Impact of Malaria Control on Mortality and Anemia among Tanzanian Children Less than Five

24 Pages·2015·1.17 MB·English

RESEARCHARTICLE
Impact of Malaria Control on Mortality and
Anemia among Tanzanian Children Less than
–
Five Years of Age, 1999 2010
PaulSmithson1*,LiaFlorey2,S.ReneSalgado3,ChristineL.Hershey3,HonoratiMasanja1,
AchuytBhattarai4,AlexMwita5,PeterD.McElroy4,TanzaniaMalariaImpactEvaluation
ResearchGroup¶
1 IfakaraHealthInstitute,DaresSalaam,UnitedRepublicofTanzania,2 ICFInternational,Rockville,
Maryland,UnitedStatesofAmerica,3 UnitedStatesAgencyforInternationalDevelopment,U.S.President’s
a11111 MalariaInitiative,Washington,DC,UnitedStatesofAmerica,4 CentersforDiseaseControlandPrevention,
U.S.President’sMalariaInitiative,Atlanta,Georgia,UnitedStatesofAmerica,5 NationalMalariaControl
Programme,MinistryofHealthandSocialWelfare,DaresSalaam,UnitedRepublicofTanzania
¶MembershipoftheTanzaniaMalariaImpactEvaluationResearchGroupisprovidedinthe
Acknowledgments.
*[email protected]
OPENACCESS
Abstract
Citation:SmithsonP,FloreyL,SalgadoSR,Hershey
CL,MasanjaH,BhattaraiA,etal.(2015)Impactof
MalariaControlonMortalityandAnemiaamong
TanzanianChildrenLessthanFiveYearsofAge, Background
1999–2010.PLoSONE10(11):e0141112.
doi:10.1371/journal.pone.0141112 MainlandTanzaniascaledupmultiplemalariacontrolinterventionsbetween1999and
2010.Weevaluatedwhether,andtowhatextent,reductionsinall-causeunder-fivechild
Editor:LuziaHelenaCarvalho,CentrodePesquisa
ReneRachou/FundaçãoOswaldoCruz(Fiocruz- mortality(U5CM)trackedwithmalariacontrolintensificationduringthisperiod.
Minas),BRAZIL
Received:January23,2015 Methods
Accepted:October5,2015 Fournationallyrepresentativehouseholdsurveyspermittedtrendanalysisformalariainter-
ventioncoverage,severeanemia(hemoglobin<8g/dL)prevalence(SAP)amongchildren
Published:November4,2015
6–59months,andU5CMratesstratifiedbybackgroundcharacteristics,age,andmalaria
Copyright:Thisisanopenaccessarticle,freeofall
endemicity.Prevalenceofcontextualfactors(e.g.,vaccination,nutrition)likelytoinfluence
copyright,andmaybefreelyreproduced,distributed,
transmitted,modified,builtupon,orotherwiseused U5CMwerealsoassessed.Populationattributableriskpercentage(PAR%)estimatesfor
byanyoneforanylawfulpurpose.Theworkismade malariainterventionsandcontextualfactorsthatchangedovertimewereusedtoestimate
availableundertheCreativeCommonsCC0public
magnitudeofimpactonU5CM.
domaindedication.
DataAvailabilityStatement:Alldatasetsrelatedto
Results
theunderlyingfindingsinthisreportareavailableat
thefollowingICFInternationalsites:the1999 Householdownershipofinsecticide-treatednets(ITNs)rosefromnearzeroin1999to64%
TanzaniaReproductiveandChildHealthSurvey
(95%CI,61.7–65.2)in2010.Intermittentpreventivetreatmentofmalariainpregnancy
(http://dhsprogram.com/data/dataset/Tanzania_
Standard-DHS_1999.cfm?flag=0.2004/5),the reached26%(95%CI,23.6–28.0)by2010.Sulfadoxine-pyrimethaminereplacedchloro-
TanzaniaDemographicandHealthSurvey(http:// quinein2002andartemisinin-basedcombinationtherapywasintroducedin2007.SAP
dhsprogram.com/data/dataset/Tanzania_Standard- amongchildren6–59monthsdeclined50%between2005(11.1%;95%CI,10.0–12.3%)
DHS_2004.cfm?flag=0.2007/8),theTanzaniaHIV/
and2010(5.5%;95%CI,4.7–6.4%)andU5CMdeclinedby45%betweenbaseline
AIDSandMalariaIndicatorSurvey(http://
dhsprogram.com/data/dataset/Tanzania_Standard- (1995–9)andendpoint(2005–9),from148to81deaths/1000livebirths,respectively.
