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DESCRIPTIO NO F TH E DOSE-RESPONS E AN D RIS K MODELIN G EFFOR T

Ronal d G . Whitfiel d Argonne Nationa l Laboratory , Argonn e 11 1

Augus t 198 3P. 3

DESCRIPTIO N

O F TH E DOSE/RESPONS E ANDRIS KMODELIN GEFFOR T
1 . Backgroun d Argonn e Nationa l Laborator y (ANL ) i s providin g EPA' s Offic e o f Ai r Quality , Plannin g andStandards , Strategie s andAi r Standard s Divisio n (OAQPS/SASD ) wit htechnica l assistanc e i nassessin g th e risk s o f alternativ e Nationa l Ambien t Ai r Qualit y Standard s (NAAQS ) fo r lead . Becaus e o f th e uncertai nnatur e o f ho w lea dexposure s caus e advers e healt heffects , thi s wil l b e a probabilisti c ris kassessment . ANL' s effort s ar e par t o f a large r effor t funde db y EP A t o produc e probabilisti c ris kestimates . Th e thre e majo r component s o f thi s effor t ar e anexposur e mode l , a physiologica l respons e mode l , anda dose/respons e model . Th e integratio no f thes e thre e components , calle dth e ris kmodel' , produce s th e desire dris kestimates . ANL i s specificall y responsibl e fo r developin g a dose/respons e mode l an dintegratin g result s t o for m a ris kmode l whic hproduce s overal l ris kestimates . Ther e ar e man y

activitie s neede dt o accomplis hthes e things . A n outlin e an ddetail s o f ANL' s tentativel y planne deffort s are describe da s follows . 2 . Outlin e o f Planne dEffort s Th e basi s fo rthi s probabilisti cris k assessmen t i s th e criteri a documen t fo rlead
. However , ther e ar e oftentime s gaps betwee n th e scientifi c knowledg e i n th e criteri a documen t an d th e knowledg e neede d t o complet e a ris k assessment
. AN

L wil l elici t probabilit yjudgement s fro m lea d healt h expert s t o complet e thi s ris k assessment
. EP

Awil l provid e a lis t o flea d healt h expert s t o be consulte d fo rthes e judgements
. Th e furthe rstep s fo rwhic h AN L i s responsibl e include :P. 4

1 . Develo pa probabilit y encodin g methodology , 2 . Perform

exper t encodin g sessions , 3 . Analyz e result s o f th e encodin g sessions , 4 . Develo pris kestimates , 5 . Perform

sensitivit y

analyses , and 6 . Documen t methods , models , andresults .

A s par t o f th e lea dris kassessmen t program , ANL staf f i s prepare dt o interac t wit hothe r group s charge dwit hprimar y responsibilit y

i ndevelopin g exposur e models , physiologica l effect s models , an dhealt heffect s models . Thi s i s necessar y

i norde r t o assur e tha t th e submodel s fi t togethe r t o for m a consistent , overal l model , tha t complet e coverag e i s give ni nth e assessment of-expert-judgmen t task , tha t th e ris kmeasure s ar e compatibl e wit hthes e models , andtha t ANL andit s subcontractor(s ) thoroughl y understan dth e model . Thi s las t aspec t i s importan t i f th e probabilit y encodin g session s ar e t o b e conducte di na nefficien t andknowledgeabl e fashion . Par t o f thi s tas kconsist s o f coordinatin g with , fo r example , thos e peopl e wit hprimar y

responsibilit y

fo r developin g physiologica l model s and indices . Th e goa l i s t o develo pmathematica l and/o r statistica l relationship s betwee nai r qualit y

an dmeasure s o f healt heffects . I t i s crucia l tha t suitabl e indice s o f physiologica l respons e b e chosen , tha t relationship s betwee nphysiologica l respons e andhealt heffect s b e developed , andtha t meaningfu l measure s o f th e ris ko f advers e healt heffect s b e used . 3 . Detaile dDescriptio no f Planne dEffort s Th e exposur e mode l link s ai r qualit y level s an

dhuma nactivit y

pattern s i ntim e andspac e t o produc e estimate s o f lea dexposure . Th e physiologica l mode l link s exposur e estimate s t o produc e estimate s o f physiologica lP. 5

response . The physiologica l respons e i s expresse d i n term s o fphysiologica l indice s (e.g. , bloo d lead , bon e lead , dentin e lead , sof t tissu e lead)
. The dose/respons e mode l link s level s o fphysiologica l respons e t o healt h effect s (e.g. , reduce d hem e synthesis , decrease d centra l nervou s syste m capability , cognitive/behaviora l damage)
. A s mentioned , ther e ar e gaps i n th e knowledg e bas e whic h must b e bridge d i n orde rt o complet e thi s ris k assessment
. The probabilit yjudgement s o fexpert s wil l be use d t o accomplis h thi s goal
. 3. 1 Develo p a Probabilit yEncodin g Methodolog y Ther e ar e a numbe ro fpractica l issue s whic h affec t th e metho d t o b e use d t o quantif yexper t judgement
. The idea l metho d woul d assur e tha t bia s wa s minimize d an d woul d promot e th e coherenc e an d consistenc yo fassessment s develope d wit h a particula rexpert
. Thes e goal s must be balance d agains t th e realit yo flimite d time , money , an d people t o perfor m th e encodings
. AN L wil l be assiste d b yeithe rSR I Internationa l o rWoodwar d Clyd e Consultant s (WCC

