Modelling onchocerciasis transmission and control

rr;-, ! , j i r{ :'i l' ':!'.'".jtMode[ing onchocerciasis transmission and control Final report for Technical Service Agreement No. 08/181/85 provided by the World Health Organization on behalf of the Onchocerciasis Control Programme in West Africa for the period June 1 L993 to December I 1993 October 1994 Centre for Decision Sciences in Tropical Disease Control (CDTDC) Dept. of Public Health, Erasmus University Rotterdam P.O. Box 1738, 3000 DR Rotterdam, The Netherlands ) 'F /:) i'\,/-\ r \rr) Introduction The proposed activities for the TSA 1993 were almost exclusively devoted to the assessment of the effectiveness of ivermectin treatment as a means to control transmission: either when used alone or in addition to vector control. In Part I (page 3) we report the model based analysis of the results of the community treatment in Asubende (Ghana). We have attempted to quantiff the model-parameters for the effects of a treatment on the microfilariae and the adult parasite. An important question that we tried to answer is whether the impact on the adult worm is permanent ('macrofilaricide-like') or reversible. This analysis has a value in its own and has been submitted as a scientific paper. Part II (page 21) of the report deals with the consequences of the new insights for the role of ivermectin based strategies. We have tried to find those strategies based on annual ivermectin treatment and vector control which, under certain conditions, will lead to eradication of the parasite from a given area, i.e. will give rise to negligible recrudescence risks. Part III (page 33) comprises some miscellaneous notes which have been sent to OCP in view of the meeting of EAC15. An important item in these notes concerns the possible use of entomological criteria in post-larviciding surveillance. 2 Part I 3 Irreversible effects of ivermectin on adult parasites in onchocerciasis patients in the Onchocerciasis Control Programme in West Africa Absffact Ivermectin (MectizanR) is the drug of choice for onchocerciasis. It eliminates microfilariae from the skin and considerably suppresses their reappearance. In this paper it is investigated in what way this suppression is associated with the fecundity of adult Onchocerca volvulus. Predictions based on hypotheses about reversible and irreversible effects are compiued with post-treatment microfilarial counts of 114 adult persons from Ghana. These persons were followed during five years of annual community treatment by the Onchocerciasis Control Programme in West Africa. It is shown that the trend in microfilarial counts can only be explained when it is assumed that ivermectin, in addition to causing a temporary fall in the microfilariae production, also affecs the fecundity of the worms irreversibly. Following each treatment, worms recover during a period of about 10 to 11 months, and reach a new stablelevel of microfilariaeproduction which is 30% less than before treatment. Key words: Onchocerciasis, Onchocerca volvulus, Ivermectin, Modelling 4 The registration of the anthelminthic drug ivermectin (MectizanR) in 1987 was a landmark in the control of human onchocerciasis or river-blindness, a parasitic disease caused by the filarial nematode Onchocerca volvulus. Oral administration in a standard dose of 150-200p.glkg body weight is followed by rapid elimination of microfilariae (mf) from the skin and gradual reduction of ocular mf levels [1]. Side effects are generally mild and this makes ivermectin a better therapeutic option than Diethylcarbamazine @EC), which is often accompanied by severe Mazotti reactions and ocular damage. Ivermectin outperforms DEC also in a longer suppression of mf- repopulation of the skin [2,3]. This additional effect of the drug, which was obvious in all studies done thus far, has initiated research on the effect of the drug on adult parasites. Adult female parasites in treated persons showed an interruptionof the normal embryogenesis, but after a single treatment this appeared to be reversible for most of the worms [4,5]. Excess worm mortality has never been observed after a single treatment U,2,61. Irreversible effects on worms were found after many treatments with short intervals varying between two weeks and six months [6-11]. These studies revealed significantly more dead and moribund female worms in frequently treated patients than in not or only once treated controls. Furthermore, the reproductive activity of the surviving worms was markedly reduced. Since the examinations were done shortly after the last treatment it remains