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 1/24
ImpactofMalariaControlinTanzania
AIS_2007.cfm?flag=0),andthe2010Tanzania Mortalitydeclined55%amongchildren1–23monthsofageinhighermalariaendemicity
DemographicandHealthSurvey(http://dhsprogram. areas.AlargereductioninU5CMwasattributabletoITNs(PAR%=11)withothermalaria
com/data/dataset/Tanzania_Standard-DHS_2010.
interventionsaddingfurthergains.Multiplecontextualfactorsalsocontributedtosurvival
cfm?flag=0).
gains.
Funding:Thehouseholdsurveysincludedinthis
analysiswerefundedinpartbytheUnitedRepublic
Conclusion
ofTanzaniaMinistryofHealthandSocialWelfare,U.
S.AgencyforInternationalDevelopment,United MarkeddeclinesinU5CMoccurredinTanzaniabetween1999and2010withhighimpact
NationsChildren'sFund,TheGlobalFund,
fromITNsandACTs.High-riskchildren(1–24monthsofageinhighmalariaendemicity)
DepartmentforInternationalDevelopment,United
NationsPopulationFund,WorldFoodProgramme, experiencedthegreatestdeclinesinmortalityandSAP.Malariacontrolshouldremainapol-
UnitedNationsDevelopmentProgramme,andIrish icyprioritytosustainandfurtheraccelerateprogressinchildsurvival.
Aid.Theauthorsreceivednospecificfundingforthis
work.
CompetingInterests:Theauthorshavedeclared
thatnocompetinginterestsexist.
Introduction
Malariacontrolinsub-SaharanAfricaattainedunprecedentedmomentumduringthedecade
after2000[1–3].DonorassistanceformalariacontrolinAfricaincreased10-foldbetween
2000and2010,from$200milliontonearly$2billionannually[4].Mostsupportcameafter
2005fromnationalgovernments,theGlobalFundtoFightAIDS,TuberculosisandMalaria,
theWorldBankBoosterProgram,andtheU.S.President’sMalariaInitiative.Theseresources
permittednationwidescale-upofhighlyeffectivemalariacontrolinterventions,including
insecticidetreatedbednets(ITNs),indoorresidualspraying(IRS)ofhouseholdwallswith
insecticides,intermittentpreventivetreatmentofmalariaduringpregnancy(IPTp),andarte-
misinin-basedcombinationtherapy(ACT)[4,5].NumerousAfricancountriesareontrackto
meettheWorldHealthAssemblytargetofa75%reductioninmalariaincidenceby2015[2].
However,evaluationsofthepublichealthimpactofmalariacontrolatnationalscalearesparse
[6–8].
Atleast97%oftheTanzaniapopulationlivedinareaswithintenseperennialmalariatrans-
missionin2000[9,10].Overthefollowingdecade,fundingformalariacontrolincreaseddra-
matically—fromlessthan$1millionin2000tomorethan$30millionin2006andnearly$140
millionin2010–acumulativeinvestmentof$452million(S1AandS1BFig).Thisfunding
facilitatedtheadoptionandimplementationofaseriesofmalariacontrolpoliciesandstrate-
gies(Fig1)[11,12].SocialmarketingofITNsandinsecticidetreatmentkitsbeganin2000[13].
Ayearlater,highlevelsofchloroquineresistancepromptedashifttosulfadoxine-pyrimeth-
amine(SP)asfirst-linetherapyforuncomplicatedmalaria[14,15].In2002,NMCP’sfirst
Medium-termStrategicPlan2002–7wasimplementedandIPTpusingSPwasadoptedtocon-
trolmalariainpregnancy.Large-scaleITNdistributionbeganwiththeTanzaniaNational
VoucherSchemetargetedtopregnantwomen[16]in2004andtheninfantsin2007[17].A
secondMedium-termStrategicPlan2008–13calledforanACT(artemether-lumefantrine)as
first-linetherapy(from2007),RDTsatperipheralhealthfacilities(from2009),andatargetof
80%ITNcoverageby2010.Distributionof8.6millionfreelong-lastinginsecticidalnets
(LLINs)toallchildrenlessthanfiveyearsofagebeganin2009andwascompletedin2010
[18].Laterthatyearauniversalcoveragecampaignbegantodistribute18millionfreeLLINsto
coverallremainingsleepingspaces[19].IRSwasimplementedinKagerabeginningin2007,
andadvancedtoMwanzaandMara(threeoftheoriginal21administrativeregions)by2010,
butcoveredonly6%ofthenationalpopulation.