) i n developin g th e probabilit yencodin g methodolog yfo r lead
. Decisio n analyst s fro m thes e tw o organization s hav e bee n assistin g OAQP S i n developin g a ris k assessmen t methodolog yfo rcarbo n monoxide
. EPA' s choic e betwee n thes e tw o group s wil l be influence d b yANL' s evaluatio n o fth e tw o methodologie s an d feedbac k fro m th e Clea n Ai rScienc e Advisor yCommitte e fo rlead
. Preparator ymateria l wil l be develope d fo rth e experts
. Thi s materia l wil l be distribute d t o th e expert s befor e th e intervie wdates
. Materia l wil l be prepare d fo reac h effect
. The purpos e i s t o infor m eac h participan t of : (1 ) th e exac t natur e o fth e judgement s whic h wil l be sough t (specifi cdose respons e relationships , o rothe rcritica l exogenou s o rendogenou s variable s i n th e ris k model) , an d (2 ) th e genera l approac h whic h wil l b e use d i n orde rt oP. 6

asses s thi s information
. At times , th e judgement s neede d fro m a n exper t wil l consis t o fa determinatio n o fth e significanc e o fth e researc h o fanothe r perso n fo rmakin g probabilit yassignments
. I n suc h cases , th e participan t wil l b e instructe d t o revie wth e researc h befor e th e intervie wdate
. Thi s materia l provide d t o th e expert s wil l als o indicat e th e kind s o f relevan t condition s (health , exposur e history , exposur e levels , definition s o f healt h effect s an d sensitiv e groups , etc. ) unde rwhic h th e dose-respons e relationship s an d othe runcertai n factor s wil l be encoded
. Worksheet s wil l b e prepare d t o structur e th e session
. Thes e worksheet s are primaril yintende d fo rth e us e o fth e assessors . I n orde rt o minimiz e th e chance o fintroducin g bia s durin g th e intervie wprocess , th e orde ri n whic h question s ar e aske d ca n be varie d betwee n expert s an d eve n withi n a sessio n wit h a give n expert
. These detail s wil l be decide d befor e th e interview s tak e place
. Amedica l docto rfamilia rwit h th e healt h effect s o flea d wil l als o be consulte d durin g th e developmen t o fth e methodology
. Th e rol e o fth e medica l docto rwil l includ e assistin g ANL in : (1 ) th e desig n o fpreparator yan d i ntervie wmateria l s t o assur e tha t prope rterminolog yi s used , (2 ) settin g th e condition s fo rwhic h dose/respons e relationship s wil l be elicited , (3 ) definin g healt h effects , an d (4 ) th e phrasin g o fencodin g questions
. The inten t o fthi s collaboratio n i s t o insure , t o th e exten t possible , tha t th e encodin g methodolog yi s medicall ycorrec t an d understandable , an d tha t i t doe s no t confoun d importan t effect s o rintroduc e bias
. Th e sub-contracto rchose n t o continu e o n thi s lea d ris k assessmen t wil l b e responsibl e fo robtainin g th e service s o fth e neede d medica l doctor
. Sinc e encodin g o fexper t judgemen t i s no t a proces s tha t ca n b e completel ydetermine d i n advance , th e assessor s must be prepare d t o adap t th eplanne dlin e o f questionin g a s situation s dictate . Condition s (e.g. , health ,

exposur e history , etc. ) unde r whic hth e assessment s wil l be mad e mus t b e considere dandexplicitl y incorporate dint o thes e materials . Al l assessore s wil l be briefe do nth e assessmen t methodology , assessmen t materials , andpertinen t healt hissues . Th e briefin g wil l tak e plac e a t AN

