Module for training in data processing and analysis of epidemiological evaluation data

WORLD HEALTH ORGANISATION ONCHOCERCIASIS CONTROL PROGRAMME rN WBST AFRTCA (OCP) MODULE FOR TRAINING IN DATA PROCESSING AND ANALYSIS OF EPIDEMIOLOGICAL EVALUATION DATA January 1994 ONCHOCERCIASIS CONTROL PROGRAMME IN WEST AFRICA MODULE FOR TRAINING IN DATA PROCESSING AND ANALYSIS OF EPIDEMIOLOGICAL EVALUATION DATA OBJECTIVES At the end of the training, participants will be able to: 1) understand how microcomputers work 2) use a microcomputer to make simple calculations and graphs 3) use a microcomputer for word processing 4) carry out the different steps necessary for the analysis of epidemiological evaluation data of a village within the Onchocerciasis Control Programme: - manual processing of an evaluated village - calculation of raw, standardized prevalence - calculation of CMFL - Longitudinal analysis PROGRAMME The programme covers five days. Each participant is requested to read the documents and revise the different educational software in order to better understand and use a microcomputer lst day: DOCUMENT OCP/BIS/INF/3 Introduction to the operation of a microcomputer Knowledge of DOS Loading of a programme Study of an educational software * IBM educational software * DOS educational software * WORDPERFECT educational software (English only) * LOTUS educational software (English only) 2nd day: DOCUMENT OCP/BIS/INF/2 Manual processing of a village * Classification by sex and age - Manual calculation of prevalence - Demonstration of EpICROS - DOS educational software - Introduction to Lotus 123 3rd day: Lotus 123 manual Using the computer for: - Calculation of raw prevalence - Calculation of standar dized prevalence - Calculation of CMFL - Exercises on the calcuration of differents indices 4th day: WORD PERFECT and EpI_INFO manuals Introduction to WORDPERIECT Demonstration of the EPI-INFO software Discussion on epidemiological surveillance Introduction to longitudinal analysis 5th day Verification of different documents Copy of certain programmes Revision of differents concepts Preparation of the end-of-training report Remark: Those who alreadl' have an advanced knowledge of data processing could startdirectly rvith the data analysis by using as much as possible Lotus 12: and,the EpI-INFosoftware. WORLD HEALTH ORGANISATION ONCHOCERCIASIS CONTROL PROGRAMME rN WEST AFRTCA (OCP) PROCESSING AND ANALYSIS OFEPIDEMIOLOGICAL EVALUATION DATA This document concerns only the parasitological results of form N.602 Document OCp/BIS/INF/2 January 1994 DATA PROCESSING AND AI\ALYSIS Data entry and validation The type of form used for the simple epidemiological evaluation is N602 (Annex1)' In the field, the team uses the Annei 2 form for the preliminary processing of theresults of the current survey. Immediately after returning from the fi.ld, tt. forms onthe villages evaluated are given to the data entry clerks for the update of theepidemiological data bank on the OCp micro.o-prt"rr. - The very first operation consists in systematically checking all the columns of allthe forms in order to correct the codes oi put them ln the apf,ropriate places. This verification is done family by family, individual by individual. -in th. .ur" of a village with more than one passage, two persons carry out this verification: the first reads theprevious passage and the second checks the iurrent passage. For example, a village should bear, on all the forms, the same value for some columns (month, year, village, state, etc.) while some colurlns vary, such as the family (within the village; or theindividual number (within a family). Any new village receives a number as well as each newly recorded individual. The village numbers urrd irdiuidual numbers