 70%onpeopleinjuredorillattributedtodisasters▫ 57-65%onpeoplewhosedwellingsweredamagedordestroyedduetodisasters.However,

whentakingproxydataonthenumberofdwellingsdamagedanddestroyed,combinedwithstatisticaldataonpopulation,70%ofcountriesareabletomeasuretherespectiveindicators.

53-57%ofcountriesreportingtotheReviewareabletodevelopabaselinewithexisting2005-2015data.

▫ 39%ofcountriescollectdataonthenumberofpeoplewhoselivelihoodsthatweredisruptedordestroyedattributedtodisasters

▫ 68%onphysicaldamagetolivelihoods,which,whencombinedwithpopulationdatacanbeusedasaproxy.

▫ 56-63%on losses to livestockandcrops, and30-49%on losses toaquacultures, forestandfishingvessels.

ThepercentageofcountriesreportingtotheReviewabletodevelopabaselinewithexisting2005-2015dataisasfollows:

▫ 45%forphysicaldamagetolivelihood▫ 25%onnumberofpeoplewithlivelihoodsdisruptedordestroyed.


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GlobaltargetC:Reducedirectdisastereconomiclossinrelationtoglobalgrossdomesticproduct(GDP)by2030.

IndicatorC2:Directagriculturallossattributedtodisasters

DataavailabilityIndicatorC-2(Directagriculturallossattributedtodisasters)

Current data availability: Data for ‘direct agricultural loss attributed to disasters’ are currentlyavailable in 59 countries (representing 68% of reporting countries). 21% of reporting countriesindicatedthattheydonotcollectthedirectagriculturallossattributedtodisastersand11%didnotrespond.




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Indicator C3: Direct economic loss due to all other damaged or destroyed productive assetsattributedtodisasters

DataavailabilityIndicatorC-3(Damagedordestroyedproductiveassets)

Current data availability: Data for ‘direct economic loss due to all other damaged or destroyedproductiveassetsattributedtodisasters’arecurrentlyavailablein36countries(representing41%ofreportingcountries).47%ofreportingcountriesindicatedthattheydonotcollectthedirecteconomiclossduetoallotherdamagedordestroyedproductiveassetsand12%didnotrespond.



AlternativedataforindicatorC3:

C3a:Physicalimpacttoallotherdamagedordestroyedproductiveassetsattributedtodisasters

Current dataavailability: Data for ‘physical impact to all otherdamagedor destroyedproductiveassetsattributedtodisasters’arecurrentlyavailablein35countries(representing40%ofreportingcountries). 47%ofreportingcountries indicatedthattheydonotcollectthephysical impacttoallotherdamagedordestroyedproductiveassetsand12%didnotrespond.




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C3a1:Numberofindustrialfacilitiesdestroyedordamagedbydisasters

Currentdataavailability:Datafor‘numberofindustrialfacilitiesdestroyedordamagedbydisasters’are currently available in31 countries (representing36%of reporting countries). 5%of reportingcountriesindicatedthattheydonotcollectthenumberofindustrialfacilitiesdestroyedordamagedand59%didnotrespond.

C3a2:Numberofcommercialbuildingsdestroyedordamagedbydisasters

Current dataavailability:Data for the ‘numberof commercial buildings destroyedor damagedbydisasters’ are currently available in31 countries (representing36%of reporting countries). 5%ofreportingcountriesindicatedthattheydonotcollectthenumberofcommercialbuildingsdestroyedordamagedand59%didnotrespond.

C3a3:Numberoftourismfacilities(suchashotel)destroyedordamagedbydisasters

Currentdataavailability:Datafor‘numberoftourismfacilities(suchashotel)destroyedordamagedbydisasters’arecurrentlyavailablein29countries(representing33%ofreportingcountries).7%ofreportingcountriesindicatedthattheydonotcollectthenumberoftourismfacilities(suchashotel)destroyedordamagedand60%didnotrespond.

IndicatorC4:Directeconomiclossinthehousingsectorattributedtodisasters

DataavailabilityIndicatorC-4(Directeconomiclossinthehousingsectorattributedtodisaster)

Current data availability: Data for ‘direct agricultural loss attributed to disasters’ are currentlyavailable in 44 countries (representing 51% of reporting countries). 37% of reporting countriesindicatedthattheydonotcollectthedirectagriculturallossattributedtodisastersand13%didnotrespond.




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C4a:Officialstatisticaldatasourcewhichprovidesaveragevaluepersquaremeterofconstruction,averagesizeofdwelling,averagevalueofdwelling

Current dataavailability: Official statistics detailing the ‘numberof dwellings thatweredamagedattributed to disasters’ are currently available in 38 countries (representing 44% of reportingcountries).44%ofreportingcountriesindicatedthattheydonotcollectthenumberofdwellingsthatweredamagedand12%didnotrespond.


C4b:Numberofdwellingsthatweredamagedattributedtodisasters

Currentdataavailability:Datafor‘numberofdwellingsthatweredamagedattributedtodisasters’arecurrentlyavailable in60countries(representing69%ofreportingcountries). 20%ofreportingcountriesindicatedthattheydonotcollectthenumberofdwellingsthatweredamagedand11%didnotrespond.


C4c:Numberofdwellingsthatweredestroyedattributedtodisasters

Currentdataavailability:Datafor‘numberofpeoplewhosedwellingsweredestroyedattributedtodisasters’arecurrentlygloballyavailable in60countries(representing69%ofreportingcountries).20%ofreportingcountriesindicatedthattheydonotcollectthenumberofmissingpersonsand11%didnotrespond.

Baseline development: Globally 45 countries (representing 52% of reporting countries) reportedhavingdatatocovertheentireperiod2005-2015.


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Indicator C5: Direct economic loss resulting from damaged or destroyed critical infrastructureattributedtodisasters

DataavailabilityIndicatorC-5(Directeconomiclossresultingfromdamagedordestroyedcriticalinfrastructure)

Currentdataavailability:Datafor‘directeconomiclossresultingfromdamagedordestroyedcriticalinfrastructure’arecurrentlyavailablein41countries(representing47%ofreportingcountries).40%of reporting countries indicated that they do not collect the direct economic loss resulting fromdamagedordestroyedcriticalinfrastructureand13%didnotrespond.




C5a:Numberofotherdestroyedordamagedcriticalinfrastructureunitsandfacilitiesattributedtodisasters

Currentdataavailability: Data for ‘numberdestroyedordamagedcritical infrastructureunitsandfacilities’arecurrentlyavailable in48countries (representing55%of reportingcountries). 30%ofreportingcountriesindicatedthattheydonotcollectthenumberofdestroyedordamagedcriticalinfrastructureunitsandfacilitiesand15%didnotrespond.




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C5b:Officialstatisticaldatasourcewhichprovidesaveragevaluepersquaremeterofconstructionfor schools, hospitals, average size of critical infrastructures (squaremeters) average value perkilometreofroadconstruction

Currentdataavailability: Official statisticaldataproviding the ‘averagevalueper squaremeterofconstruction for schools,hospitals,averagesizeofcritical infrastructures (squaremeters),averagevalueperkilometreofroadconstruction’arecurrentlygloballyavailablein27countries(representing31%ofreportingcountries).55%ofreportingcountriesindicatedthattheydonotcollectsuchdataand14%didnotrespond.


C5c:Numberofeducationalfacilitiesdestroyedordamagedbydisasters

Current data availability: Data for ‘number of educational facilities destroyed or damaged’ arecurrently available in 56 countries (representing 64% of reporting countries). 22% of reportingcountriesindicatedthattheydonotcollectthenumberofeducationalfacilitiesdestroyedordamagedand14%didnotrespond.

C5d:Numberofhealthfacilitiesdestroyedordamagedbydisasters

Currentdataavailability:Datafor‘numberofhealthfacilitiesdestroyedordamaged’arecurrentlyavailable in 56 countries (representing 64% of reporting countries). 22% of reporting countriesindicatedthattheydonotcollectthenumberofhealthfacilitiesdestroyedordamagedand14%didnotrespond.

C5e:Numberofkilometresofroadsdestroyedordamagedbydisasters

Currentdataavailability: Data for the ‘numberofkilometresof roadsdestroyedordamaged’arecurrently available in 38 countries (representing 44% of reporting countries). 11% of reportingcountriesindicatedthattheydonotcollectthenumberofkilometresofroadsdestroyedordamagedand45%didnotrespond.


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IndicatorC6:Directeconomiclosstoculturalheritagedamagedordestroyedattributedtodisasters

DataavailabilityIndicatorC-6(Damagedordestroyedculturalheritage)

Currentdataavailability: Datafor‘directeconomiclosstoculturalheritagedamagedordestroyedattributed to disasters’ are currently available in 32 countries (representing 37% of reportingcountries). 49% of reporting countries indicated that they do not collect direct economic loss toculturalheritagedamagedordestroyedand14%didnotrespond.




C6a:Numberofculturalheritagemobileandnon-mobileassetsdamagedordestroyedbydisasters

Current data availability: Data for ‘number of cultural heritage mobile and non-mobile assetsdamaged or destroyed by disasters’ are currently available in 23 countries (representing 26% ofreportingcountries). 60%of reportingcountries indicated that theydonotcollect thenumberofculturalheritagemobileandnon-mobileassetsdamagedordestroyedand14%didnotrespond.

C6b:Costsofreconstructionand/orrehabilitationofdamagedand/ordestroyedculturalheritageassets

Current data availability: Data for the ‘costs of reconstruction and/or rehabilitation of damagedand/ordestroyedculturalheritageassets’arecurrentlyavailablein24countries(representing27%ofreporting countries). 59% of reporting countries indicated that they do not collect the costs ofreconstructionand/orrehabilitationofdamagedand/ordestroyedculturalheritageassetsand14%didnotrespond.