By2010malariainterventioncoveragehadbeenbroughttolevelswhereanimpactmayrea-
sonablybeexpected.Afteradecadeofstagnation,all-causeunder-fivechildmortality(U5CM)
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 2/24
ImpactofMalariaControlinTanzania
Fig1.Timelinedepictingyearswhennational-levelimplementationofspecificmalariacontrol
policiesandinterventionsbeganinMainlandTanzania,2000–2010.
doi:10.1371/journal.pone.0141112.g001
declineswerealreadyevidentby2005[20],andcurrentUNICEFdataindicateTanzanialikely
achievedtheirMillenniumDevelopmentGoal4(MDG4)targetofatwo-thirdsreductionin
U5CMbetween1990and2015:modeledratesofU5CMdeclinedfrom166to132to54deaths
per1000livebirthsin1990,2000,and2012,respectively(a68%decline)[21].
TheRollBackMalaria(RBM)Partnership’sMonitoringandEvaluationReferenceGroup
(MERG)recommendsU5CMastheprimaryindicatorofmalariacontrolimpact[22].This
recommendationisbasedonour:1)inabilitytomeasuremalaria-specificmortalityinmost
developingcountries,2)expectationthatrapidscale-upofinterventionstohighlevelswill
resultinmeasurabledeclinesinU5CM,and3)recognitionthatmalariahasasubstantialindi-
recteffectonmortalitythatwillbecapturedinU5CMestimates[23].TheMERGapproach
assumesthataportionofthedecliningtrendsinU5CMcanbeplausiblyattributedtomalaria
controleffortsifimprovementsinpopulation-levelmeasurementsarefoundinstepsalongthe
causalpathway(e.g.,increasedITNcoverageandreducedsevereanemiaprevalence)[24].As
U5CMratesandsevereanemiaprevalencedeclineatanacceleratedpace,precededbyrapid
scale-upofinterventioncoverage,theconclusionthatmalariacontroleffortsreducedmalaria-
specificmortalitybecomesmoreplausible.Thisplausibilityisstrengthenediftrendsinother
contextualfactors(e.g.,immunization,micronutrientsupplementation,climate)affectingmor-
talitydidnotappreciablychangeduringthesameperiod.
OurobjectivewasasummativeevaluationtodetermineifTanzania’sscale-upofmalaria
interventionsduring1999–2010helpedacceleratedeclinesinmalariamorbidity(particularly
severeanemia,acommonmanifestationofPlasmodiumfalciparuminfectioninhightransmis-
sionareas[25,26])andU5CM.TheevaluationisrestrictedtoTanzaniaMainlandsinceZanzi-
barhasaseparateMinistryofHealthanditsNationalMalariaControlProgramfolloweda
differenttrajectory.
Methods
AllsurveyswereapprovedbytheethicalreviewboardofTanzania'sNationalInstitutefor
MedicalResearchandICFInternational'sinstitutionalreviewboard.Verbalinformedconsent
wassoughtfromallsurveyrespondents,withaninformedconsentstatementsignedbyeach
surveyinterviewer.Allanalyseswereperformedonanonymizedandde-identifieddatasets.
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 3/24
ImpactofMalariaControlinTanzania
Fig2.ConceptualframeworkforconstructinganadequacyandplausibilityassessmenttosupporttheMainlandTanzaniamalariaimpact
evaluation.
doi:10.1371/journal.pone.0141112.g002
Evaluationdesign
Ouroverallevaluationdesignembracedbothadequacyandplausibilityaspects(Fig2)[24].
Ourinitialadequacyassessmentexaminedtemporaltrendsinmalariainterventioncoverage
andwhetherdeclinesinsevereanemiaprevalence(SAP)andU5CMwereobserved.Thisstep
alsoexploredinequitiesinmalariainterventioncoverageacrossfourbasicdemographicchar-
acteristicsandwhetherthesameinequitiesexistedforSAPandU5CMrates.Adequacyassess-
mentslackcomparisongroupsanddonotaddressnon-malarialcontextualfactorsthoughtto
affecttheimpactindicatorsofinterest[24].Theplausibilityassessmentincludedaseriesof
analysestocomplementtheadequacyassessmentandgarnergreaterconfidencethataportion
ofthereductionsinSAPandU5CMwereduetomalariainterventionscale-up[27].Theplau-
sibilityassessmentstemsfromHill’sspecificitycriteria[28].Thiseffortcontributedtothecon-
sistencyandspecificityofourplausibilityassessment.Weassessedwhethermalariacontrolled
tomoreaccelerateddeclinesinSAPandU5CMinyounger(<23months)versusolder(24–59
months)children,andamongthoselivinginhigherversuslowerareasofmalariaendemicity.