are kept up todate in a notebook. As soon as the verification is finished the entry can start. The data on the villages are entered twice on the computer. The two entry operations are undertaken by two different persons. This double entry of the same data minimizes typographical errors while ensuring the integrity of ine data entered.However, possible errors are corrected as many times as necessary. The data entered in this way on diskettes are copied on the hard disk in order tostart their validation. The validation mainly concerns villages with more than onepassage' In the validation process, the codes in the columns of*re previous passage are compared with those of the current passage. For example, the sex of an individual :19]10 not change from one passage to another, while the age should be increased by thedifference in years between the two passages. validation errors are corrected. Thevalidation/correction/validation( cycle is repeated till there is no longer anyerror. A few examples of validation errors: - transposition of individual numbers; - giving of two different individual numbers to one individual; - change in sex; - wrong age; - individual whose examination status code was 5 or 6 in previous passages andfound again in the new passage; - missing individual number. There is a subtle error. An example is an individual whose sex has been coded as male and who is found to be female after several passages. These coding anomaliesdetected in the field should be the subject of a speciai correction on the data for all the previous passages before any validation of the data on the current passagethese anomalies concern sex, age and examination status. 2 Generally, once the data have been correctly validated, the creation of analysis files(updating of data banks) is started. They constitute inputs for the projrarnmes whichhelp to produce results on the printer or output files for future ,r" ,iritt specializedprograrnmes. Data analysis The basic unit used in the analysis of the evaluations is the village. Two types ofanalysis are made: cross-sectional analysis (Annex 3) and longitudinal analysis (Annex4)' Annexes 3 and 4 give a printout of iesults, using tir. p.og.u- analyzer developed byoCP/BIS' In each oCP Participating Country whicn nis a microcomputer, the SEpTprogram, used for transferring old oCP data, will make it possible to have the sameresults. The calculation examples are attached hereto as Annex 6. The cross-sectional analysis makes it possible to get a picture of the epidemiological situation at a given time. It is based on the wnJe population examined. The usualstatistical calculations are made on the distribution^ or tn. population enumerated,present and examined by sex and age. The indices normally ,r"o u." prevalence and community microfilarial load (CMFL). The CMFL is calculated only for adults aged. 20or more. The detailed formulae are attached hereto as Annex 5. Longitudinal analysis is more complex and necessitates knowledge of cohortanalysis' It is mainly based on the monitoring over time of the cohort of adults aged, 20or more selected during the first epidemiological evaluation passage in a given village.It makes it possible to detect epidemiological changes that hid occurred over time, inthe cohort' For a very successful vector control, the prevalence and CMFL should tendtowards zero in the cohort of adults. (See Anne*.r 4A and 48 for an example). Calculation of usual indices The method of calculation given below is based firstly on a manual processing,using the Annex 2 form. The skin-inip reading results are recorded on this fbrm, usingthe classification by age group and sex. (a) If a person has negative results for the two skin snips, use the notationlol (b) If a person has a positive result for at least one skin snip, write the twofigures, e.g., lo_1 | or le_rs | . count the total number of persons having positive results and the total numberof persons examined in each age group and for "i"i, ,.