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SummaryTargetC


▫ 68%ondirectlossestoagriculture▫ 41% on direct economic loss due to all other damaged or destroyed productive assets

attributedtodisasters▫ 51%ondirecteconomiclossinthehousingsectorattributedtodisaster▫ 69%ondamagedanddestroyeddwellings,whichcanbeusedasaproxy▫ 47%ondirecteconomiclossresultingfromdamagedordestroyedcriticalinfrastructure▫ 55%onthenumberofotherdestroyedordamagedcriticalinfrastructureunitsandfacilities▫ 65%onthenumberofhealthandeducationalfacilitiesdestroyedordamagedbydisasters.▫ 39%onthenumberofpeoplewhoselivelihoodsthatweredisruptedordestroyedattributed

todisasters▫ 68%onphysicaldamagetolivelihoods,whichcanbeusedasaproxy,whencombinedwith

populationdata.


▫ 45%onlossestoagriculture▫ 29%fordirecteconomiclossestoproductiveassets▫ 31%fordirecteconomiclossinthehousingsector▫ 45%forphysicaldamagetolivelihood▫ 25%fornumberofpeoplewithlivelihoodsdisruptedordestroyed

33-36%ofcountriesareabletodisaggregateproductiveassets lossdata intocommercial facilities,industrialfacilitiesandtourismfacilities.


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Global target D: Substantially reduce disaster damage to critical infrastructure anddisruption of basic services, among them health and educational facilities, includingthroughdevelopingtheirresilienceby2030.

IndicatorD2:Numberofdestroyedordamagedhealthfacilitiesattributedtodisasters

DataavailabilityIndicatorD-2(Damagedordestroyedhealthfacilities)

Currentdataavailability:Datafor‘numberofhealthfacilitiesdestroyedordamaged’arecurrentlyavailable in 56 countries (representing 64% of reporting countries). 22% of reporting countriesindicatedthattheydonotcollectthenumberofhealthfacilitiesdestroyedordamagedand14%didnotrespond.




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IndicatorD3:Numberofdestroyedordamagededucationalfacilitiesattributedtodisasters

DataavailabilityIndicatorD-3(Damagedordestroyededucationalfacilities)

Current data availability: Data for ‘number of educational facilities destroyed or damaged’ arecurrently available in 56 countries (representing 64% of reporting countries). 22% of reportingcountriesindicatedthattheydonotcollectthenumberofeducationalfacilitiesdestroyedordamagedand14%didnotrespond.


Resourcesneededtocollectdata:Financialresources–90%ofreportingcountries;Capacity–70%;andTechnologytransfer–65%.Notethatonly23%ofreportingcountriesrespondedtothisquestion.Indicator D4: Number of other destroyed or damaged critical infrastructure units and facilitiesattributedtodisasters

DataavailabilityIndicatorD-4(Damagedordestroyedcriticalinfrastructureunitsandfacilities)


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Currentdataavailability: Data for ‘numberdestroyedordamagedcritical infrastructureunitsandfacilities’arecurrentlyavailable in48countries (representing55%of reportingcountries). 30%ofreportingcountriesindicatedthattheydonotcollectthenumberofdestroyedordamagedcriticalinfrastructureunitsandfacilitiesand15%didnotrespond.



AlternativedataforindicatorD4:

D4a:Numberofkilometresofroadsdestroyedordamagedbydisasters

Currentdataavailability:Datafor‘numberofkilometresofroadsdestroyedordamaged’arecurrentlyavailable in 38 countries (representing 44% of reporting countries). 11% of reporting countriesindicatedthattheydonotcollectthenumberofkilometresofroadsdestroyedordamagedand45%didnotrespond.

22countriesprovidedadditionalinformationonOtherdataoncriticalinfrastructuredamagedanddestroyedcollected,namely:

• Sewagesystems,waterpipes• Bridges• Portsairports• Powersupply• Telecommunicationinstallation• Drainagesystems


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IndicatorD6:Numberofdisruptionstoeducationalservicesattributedtodisasters

DataavailabilityIndicatorD-6(Disruptionseducationalservices)

Current data availability: Data for ‘number of disruptions to educational services attributed todisasters’arecurrentlyavailablein39countries(representing45%ofreportingcountries). 40%ofreporting countries indicated that they do not collect the number of disruptions to educationalservicesattributedtodisastersand15%didnotrespond.




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IndicatorD7:Numberofdisruptionstohealthservicesattributedtodisasters

DataavailabilityIndicatorD-7(Disruptionshealthservices)

Currentdataavailability:Datafor‘numberofdisruptionstohealthservicesattributedtodisasters’arecurrentlyavailable in39countries(representing45%ofreportingcountries). 40%ofreportingcountriesindicatedthattheydonotcollectthenumberofdisruptionstohealthservicesattributedtodisastersand15%didnotrespond.




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IndicatorD8:Numberofdisruptionstootherbasicservicesattributedtodisasters

DataavailabilityIndicatorD-8(Disruptionsotherbasicservices)

Current data availability: Data for ‘number of disruptions to other basic services attributed todisasters’arecurrentlyavailablein37countries(representing43%ofreportingcountries). 41%ofreportingcountriesindicatedthattheydonotcollectthenumberofdisruptionstootherbasicservicesattributedtodisastersand16%didnotrespond.



AlternativedataforindicatorD8

D8a:Numberofdisruptionstowatersupplybydisasters

Currentdataavailability:Datafor‘numberofdisruptionstowatersupplybydisasters’arecurrentlyavailable in 33 countries (representing 38% of reporting countries). 5% of reporting countriesindicatedthattheydonotcollectthenumberofdisruptionstowatersupplybydisastersand57%didnotrespond.

D8b:Numberofdisruptionstoseweragesystembydisasters

Current data availability: Data for ‘number of disruptions to sewerage system by disasters’ arecurrently available in 27 countries (representing 31% of reporting countries). 12% of reportingcountriesindicatedthattheydonotcollectthenumberofdisruptionstoseweragesystembydisastersand57%didnotrespond.


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D8c:Numberofdisruptionstocommunicationbydisasters

Currentdataavailability:Datafor‘numberofdisruptionstocommunicationbydisasters’arecurrentlyavailable in 34 countries (representing 39% of reporting countries). 4% of reporting countriesindicatedthattheydonotcollectthenumberofdisruptionstocommunicationbydisastersand57%didnotrespond.

D8d:Numberofdisruptionstopowerandenergybydisasters

Current data availability: Data for ‘number of disruptions to power and energy by disasters’ arecurrently available in 35 countries (representing 40% of reporting countries). 3% of reportingcountries indicated that they do not collect the number of disruptions to power and energy bydisastersand57%didnotrespond.

D8e:Numberofdisruptionstotransportationbydisasters

Currentdataavailability:Datafor‘numberofdisruptionstotransportationbydisasters’arecurrentlyavailable in 33 countries (representing 38% of reporting countries). 5% of reporting countriesindicatedthattheydonotcollectthenumberofdisruptionstotransportationbydisastersand57%didnotrespond.

SummaryTargetD


▫ 64%onthenumberofdestroyedordamagedhealthandeducationalfacilitiesattributedtodisasters

▫ 55%ondestroyedordamagedcriticalinfrastructureunitsandfacilitiesattributedtodisasters▫ 45%onnumberofdisruptionstoeducationalservicesattributedtodisasters▫ 45%onnumberofdisruptionstohealthservicesattributedtodisasters▫ 43%onnumberofdisruptionstootherbasicservicesattributedtodisasters

33-40% of countries able to disaggregate by type of the basic services being disrupted (namelycommunication,watersupply,transportation,seweragesystemsandpowerandenergy).


▫ 40%forlossestohealthandeducation▫ 33%fordamagetocriticalinfrastructureunitsandfacilities▫ 30%fordisruptionstohealth,educationandotherbasicservices


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GlobaltargetE:Substantiallyincreasethenumberofcountrieswithnationalandlocaldisasterriskreductionstrategiesby2020.

Indicator E1: Number of countries that adopt and implement national disaster risk reductionstrategiesinlinewiththeSendaiFrameworkforDisasterRiskReduction2015-2030

DataavailabilityIndicatorE-1(NationalDRRStrategies)

Currentdataavailability:Datafor‘numberofcountriesthatadoptandimplementnationaldisasterrisk reduction strategies’ are currently available in 47 countries (representing 54% of reportingcountries).30%ofreportingcountriesindicatedthattheydonotcollectthenumberofcountriesthatadoptandimplementnationaldisasterriskreductionstrategiesand16%didnotrespond.


The assumption in the questionnaire of theReviewwas that few countries demonstrated alignednationaldisasterriskreductionstrategies,andsocountrieswereaskedwhatresourceswererequiredfornationalstrategiestobecomprehensivelyalignedwiththeSendaiFramework.

AdditionaldataforindicatorE1

Theadditionaldatapertaintothekeyelementsoftheindicator,andthetencorerequirementsfornationaldisasterriskreductionstrategiesthatallowqualitativemeasurementofthedegreetowhichstrategiesareinlinewiththeSendaiFramework.

E1a:NationalDRRstrategyadopted

Currentdataavailability: Datafor ‘numberofcountriesthatadoptnationaldisasterriskreductionstrategies’arecurrentlyavailable in43countries(representing49%ofreportingcountries). 7%of


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reporting countries indicated that they do not collect data on adoption of national disaster riskreductionstrategiesand44%didnotrespond.


E1b:NationalDRRstrategyimplemented

Current data availability: Data for ‘number of countries that implement national disaster riskreductionstrategies’arecurrentlyavailablein33countries(representing38%ofreportingcountries).9%ofreportingcountriesindicatedthattheydonotcollectdataontheimplementationofnationaldisasterriskreductionstrategiesand53%didnotrespond.


E1c:NationalDRRstrategyhasacleartimeframe

Currentdataavailability:Datafor‘nationalDRRstrategyhasacleartimeframe’arecurrentlyavailablein29countries(representing33%ofreportingcountries). 4%ofreportingcountriesindicatedthattheydonotcollectdataonthetimeframeofthenationalDRRstrategyand63%didnotrespond.

E1d:NationalDRRstrategyhascleartargets

Currentdataavailability:Datafor‘nationalDRRstrategyhascleartargets’arecurrentlyavailablein28countries(representing32%ofreportingcountries).5%ofreportingcountriesindicatedthattheydonotcollectdataonthetargetsofthenationalDRRstrategyand63%didnotrespond.