unknown to what extent the impact on reproduction is transient or irrevers- ible. Recent research, however, demonstrates that also one and a half year after five six-monthly doses the fecundity of female worms is still considerably reduced [12]. A question which is important in view of the limited resources available to health services in developing countries is whether the findings for short treatment intervals are also applicable to regimes with intervals of one year, which is the current practice in nearly all control progralnmes [1a]. In the present paper we address this question by analyzing data from a large community based study of annual treatments in a hyperendemic region (Asubende, Ghana), organised by the Onchocerciasis Control Programme in West Africa (OCP) Il4-17). The data consist of microfi- larial (mf) counts in skin-snips from persons who were surveyed over a period of almost five years in order to evaluate the first five treatments. We have investigated whether the observed trend in mf counts can be explained from short-term and transient effects of ivermectin only, or whether long-term and irreversible effects on the adult worms are involved too. Materials and Methods Study area and selection of cohorts. The Asubende region is located along the lower reaches 5 of the Pru river in Ghana, just west of Lake Volta. OCP started control of the vector (the blackfly Simulium damnosum) in this river basin in January 1986. Flies have been collected since 1979 to assess the vector biting rate and the vector infectivity. A clinical survey was done in September 1987 among 796 persons living in a cluster of three villages in the middle of the area. Both entomological and clinical findings revealed that the area was hyperendemic for the savanna form of O.volwlus. The skin microfilarial densities were among the highest encountered in the OCP area [13]. The community trial of annual ivermectin treatment was started in October 1987. In the first round of treatment more than 15,000 persons were treated, comprising 6L.5% of the study population. In the present analysis we use data consisting of mf counts in skin-snips which have been collected to evaluate the first five treatments (1987-1991). The organization of the trial, the trends in the skin mf densities, and the joint effect of vector control and ivermectin treatment on the transmission potential of the flies have been described elsewhere II4,l7l. Treatment dosage varied between 130 and 2ffipglkg body weight. From the 796 persons examined at the baseline survey in 1987, we selected the 114 adult persons ()20 years) who satisfy the inclusion criteria of the following two cohorts. The first cohort (n=78) consists of persons who were treated in all five rounds and were re-examined in all eight follow-up surveys which were done at 4 and 12 months after the first two treatments, 5 and 12 months after the third, 11 months after the fourth and 6 months after the fifth treatment. The second cohort was selected for a longer follow-up period of a single treatment. It consists of 36 persons who were treated at the first but not at the second round, and who were re-examineA 24 months after the first treatment. We restricted ourselves to adult persons because it is only for older ages that one may expect a constant infection level and, hence, exclude the confounding effect of ageing [18]. The dark bars in Figure 1 show the frequency distribution of mf counts in skin-snips before treatment and at the follow-up surveys. Modelling the effects of ivermectin. Hypotheses on the effect of ivermectin have been tested using the stochastic simulation model ONCHOSIM. This model describes the development of O.volvulus in man and flies and the transmission of the parasite. Elsewhere we explain the model in full and report its validation ll9-221. ONCHOSIM allows for a detailed simulation of control strategies. This enabled us to mimic the vector control activities employed in the Asubende area, thus accounting for the observed fluctuations in the transmission potential of the flies [17]. The microsimulation method, which is characterized by simulating the life-histories of individual hypothetical persons in a dynamic population (birth, acquisition of parasites, accumulation of mf, 6 death) and individual parasites (maturation, mating, mf-production, death), allows for describing and testing possible effects of ivermectin on the level of worms and humans. Since the output of the calculations is on an individual level, we were able to select those adult persons from the simulated population for whom the timing of