* and write the two figures at therighrhand bottom corner of the corresponding box: e.g.,0/8 for male subjects aged 0 -4 years. 3Finally, at the bottom of the form, write, at the left-hand side, the total number of male subjects having positive results and the total number examined, and, at the righrhand side, the total number of female subjects having positive results and the total number examined, and then the grand total for both s&es in the middle. Check the processing a second time. Standardized prevalence Since the raw prevalence rate depends on the age-group and sex composition of the population, it would be misleading to compare two given populations by using the two overall prevalence rates unless the two populations have the same structure in terms of age and sex. Prevalence standardized by the direct method makes it possible to correct raw prevalence by applying it to the standard population with a view to taking into account the variability due to sex and age. The calculations are made as follows: (1) classifying by sex and age rhe population examined; (2) classifying by sex and age the positive population. For points (1) and (2), refer to Annex 2 for the processing and classification by sex and age. (3) Calculate the raw prevalence by sex and age, i.e.,for sex-age class ij, the number of positives in this class ij divided by the number examined in this same class ij. (4) Apply these raw prevalences to the standard population. positives expected in the standard population. They are the (5) Standardized prevalences are calculated by dividing the sum of the expected positives (Male, Female, Total) by the total of the standardpopulation (Male, Female, Total). Such standardized prevalence rates make possible comparisons between the villages. For further details, see annex 5. Geometric mean and CMFL 1. Calculate for each person the arithmetic mean of the results of the two snips,i.e.,X, : (sl + sZ)lZ; i being the index for any individual; 2. Do the t-og transformation of the result obtained in step l plus 1: i.e.,y, :[.og (x, + 1). Log being the Napierian logarithm 3. Calculate the arithmetic mean of the y, series, i.e.,y. CMFL For the community microfilarial load (CMFL), the calculation is made in thesame way as the geometric mean but it is for all adults aged, 20or more examined duringa passage' It makes it possible to measure the force of onchocercal infection. Forfurther details, see Annex 5. Interpretation of results In the case of cross-sectional analysis, Prost et al. (lg7g) have given aclassification of the different levels of onchocercal endemicity ba;ed on prevalence. It therefore emerges from the work of these authors that: (l) when onchocerciasis affects 60%, or more, of individuals in a community, the situation is intolerable or could become so in the short or medium term; thebalance of these popurations is precarious: this is hyperendemicitf; (2) when onchocerciasis affects less than 35% of individuals, the disease has onlylimited effects and is socially inconspicuous: This is hypoendemicity, the tolerablelevel of the disease; (3) between 35% and 60% of affected patients, the level of severity is variable bothbetween the groups and between individuals within the sam! group: this is mesoendemicity. These definitions, based on observations made in the West African Savanna areas,are not universally valid. However, we consider that onchocerciasis is found in itsseverest form in this region and that there is very little chance that studies conducted inother ecosystems would result in a decrease in itre two thresholds defined. As regards longitudinal analysis, it representation in order to assess better the annexes 44 and 48 for an example). 