Trendsinprevalenceofothercontextualfactorswithrecognizedpotentialtocontributealter-
nativeexplanationsforchangesinU5CMwereexplored.Finally,weexaminedwhetherthe
increaseinmalariainterventioncoveragewascompatiblewiththetimingandmagnitudeof
reductionsinSAPandU5CM,whilealsoconsideringchangesinrelevantcontextualfactors.
Datasourcesandindicators
Malariainterventioncoverage,malariaparasitemia,SAP,all-causemortality,demographic
characteristics,andcoverageofotherhealthinterventionswereobtainedfromfour,nationally-
representativehouseholdsurveysin1999,2004/5,2007/8,and2010thatincluded2747,7847,
6332and7720mainlandhouseholds,respectively[29–32].Eachsurveyincludedasampling
designthatwas100%inclusiveofall20regions,plusDaresSalaam.Allsurveysoccurred
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 4/24
ImpactofMalariaControlinTanzania
duringthedrierseason(Sep-Feb),butfieldworkforthe2010surveyextendedthreemonths
longer.MalariainterventioncoveragewasmeasuredusingsixstandardRBMindicators[33]
includingtheproportionof:householdsthatownedatleastoneITN;children<5yearsofage,
pregnantwomen,anddefactosurveypopulationwhosleptunderanITNthenightbeforethe
survey;womenwhoreceivedIPTp-2forpregnancieswithinthepasttwoyears;andchildren
<5yearsofagewithfeverinthepasttwoweekswhoreceivedtreatmentwithafirst-lineanti-
malarialthesameornextdayafterfeveronset.Capillarybloodspecimenswereobtainedvia
fingerorheelprickfromchildren6–59monthsofagewhosleptineachhouseholdthenight
1
beforethesurvey.Hemoglobin(Hb)concentrationwasmeasured(HemoCue instrument)
andsevereanemiadefinedasHb<8.0g/dL,adjustedforaltitude[34,35].Ahistidine-richpro-
1
tein2-basedRDT(Paracheck )detectedP.falciparumparasitemia(2007/8surveyonly).
Contextualfactors(socio-economic,maternalandreproductivehealth,nutrition,immuni-
zation,othermorbidities)weresourcedfromthesamesurveysdescribedabove[29–32].Addi-
tionalpublishedsourcesarecitedfortrendsinrainfall,growthingrossdomesticproduct
(GDP)[36],andHIV/AIDSindicators[37–39].Rainfalldata(1983–2010)wereobtainedfrom
approximately200ground-basedstationsoftheTanzaniaNationalMeteorologicalAgency.
Minimum/maximumtemperaturesweregeneratedbycombiningweatherstationmeasure-
mentswithNASA’slandsurfacetemperatureestimateswithadigitalelevationmodel.
Analyses
Trendsininterventioncoverage,SAPandU5CM. Foreachsurvey,RBMcorecoverage
indicatorswerecalculatedwithcorresponding95%confidenceintervals(CIs)usingstandard
errorscorrectedformulti-stagesurveydesign[34].SAPestimateswith95%CIswerecalculated
forchildren6–59monthsofage.DirectestimatesofU5CMand95%CIswerecalculatedwith
thesyntheticcohortlifetableapproachusingbirthhistoriesover0–4yearspriortoeachsur-
vey.Achi-squaretestforlineartrendinproportionsassessedchangesininterventioncoverage,
SAPandU5CM.ITNuse,SAP,andU5CMwerefurtherstratifiedbyfourkeydemographic
characteristicsincludingsex(male/female),residence(urban/rural),wealthquintile,maternal
education(none,primaryincomplete,primarycomplete,secondary+)andplottedwithcorre-
sponding95%CIstoassesstrendsinequity.Under-five,infant,andneonatalmortalityrates
with95%CIswereplottedtoreflecttemporaltrendsfrompre-baseline[40,41]through
endpoint.
Plausibilityassessment(1):Temporaltrendsbyage. Malariamorbidityandmortality
arehighlyage-dependent,withyoungerchildren(<24months)atgreaterriskforbothout-
comes,particularlyinareaswithhigherintensityP.falciparumtransmission[42–44].SAPwas
stratifiedbyage(6–23and24–59months).Furthermortalityanalysesexcludedneonatal
deathssinceaminimalproportionofthesedeathswerelikelyattributabletomalaria[45].Thus
all-causemortalitywasdichotomizedat1–23and24–59monthsofage.