treatments and surveys satisfied the same criteria used for selecting the cohorts, and for whom the skin-snip count distribution before the first treatment was identical to that of the cohorts. An assumption used throughout the analysis is that ivermectin treatment eliminates all mf in a person. Apart from this immediate effect, we will investigate one transient and two types of irreversible effect on the fecundity of adult female worms. The transient effect is modelled as a recovery period during which the mf production rate increases from zero to a new stable level. In case of the first type of irreversible effect of the drug, called oroductivity reduction, this new stable level will be lower than before treatment for all female worms. The second type of irreversible effect is the immediate and permanent cessation of mf-production in a certain fraction of the parasites, be it by death or by total loss of fecundity (.fecundity loss), while the other worms recover to their pre-treatment productivity. The magnitude of differences in transient and irrever- sible effects between persons and between treatments is called effect variability and is measured by the variation coefficient, i.e. quotient of the standard deviation and the mean of the effect. We explicitly test whether the increase in the mf-production during the recovery period is linear or not. In the Annex we give a mathematical description of the assumptions. Testing of hypotheses. According to the definitions of the model parameters, we will test two basic hypotheses I and II for the effect of ivermectin on adult worms: I. Treatment has transient effects only, i.e. there is no productivity reduction or fecundity loss; II. Treatment has also irreversible effects. To check whether the two types of irreversible effect differ in their explana- tion of the data, we will also test them separately. Hypothesis IIa states that an irreversible effect is only caused by permanent productivity reduction; in hypothesis IIb it is only caused by fecundity loss. When both effecs are combined, a fraction of worms immediately looses fecun- dity, and the remainder eventually reaches a stable mf-production, but on a reduced level. Each hypothesis is tested by a x'based comparison of observed and predicted skin-snip distributions for the follow-up surveys of each cohort. Some skin-snip count categories shown in Figure I have been combined so that the number of individuals is at least 5 per category. Estimation of parameters is achieved by minimizing X'using a downhill-simplex method 1231. Apart from the parameters directly related to the effect of ivermectin, we will estimate the mf-lifespan, since ttris parameter is an important determinant of the delay between stabilization of the mf-production and 7 stabilization of the mf{ensity in the skin (see Annex). Furthermore, we always assume 3% treatment failure. Such failure has been reported before and has been mainly ascribed to mal absorption (d iarrhoea, vo mitin E, etc. I24l) . Results The results of fitting the hypotheses about the effect of ivermectin to the data of the surveys after five treatment rounds strongly suggest that the drug affects the mf-production of female parasites not only temporarily (P<0.01) but also irreversibly (P>0.1); see Table 1. The irreversible effect can be quantified as a productivity reduction of 35% for all female worms, or as a total loss of fecundity (or death) for 28% of the worms. The data are explained well by both hypotheses, and detailed biological data would be required to differentiate between them. The goodness-of-fit did not improve significantly by combining the two types of irreversible effect; they appear to be interchangeable. Lower values for productivity reduction have to be compensated by higher values for total loss of fecundity in such a way that the combined loss of productivity in a patient equals about3?%. The recovery in mf-production is estimated to take 10-l l months, and the mf-production accelerates during this period (the associated shape parameter, not shown in the Table, has a value of 1.5 with a 95Vo confidence interval from 1.2 to 1.9). Note that the absence of an irreversible effect leads to larger values for the recovery period and the mf-lifespan, but apparently without achieving a sufficiently good explanation of the data. There appears to be a considerable variability between patients in the effect of treatment. The values of 0.52 and 0.54 for the effect variability imply an inter-quartile range, i.e. a range of values which covers the centre half of the patients, of 6 to 14 months