4 4' Finally, calculate the geometric mean which is the exponential transformation of the result obtained in step 3 minus 1, i.e.,GM : exp (y) _ 1. will be based mainly on a graphic epidemiological rrend in the village (see 5Bibliography Armytage P., Berry G. Statistical Methods in mecidal research. Blackwell Scientific publications. Oxford, [,ondon. Second Edition. Betty R. Kirkwood. Essentiars of Medicar Statistics Oxford, London. Blackwell Scientific Publications Jenicek M, Cleroux R. (19g2) Maloine, I Vol., paris Epid6miologie. Principes. Techniques. Applications Prost A., Hervouet J.P., & Thylefors B. (lg7g). L.es niveaux d,end6micit6 dansl'onchocercose. Bulletin de l'Organisation mondiale de la Sant6 , 57(4.),655-662 smith P'G' and Morrow R.H. (1991). Methods for field trials of interventions againsttropical diseases. A toolbox. WHO/TDR. Oxford Medical publications. OxfordUniversity press, New york. Remme J',Ba O.,Dadzie K.Y.and Karam M. (1986). A force-of-infection model for onchocerciasis and its application in the epidemiological evaluation of theOnchocerciasis Control Programme in the votta Rivei Basin area, Bulletin del'Organisation mondiale de la Sant6, 64,667_6g1. Rumeau-Rouquette C., Breart G., Padieu R. (1985). M6thodes en 6pid6miologie. Echantillonnage - Investigations - Analyse (3d 6dition). Flammarion M6decine- sicneces, Paris. Vaughan J'P. & Morrow R.H. (1991). Manuel d'6pid6miologie pour la gestion de la sant6 au niveau district. organisation mondiale de la Sante, Gendve. 6Annex 1 oo! m mC 4 o io !ll ool) m o m l- Cl m o oz --{fl m t- ozor oo mIlo o U) m mz -n ! 6C m o m t: oC m a) : m rC J oz L !r m -n oll Cr l, m or @ -oo'9J(D -ct -Fqao @ { o ocq, +.o _- (o a U' o, f f(D. (D (o o T A) U'a 0)(o o =c 3(u, o (o lu 'Tl o, 3 (D =c 3(tr o l\) m O) E C,) -O) 5 o)(o : E tol\) I\)5 m = = P 5 Eliopsie Odre z.o3 o-(D q, R c,o =, =<D I tIt-l-_ L_ I t_ I |-_ E=<,3 o- (D- Ea CN(D (D (o(D ''zig a9E <o Q')5q3g CJ) =:.Ifo)o €.,3q.(D a Ea(D =.a:d O-=zoda (DEf,o a:-_. o_-o5-@@<g, e, (D3 ='r f3p 3 TE E (D. ooq,(D ? O) o =o z o, o N f o I A Ut I ro ts o I HA ts(, I (4) (^)c I s(o (J'l o + o fr, N)O (o ?{C-x oFI EF l]-. t-li. =C) rri @ C. : Annex 2 C'Zso =Et-I aa c, rq(4, -+( I+ o s o \ a{ \ o a\o\ U\, o\ lo\ , O)\-{q, a\o o o9& Or <\\q, a'(o\,\A. 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S.E. REI.AIII,EDAIE FLA6 Col{TRor. txAil. (Iil t) PREV. Cilfr (95t co}rF.rilr. r cilrl:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 7510 0 0.8r Jl 9J.5t {.4t 5J.{8 ( j2.06 _ 8S.76) lo0.0t 79t2 0 5.00 Jl 9j.5t {.41 J0.58 ( i8.51 - 50. lj) 51 .?l 8lr2 0 7.00 3l 90.Jt 5.31 2{.t5 ( rj.60 _ 42.J6) 45.21 8412 0 10.00 Jl 71.01 8.?t 7.21 ( J.57 _ 1J.98) 13.6t 8512 0 12.00 jt 48.41 9.0t 1.40 ( 0.58 _ 2.66) 2.6t 8901 0 l{.08 31 12.9t 6.01 0.jl ( -0.02 - 0.75) c.6t Annex 4 date:07-28-I99J 9 T rre:08: b5: l0 PRIO I CITD RTLAI. CIlFI :::::::: r00.01 60.8t 4t.2t U .8t - 7.81 -28.1t OISIRIEUII()ll OT HF FOR IllE Ct)l'l()RI OAIi FLA6 YEARS I{UIl8ER c0t{tR0L txAtl ttuilEtR 0i Ii Pin s|1IP--_-____0 0.5 l- ?- 4_ 8_ l5_ 7510 7 9I? 8r12 8412 8512 8901 0.81 5.00 7 .00 10.00 12.00 1{ .08 YIARS c0t{TR0L 0 0 0 0 0 0 JI ?tJI JI trJ1 JI JI 2 2 7 9 l5 21 00 0 I 2 0 j !) 0 0j0 t? t l0 tJ 0 0 6 600 a 2 c0 RESULTS FOR ItlOSE Sl{IPPTO AT TllE F()LLOIi.UP SURVTY II{OICATEO AI{O AT TllE FIFJT SURViY (SiItI COhOFi] OAII TLAG t{ utl8 tR E )(Ar,{ s.t PRTV 2.1t , ,c J.9t 5.4i t.7l 5.6t EASE illtL 71.J1 61 .28 72.0? 66.i1 6J. 74 54.i1 AiLAIi\,E rlllFL LlA .e'1 a, co 16.51 ll.7t J.0i 0.(,L oFtDIaTr: EEL;T.Cr.1;L l,lC Dt ,10 . 