L an di t wil l b e schedule di nadvanc e o f th e star t o f th e interviews . Thes e material s wil l be revise da s neede ddurin g th e cours e o f th e firs t roun do f interviews . Tw o round s o f interview s wil l be conducted . I t i s desirabl e tha t n o majo r revision s be mad e t o th e intervie w methodolog y afte r th e secon droundo f interview s begins . Ther e ar e a numbe r o f probabilit y encodin g method s tha t ma y b e employe d i nth e interviews . Thes e includ e (for continuou s quantities) : o fixe dvalu e method s - th e probabilit y tha t th e uncertai n quantit y lie s i na specifie drang e o f value s i s elicite d fro m anexpert , o fixe dprobabilit y method s - th e value s o f anuncertai n quantif y

whic hboun dspecifie dprobabilit y interva l ar e elicite dfro

m anexpert , o directl y

drawin g point s o

nth e distributio ncurv e fo r eithe r th e cumulativ e densit y functio no r th e probabilit y densit y function , and o estimatin g parameter s fo r a famil y o f distributio n functions . Mos t popula r ar e th e fixe dvalu e andfixe dprobabilit y method s whic h ca nb e use dtogethe r t o perform consistenc y

check s (i.e. , d o th e value s assesse db

y a numbe r o f method s agree?) . Device s lik e probabilit y wheel s (modifie d"wheel s o f fortune" ) canb e use da s visua l aid s fo r th e expert .P. 8
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Th e objectiv e i nusin g a variet y o f assessmen t method s andconsistenc y check s i s t o maximiz e th e chance s o f elicitin g th e "bes t possible " judgement s fro m th e expert . 3. 2 Perform

Exper t Encodin g Session s It i s anticipate dtha t a tota l o f fiv e healt heffect s wil l b e considere di nthi s ris kassessment . Th e sensitiv e grou pi s childre nfro m conceptio nthroug hag e 6 . Thre e expert s wil l b e consulte dfo r eac hhealt h effect , andeac hexper t wil l b e interviewe dtwice . Thi s i s a tota l o f 3 0 interview s fo r th e ris kassessment . Th e healt hexpert s wil l b e pai da smal l honorarium

fo r eac hintervie w

session . Inthes e interviews , judgement s wil l b e elicite do nissue s fro

m th e followin g lists : Relationship s o Bon e lea dt o physiologica l respons e o Soft-tissu e lea dt o physiologica l respons e o Bloo dlea dt o physiologica l respons e o Physiologica l respons e t o healt heffect s Healt hEffec t Categorie s o Hem e biosynthesi s o Erythropoieti c effect s o Cognitive/behaviora l effect s o Electrophysiologica l effect s (centra l nervou s system ) (periphera l nervou s system ) o Rena l functio n o Cardiovascula r o Immunologica l7
o Carcinogenicit y o Reproductive/developmenta l effect s o Deliver ycomplication s (the mother ) (the fetus ) Thi s informatio n wil l b e developed , a s needed , throug hthes e planne d interview s wit hrecognize d exper t healt hscientists . Th e scientifi c basi s fo r thes e assessment s include s th e lea d criteri a document . Th e goa l i s t o quantify , t o th e exten t practical , relevan t uncertaintie s i n th e dose/respons e mode l , th e physiologica l mode l , o r th e exposur e model . Assessment s wil l b e conducte d i n 2 rounds . Th e firs t round ha s a s on e majo r goa l tha t o f instructin g th e exper t i n th e proces s o f elicitin g probabilit yjudgements . I t i s anticipate d tha t th e secon d round o f encodin g wil l produc e th e judgement s t o b e use d i n computin g th e fina l ris k estimates . Becaus e o f th e larg e numbe r o f interview s required , AN L wil l nee d th e assistanc e o f decisio n analyst s fro meithe r SR I o r WC C t o complet e thi s phas e o f th e ris k assessment . I t i s anticipate d tha t a t abou t thre e two-perso n team s wil l b e forme d fro mth e availabl e poo l o f assessor s t o conduc t thes e interviews . W e estimat e tha t trave l wil l b e require d t o abou t 1 0 differen t citie s i n th e midwes t an d easter n U.S . 3. 3 Analyz e th e Result s o f th e Assessment s Encodin g result s i n th e form o f probabilitie s wil l b e analyze d t o chec k fo r bias , consistency , and coherence . Th e inten t o f thi s activit yi s t o assur e tha t th e probabilit yjudgement s elicite d fro mth e expert s ar e th e bes t possible . Anydetail s overlooke d durin g th e interview s wil l b e resolve d wit h th e exper t (hopefully , ove r th e telephone ; i n perso n i f necessary) .P.1 0

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Thre e expert s wil l b e interviewe dfo r eac hhealt heffect . Eac hse t o f judgement s wil l b e viewe da s uniquel y importan t i nth e ris kassessmen t process , andthi s uniquenes s wil l b e maintaine da s ris kestimate s ar e developed . I f divers e judgement s ar e average di nany way , thi s wil l b e clearl y pointe dout . Thes e difference s i njudgemen t ar e importan t source s o f uncertainty . Th e anonymit y

o f th e healt hexpert s wil l b e preserve di nal l publi c document s prepare dthroug hthi s ris kassessment . I t i s no t planne dt o mak e tap e recording s o f thes e session s becaus e o f thei r limite dvalue ; i t i s tim e consumin g t o revie w

thes e tape s afte r th e intervie w session . Instead , 2 assessor s wil l conduc t eac hprobabilit y encodin g sessio nandthe y wil l b e ver y carefu l t o obtai nal l neede dresult s b y th e endo f th e interview . 3. 4 Develo pRis kEstimate s Ris kestimate s wil l b e develope dfo r eac ho f 1 0 cities , fo r eac ho f approximatel y