Plausibilityassessment(2):Temporaltrendsbymalariaendemicity. SAPandmortality
rateswerestratifiedbylevelofmalariaendemicitytoassesswhethergreaterimpactwas
observedinhigherendemicityareas.Tanzaniamainlandregionsweredividedintothree
endemicitycategories:“lower”(7regions,prevalence0–9.2%),“moderate”(7regions,preva-
lence10.4–21.9%),and“higher”(6regions,prevalence28.7–32.6%)usingregion-specificP.fal-
ciparumprevalencefrom2007/8(theonlynationalsurveytoincludethisindicator).Survey-
specificadjustedoddratios(ORs)forsevereanemiaandrateratios(RRs)forall-causemortal-
itywereobtainedusinglogisticandCoxproportionalhazardsregressionmodels,respectively,
tocontrolforthefourkeydemographiccharacteristicsdescribedabove,malariaendemicity
level,andage(logisticmodelonly).
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 5/24
ImpactofMalariaControlinTanzania
Plausibilityassessment(3):Temporaltrendsbyageandmalariaendemicitycom-
bined. AgeandmalariaendemicityexhibiteddifferentialriskforSAPandall-causechild
mortality.Trendsintheseoutcomeswereassessedseparatelyforchildren1–23monthsofage
andchildren24–59monthsofage,stratifiedbyendemicity.
Plausibilityassessment(4):Accountingforcontextualfactors. Climatedatawereexam-
inedinathree-stepanalysis(IRIReport,supplementalonlinematerial).TheClimateSuitabil-
ityforMalariaTransmissionTool[46]wasfirstusedtoestimatethenumberofmonthsduring
theyearwhenclimatologicalconditionsweresuitableformalariatransmission.AWeighted
AnomalyofStandardizedPrecipitation(WASP)Tool[47,48]estimatedthechangeinrainfall
overtheevaluationperiodrelativetobaseline(1995–99).WASPandtemperaturedatawere
combinedtoassesswhethertheprevailingclimateinTanzaniawassuitableformalariatrans-
missionrelativetobaseline.TheClimateAnalysisToolexploredannualprecipitationandtem-
peraturedataaccordingtotemporalandspatialfactorsaffectingmalariatransmission.Change
inpercapitaGDP(constantprices)wasexpressedascumulativechangebetween1995–1999
and2005–2009.Forallothercontextualfactors,baseline(1999)andendpoint(2010)values
with95%CIsandpercentchanges(relative)wereobtained.Differencesinbaselineandend-
pointvalueswereassessedwithaZ-testusingthestandarderrorsintheZ-scoreformula.Fora
smallsubsetoffactorslacking1999and2010values(e.g.,HIV/AIDSindicators)theearliest
andlatestavailableestimateswereusedforbaselineandendpoint.
Plausibilityassessment(5):Magnitudeofreductionsinall-causemortality. Wederived
theattributablechangesinU5CMduetotheobservedincreasesinmalariainterventioncover-
agebetween1999and2010andforcontextualfactorswithsignificantchangeoverthesame
period.Thesereductionswerederivedusingpopulationattributableriskpercentage(PAR%)
calculationsbasedonprevalenceofexposure(E)andnon-exposure(Ē)toeachfactorin1999
and2010,respectively,andpublishedestimatesofrelativerisk(RR)forall-causemortality
associatedwiththatexposurefactor[49–59].ThepublishedRRestimateforeffectivefirst-line
antimalarials(specificallyACTs)usedmalaria-specificmortalityratherthanall-causemortal-
ity.TheunadjustedPAR%isusefulforcomparingthecrudemarginaleffectsofmultipleinter-
ventionsandwascalculatedas:
PAR% ¼ E(cid:1) þ RRðE Þ (cid:2) ½E(cid:1) þ RRðE Þ(cid:3) = E(cid:1) þ RRðE Þ
2010 2010 1999 1999 1999 1999
[60].
Itisanestimateofhowthechangeinprevalenceofeachriskfactor(interventionorexpo-
sure)andknownstrengthoftheassociationwithmortalityresultedineitherincreasesor
decreasesinratesofU5CM.ThePAR%providesaninformativelinkbetweencausalityand
publichealthaction[61,62].