E1e:NationalDRRstrategyhasindicators

Currentdataavailability:Datafor‘nationalDRRstrategyhasindicators’arecurrentlyavailablein22countries(representing26%ofreportingcountries).11%ofreportingcountriesindicatedthattheydonotcollectdataontheindicatorsofthenationalDRRstrategyand63%didnotrespond.

E1f:NationalDRRstrategyintegratesDRRwithinandacrosssectors

Currentdataavailability: Datafor‘nationalDRRstrategyintegratesDRRwithinandacrosssectors’are currently available in 32 countries (representing 37% of reporting countries). None of thereporting countries indicated that theydonot collectdataon the integrationof thenationalDRRstrategywithinandacrosssectorsand63%didnotrespond.

E1g:NationalDRRstrategyembeddedwithinandacrossallsectors

Currentdataavailability: Datafor‘nationalDRRstrategyembeddedwithinandacrosssectors’arecurrently available in 30 countries (representing 34% of reporting countries). 3% of reportingcountriesindicatedthattheydidnotcollectdataontheembeddingofthenationalDRRstrategywithinandacrosssectorsand63%didnotrespond.


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E1h:NationalDRRstrategypromotespolicycoherenceandcompliance

Currentdataavailability:Datafor‘nationalDRRstrategypromotespolicycoherenceandcompliance’are currently available in 32 countries (representing 37% of reporting countries). None of thereportingcountriesindicatedthattheydidnotcollectdataonthenationalDRRstrategy’spromotionofpolicycoherenceandcomplianceand63%didnotrespond.

E1i:NationalDRRstrategydefinesrolesandresponsibilities

Current data availability: Data for ‘national DRR strategy defines roles and responsibilities’ arecurrently available in 30 countries (representing 34% of reporting countries). 3% of reportingcountriesindicatedthattheydidnotcollectdatapertainingtothenationalDRRstrategydefiningrolesandresponsibilitiesand63%didnotrespond.

E1j:NationalDRRstrategypreventsthecreationofnewrisk

Current data availability: Data for ‘national DRR strategy prevents the creation of new risk’ arecurrently available in 28 countries (representing 32% of reporting countries). 5% of reportingcountriesindicatedthattheydidnotcollectdatapertainingtothenationalDRRstrategypreventingthecreationofnewriskand63%didnotrespond.

E1k:NationalDRRstrategyreducesexistingrisk

Currentdataavailability:Datafor‘nationalDRRstrategyreducesexistingrisk’arecurrentlyavailablein32countries(representing37%ofreportingcountries).NoneofthereportingcountriesindicatedthattheydidnotcollectdatapertainingtothenationalDRRstrategyreducingexistingriskand63%didnotrespond.

E1l:NationalDRRstrategystrengthenseconomic,social,healthandenvironmentalresilience

Currentdataavailability: Datafor ‘nationalDRRstrategystrengthenseconomic,social,healthandenvironmental resilience’ are currently available in 31 countries (representing 36% of reportingcountries).1%ofreportingcountriesindicatedthattheydidnotcollectdatapertainingtothenationalDRRstrategystrengtheningeconomic,social,healthandenvironmentalresilienceand63%didnotrespond.

E1m:NationalDRRstrategybasedondisasterriskassessment

Current data availability: Data for ‘national DRR strategy based on disaster risk assessment’ arecurrently available in 29 countries (representing 33% of reporting countries). 4% of reportingcountriesindicatedthattheydonotcollectdatapertainingtothenationalDRRstrategybeingbasedondisasterriskassessmentand63%didnotrespond.

E1n:NationalDRRstrategyhasamechanismforfollow-up

Currentdataavailability:Datafor‘nationalDRRstrategyhasamechanismforfollow-up’arecurrentlyavailable in 31 countries (representing 36% of reporting countries). 1% of reporting countriesindicatedthattheydidnotcollectdataonthenationalDRRstrategyhavingamechanismforfollow-upand63%didnotrespond.


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Indicator E2: Percentage of local governments that adopt and implement local disaster riskreductionstrategiesinlinewithnationalstrategies

DataavailabilityIndicatorE-2(LocalDRRStrategiesledbylocalgovernment)

Currentdataavailability:34countries(39%ofreportingcountries)arereportingthattherearelocalDRRstrategiesledbylocalgovernments.OfthosethatreportedintheReview,10(11%ofreportingcountries)indicatethatthepercentageoflocalgovernmentswithDRRstrategiesisbetween50%and100%coverage,withtheremainderrangingbetween0and30%.


TheassumptioninthequestionnaireoftheReviewwasthatfewcountriescouldreportthatalllocaldisaster risk reduction strategieswerealignedwith theSendai Framework, and so countrieswereaskedwhatresourceswererequiredforcomprehensivealignmentofalllocalstrategies.

E2a:LocalDRRstrategiesadopted

Currentdataavailability: Data for the ‘numberof localgovernments thatadopt localdisaster riskreductionstrategies’arecurrentlyavailablein29countries(representing33%ofreportingcountries).5%ofreportingcountriesindicatedthattheydonotcollectdataonthenumberoflocalgovernmentsadoptinglocaldisasterriskreductionstrategiesand62%didnotrespond.


E2b:LocalDRRstrategiesalignedtonationalDRRstrategy

Currentdataavailability:Datafor‘numberoflocaldisasterriskreductionstrategiesthatarealignedwithnationaldisasterriskreductionstrategies’arecurrentlyavailablein26countries(representing30%ofreportingcountries).4%ofreportingcountriesindicatedthattheydonotcollectdataonthe


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alignmentoflocaldisasterriskreductionstrategieswithnationaldisasterriskreductionstrategiesand66%didnotrespond.


E2c:LocalDRRstrategiesimplemented

Currentdataavailability:Dataforthe‘numberoflocalgovernmentsthatimplementlocaldisasterrisk reduction strategies’ are currently available in 22 countries (representing 25% of reportingcountries).4%ofreportingcountriesindicatedthattheydonotcollectdataonthenumberoflocalgovernmentsimplementinglocaldisasterriskreductionstrategiesand71%didnotrespond.


SummaryTargetE


▫ 54% on number of countries that adopt and implement national disaster risk reductionstrategies

▫ 49%onnumberofcountriesthatadoptnationaldisasterriskreductionstrategies▫ 38%onnumberofcountriesthatimplementnationaldisasterriskreductionstrategies▫ 33-37%ofcountriesreportthattheirstrategiesfulfiladditionalrequirements.

▫ 39% on percentage of local governments that adopt and implement local disaster risk

reductionstrategiesinlinewithnationalstrategies

▫ 33%onnumberoflocalgovernmentsthatadoptlocaldisasterriskreductionstrategies▫ 30% on number of local disaster risk reduction strategies that are aligned with national

disasterriskreductionstrategies▫ 25%onnumberoflocalgovernmentsthatimplementlocaldisasterriskreductionstrategies


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Global targetF:Substantiallyenhance internationalcooperationtodevelopingcountriesthrough adequate and sustainable support to complement their national actions forimplementationofthisframeworkby2030

IndicatorF1:Totalofficialinternationalsupport,(officialdevelopmentassistance(ODA)plusotherofficialflows),fornationaldisasterriskreductionactions

DataavailabilityIndicatorF-1(totalofficialODAsupportfornationalDRRactions)

Currentdataavailability:Datafor‘totalofficialinternationalsupport(ODAplusotherofficialflows)fornationaldisasterriskreductionactions’arecurrentlyavailablein33countries(representing38%ofreportingcountries).38%ofcountriescollectdataonODAandonly26%alsocollectdataon‘otherofficial flows’. 42%of reporting countries indicated that they donot collect data on total officialinternationalsupportfornationaldisasterriskreductionactionsand20%didnotrespond.


Resourcesneededtocollectdata–inrespectofODA:Financialresources–92%ofreportingcountries;Capacity–73%;andTechnologytransfer–62%.Notethatonly43%ofreportingcountriesrespondedtothisquestion

Resourcesneeded tocollectdata– in respectof ‘otherofficial flows’:Financial resources–93%ofreportingcountries; Capacity–67%;andTechnology transfer–67%. Note that53%of reportingcountriesrespondedtothisquestion


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IndicatorF2:Totalofficialinternationalsupport(ODAplusotherofficialflows)fornationaldisasterriskreductionactionsprovidedbymultilateralagencies

DataavailabilityIndicatorF-2(supportfrommultilateralagencies)

Currentdataavailability:Datafor‘totalofficialinternationalsupport(ODAplusotherofficialflows)fornationaldisasterriskreductionactionsprovidedbymultilateralagencies’arecurrentlyavailablein33countries(representing38%ofreportingcountries).43%ofreportingcountriesindicatedthattheydonotcollectdataontotalofficialinternationalsupportfornationaldisasterriskreductionactionsprovidedbymultilateralagenciesand19%didnotrespond.All33countriesreportingavailabilityofdata,collectdataonODA,and23countries(representing26%ofreportingcountries)collectdataon‘otherofficialflows’providedbymultilateralagencies.




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IndicatorF3:Totalofficialinternationalsupport(ODAplusotherofficialflows)fornationaldisasterriskreductionactionsprovidedbilaterally

DataavailabilityIndicatorF-3(dataonsupportfrombilateralsources)

Currentdataavailability:Datafor‘totalofficialinternationalsupport(ODAplusotherofficialflows)fornationaldisasterriskreductionactionsprovidedbilaterally’arecurrentlyavailablein32countries(representing37%ofreportingcountries).2%ofreportingcountriesindicatedthattheydonotcollectdata on total official international support for national disaster risk reduction actions providedbilaterallyand61%didnotrespond.20ofthe32countriesreportingavailabilityofdata,collectdataonODA(representing23%ofreportingcountries),and17countries(representing20%ofreportingcountries)collectdataon‘otherofficialflows’providedbilaterally.



Very few countries collect dataon support fromother sources; exemplars of data sources include:projects,programmes,privatesectorandresearchorganizations.