for the recovery period, of lTVo to 38% for the fecundity loss, and of 20% to 47% for the productivity reduction. Table 1 also gives 95% confrdence intervals for the parameter estimates. Since the recovery period and the mf-lifespan jointly determine the speed of mf-repopulation of the skin, they are to some extend interchangeable, and consequently fairly wide confidence intervals were found for these parameters. The limited information on the lifespan of microfilariae [25) suggests that 4 months (our lower limit) is highly unlikely. This implies that the associated upper limit of 16 8 months for the recovery period is possibly also too high Figure I compares the observed mf-count frequency distributions for the post-treatment surveys with the predictions from the hypothesis of permanent productivity reduction (Hyp. IIa). There are no systematic differences between prediction and observations for cohort 1 (Fig. 1a). The lowest and highest mf-count categories are underestimated for the follow-up survey of cohort 2 (Fig. 1b), which suggests that the longer-term effect of treatment may vary more between patients ttran predicted by the model. The fit of the predictions to the survey data is summarized in Figure 2. The data are represented as a geometric mean mf-count. We fitted an exponential curve to the peaks of the predicted post-treatment trends, which represent the situation just before a new annual treatment. The figure clearly shows that disregarding irreversible effects of ivermectin leads to an underes- timation of the additional effect of each further treatment. Discussion Our analysis of the results of five consecutive annual treatments provides strong evidence that apart from killing microfilariae, ivermectin also has a significant impact on the viability of adult female parasites. A good explanation of the trends in mf-counts was obtained by assuming that each treatment is followed by a period of about l0 months of gradually increasing mf production to a level which is 30% lower than before treatment. The data did not allow us to differentiate between the hypothesis that all female parasites in a person are affected equally and the hypothesis that a fraction looses fecundity completely (or dies) while the others recover to their pre-treatment mf-production level. The temporary effect is in line with the results from earlier studies which showed that in most worms the normal release of mf was interrupted after treatment, but that I0 to 12 months later the percentage of worms with normal production had increased again significantly 14,5,26). Although none of these studies revealed excess mortality of worms by a single treatment, after one year a considerable fraction (40% lsD was not (yet) releasing mf. This explains the delay in repopulation of the skin by mf 11,3,27-291. Even after two years markedly reduced mf-levels were found [30,31], although most persons had become mf-positive again. Also in our cohort 2,the mean mf- 9 density after two yqus was still less than half the pre-treatment level. These observations suggest a lasting treatment effect. On the other hand, the dashed line in Figure 2 makes clear that one has to be careful in drawing conclusions from visual inspection of mf-trends: also without irreversible drug effects the predicted trend shows an, albeit insufficient, decrease in the mf-count at the 12- month follow-up surveys (the peaks of the curves). This predicted decrease is exclusively due to the reduced transmission of the parasite as a consequence of ivermectin treatment and (partial) vector control [17]. Conclusive biological evidence of irreversible effects of ivermectin was obtained from patients who had received four to twelve doses at intervals of two weeks to six months. More dead or moribund female parasites were found in these patients than controls who received no or a single treatment [5-7,9,10]. Excess worm mortalities of 25 to 33% were found in patients who received eight to eleven 3-monthly doses [9]. These percentages are about the same as the irreversible effect we found per treatment round. This suggests that this effect is predominantly due to a productivity reduction for all female worms and to a much lesser extent due to total fecundity loss or death. Analogous to our results, six months after the last dose (the longest follow-up in most studies) most female worms had not resumed normal embryogenesis and the percentage of viable worms was markedly reduced. Recent investigations suggest that recovery to full productivity after this short follow-up period is unlikely or will at least take more