Results
Adequacyassessment:Trendsininterventioncoverageandratesof
SAPandU5CM
Malariainterventioncoveragegenerallyimprovedbetween1999and2010(Table1).House-
holdownershipofITNsandITNusebychildrenlessthan5yearsofage,pregnantwomen,
andthedefactopopulationasawholeincreasedby61,62,55,andapproximately45percent-
agepoints,respectively.AmarkedincreaseinITNcoveragebetween2007/8and2010followed
thedistributionof18millionfreeITNstochildrenlessthan5yearsofage(May2009–May
2010).TheproportionofpregnantwomenwhoreceivedatleasttwodosesofSPforIPTp
increasedfrom21%in2005to26%in2010(p<0.0001).During1999–2010,ahighpercentage
(53%in1999and60%in2010)ofchildrenwithfeverinthetwoweeksprecedingthe
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 6/24
ImpactofMalariaControlinTanzania
Table1. Trendsinmalariainterventioncoverageindicators,MainlandTanzania,1999–2010.
Variable†† 1999 2004/5 2007/8 2010
% % % %
(95%CI) (95%CI) (95%CI) (95%CI)
N N N N Change(abs.)* p†
Nets
Householdownership(cid:4)1 29.8 45.9 55.6 74.7 44.9 <0.0001
(25.6–34.3) (43.1–48.6) (52.9–58.2) (72.8–76.4)
3,526 9,483 8,269 9,377
ITNs
Householdownership(cid:4)1 ~2.4 22.5 38.3 63.5 61.1 <0.0001
- (20.5–24.6) (36.1–40.6) (61.7–65.2)
3,526 9,483 8,269 9,377
Use(children<5yrs) ~1.7 15.8 24.8 63.9 62.2 <0.0001
(1.2–2.8) (13.9–18.0) (22.6–27.2) (61.2–66.5)
3,495 8,147 7,319 7,768
Use(pregnantwomen) ~1.9 15.7 26.0 57.1 55.2 <0.001
(0.8–4.6) (12.9–19.1) (21.7–30.9) (52.4–61.6)
369 1,054 823 922
Use(allpersons) n/a** 14.9 19.7 45.1 ~45 <0.0005
(13.3–16.7) (17.8–21.6) (43.4–46.9)
44,830 40,660 45,125
IPTpduringlastpregnancy
2+doses n/a 20.8 29.6 25.7 25.7 <0.0001
(19.0–22.7) (27.0–32.3) (23.6–28.0)
3,415 2,969 3,179
1+dose n/a 50.1 56.9 59.9 59.9 <0.0001
(47.1–53.1) (53.5–60.3) (56.8–62.9)
3,415 2,969 3,179
Malariatreatment
Anyantimalarial(timingnotconsidered) 53.0 58.2 57.0 60.1 7.1 0.2347
(45.2–60.6) (54.7–61.5) (52.4–61.6) (56.7–63.4)
988 1,882 1,320 1,715
Recommendedfirst-line(sameornextday)‡ n/a 21.4 14.2 26.7 5.3‡ 0.0002
(18.7–24.2) (11.6–17.2) (23.8–29.8)
1,882 1,320 1,715
*Percentabsolutechange,earliestvaluevs.2010
†P-valueobtainedfromchi2testforlineartrendinproportionsacrossthefoursurveys(trendtestbeginswith2004/5forindicatorswith“n/a”in1999)
‡First-linetherapyin1999:chloroquine;2004/5:sulfadoxine/pyrimethamine;2007/8and2010:ACT
**NoITNindicatorswereobtainedinthe1999(baseline)surveysincetheseindicatorswereonlydevelopedandpromotedbyRBMafter2002.
Consequently,the1999surveyquestionnairedidnotincludeafullrosterofnets,nettreatmentanduse.Allfamilieswerequestionedaboutthenumberof
netstheyownedandthenumberofchildren<5yearsofageperhouseholdwasrecorded,butnettreatment(soakingininsecticidalsolution)wasasked
onlyforhouseholdswithchildren<5yearsofagewheresomeorallchildrensleptundernets.Thedataavailablepermittedapreciseestimateof
householdnetownership;afairlypreciseestimateofnetandITNusebychildrenunderfive,andanestimateofhouseholdITNownershipusingavailable
dataonproportionofnetsthatweretreated.
††Ninthetablerepresentsweighteddenominator(numberofhouseholds,childrenunder5yearsofage,pregnantwomen,allpersons,orfebrilechildren
under5yearsofage)foreachvariableshown
doi:10.1371/journal.pone.0141112.t001
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 7/24
ImpactofMalariaControlinTanzania
householdsurveyreceivedantimalarialtreatment.Thepercentageofchildrenwhoreceiveda
first-lineantimalarialthesameornextdayfollowingfeveronsetdidnotexceed27%and
showednoconsistenttrend.