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IndicatorF4:Totalofficialinternationalsupport(ODAplusotherofficialflows)forthetransferandexchangeofdisasterriskreduction-relatedtechnology

DataavailabilityIndicatorF-4(ODAsupportforthetransferandexchangeofDRRrelatedtechnology)

Currentdataavailability:Datafor‘totalofficialinternationalsupport(ODAplusotherofficialflows)for the transfer and exchange of DRR related technology’ are currently available in 20 countries(representing 23%of reporting countries). 56%of reporting countries indicated that they do notcollect data on total official international support for the transfer and exchange of DRR relatedtechnologyand21%didnotrespond.All20countriesreportingtheavailabilityofdata,collectODA(representing23%ofreportingcountries),and16countries(representing18%ofreportingcountries)collectdataon‘otherofficialflows’.




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Indicator F5:Numberof international, regionalandbilateralprogrammesand initiatives for thetransfer and exchange of science, technology and innovation in disaster risk reduction fordevelopingcountries

DataavailabilityIndicatorF-5(numberofprogrammesandinitiativesforthetransferandexchangeofscience,technologyandinnovationindisasterriskreductionfordevelopingcountries)

Currentdataavailability: Dataonthe‘numberof international,regionalandbilateralprogrammesand initiatives for the transferandexchangeof science, technologyand innovation indisaster riskreduction for developing countries’ are currently available in 26 countries (representing 30% ofreporting countries). 49% of reporting countries indicated that they do not collect data on the‘numberofinternational,regionalandbilateralprogrammesandinitiatives’and21%didnotrespond.23ofthe26countries(26%ofreportingcountries)reportingavailabilityofdata,collectnumberofinternationalandregionalinitiatives,ofwhich21countries(24%ofreportingcountries)collectdataonbilateralinitiatives.




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Indicator F6: Total official international support (ODA plus other official flows) for disaster riskreductioncapacity-building

DataavailabilityIndicatorF-6(totalofficialODAsupportfordisasterriskreductioncapacitybuilding)

Currentdataavailability:Datafor‘totalofficialinternationalsupport(ODAplusotherofficialflows)fordisasterriskreductioncapacity-building’arecurrentlyavailablein26countries(representing30%ofreportingcountries). 49%ofreportingcountriesindicatedthattheydonotcollectdataontotalofficialinternationalsupportfordisasterriskreductioncapacity-buildingand21%didnotrespond.All26countriesreportingavailabilityofdata,collectdataonODA,and20countries(23%ofreportingcountries)collectdataon‘otherofficialflows’.




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IndicatorF7:Numberofinternational,regionalandbilateralprogrammesandinitiativesfordisasterriskreduction-relatedcapacity-buildingindevelopingcountries

Data availability Indicator F-7 (number of programmes and initiatives for DRR related capacity building indevelopingcountries)

Currentdataavailability: Dataonthe‘numberof international,regionalandbilateralprogrammesand initiatives for disaster risk reduction-related capacity-building in developing countries’ arecurrently available in 29 countries (representing 33% of reporting countries). 46% of reportingcountriesindicatedthattheydonotcollectdataonthe‘numberofinternational,regionalandbilateralprogrammesandinitiatives’and21%didnotrespond.25ofthe29countriesreportingtheavailabilityof data (representing 29% of reporting countries) collect data on the number of internationalinitiatives,26(representing30%ofreportingcountries)onregionalinitiatives,and23(representing26%ofreportingcountries)onbilateralinitiatives.




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Indicator F8: Number of developing countries supported by international, regional and bilateralinitiativestostrengthentheirdisasterriskreduction-relatedstatisticalcapacity

DataavailabilityIndicatorF-8(initiativestostrengthenyourDRRrelatedstatisticalcapacity)

Currentdataavailability: Dataonthe‘numberofdevelopingcountriessupportedbyinternational,regionalandbilateralinitiativestostrengthentheirdisasterriskreduction-relatedstatisticalcapacity’arecurrentlyavailable in25countries(representing29%ofreportingcountries). 51%ofreportingcountriesindicatedthattheydonotcollectdataonthe‘numberofinternational,regionalandbilateralprogrammesandinitiatives’and21%didnotrespond.17ofthe25countriesreportingavailabilityofdata (20% of reporting countries) specify that they collect data on ‘international and regionalprogrammes and initiatives’ and 18 (21% of reporting countries) on ‘bilateral programmes andinitiatives’.




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SummaryTargetF

CriticalgapsexistintheabilityofcountriestocollectdatarequiredtoreportontherecommendedindicatorsforTargetF.OfthosecountriesthatreportedtotheReview,thepercentagesthatcollectdataareasfollows:

▫ 38%ontotalofficialinternationalsupport(ODAplusotherofficialflows)fornationaldisasterriskreductionactionsprovidedbymultilateralagencies

▫ 37%ontotalofficialinternationalsupport(ODAplusotherofficialflows)fornationaldisasterriskreductionactionsprovidedbilaterally

▫ 23%ontotalofficialinternationalsupport(ODAplusotherofficialflows)forthetransferandexchangeofDRRrelatedtechnology

▫ 30%on total official international support (ODAplus other official flows) for DRR capacitybuilding

▫ 29-33%onthenumberofinternational,regionalandbilateralprogrammesandinitiativesforcapacity building, technology transfer and support to statistical capacity in developingcountries

Between18%and28%ofcountriesreportingtotheReviewarecurrentlyabletodevelopabaselineformonitoringtheseindicators.Approximately50%ofreportingcountriesplantocollecthistoricaldataforthefurtherdevelopmentofbaselinesforthisTargetF.


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GlobaltargetG:Substantiallyincreasetheavailabilityofandaccesstomulti-hazardearlywarningsystemsanddisasterriskinformationandassessmentstothepeopleby2030.

IndicatorG2:Numberofcountriesthathavemulti-hazardmonitoringandforecastingsystems

DataavailabilityIndicatorG-2(Multi-hazardmonitoringandforecastingsystems)

Currentdataavailability:Datafor‘numberofcountriesthathavemulti-hazardearlywarningsystems’arecurrentlyavailable in54countries(representing62%ofreportingcountries). 17%ofreportingcountriesindicatedthattheydonotcollectdataonthenumberofcountriesthathavemulti-hazardearlywarningsystems(MHEWS)and21%didnotrespond.31ofthe54countrieswithearlywarningsystems,takeintoaccountthepotentialinterrelatedeffectsofmultiplehazards.




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Of the 69Member States that gave an indication of the principle hazards affecting each country,meteorological,hydrological,climatological,man-made,geophysicalandenvironmentalhazardswereidentifiedbyatleast72%ofreportingcountries.

Thesefeatureintheearlywarningsystemsofthe54countriesthatresponded.ThemostapparentdiscrepancybetweenaffectationandinclusioninnationalMHEWS,isinrespectofman-madehazards,whereprevalence(80%)isnotmatchedbyearlywarningcapabilities(31%).


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IndicatorG3:Numberofpeopleper100,000thatarecoveredbyearlywarninginformationthroughlocalgovernmentsorthroughnationaldisseminationmechanisms

DataavailabilityIndicatorG-3(Monitoringandforecastingsystemscoveringallgeographicalareasaffectedbyoneormoreofthemajorhazards)

Current data availability: Data for the ‘number of people per 100,000 that are covered by earlywarninginformationthroughlocalgovernmentsorthroughnationaldisseminationmechanisms’arecurrently available in 54 countries (representing 62% of reporting countries). 17% of reportingcountries indicated that they do not collect data on the number of people per 100,000 that arecoveredbyearlywarninginformationand21%didnotrespond.

23ofthe54countrieswithearlywarningsystems(26%ofreportingcountries)collectdataonthenumberofpeoplewhohaveaccesstoearlywarninginformationthroughlocalgovernments,and24countries(28%ofreportingcountries)collectdataonthenumberofpeoplewhohaveaccesstoearlywarninginformationthroughnationaldisseminationmechanisms.

44ofthe54countriesthathavedataonnumberofpeoplecoveredbyearlywarninginformation(51%ofreportingcountries)havedataonmonitoringandforecastingsystemscoverageofallgeographicalareasaffectedbyoneormoreofthemajorhazards.41countries(47%ofreportingcountries)specifythattheyhavedatapertainingtothepopulationinareaspronetohazardsthatarecoveredbyearlywarninginformation.




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IndicatorG4:Percentageoflocalgovernmentshavingaplantoactonearlywarnings

DataavailabilityIndicatorG-4(dataonpercentageoflocalgovernmentshavingaplantoactonearlywarnings)

Currentdataavailability:Dataonthe‘percentageoflocalgovernmentshavingaplantoactonearlywarnings’arecurrentlyavailablein36countries(representing41%ofreportingcountries). 38%ofreportingcountriesindicatedthattheydonotcollectdataonpercentageoflocalgovernmentshavingaplantoactonearlywarnings,and21%didnotrespond.

54countries(62%ofreportingcountries)reportedthattheycollectdataonlocalgovernmentplanstoactonearlywarnings.Theseplanstakeintoaccountthepotentialinterrelatedeffectsofmultiplehazardsin38countries(44%ofreportingcountries).



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Indicator G5: Number of countries that have accessible, understandable, usable and relevantdisasterriskinformationandassessmentavailabletothepeopleatthenationalandlocallevels.

DataavailabilityIndicatorG-5(riskinformationandassessmentaccessible,understandableandusablebythepeople)

Currentdataavailability: Data for the ‘numberofcountries thathaveaccessible,understandable,usableandrelevantdisasterriskinformationandassessmentavailabletothepeopleatthenationalandlocallevels’arecurrentlyavailablein63countries(representing72%ofreportingcountries).7%ofreportingcountriesindicatedthattheydonotcollectdataon‘accessible,understandable,usableandrelevantdisasterriskinformationandassessment’and21%didnotrespond.

40ofthe63countries(46%ofreportingcountries)reportthatriskinformationandassessmentareaccessible, understandable, and available in the public domain. 36 countries (41% of reportingcountries)reportthatriskinformationandassessmentsareavailabletoallpeopleatnationalandlocallevels.



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Thereisastrongcorrelationbetweenthemajorhazardsincludedinriskassessmentandinformationandaffectation,althoughlesssoforman-madehazards.