61 4 t .21 I r ou - 10 7! EASE t)astRv PREV. PRIV 08stRvcl,rFL (95t t0NF.tflt. ) 7 510 19t2 o! raOLLI 8412 86t2 890 I 0 0 0 0 0 0 0.81 5.00 7.00 10.00 12.00 14.08 :::::::::: 66 5l 49 45 40 ,t 97.0t 95.1t e5.9t 95.5t e5 .0t 94.61 97.0t 94. lt el.8t 75.6t 52.5t 13. 5t 7l . i4 36. 70 26.J0 7.81 .l 9l 0.3? ( 5J.70 - e4.61) ( :2.2{ - 6C. t5 ) ( :A, 18 - 42 tt) ( 4.26- ll 85) { 0.9i- .1.,14) (0.0?- 0.71) 10Annex 4 Vil,tryefltabcr Couttry code 3rsln codc Phasc codc u t 3t t EPI DATABAS€ stIilANY SYSTEH Vlttegc nc ..... Cq,ltry n[c ..... 3asin n* Ptase n* TIEROruM EURrIIA FASO rosot_o./LERAE^./CO{o€ r 7501 lltrlbcr of survcys : 6Prev. prcv. of XFS CHFL Btird. Ftag Coordinates - l0il 5rf, 4tE,1lqtSurvcy Dur.tim pop. pop. pop.lto. Datc TlTc cqltro[ ccnsus prcsctrt Exanined 1 7510 s 2 7912 s 3 8112 s I u12 -s58612s 6 8901 s 0.81 5.00 7.00 10.00 12.00 1/r.08 71 .31 29.8 22.02 5 .23 1.26 0.23 162 154 170 173 183 189 135 140 117 15t 153 165 131 138 132 136 155 152 n.6 65.8 60.8 38.1 19.1 1.8 6.5 3.7 2.9 2.7 5.5 0.9 0 0 0 0 0 0 Tierkoura (Comoe) BURKINA FASO100 90 BO a 970 o S60o lso\oo\ 840c o E- so .q) (L 20 10 o 20 46810 12 14 16 18 20 Pr6valence en mf A. 3 4 g dans la population V '+. CMFC '+ Tendance Observ6e - Pr6dite Pr6valence en mf dans la cohorte des adultes Ann6es de lutte antivectorieile A 11 Annex 5 This annex gives details of the formulae used in the programme analyzers whichenabled the result in Annexes 3 and 4 to be proOrr".J 1. Age group Seven age groups are usually used in OCp, i.e.: 2. Standard population For the standardization of some variables, such as prevalence, an invariablepopulation, composed of the ftst 22,041 individuat, .*u*in d, is used. This populationis termed standnrd. population and is summarized in the following table named sTD inthe formulae. GROUP CLASS I 0-4 2 5 -9 J t0-14 4 15-19 5 20 -29 6 30-49 7 50 or more AGE MALE FEMALE TOTAL 0-4 L40L 1353 2,754.00 5-9 1769 1507 3,276.00 10-14 1739 1465 3,204.00 15-19 1085 92r 2,006.00 20 -29 1409 1738 3,147 .W 30-49 2388 2821 5,209.00 50 and more 7208 1237 2,445.00 TOTAL 10,999.00 LL,042.00 22,041.w t23. Census population The census population is calculated in relation to the examination status. It is allindividuals whose status is l, Z, 3, 4, or 7 . 4. Population present The population present is also related to the examination status. It is allindividuals whose examination code is 1,2 or 3. 5. Number examined The number examined is that of all individuals whose examination code is l. 6. Positive population (MFS positive) The positive population is that of all individuals whose examination code is 1 andthe arithmetic mean of the two skin snips is more than 0 and different iy 999. IEXAM : 1 I AND t(sNlpl + SNIP 2)/2 > 0 AND < >9991 7. Prevalence of MFS Either ExAij crosstable (age group by sex) of the number EXAmined, or posijcrosstable (age group by sex) of the Pos itive popuiation, or STD1 crosstable (age groupby sex) of the standard population (srD), i ueing the index of the age groups and j thatof the sexes, the following calculations are made for: 1) Prevalence of microfilariae 7 Epos prev = +i, ,* Eta U Epos,, P,"urru, = ;Lx roo E {i=t ; t (age) A j=t ; 2(Ser) } {i=t ; t (age) A j=t (sex) } 7 E,Em,, i=1 13 PrevStd- remat6 i=t {t=t ; t (age) Aj=t (ser)} x100 ( t=t ;7 (age) A j=t (sex) ) x100 { ;=t ; 7 (age) A i=2 1sex1 t Prev-rcruks, Prev-robt 7 EPos,, = '=l x l(X) 7 EEmi2 i=l Pos 7 DExa i=l 7 E i=l 2 E 2 Ej=t tj x100 { ;=t ; 7 (age) A j=t ; 2 (sex) I q 2) Standardized preyalence Exa 7 E i=l 72 E E PosrxStd, Ezxa J=t u 7 E t= I 7 E,Pos,,xStd,, tl PrevStduor," 7 i=l E std,, 7 t= I \Pos,rxStd,, E,Em,, E std,, i=l 7Z E Esta.. ,=1 j=l U x100 {;=t;7 (age) Aj=t;Z(sex)I 95Vo Confidence interval of Geometric mean i.e., x the arithmetic mean of the skin snips n the total