SAPamongchildren6–59monthsofagedeclined50%:from11.1%(95%CI,10.0–12.3%)
in2004/5,to7.5%(95%CI,6.6–8.6%)in2007/8,and5.5%(95%CI,4.7–6.4%)in2010(trendp
<0.0001).U5CMratesdeclined45%:from148(95%CI;129–166)deathsper1000livebirths
in1999,to112(95%CI,103–122)in2004/5,to92(95%CI,83–101)in2007/8,and81(95%
CI,72–90)in2010(trendp<0.0001);adeclineof67deathsper1,000livebirthsrelativeto
baseline.MuchofthedeclineinU5CMwasduetoa49%reductionininfantmortalityrate,
butwithnosignificantimprovementinneonatalmortality(Fig3):ratesremainedrelatively
unchangedacrosspre-baselineperiods:1987–91,1991–5,and1995–99.
StratificationbydemographiccharacteristicsrevealedtrendsinITNuseamongchildren
lessthan5yearsofage,SAP,andU5CMassociatedwithresidence,wealth,andmaternaledu-
cation,butnotsex.Intheearliersurveys,ITNusewaslower(S2AFig)andSAP(S2BFig)and
mortalityrates(S2CFig)werehigheramongruralchildren,amongchildrenfrompoorer
households,andamongchildrenwithlesseducatedmothers.Thesedisparitiesdisappearedby
2010.Smallnumbersinthemalariatreatmentcategoriesprecludedanalysisoftrendsbyresi-
dence,wealth,andmaternaleducation.
Plausibilityassessment(1and2):SAPandall-causemortalitydeclined
fasteramongyoungestchildrenandthoseresidinginhigherendemicity
areas
In2004/5,theSAPamongchildren6–23monthsofage(17.1%)wasovertwiceashighthanin
children24–59monthsofage(7.8%)(adjustedOR=2.5,95%CI2.1–2.9).Subsequently,age-
stratifiedSAPestimatesimprovedovertime,withamoreaccelerateddeclineamongchildren
6–23months(Fig4A).In2004/5,SAPwasgreateramongchildreninthehigher(15.8%)and
moderate(10.3%)endemicitystrataascomparedtochildreninthelower(6.5%,referent)stra-
tum(adjustedOR=2.4,95%CI1.8–3.2andOR=1.5,95%CI1.1–2.0,respectively).By2010,
declinesinSAPinthehigherandmoderateendemicityareaswereatleasttwiceasgreatasthe
declinesinlowerendemicity(Fig4C).Notably,thedisparityinSAPacrossendemcitylevels
waslesspronouncedin2007/8,andby2010nodifferencesweredetected(adjustedOR=1.4,
Fig3.Trendsin5-yearestimatesofall-causeneonatal,infant,andunder-fiveyearmortalityratesin
MainlandTanzania,1990–2010.Footnote:Eachratepresentedasthemid-pointofthefive-yearintervalit
reflects(e.g.,2010survey,measuringmortality2005–2009,wasplottedat2007).Mortalityamongchildren
1–59monthsofagedeclined54%between1999and2010(from111to57deathsper1000livebirths)
comparedtothe45%relativedeclineforthetraditional0–59monthagegroupdescribedintext.
doi:10.1371/journal.pone.0141112.g003
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 8/24
ImpactofMalariaControlinTanzania
Fig4.Severeanemiaprevalenceandall-causemortality(deathsper1000livebirths)accordingtoage
group(A)and(B)andmalariaendemicity(C)and(D),respectively.
doi:10.1371/journal.pone.0141112.g004
95%CI0.9–2.2andOR=1.3,95%CI0.8–2.1forhigherandmoderateendemicity,
respectively).
Children1–23monthsofageexperiencedamoreaccelerateddeclineinmortalityrateover
time(from78to35deathsper1000livebirths)ascomparedto24–59montholdchildren
(from28to19deathsper1000livebirths)(Fig4B).
In1999,mortalitywashigherinchildrenfromhigherendemicitycomparedtolower
endemicityareas(adjustedRR=1.4,95%CI1.1–1.8),butnotinthosefrommoderate
endemicityareas(adjustedRR=1.1,95%CI0.9–1.6).Theseall-causemortalitytrendsinchil-
dren1–59monthsofagealsodeclinedmarkedlyacrossendemicity(Fig4D),withgreater
declinesamongchildrenfromthehigherandmoderateendemicityareasinapatternsimilarto
theSAPanalysis.Mortalityriskin2004/5remainedgreaterinthehigher(adjustedRR=1.4,
95%CI1.2–1.7)andmoderate(adjustedRR=1.4,95%CI1.2–1.7)endemicitygroups.By
2010,mortalityinthehigherendemicitystratumstillremainedgreater(RR=1.7,95%CI1.3–
2.1),butratesinthemoderateandlowerstratahadconverged.Overall,amoreaccelerated
declineinall-causemortalityamong1–59monthsofageoccurredbetween2000and2010in
thehigherandmoderateendemicityareas(reductionsof70and100deathsper1000live
births,respectively)ascomparedtothelowerendemicityareas(reductionof38deathsper
1000livebirths).