IndicatorG6:Percentageofpopulationexposedtooratriskfromdisastersprotectedthroughpre-emptiveevacuationfollowingearlywarning

Dataavailability IndicatorG-6(dataonpercentageofpopulationexposedoratriskfromdisastersprotectedthroughpre-emptiveevacuationfollowingearlywarning)

Currentdataavailability:Datarequiredtocalculatethe‘percentageofpopulationexposedtooratriskfromdisastersprotectedthroughpre-emptiveevacuationfollowingearlywarning’arecurrentlyavailable in 23 countries (representing 26% of reporting countries). 53% of reporting countriesindicated that they do not collect data on ‘percentage of population exposed to or at risk fromdisastersprotected’and21%didnotrespond.


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50countries(representing57%ofreportingcountries)reporthavingdataonthenumberofpeopleevacuatedattributedtodisasters.


SummarytargetG

TheReviewdemonstratesthewidevariationsintheavailabilityofthedatarequiredtoreportagainstthe recommended indicators of the target. Of those countries that reported to the Review, thepercentagesthatcollectdataareasfollows:

▫ 62%onnumberofcountriesthathavemulti-hazardearlywarningsystems▫ 62%on the number of people per 100,000 that are covered by earlywarning information

throughlocalgovernmentsorthroughnationaldisseminationmechanismso 31of54countrieswithearlywarningsystems(36%ofreportingcountries),takeinto

accountthepotentialinterrelatedeffectsofmultiplehazards▫ 41%onthepercentageoflocalgovernmentshavingaplantoactonearlywarnings▫ 62%onlocalgovernmentplanstoactonearlywarnings

▫ 72% on accessible, understandable, usable and relevant disaster risk information and

assessmentavailabletothepeopleatthenationalandlocallevels

o 46%ofreportingcountriesreportthatriskinformationandassessmentisaccessible,understandableandinaformthatcanbeused

o 41%ofreportingcountriesreportthatriskinformationandassessmentisavailabletoallpeopleatnationalandlocallevels

▫ 23%onthepercentageofpopulationexposedtooratriskfromdisastersprotectedthroughpre-emptiveevacuationfollowingearlywarning

o 57%onnumberofpeopleevacuatedattributedtodisasters.

Approximately23%ofcountriesreportingtotheReviewareabletodevelopbaselinesformeasuringtherecommendedindicatorsofTargetG.


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Chapter2. Dataquality

IncallingfortheSendaiFrameworkDataReadinessReview(theReview),MemberStatessoughttoimprovetheunderstandingofthestateofnationaldisaster-relateddataavailability,toidentifythedata gaps, as well as the resources required to be able tomonitor and report on the indicatorsmeasuringtheSendaiFrameworkglobaltargets.However,feedbacktotheReviewhasadditionallyidentifiedthatdataavailabilitycannotbedissociatedfromaspectsofdataqualityandaccessibility.

The implementation,monitoringandreportingof theSendaiFrameworkandthe2030Agenda forSustainableDevelopmentispredicatedonthegenerationandprovisionof,andaccessto,highqualitydisaster-relateddatathatwillalloweffectivecollation,comparisonandanalysisbyMemberStatesandotherstakeholders,bothwithinacountrycontext,aswellasbetweencountriesandregions.Thiswillbemademuchmoredifficultwithout theapplicationofcommonlyagreedmethodologiesandqualitystandards.

Theendorsementoftheglobal indicatorframeworkfortheSDGs6bytheUnitedNationsStatisticalCommission (UNSC)7means that thedata required tomeasurekey indicators for fiveof thesevenglobaltargetsoftheSendaiFrameworkwillalsobeusedtomeasuredisaster-relatedtargetsofSDGs1,11and13.MemberStatesdeterminedthattheglobalindicatorframeworkdevelopedforthe2030Agenda for Sustainable Development, should be supported by robust data, underpinned, whererelevant,bytheFundamentalPrinciplesofOfficialStatistics.Furthermore,tosupportimplementationatalllevels,the2030Agendaalsoincludedtheneedtoexploitthecontributiontobemadebyawiderangeofdata,includingEarthobservationsandgeospatialinformation.

Recognising the need for quality and consistent methodological approaches, in support of theoperationlisationoftheglobalindicatorstomeasureachievementoftheglobaltargetsoftheSendaiFramework and the SDGs, the OIEWG called upon the UNISDR to undertake work with relevanttechnical partners8 , inter alia to develop minimum standards, methodologies and metadata fordisaster-relateddata,statisticsandanalysis.

Whilethemajorityofexistingdisaster-relateddataaresourcedfromnationaldisastermanagementinstitutions,sectorallineministries,aswellastheemergencyservices,theintegrationoftheSendaiFramework indicators within the global indicator framework of the SDGs, will prompt increasingcollaborationwithnationalmappingandgeo-informationinstitutions,andtheNSOs,inthefollow-uptotheSendaiFramework.

6developedbyMemberStates,regionalandinternationalorganisationsintheInter-agencyandExpertGrouponSDGsIndicators(IAEG-SDGs)7http://unstats.un.org/unsd/statcom/48th-session/TheUNSCisthehighestdecisionmakingbodyforinternationalstatisticalactivities-settingstatisticalstandards,developingconceptsandmethodsandimplementingatthenationalandinternationallevels.8includingnationalgovernmentfocalpoints,nationaldisasterriskreductionoffices,nationalstatisticaloffices,theDepartmentofEconomicandSocialAffairsandotherrelevantpartners


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2.1. Disasterlossaccounting,geospatialdata,bigdataandstatistics

As the OIEWG concluded its programme of work, collaboration with the international statisticalcommunityintensifiedsoastopromotethealignmentofframeworks,standardsandclassificationsfordisaster-relatedstatistics.ThisbuiltontheworktodateledbytheNSOsandDisasterManagementAgencies(DMAs)oftheEuropeandAsia-Pacificregions,andrespectivelysupportedbythestatisticaldivisionsof theUnitedNationsEconomicCommission forEurope (UNECE)and theUnitedNationsEconomicandSocialCommissionforAsiaandthePacific(ESCAP).

As the gatekeepers of social, economic and environmental statistics, NSOs arewell positioned torespond to important data needs arising from the Sendai Framework, the 2030 SustainableDevelopmentAgenda,theParisAgreementandotherglobalinitiatives.TheConferenceofEuropeanStatisticians (CES) for instance, has supported countries in developing national road maps 9 fordevelopingclimate-changerelatedstatistics,interaliatoassistprioritizationofcountriesinlinewithinternational climate reporting requirements, to understand data gaps and needs, and evaluateavailableresources.

MemberStatesneverthelessrecognizedthattheNSOsalonewouldnotbeabletocapturetheentiretyof data required to track progress towards the Goals and Targets of the SDGs, and that a globalindicator framework should capture themultifaceted and ambitious aspirations for the continueddevelopmentofnationsandsocieties10.

They recognized thecritical importanceof“transparentandaccountablescaling-upofappropriatepublicprivatecooperationtoexploitthecontributiontobemadebyawiderangeofdata,includingEarthobservationandgeospatialinformation,whileensuringnationalownershipinsupportingandtrackingprogress”,capitalizingonmoderndataprocessingtechniquesabletomanagelargevolumesofdata.

EffectivereportingofprogresstowardtheglobaltargetsoftheSDGsandtheSendaiFrameworkusingtheagreedindicatorsrequirestheuseofmultipletypesofdata, including:disaster lossaccountingandstatisticaldatasources11,aswellastheuseofnewsourcesofdata–notablyEarthobservations(EO)andgeospatialinformation(GI).

The data quality elements to be considered for location or geospatial data include: positionalaccuracy,logicalconsistencyandcompleteness.

9ExampleRoadMapsforDevelopingClimateChange-RelatedStatistics.UNECEExpertForumforProducersandUsersofClimateChange-RelatedStatistics.March201710EarthObservationsinsupportofthe2030AgendaforSustainableDevelopment,March2017,GEOundertheEO4SDGInitiative11suchastraditionalnationalaccounts,householdsurveysandroutineadministrativedata


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2.2. Disaster-relatedearthobservationdata

Earthobservation (EO) data and information –which include satellite, airborne, land andmarine-baseddata,aswellasmodeledoutputs–cantrackchangesinhighresolutionandinrealtime,andarefundamentaltodefiningtheenvironmentaldimensionoftheSDGsandtheSendaiFramework.ProvidingahistoricalrecordofchangestotheEarth–suchaslandusechange,flood,droughtandotheraspectsofdisaster–earthobservationscanbecombinedwithdemographic, statistical,andotherdata, to supportdata-drivendecision-makingandactionacrossgovernment institutionsandprogrammes.

EO has the potential to expandmonitoring capabilities across sectors and providemore dynamicdisaggregateddatatosupportnationsandotherstakeholdersininformeddecision-making,planning,and inmaking the necessary adjustments and course corrections to enhance the sustainability ofcollectiveeffortstoimplementthe2030Agenda12andtheSendaiFramework.

A number of NSOs are exploring the integration of open EO data and statistical data in existingdecision-makingarchitecture.ThecomplementarityofEOwithtraditionalstatisticalmethodsmeansthatEOcanoffervalidationoptionsofin-situdatameasurements(suchassurveyandinventorydata),can communicate and visualize the geographic dimensions and context of the SDGs and SendaiFrameworkindicators,andwhereappropriate,providedisaggregationoftheindicators13.

TheintegrationofEOandGI,usingtechniquescapableofprocessinglargevolumesofdata,canhelpshapehowsustainabledevelopmentistracked,andhowwell-beingismonitored14.SinceEOandGIareoftencontinuousintheirspatialandtemporalresolutions,theiruseinmonitoringtheSDGsandtheSendaiFrameworkcanprovideinsightsinthetrendsinthereductionofdisasterriskandeffortstoimplementthe2030Agenda.

EOandGIwillamplifymonitoringcapabilitiesatlocal,national,regionalandgloballevels,andacrosssectors,andcansignificantly reduce thecostburden tocountriesofmonitoring theSDGsand theSendaiFramework.Satellitedata,forinstance,isavailableatallscales(fromlocaltoglobal),canbederived in relatively short timeframes, and offer consistency and comparability underpinned bylengthytimeseries,allowinggovernmentstotrackprogressandestablishbaselines15.AnincreasinglydiversearrayofEOdataareavailable,withdozensofgeophysicalparametersthatcouldbebroughttobearinmonitoringimplementationofthe2015frameworks.