than two years [12]. Our findings partially rely on the interpretation of entomological data (counts of flies and their parasite load). We have taken into account the vector control schedule and the resulting trend in the transmission potential of the flies [7]. In calculating this transmission potential we assumed that the parasite larvae in flies originate from inhabitants of Asubende and will again be trans- mitted to them. Such an assumption would not be valid in areas with migration of flies. However, Asubende is an isolated focus with a local transmission [3], and hence ideal to test the impact of ivermectin. The data on mf-counts enabled us to test hypotheses on the effect of ivermectin, but do not allow to draw inferences on the exact biological mechanisms involved. Unavoidably, simplifications had to be made in the model. We will briefly discuss two simplifications which may be important for the interpretation of our results. Firstly, we disregarded any effect on the adult male worms. In some studies a significant reduction of the number of male worms were found [7,9], while in others this could not be concluded [5,6,10]. Although lower counts of male l0 wonns may be due to their ability to leave nodules [32], it may, at least temporarily, lead to reduced mating chances. Hence, the transient and irreversible reduction in mf-production we found could partly be attributed to absence or reduced viability of male worns. Secondly, we assume no prophylactic effect of ivermectin. Such drug induced protection against (super)infection would lead to a lower transmission than expected on the basis of fly-infection data. In experi- mentally infected chimpanzees a partial prophylactic effect was found on L3Jarvae, but not on later stages [33]. Since the L3-stage lasts for only 3 to 4 days and ivermectin is rapidly cleared from the body, no important prophylactic effects are to be expected. We have tested several other assumptions and extensions of the model, like effect-variability between the worms in one patient, genetic predisposition of treatment effect, etc. None of them affected our conclusion on the transient and irreversible nature of treatment effect or led to a significantly different quantification. It is, however, important to stress that our conclusions have been based on the results of annual treatment using a dose of l3D-ZDpglkg body weight. Changes in treatment frequencies or doses may lead to other effects per treatment. Our conclusions have important implications for the public health impact of strategies based on annual ivermectin treatment, which is the currently recommended regimen. In earlier studies we emphasized the potential of the drug for reducing the burden of blindness [20,34]. However, due to lack of sufficient follow-up data at that time, an irreversible effect of treatment on the adult worms could not demonstrated. This was the main reason for doubts about the potential of ivermectin for transmission control and thus for our cautiousness in designating it as the successor of vector control. Our new results certainly merit a reconsideration of this point of view. It should, for example, be noted that when each treatment leads to an over-all irreversible reduction of the fecundity of worms with30Vo, after five treatments this will be more than 80% on average for those female worms that survive the whole treatment period. Translating this figure to the impact of a long period (> 10) of annual treatment is not straightforward. Two complications are that not everybody will be treated (a coverage of 65-70% would be excellent in routine health care) and that transmission will continue (albeit on a lower level) so that new infections will occur. Preliminary predictions with ONCHOSIM indicate that, although the impact of long term ivermectin strategies is much more pronounced than we concluded earlier, the parasite will not be eradicated within a period of 15 years of annual treatment in an endemic area. We will start shortly with extensively analyzing the possibilities of applying annual ivermectin treatment to stop vector control earlier than originally planned in some areas of the OCP. We will also further explore the potential of the drug to control recrudescence of infection if it occurs after stopping 11 vector control. Finally, the promising resuls of our study will stimulate the assessment of the impact of higher doses on the viability of adult parasites. Acknowledgement We would like to thank Dr. E.M. Samba, Director OCP, and the staff of OCP and the National Oncho Team in Ghana for their support of our work. T2 