Plausibilityassessment(3):SAPandall-causemortalitydeclinedeven
fasteramongyoungerchildrenresidinginhigherendemicity
ReductionsinSAPovertimeweremoreevidentuponcombinedstratificationbyageand
endemicity(Table2).In2004/5,SAPamong6–23montholdchildrenfromlow,medium,and
highendemicity(8.5%,13.5%,and20.5%,respectively)weregenerallytwiceashighasthe
endemicity-specificestimates(4.9%,7.1%,and11.0%respectively)amongthe24–59month
oldchildren.TheoverallreductionofSAPwasmostpronouncedforthe6–23monthage
grouplivinginhigherendemicityareaswhereSAPdeclined67%between2004/5and2010
(from20.5%to7.9%).
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 9/24
ImpactofMalariaControlinTanzania
Table2. Trendsinsevereanemiaprevalencestratifiedbymalariaendemicity*levelsandageinMainlandTanzania,2004/5-2010.
2004/5 2007/8 2010
% % %
(95%CI) (95%CI) (95%CI)
N N N Change(abs.)† p‡
Endemicity(6–23mo.)
Lower 8.5 5.8 6.4 -2.1 0.0062
(6.5–11.1) (3.8–8.7) (4.4–9.2)
1,099 701 596
Moderate 13.5 14.8 9.4 -4.1 <0.0001
(11.2–16.0) (11.8–18.6) (6.1–14.2)
944 677 754
Higher 20.5 14.4 7.9 -12.6 <0.0001
(17.3–24.0) (11.3–18.1) (5.8–10.6)
1,269 801 837
Endemicity(24–59mo.)
Lower 4.9 2.0 3.2 -1.7 0.0084
(3.53–6.83) (1.3–3.2) (2.1–5.0)
1,604 1,327 1,190
Moderate 7.1 6.0 3.4 -3.7 0.0001
(5.7–8.8) (4.6–7.8) (2.5–4.5)
1,289 1,171 1,512
Higher 11.0 7.5 5.8 -5.2 <0.0001
(9.0–13.3) (5.6–10.0) (4.4–7.6)
1,713 1,584 1,620
*Endemicitycategories:lower=0–9.2%;moderate=10.4–21.9%;higher=28.7–32.6%
†Percentagepointsabsolutechange,earliestvaluevs.2010
‡P-valueobtainedfromchi2testforlineartrendinproportionsacrossthethreesurveys
doi:10.1371/journal.pone.0141112.t002
Whenmortalityrateswerestratifiedbybothageandendemicity(Table3),onlythe1–23
monthagegroupshowedasignificantdeclineacrosstheevaluationperiod(trendp<0.0001).
Thelargestmortalitydeclinesoccurredamongchildrenaged1–23monthslivinginareasof
moderateandhighermalariaendemicity(65.7%and54.7%relativedeclines,respectively).No
significantdeclinesinmortalityweredetectedforthe24–59monthagegroupwithinthethree
endemicitystrata.
Plausibilityassessment(4):Changesinsomecontextualfactorsalso
influencedU5CM
Table4includesbaselineandendpointprevalenceestimates(ormedianswhereappropriate)
forhealth-relatedcontextualfactorsthoughttoinfluenceU5CM.
Climate. The12-monthWASPtrendovertheperiod1985–2010revealedconditionswere
generallydrierthanthelong-termaverageafter1999(S3Fig).Theperiodoverwhichbaseline
mortalitywasmeasured(1995–9)includedamajorElNiñoyear(1997–8).Bycontrastevery
yearafter1999wasdrierthanthelong-termaverage,withtheexceptionof2006–7.Evidenceof
significantwarming(~0.3°Cperdecade)inmanyregionsofTanzaniawasdetected.
Socio-economicfactors. Atthenationallevel,percapitaGDPwas47%higherin2005–09
comparedto1995–9.Themeanyearsofschoolingamong15–49yearoldfemalesincreasedby
1.0yearbetween1999and2010.Theproportionofhouseholdswithaccesstoanimproved
PLOSONE|DOI:10.1371/journal.pone.0141112 November4,2015 10/24