Freeandopenaccessdataisontheincrease–takeUSmissiondataorthedatapolicyofEurope’sCopernicusprogramme,forinstance–theprospectsforaccesstotheEOdatarequiredbydevelopingcountries have improved considerably. High performance computing and cloud storage andprocessingcapabilitiesaremakingitsimplertohandleandapplysuchlargeandcomplexdatasets.

Earthobservation-derivedmonitoringandmethodologiesarebeingexploredbytheIAEG-WorkingGrouponGeospatialInformation(WGGI)andtheUNcustodianagencies.Thesemethodologieswill

12http://www.data4sdgs.org/earth-observation-data-to-support-the-sdgs13EarthObservationsinsupportofthe2030AgendaforSustainableDevelopment,March2017,GEOundertheEO4SDGInitiative14http://www.earthobservations.org/documents/publications/201703_geo_eo_for_2030_agenda.pdf15Idem.GEOundertheEO4SDGInitiative.March2017


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be integratedintostatisticalpracticestandardsandmanualsandsupportedbyfreeandopendatasourcesfromglobaldatastores.

With the integrationofanumberof thekey indicatorsof theSendaiFrameworkwithin theglobalindicator framework of the SDGs, the degree towhich Earth observation-derivedmonitoring andmethodologiescanalsobedevelopedforSendaiFrameworkindicatorsshouldbeexplored.

Specificapplicationsofearthobservationdatafordisasterriskreduction.

The Group on Earth Observations (GEO)16 has a number of disaster-related activities underwaythroughtheGEOWorkProgramme:

▫ DataAccessforRiskManagement(GEO-DARMA)17fosterstheuseofEOdataandEO-basedriskinformationbyendusers and includes anEO-related capacity-building component. It aims tosupportoperationalriskreductionactivitiesfocusingonenduserprioritiesinlinewiththeSendaiFramework, together with end-to-end projects that rely on the use of multiple sources ofobservation data. Methodologies have been defined and tested by the Committee on EarthObservationSatellites(CEOS)anditspartners.

16http://www.earthobservations.org/index.php17http://www.earthobservations.org/activity.php?id=110

TheNationalStatisticsOfficeinColombia(DANE)undertookapilotprojecttoexploretheuseofsatellite imagestoimproveandeventuallyproduceofficialstatisticsfortheSustainableDevelopmentGoals(SDGs)interalia.

DANEfoundthatintermsofgeospatialdata,imageswithsimilarspatialandspectralresolutions are required formulti-temporal studies. Improvements are required,includingforfreedatasourcedfromtheLandsatplatform,toovercomeissuessuchascloudshadowanddatagaps.

DANE also concluded that population data integrity issues could potentially beaddressed by using data from administrative registers, although such registersrequiretransformationbyNSOsbeforebeingintegratedintoofficialstatistics.Thetransformationprocesswouldincludegeo-referencingregisters,andconclusiononuse,processing,custody,confidentialityanddisseminationpolicies,amongothers.

Alternative sources and procedures can assist in comparing results and guidingdecision-making,however,validationofBigDataforexample,ismandatoryifthesearetobeusedforthegenerationofofficialstatistics. Severalmethodshavebeenpilotedtovalidatethedata,e.g.the‘Shape-Theme-Edge-Position’(STEP),‘confusionmatrixes’interalia.

Source: Use of Satellite Images to Calculate Statistics on Land Cover and Land Use.GEO,Colombia


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▫ Geohazard Supersites andNatural Laboratories (GSNL) international partnership18the aim ofwhich is to improve geophysical scientific research and geohazard assessment in support ofdisasterriskreduction.Itpromotesabroadinternationalscientificcollaborationandopenaccesstoavarietyofspace-andground-baseddata,focusingonareaswithscientificknowledgegapsandhighrisklevels:theSupersitesandtheNaturalLaboratories.

▫ Global EarthObservations Systemof Systems (GEOSS)19is a set of coordinated, independentEarthobservation,informationandprocessingsystemsthatinteractandprovideaccesstodiverseinformation for a broad range of users in both public and private sectors. GEOSS links thesesystemstostrengthenthemonitoringofthestateoftheEarth,andensuresthatthesedataareaccessible,ofidentifiedqualityandprovenance,andinteroperabletosupportthedevelopmentof toolsandthedeliveryof informationservices. GEOSS increasesourunderstandingofEarthprocesses and enhances predictive capabilities that underpin sound decision-making.GEOSS Data Sharing Principles (2016-2025) will include Open Data by default, making dataavailable as part of the GEOSS Data Collection of Open Resources for Everyone (Data-CORE)withoutchargeorrestrictionsonreuse,subjecttotheconditionsofregistrationandattributionwhenthedataarereused.

2.3. Officialstatisticsanddisaster-relateddatafortheSendaiFrameworkandtheSDGs

To support the development of multi-purpose datasets, of adequate quality able to supportsimultaneousmonitoringandreportingagainsttheSDGs,theSendaiFrameworkandpotentiallytheParis Agreement, itwill be essential to integrate disaster loss information into official statistics isessential.Otherdata,suchageospatialdataorbigdatacanbeusedtoincreasedataavailability,foraslongastheyfulfilminimumcriteriaforapplication.Ingeneratingofficialstatistics,theNSOsapplysevencomponentsofstatisticalquality: Relevance,Accuracy,Timeliness,Punctuality,Accessibility,Clarity,andComparability.

Dataqualityisthereforeakeyaspectthatcountrieswillneedtoaddresswithrelevantstakeholdersinstrengtheningmonitoringandreportingcapabilities.Guidelinesondatastandards,methodologiesformeasuringtheindicatorsandtheprocessingofstatisticaldatafortheglobaltargetsoftheSendaiFramework,arecurrentlybeingdeveloped.ThisisacoordinatedundertakingoftheUNISDR,MemberStates and relevant technical partners, including the international statistical community for thedevelopmentofdisaster-relatedstatistics.

In the development of national disaster loss accounting systems, methodologies vary amongcountries. ThemajorityofexistingdatasetsworldwideusetheDesInventarmethodology,which iscurrently being applied in 98 national disaster loss databases 20 . DesInventar considers lossesassociatedwithdisastersatall scales,andentailsaminimumdisaggregationof lossesby location,eventandhazardtype.AsidentifiedinstudiescarriedoutbytheUnitedNationsEconomicandSocialCommissionforAsiaandthePacific(UNESCAP)andUnitedNationsDevelopmentProgramme(UNDP)18http://www.earthobservations.org/activity.php?id=11519https://www.earthobservations.org/geoss.php20http://Desinventar.net/index_www.html


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infivecountriesintheAsiaandPacific,theanalysisofdirectandindirectimpactsfromdisastersisconductedonaspecificcase-by-caseapproach.Ingeneral,theDamageandLossAssessment(DALA)methodologydevelopedbyECLACisnotbeingconsistentlyappliedinallcountries.Statisticsonrisksand vulnerability to disasters are dependent to a large extent on the availability of detailedinformationonpopulation.

Substantiveworkdevelopingdisaster-relatedstatisticstomeetthereportingrequirementsofboththeSDGsandtheSendaiFrameworkisongoing.TheUNEconomicCommissionforAsiaandthePacific(UNESCAP)Asia-PacificExpertGrouponDisaster-relatedStatisticshasbeguntheworkofdevelopingacoresetofdisaster-relatedstatistics,ofwhichadraftDisaster-RelatedStatisticsFrameworkisapart.

Source:DraftDisaster-relatedStatisticsFramework,UNESCAPThisworkwassupportedbyaseriesofpilotstudiesin2016,inwhichdisasterimpactdatabaseswerereviewedinfourAsia-Pacificcountries:Bangladesh,Fiji,Indonesia,andthePhilippines.Thesynopsisandrecommendationsfocusonthequalitativeaspectsofthedata–comparability,robustness,andrelevance–andassessavailabilityofdatainrelationtotheSendaiFrameworkindicators,includingdisaggregation.

Inparallel,theBureauoftheConferenceofEuropeanStatisticians(CES)establishedtheTaskForceonmeasuringextremeeventsanddisaster21inFebruary2015.Itsprincipalobjectivebeingtoclarifytheroleofofficialstatisticsinprovidingdatarelatedtoextremeeventsanddisasters,andidentifypracticalsteps for NSOs, in coordination with national agencies responsible for disaster management, tosupportdisastermanagementandriskreduction.

Recognizingthatpartnershipsthatarealreadyinevidenceinsomecountriesandregionswillneedtobe replicatedat scale in a coherentmanner,NSOsat theUnitedNationsWorldData Forum2017establishedaglobalpartnership fordisaster-relatedstatistics toassist indelivering theoutcomescalledforbyMemberStatesinintergovernmentalworkinggroups.

21Membership:NSOsofArmenia,Italy(chair),Kazakhstan,Mexico,RepublicofMoldova,NewZealand,Nigeria,SouthAfricaandTurkey.Internationalorganizations:FAO,theJointResearchCentreoftheEuropeanCommission(JRC),Eurostat,UN-ECLAC,UN-ESCAP,UNISDR,WHOandtheWMO.


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Chapter3. Dataaccessibility

Manycountriesfacenumerouschallengesinrespectofdataaccessibility.Asobservedinanumberofcases,includinginUNISDR’sworksupportingthedevelopmentofdisasterlossdatabases,datamaybeavailablebutnotfreeofcharge.Forexample,governmententitiesmaybechargedapremiumtoreceive(official)statisticaldata.

An example from a UNESCO-led initiative assessing data access, availability and quality for thedevelopmentofafloodforecastingmodelforNamibiain201422,revealedseriouschallengesregardingaccesstoavailablemeteorologicalandhydrologicalnationaldataandinformationcriticalforeffectivefloodanddroughtmodeling.

22DataAccess,AvailabilityandQualityAssessmentfortheDevelopmentofaFloodForecastingModelforNamibia,FinalReport,April2014,UNESCO

TheUNESCO-ledsurvey inNamibia requested categorical informationabout thetypesofdatacollected,dataqualities(suchastheaverageamountofmissingdatapointsandaveragelengthofrecord,thenumericalareaofdatacollection),andtheeaseofinformationsharing.