Annex If m denotes the mean fraction fecundity loss and yii the effectiveness of treatment round ! G:1,..,5) in person j, then a fraction v;3m of the worms in person j will permanently cease mf- production immediately after treatment !. vij is a random variable, which for each treatment ! and each person j is generated from a gamma probability distribution with mean 1.0 and a standard deviation equivalent to the effect-variability. For those female wonns in person j which do not loose fecundity after treatment ! (a fraction 1:,:d the mf-productivity I1r of each worm k at time I after treatment is described by: r,,r(t) = r,l.dortr -vfl = ,,|*(r)r(t -v,d) for t<vrrTr for t>v,rTr "( )" (1) t vrrTr In this expression dg1 is the mf-productivity of worm k without treatment. This basic mf- productivity depends on the age and the mating history of the worm. The parameter d is the mean irreversible productivity reduction, Tr is the mean duration of the recover), period, and S is the shape of the recovery. If s>1, then the increase in the mf-productivity is initially slow and accelerates by the end of the recovery period. If g:1, then this increase is linear. In the hypothetical case that the random variable v13 takes such high values that v1i4q and/or v1,d exceed 1 the products are truncated to 1. Given the estimates of the effect-variability (around 0.5; Table 1) these situations are however highly unlikely to occur. In case of repeated treatment G> 1), in the model it is not allowed that an ineffective treatment (which implies a short recovery period) accelerates the recovery of a previous (effective) treatment. In case of total treatment failure (3Vo of treated persons) v;, is zero and no mf are killed. It is assumed that mf will in principle be detectable in the skin immediately after their release from the worm. No provision is made for a delay due to dispersal in the body and penetration of skin tissues. Mf are assumed to have a fixed lifespan CIm). In this simple concept, if the mf-production rate of the worms in a person stabilises at time !, then the mf-density in the skin stabilises at time t*Tm. 13 References 1. Awadzi K, Dadzie KY, Schulz-Key H, Haddock DRW, Gilles HM, Aziz MA. The chemo- therapy of onchocerciasis X. An assessment of four single dose treatment regimes of MK-933 (ivermectin) in human onchocerciasis. Ann Trop Med Parasitol 1985;79:63-78. 2. Greene BM, Taylor HR, Cupp EW, et al. Comparison of ivermectin and diethylcarbamazine in the treatment of onchocerciasis. N EnglJ Med 1985;313:133-8. 3. Larivibre M, Vingtain P, Aziz MA, et al. Double-blind study of ivermectin and diethylcar- bamazine in African onchocerciasis patients with ocular involvement. Lancet 1985;2:174-7. 4. Schulz-Key H, Klager S, Awadzi K, Diallo S, Greene BM, Larivibre M, Aziz MA. Treat- ment of human onchocerciasis: the efficacy of ivermectin on the parasite. Trop Med Parasit 1985;36 Suppl II:20. 5. Duke BOL, Zea-Flores G, Mufloz B. The embryogenesis of Onchocerca volvulus over the first year after a single dose of ivermectin. Trop Med Parasitol 199l:42:175-80. 6. Duke BOL, Zea-Flores G, Castro J, Cupp EW, Muffoz B. Comparison of the effects of a single dose and four six-monthly doses of ivermectin on adult Onchocerca volvulus. Am J Trop Med Hyg 199l;45:132-7. 7. Duke BOL, Zea-Flores G, Castro J, Cupp EW, Muffoz B. Effecs of multiple monthly doses of ivermectin on adult Onchocerca volvulus. Am J Trop Med Hyg 1990;43:65744. 8. Duke BOL, Pacqud MC, Mufioz B, Greene BM, Taylor HR. Viability of adult Onchocerca volwlus after six 2-weekly doses of ivermectin. Bull Wld Hlth Org 199l;69:163-8. 9. Duke BOL, Zea Flores G, Castro J, Cupp EW, MufrozB. Effects of three-month doses of ivermectin on adult Onchocerca volvulus. Am J Trop Med Hyg 1992;46:189-94. 10. Chavasse DC, Post RI, Lemoh PA, Whitworth JAG. The effect of repeated doses of ivermectin on adult female Onchocerca volvulus in Sierra Leone. Trop Med Parasitol t4 1992;43:256-262 11. Chavasse DC, Post RI, Davies JB, Whitworth JAG. Absence of sperm from the seminal receptacle of female Onchocerca volvulus following multiple doses of ivermectin. Trop Med Parasitol 1993;44:155-8. 12. Kllger S, Whitworth JAG, Post RI, Chavasse DC, Downham MD. How long do the effects of ivermectin on adult Onchocerca volvulus persist. Trop Med Parsitol 1993;44:305-10. 13. Remme J, Baker RHA, De Sole G, et al. A community trial of ivermectin in the onchocerciasis focus of Asubende, Ghana. I. Effect on the microfilarial reservoir and the transmission of Onchocerca volvulus. Trop Med Parasitol 1989;40:367-74. 