1 0 alternativ e NAAQ S ( 5 levels , eac ha t 2 averagin g times ) t o b e specifie dby

th e EPA . Ris koutpu t measure s wil l b e o f thre e types , benchmar k risk , hea dcoun t risk , andexpecte dhea dcounts . Th e hea dcoun t estimate s wil l b e performe dfo r bot hincidence s (count s multipl e incidence s fo r a singl e perso ni na prescribe dtim e period ) an dpersons . T o obtai nthes e estimates , i t wil l b e necessar y

t o integrat e th e output s o f th e exposur e mode l , th e physiologica l respons e mode l , andth e dose/respons e mode l develope di nthi s andothe r effort s i nth e EPA' s lea dris kprogram . Benchmar kris ki s a simpl e measur e o f riskt o a sensitiv e population . I t doe s no t requir e tha t anaccoun t b e mad e o f th e activitie s an dmovement s o f sensitiv e individuals . Th e focu s i s o nth e probabilit y

tha t pea k concentration s occu r a t hig henoug hlevel s t o caus e healt heffects . Thi s measur e i s a

nestimat e o f th e ris ktha t pollutan t concentration s wil l occu rP.1 1

tha t woul d caus e a specifie d percentage , sa y10% , o fth e person s i n th e most sensitiv e populatio n t o suffe radvers e healt h effects , i fexposed
. T o calculat e thi s measure , i t i s necessaryto : (1 ) defin e exactl ywha t i s mean t b ya n advers e healt h effect , an d (2 ) construc t a probabilit ydistributio n fo r eac h o ftw o factor s (nt h highes t concentratio n leve l ove rth e subjec t tim e period , an d th e dos e whic h woul d adversel yaffec t a specifie d percen t o fth e most sensitiv e individual s experiencin g th e advers e healt h effect)
. Give n thes e distributions , benchmark ris k i s calculate d vi a a convolutio n integral
. Hea d coun t risk s dea l wit h th e actua l number s o fsensitiv e people wh o ma yexperienc e advers e healt h effects
. Thes e estimate s conside runcertaintie s i n (1 ) dose-respons e relationships , (2 ) ai rpollutan t concentratio n levels , am d (3 ) huma

n activitie s an d locations
. Tw o measure s o fhea

d coun t ris k

wil l be calculated : incidence s an d persons . The late rmeasur e count s an individua l onl yonce i n th e subjec t tim e perio d eve n thoug h h e ma yhav e experience d mor

e tha n on e occurrenc e o fa healt h effect
. Th e forme rcount s al l occurrence s o fa healt h effect , includin g multipl e occurrence s fo ra n individua l person . These risk s wil l be i n th e for m o fprobabilit y distributions
. Expecte d head coun t measures , bot h incidence s an d persons , ar e derive d fro m head coun t ris k

distributions
. 3. 5 Perfor m Sensitivit yAnalyse s Sensitivit yanalyse s wil l b e performe d t o investigat e th e relativ e contribution s o f variou s factor s t o uncertaint yi n th e risk output s (i.e. , estimate s o f benchmar k risk , hea d coun t risk , an d expecte d hea d coun t risk) . 3. 6 Documen t Methods , Models , an d Result s AN L wil l prepar e a draf t and fina l draf t repor t fo r thi s portio n o f th e ris k assessmen t program . A s backgroun d material , i t wil l summariz e th e othe rP.1 2

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lea d ris k progra mreport s o n exposur e modelin g an d physiologica l modeling . Th e overal l mode l whic hintegrate s thes e component s wil l be presented . Result s o f th e exper t encodin g session s wil l b e documente d i n detail , alon g wit ha thoroug hdescriptio n o f th e encodin g methodology . Al l result s o f th e encodin g session s (dose-respons e relationships , exogenou s an d endogenou s variables ) wil l b e clearl ydisplaye d an d discussed . Discussio n wil l cove r suc hissue s a s bias , consistency , an d coherenc e o f encode d judgements . Ris k outpu t measure s wil l be presente d an d thoroughl ydiscussed . Anyassumption s neede d t o complet e th e estimate s wil l b e documente d an d th e scientifi c basi s wil l be referenced . Th e sensitivit yo f result s t o thes e assumptions , th e structur e o f model s an d submodels , an d encode d informatio n wil l b e reported .