Thesurveyfound thatspecificdetailswere lacking– includingthoserequiredtoevaluate how to improve the data, and determine optimal flood forecastingmethodsforNamibia. Severalgovernmentservicesexpressedconcern thatdatasharing may discredit their work. In addition, institutional proprietary issuesimpededthegrantingoffreeaccesstodataforfloodmodelingpurposes.

Data sharing between government institutions in some countries can bechallengingevennonexistent.Aminorityofagencieshaveasetprocedurefordataaccess,andevenifinformalexchangesoccur,publicationorsecondaryusemaybedifficultwithout officialauthorisation. Similar impedimentswere found to existwhenitcametointernationaldatasharing(betweenNamibiaandAngola);whichgiventhetransboundarynatureoffloodingintheregionpresentedacriticaldatagap.

This case illustrates how limited data accessibility and data sharing – betweengovernment institutions within and between countries – weakens the dataenvironment,withnegativeeffectsonmonitoringandreporting,theapplicationofdatafordisasterriskreduction.


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AGreenPaperproducedbythegovernmentofthePhilippinesintheaftermathofTyphoonYolanda23identified critical gaps in data availability, quality and accessibility, particularly with regard toadministrativeboundaries,keyinfrastructurelocationsandroadnetworks,aswellasinconsistenciesofsuchdatabetweendifferentnationalinstitutions.Limitationsthatseverelyhamperedtheabilityofthegovernmenttomakeinformeddecisionsandtakeappropriateandtimelyaction.

Somecountrieshavebeenproactive inestablishingdata-sharingprotocolsandportals to improvedataaccessibility.Experienceinthesecontextshasshownthattoensurethatdatamanagementandsharing at national level attains the levels of openness and quality that is required for effectivedecision-making,delivery,monitoringandreporting,thismustoftenbeprecededbyextensiveandexhaustiveadvocacy.

23IncreasingAvailability,Quality,andAccessibilityofCommonandFundamentalOperationalDatasetstoSupportDisasterRiskReductionandEmergencyManagementinthePhilippines|GreenPaper1(v1.2:29thMay2014)http://www.gaia-geosystems.org/PROJECTS/SIIEM/PHL/Green_Paper_DSWD-SIIEM_305014.pdf

Inacountrywithsuchhighexposuretonaturalhazards,theconclusionsofthisstudypromptedthegovernmentofthePhilippinestotakeconcreteactions:

1. Itdevelopedastrategicframeworkongeospatial informationandservicesfordisasters under the umbrella of the United Nations Committee of Experts onGlobalGeospatialInformationManagement(UN-GGIM).Thiswork,co-chairedbythe National Mapping and Resource Information Authority (NAMRIA) aims atensuring that accurate, timely, available, quality and accessible geospatialinformationandservices,areprovidedinacoordinatedway,todecisionmakersandoperationalleadspriorto,duringandpostdisasters.Draftpoliciesaimingat improving thedataavailability,qualityandaccessibilityare already available, while the development of supporting material forimplementationatthetechnicallevelisongoing‡.

2. Establishment of the Information Management Technical Working group(IM-TWG)bytheOfficeofCivilDefence.TheTWGworkstoensuretheavailabilityandaccessibilityofqualitygeospatial,statisticalandhumanitarianinformationacrosstheentireemergencycycle‡‡.

The work being undertaken by the Philippines is informing the revision of relatedguidancematerials,includingguidelinesonCommonOperationalDatasets(CODs)inDisaster Responseof the Inter-AgencyStandingCommittee (IASC) – currentlybeingrevisedbyUNOCHA.‡http://ggim.un.org/UN_GGIM_wg5.html‡‡http://digitaleducation.net/im-twg/


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Chapter4. Applicationofdata

TheCapeTownGlobalActionPlanforSustainableDevelopmentData24underlinedtheimportanceofqualityandtimelydataasvital forenablinggovernments, internationalorganisations,civil society,privatesectorandthegeneralpublictomakeinformeddecisionsandtoensuretheaccountabilityofrepresentativebodies.Effectiveplanning,follow-upandreviewoftheimplementationofthe2030AgendaforSustainableDevelopmentandtheSendaiFrameworkrequiresthecollection,processing,analysis and dissemination of an unprecedented amount of data and statistics at local, national,regionalandgloballevelsandbymultiplestakeholders.

However,ifthegoalsoftheSendaiFrameworkandthe2030AgendaforSustainableDevelopmentaretobeachieved,itisnotsufficientsimplytoimprovetheprovisionofqualityandtimelydata,thesedata must be accompanied by the political and operational commitment to leverage data tosystematically inform policy, planning and investment decisions. As the Global Partnership forSustainableDevelopmentDatastates,itiscrucialthatdataandevidence-basedpolicy-makingmakesitontothepoliticalagenda25.

Howeverthechallengeisgreat.ThereportAWorldthatCounts|MobilisingtheDataRevolutionforSustainableDevelopment26identifieshugeandgrowinginequalitiesinaccesstodataandinformationandintheabilitytouse it. Datadoesneedimproving,buttoooften,existingdataremainunusedbecausetheyarereleasedtoolateornotatall,notwelldocumentedandharmonized,ornotmadeavailable to theappropriate institutions/ individuals,orat the levelofdetailneeded fordecision-making.Thisisnosmallundertaking,astheauthorsofthereport–theIEAG-identified,significantinvestmentwillbeneededtobreakdownthebarriersbetweenpeopleanddata,throughinteraliaeducationprogrammesaimedat improvingthecapacityanddata literacyofpeople, infomediariesandpublicservants.

Dataneedstobegeneratedwithusersinmind.Toooftendataprovidersunderinvestinidentifyingandengagingthoseinapositiontousedatatodriveaction.Datathatcannotbetranslatedintoactionbecauseoflackofoperationaltoolstoleveragethem,entailsalosstosocietyintermsofthebenefitsthatcouldhavebeengained.Agencieswithamandatetocollectpublicinformationarenotalwayswell-suitedtoensuringtheirinformationisusedbystakeholders.

These are aspects that have been included in feedback to the Review. Two key constituenciesidentifiedbycountriesandstakeholderswhereinimprovedcollaborationisconsideredfeasibleandcouldbringimmediategains,isinthecollaborationbetweennationalstatisticaloffices(NSOs)andnationaldisasterriskmanagementinstitutions.

24preparedbytheHigh-levelGroupforPartnership,CoordinationandCapacity-Buildingforstatisticsforthe2030AgendaforSustainableDevelopment(HLG-PCCB)https://undataforum.org/WorldDataForum/launch-of-the-cape-town-global-action-plan-for-sustainable-development-data/25http://www.data4sdgs.org/data-in-action/#sthash.xiJ320OD.dpuf26preparedattherequestoftheUnitedNationsSecretary-General,bytheIndependentExpertAdvisoryGrouponaDataRevolutionforSustainableDevelopment(IEAG).November2014


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4.1. National statistical offices and national disaster risk managementinstitutions

The improvement of disaster-related data literacy, and its application in decision-making by allrelevantgovernmentinstitutions,hasbeenparticularlychallenging.Notwithstandingdatagenerationand provision aspects discussed above, the transmission of quality, relevant information toappropriateusersinatimelymanner,andinaformthatfacilitatesconsiderationindecision-making,requiresdedicatedattention.

Thechallenges in informationexchangeandcoordinationbetweenNSOsandNDMAsareacase inpoint.StudiesconductedbyUNESCAPandtheUNDPoncurrentpracticesincoordinationbetweenthe NSOs and national disaster management agencies (NDMAs) in five countries in the Asia andPacific27identifiedanumberoffactorsthatwillneedtobeaddressedifcollaborationistobeimproved.These include: traditional institutional structures andmandates; commonbaselines; capacities tomutually support and complement respective data and information sets; or information sharingprotocolsetc.

TheintegrationofmetricsfortheglobaltargetsoftheSendaiFrameworkwithintheglobalindicatorframeworkfortheSDGsprovidestheopportunityformanyoftheaspectstobeaddressedaspartofcountries’ broader follow-up to the 2015 agreements; and an appetite for joint analysis anddevelopment of applied information is observed in many countries. In 2015 and 2016, UNISDRtogetherwithUNDPundertookninepilotexercisestestingthesuiteofoptionalnational indicatorsproposedformeasuringnationallydeterminedtargetsindisasterriskreduction.Inmanycountries,theNSOswereprominent,providingprofoundcontributionstodevelopingacommonunderstandingoftheneedsandgaps,aswellasofcapacity(technicalandHR)andinformationsharingconstraints.

Assessing the impacts of disasters depends on a variety of baseline information that come fromvarious data sources, including official statistics. NSOs have sophisticated mechanisms for thecollectionofcomplexdatasetsrelevanttotheanalysisofdisasterimpact,interaliaonpopulationandeconomicactivity.PopulationCensusdatacanbeavailableatdetailedgeographiclevelswhichmakesitanimportantresource,butmaysufferissuesofaffectationandfrequencyofupdate.Issuesthatnational disastermanagement institutionsmay be in a position to redress, given that they oftenmanageorcollatedatabasesondisasterevents,affectedhouseholdsandindividuals,andextentofdamageanddestructiontoproperty.

AswasidentifiedintheoutcomeandgoaloftheSendaiFramework,therealizationofitsaspirationsis contingent upon government leadership and political commitment, including to improving theevidencebaseforeffectivepolicy,planninganddecision-makingtoeffectivelymanagedisasterrisk.Hencetheworkthathasbeeninitiatedbytheinternationalstatisticalcommunity–includingtheTaskForce of the Conference of European Statisticians, the Asia Pacific Expert Group, and the globalpartnershipcalledforbyNSOsattheWorldDataForum(seeabove)–hasthepossibilitytotransformtherelationshipbetweentheNDMAsandothergovernmentinstitutions,inthatitprovidesthebasisfor the application of the Fundamental Principles of Official Statistics in developing data andinformationsetssupportingtheimplementationoftheSendaiFrameworkandtheSDGs.