number of individuals examined (size of the sample)k an invariable ranging from 1 to n The log being the Napierian rogarithm, the term ,'exp,,representing the exponential and the term "sd" the standard deviation. PrevStdroro, 8 i=l 7 2 t4 (a) The geometric mean (GM) is given by the following formura: x=exd-1 with t=+=l,Erog(.r*+r)nn" Y=log(r+1) e r=expY-l (b) the confidence interval is calculated as follows O+ t.96x d) ,6 -1exp the folkithing intermediate calculations as the base: sdlYJ = sd(Y) 'ln95% CJ. for y: y t 1.96xsd(yl -;. t.eOrl4 'fr 9. CMFL The CMFL is based on the examined population aged.20 or more. The formulais the same as that of the geometric mean, except that it is for the above-mentionedpopulation alone. It makes it possible to measure the force of onchocercal infection. 10. Mean number of microfilariae per skin snip It is a distribution, by class, of the mean of the two skin snips of the population examined. The classes are defined as follows: 15 0 for a zero mean 0.5 for a mean between 0.1and 1.9 2for a mean between 2 and 3.9 4 for a mean between 4 and, 7.9 8 for a mean between 8 and 15.9 16 for a mean between 16 and 31.9 32 for a mean between 32 and 63.9 64 for a mean between 64 and, LZ7.g 128 for a mean between 12g and 255.9 256 for a mean between 256 and more This distribution is made by sex and age group. It makes it possible to determine exactly the group most exposed to onchocerciasis. $Catcut de Ia pr6vaLcnce standardis6e Nom du vi I tage:TierKoura code du vittage U Bassin: Como6 Date: DEC- 1gg1 TotaI examin6 I,IFT = = === =============== ====0-4 I 12 20 5-96612 10-14 5 10 16 15-19 6 7 13 20-29 9 13 22 30-19 18 13 31 50+ 9 9 18 ======================== 62 70 132 Poputation Standard de IrOCp HFT ======================== 0- 1101 1353 2751 5- 1769 1507 3276 10- 1739 1165 3204 15- 1085 921 2006 20- 1109 1738 31t7 30- 2388 2821 5209 50+ 1208 1237 Zltj = === ==== = = = ==== = = == = ==== 10999 11012 2?011 o.T3 0.57 0.61 Taux de Pr6vatence bru TZ.5 SZ.1 &.1 Positifs I,IFT = ===== = ============= === = 000 101 369 6 5 11 9 11 20 18 10 28 8816 = = = == = == === == ===== == = = = = 15 10 85 Noobre infect6 estirn6 pour [a popr.rtation standard MFT = == = == = == === = = ==== = == = = =0.0 0.0 o.o 291.8 0-0 ?91-8 869.5 879.0 1718.5 1085 -0 657.9 1712.9 1109-0 1170-6 2879.6 2388.0 2170.0 4558.0 10r5.8 1099.6 2173-3 == === = = == ==== == ==== = = = = = 7120.1 6277.0 13397_1 Annex 6 Pr6vatence brute I{FT 0-0 0.0 0.0 o_2 0.0 0.1 0.5 0.6 0.5 1.0 0.7 0.8 1.0 0.8 0.9 1.0 0.8 0.9 0.9 0.9 0.9 Pr6vatence standardis6 61.1 56.g dO.g L7 Annex 6 Catcul dc la CilFL Bg+8d tl 72 85 1s5 38 22 26 101 2? 95 101 u 78 80 21 1 16 17 0 0 10 213 91 1 27 48 0 75 18 79 110 0 172 15 0 65 2811 171 7 33 15t+ 285 25 53 221 Urg 113 155 36 193 32 13 58 211 2 48 202 17 129 111 212 0 212 <Bs+Bdt12 Ln(((BspBd)/z)+1 ) HF t{F F 36 43 77.5 19 11 1l 52 11 17.5 50.5 12 39 40 10.5 0.5 23 8.5 0 0 20 21 .5 15 -5 3.61 091 3.7U18 4 - 36309 2-99573 2.18/s90 2.63905 3-97029 2.48490 3-88156 3-94158 3.76120 3.68887 3.71357 2.41234 0.40516 3. 1 7805 2-25129 0 0 3-041s2 4.8081 1 3.83945 4.962U 0.40516 4.16014 2.67114 1-50107 3.21887 2-86220 0 1.35670 3.65065 1.96633 2-30258 2.60268 3.70130 3.31118 1-02535 1-71402. 0 4-83230 1.16590 4.283s8 3.15700 4.36309 0 2.91143 3-52636 1.57985 2-83321 2.0 1 490 3 .55534 1 -68213 0 -69311 3-21887 1.6?197 2.251?9 /+ . 18205 4.26969 1.67282 0 4.67282 2 -O1190 3.13549 3_41772 3.701 30 1.11313 3.t#072 4.77912 4.79579 0 112 85.5 3.5 16.5 T7 142-5 12.5 26.5 110.5 124.5 71 -5 77.5 18 95.5 16 6.5 34 107 1 ?4 101 8.5 61.5 70-s 106 0 106 6.5 22 29 -5 39.5 62 46.5 118 120 0 0.5 13.5 24 0 37.5 9 39.5 55 0 86 22.5 0 33 13 11 59 79 124 93 235 210 0 1?6-6 96.1 222.7 Itloyenne des LI 3 .5 Z _l 3 . l c',tFL 32-7 14.6 ?2-O