27Indonesia,Kiribati,Mongolia,theRepublicofKoreaandSriLanka


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Thiswillnothappenwithoutsignificantinvestmentintheenhancementofcapabilitiesformonitoring,evaluation and analysis within government institutions with responsibility for understanding andmanagingdisasterrisk.SotheinclusionofkeyglobalindicatorsfromtheSendaiFrameworkwithinthe global indicator framework for the 2030 Agenda for Sustainable Development, presents realopportunitiestoenhancetheapplicationofdisaster-relateddatainriskinformeddecision.

TheCapeTownGlobalActionPlanforSustainableDevelopmentDataforinstance,inStrategicArea4seeksto:Developandpromoteinnovativestrategiestoensureproperdisseminationanduseofdataforsustainabledevelopment. ThePlan identifiesaseriesofkeyactions thatareofpertinence forcountriesandstakeholders,including:

▫ Promotethedevelopmentoftechnologicalinfrastructureforbetterdatadissemination.

▫ Developeffectivecommunicationanddatadisseminationstrategiesandguidelinesforpublicandprivatedialogueorientedtopolicy-makers,legislators,themedia,thegeneralpublic,theeconomy,etc.

▫ Leveragetheuseofe-learningplatformstoshareknowledgebetweenproducersandusers.

▫ Developandimplementeducationalprogrammestoincreasedataliteracyanddatamisuserecognitionandempowerinstitutionsandindividualstousestatisticseffectivelyintheirowndecisions.


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Chapter5. Conclusions

The indicators recommended by the OIEWG were endorsed by the UN General Assembly at thebeginningofFebruary2017,whichallowedlittletimefordetailedanalysisandfeedbackbeforethe2017GlobalPlatformforDisasterRiskReduction.Despitetheconstrainedtimetable,87nationsfromallregionsparticipatedintheReview–anexcellentresponse,providingavaluablereflectiononthestateofoverallreadinessofMemberStatestoreport.

The findings of the Review provide an indication of the considerable work that will need to beundertakenforcountriestobeabletomonitortheagreedindicatorsinthemanneranticipatedbythetwointergovernmentalworkinggroups–theOIEWGandtheIAEG-SDGs.

Dataavailability:

Thefigure28belowsummarisescountries’assessmentoftheavailabilityofdatatomonitorandreportontheindicatorsmeasuringtheglobaltargetsoftheSendaiFramework(anddisaster-relatedtargetsoftheSDGs).

▫ Ingeneral,mostcountriescollectacriticalmassofdisasterlossdata–TargetsAtoD–withTargetsAandBmostwellserved;83%ofcountries identifydataavailabletoreportonthenumberofdeathsattributedtodisasters,and66%areabletoreportonnumberdirectlyaffected.

▫ Thepracticeofdisasterlossaccountingiswellestablishedinmanycountries;however,datasetsare typically more available on physical damage and human impact, and less available oneconomic losses, livelihoods, losses of specific assets and infrastructure, cultural heritage anddisruptionstobasicservices.

28ProxyindicateswherequestionswereaddedtotheReviewwhendatawereassumedtobeinconsistentorscarce,soastoallowanassessmentofdataavailabilityandsourcesthatcouldserveasaproxyfortheindicator.


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▫ 40-60%ofcountriesarecurrentlyabletodevelopabaselineformostindicatorsforthedisasterloss-relatedglobalTargetsA-D;althoughmanyfewer(29-33%)candevelopabaselineforcriticalinfrastructure,disruptionstobasicservices,lossestoproductiveassetsandthehousingsector.

▫ SendaiFrameworkTargetsE-Gconcernpolicyandother input indicators,andcountries reportwidevariationindataavailability.

▫ Thisrangesfrom57-72%fordatapertainingtoearlywarningsystems,riskinformationandpeopleevacuatedwithinTargetG,to39-54%ofcountriesfordataonnationalandlocalDRRstrategiesunderTargetE.

▫ Lowestdataavailability-withalittleover20%ofcountries–wasreportedfortheindicatorsforTargetF.

Resourcerequirements:

Countryresponsestotheresourcerequirementstoredressthedatagapsidentifiedwereorganizedusing the threemaincategoriesusedtomeasure internationalcooperation:a) financial resources,b)technologytransfer,andc)capacitybuilding.

▫ >90%ofcountriesindicatedtheneedforfinancialresourcesfirstandforemosttocoverthedatagapsobservedformostindicators.Thiswasfollowedbycapacityandthentechnologytransferresources.

▫ Internationalcooperation–financialresourcesareidentifiedasthecriticalresourcerequiredtoredressthedatagap;technologytransferisconsideredmoreimportantthancapacitybuilding.

▫ Earlywarningsystems–allreportingcountriescitecapacitybuildingandtechnologytransferasthecriticalresourcesrequiredtomeetthegapsindata;94%ofreportingcountriescitefinancialresources.

▫ Risk information – financial resources and capacity are indicated as being equally important;followedbytechnologytransfer.

Thedeterminantsofdataavailabilityarenumerous,andincludecollectionpractices,organizationalculture, data sharingmechanismsor the lack thereof, cost (for example, of establishing collectionsystems,housingdataandpurchasingdata),privatesectorproprietaryconcernsanddatagovernance.

DataavailabilitygapsshouldbeaddressedbyMarch2019,ifcountriesaretobeabletoreportagainsttheSendaiFrameworkglobalTargetsasplanned.

Dataquality,accessibilityandapplication:

▫ Dataqualityvariesbetweenreportingcountries,andalthoughalmost60%ofallMemberStatesemployastandardizedandcomparablemethodologytoproduce lossdata(usingDesInventar),manyreportingcountriesusedifferentmeasurementanddatahostingsystems,andaggregatedatadifferently.

▫ This will impact the ability to evaluate and report on the data. Internationally agreed uponmethodologiesandminimumstandards,includingforbasicdisasterstatistics,wouldsupportdatastandardizationandquality.


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▫ Thetaskathandwillnotbelimitedtoimprovingdataavailability,butshouldalsoseektoremoveinstitutionalbarriers,andcreatecommondatasharingplatformsandprotocolstoenhancedataaccessibilityandapplicability for, andby,all relevantgovernmentministries,departmentsandbodies.

▫ The integration of disaster-related data within national statistical systems can bring qualitydividendsthroughapplyingtheprinciplesofofficialstatistics.

▫ Additionalvaluemaybegainedbyemployingotherdataandinformation,forexampleinutilisinggeospatialand‘bigdata’.Thesewillrequireaseparateconcertedeffortandpossibleeconomiccost.

▫ Improved disaster-related data and statistics and associated information products, enhancesrelevance and usability, which in turn can support amplified evidence-based disaster riskmanagement.Improvingdatacollectionandstandardizingdatawouldallowforamorepertinentassessmentoftheefficacyandimpactofpolicy,investmentandpractice,andidentifyaspectsforimprovement.

Inconclusion,theReviewidentifiesthatcriticaldatagapsexistinspecificareasofdisasterloss,inallareas of international cooperation, and for many aspects of early warning, risk information anddisasterriskreductionstrategies. TheReviewconfirmsthatunlessgapsindataavailability,qualityand accessibility are addressed, countries’ ability to assure accurate, timely and high qualitymonitoringandreportingofimplementationacrossallTargetsandPrioritiesoftheSendaiFrameworkwillbeseverelyimpaired.

Suchactionwillneedtobeundertakeninacoordinatedmannertoallowthedevelopmentofconsistentandcomparabledataatthenational,sub-national,aswellasthegloballevels.Theneedforcollectiveeffortinenhancingaspectsofdataavailability,accessibilityandquality,hasbeenrecognizedbyanumberofkeycommunities–includingthenationalstatisticaloffices,andnationalmappingandgeo-informationagencies.

AGlobalPartnershipforDisaster-relatedDataforSustainableDevelopmentwouldfacilitateacollaborative,multi-stakeholdereffort(bringingtogethergovernments,internationalorganizations,theprivatesector,civilsocietygroups,andthestatisticsanddatacommunities),tooptimizeandoperationalizeexistingandfuturedisaster-relateddatainsupportofnationalandsub-nationaldisasterriskreductionefforts,andinsodoing,enhance:

i. dataavailability,includingdevelopingnewdatasets

ii. dataquality,includingtheintegrationofdisaster-relateddatainofficialstatistics

iii. dataaccessibility,includingaddressinggeospatialaspectsofdata,and

iv. theapplication/useofdata,includingthedevelopmentofcommondatasharingplatforms,protocolsandminimumstandards.


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ANNEX1–ReportingCountries

ThefollowingcountriescompletedtheSendaiFrameworkDataReadinessReview2017duringtheperiod20February2017to20April2017:

Afghanistan, Albania, Anguilla, Antigua andBarbuda, Australia, Austria, Bahrain, Bangladesh,Belarus, Bhutan, Bolivia, Brazil, Burundi, Cambodia, Canada, CentralAfricanRepublic, China,Colombia,CostaRica,Croatia,Ecuador,Egypt,Estonia,Ethiopia,FederatedStatesofMicronesia,France, Georgia, Germany, Guatemala, Guyana, Honduras, Hungary, Jamaica, Japan, Jordan,Kuwait,Lao,Lebanon,Liberia,Lithuania,Malaysia,Maldives,Mauritius,Mongolia,Montenegro,NewZealand,Nigeria,Norway,Palestine,Poland,Portugal,Qatar,RepublicofKorea,Romania,Saint Kitts and Nevis, Saint Vincent and Grenadines, Slovenia, Sri Lanka, Swaziland, Sweden,Switzerland,Tanzania,Thailand,theNetherlands,Tonga,TrinidadandTobago,UnitedKingdomofGreatBritainandNorthernIreland,Ukraine,Zimbabwe.

The following countriespartially completed theSendai FrameworkDataReadinessReview2017duringtheperiod20February2017to20April2017:

Argentina,Barbados,CookIslands,DemocraticPeople’sRepublicofKorea,Indonesia,Iraq,Ireland,Latvia,Mauritania,Mexico,Myanmar,Nauru,Pakistan,Philippines,SaudiArabia,Sudan,Turkey,Tuvalu.

TotalnumberofreportingcountriestotheSendaiFrameworkDataReadinessReview2017–87.

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UNISDR Annual Report 2016

Disaster-related Data for Sustainable Development Sendai ...global... · baselines for measuring the global targets of the Sendai Framework. This Summary Report addresses the key

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