14. World Health Organization Expert Committee on onchocerciasis control. First report Technical Report Series, in press. 15. De Sole G, Awadzi K, Remme J, et al. A community trial of ivermectin in the onchocerciasis focus of Asubende, Ghana. II. Adverse reactions. Trop Med Parasitol 1989;40:375-82. 16. Dadzie KY, Remme J, De Sole G. Changes in ocular onchocerciasis after two rounds of community-based ivermectin treatment in a holo-endemic onchocerciasis focus. Trans Roy Soc Trop Med Hyg 1991;85:267-71. 17. Alley ES, Plaisier AP, Boatin BA, Dadzie KY, Remme l, Zerbo G, Samba EM. The impact of five years of annual ivermectin treatment on skin microfilarial loads in the onchocerciasis focus of Asubende, Ghana. Trans Roy Soc Trop Med Hyg 1994; in press 18. Remme J, Ba O, Dadzie KY, Karam M. A force-of-infection model for onchocerciasis and its application in the epidemiological evaluation of the Onchocerciasis Control Programme in the Volta River basin area. Bull Wld Hlth Org 1986;64:667-81. 19. Plaisier AP, Van Oortmarssen GJ, Habbema JDF, Remme J, Alley ES. ONCHOSIM: a model and computer simulation program for the transmission and control of onchocerciasis. Comp Meth Prog Biomed 199O;31:43-56. 15 20. Habbema JDF, Alley ES, Plaisier AP, Van Oortmarssen GJ, Remme JHF. Epidemiological modelling for onchocerciasis control. Parasitol Today 1992;8:99-103. 21. Habbema JDF, Van Oortmarssen GJ, Plaisier AP. The ONCHOSIM model and its use in decision support for river blindness control. In: Epidemic models: their structure and relation to data. Cambridge University Press; in press. 22. Plaisier AP, Van Oortrnarssen GJ, Remme J, Habbema JDF. The reproductive lifespan of Onchocerca volwlus in West African savanna. Acta Trop l99L;48:271-84. 23. Nelder JA, Mead R. A simplex method of function minimization. Computer Journal 1965;7:308-12. 24. De Sole G, Remme J, Awadzi K, et al. Adverse reactions after large-scale treatment of onchocerciasis with ivermectin: combined results from eight community trials. Bull Wld Hlth Org 1989;67:707-19. 25. Duke BOL. The effects of drugs on Onchocerca volvulus I. Methods of assessment, population dynamics of the parasite and the effects of diethylcarbamazine. Bull Wld Hlth Org 1968;39:137-46. 26. Albiez EI, Walter G, Kaiser A, Ranque P, Newland HS, White AT, Greene BM, Taylor HR, Btittner DW. Histological examination of onchocercomata after therapy with ivermectin. Trop Med Parasit 1988;39:93-9. 27 . Awadzi K, Dadzie KY, Schulz-Key H, Gilles HM, Fulford N, Aziz MA. The chemotherapy of onchocerciasis XI. A double-blind comparative snrdy of ivermectin, diethylcarbamazine, and placebo in human onchocerciasis in Northern Ghana. Ann Trop Med Parasit 1,986;80:43342. 28. Taylor HR, Murphy RP, Newland HS, White AT, D'Anna SA, Keyvan Larijani E, Aziz MA. Cupp EW, Greene BM. Comparison of the treatment of ocular onchocerciasis with ivermectin and diethylcarbamazine. Arch Opthalmol I 986; 1 04:863-7 0. 16 29. Diallo S, Aziz MA, LariviDre M, Diallo JS, Diop-Mar I, N'Dir O, Badiane S, Py D, Schulz- Key H, Gaxotte P, Victorius A. A double-blind comparison of the effrcacy and safety of ivermectin and diethylcarbamazine in a placebo controlled study of Senegalese patients with onchocerciasis. Trans Roy Soc Trop Med Hyg 1986;80:921-34 30. Greene BM, White AT, Newland HS, Keyvan-Larijani E, Dukuly F, Gallin MY, Aziz MA, Williams PN, Taylor HR. Single dose therapy with ivermectin for onchocerciasis. Trans Assoc Amer Phys 1987;C:131-8. 31. Schulz-Key H, Soboslay PT, Hoffrnann WH. Ivermectin-facilitated immunity. Parasitology Today 19921'8:152-53. 32. Schulz-Key H, Karam M. Periodic reproduction of Onchocerca volvulus. Parasitology Today 1986;2:2844. 33. Taylor HR, Trpis M, Cupp EW, Brotman B, Newland HS, Soboslay PT, Greene BM Ivermectin prophylaxis against experimental Onchocerca volwlus infection in chimpanzees Am J Trop Med Hyg 1988;39:86-90. 34. Remme J, De Sole G, Dadzie KY, Alley ES, Baker RHA, Habbema JDF, Plaisier AP, Van Oortmarssen GJ, Samba EM. Large scale ivermectin distribution and its epidemiological consequences. Acta Leiden 1990;59: 177-91. t7 Table 1: Estimates of parameter values for the different hypotheses* on the working of ivermectin on the adult worm. Parameter Hypothesis I (only transient) IIa (also irreversible) IIb productivity reduction total fecundity loss recovery period (months) effect-variability (coeffi cient of variation) mfJifespan (months) goodness-of-fit (P-value ty'l) 357" (26%40V") 10.4 (7-16) 0.s4 (0.4-0.7) 28Vo Q2Vo-35%\ 10.7 0.52 19.0 0.87 l4 0.0013 [39] e (4-12) 10 0.68 [11.9] 0.42 [ls.s] Values in brackets represent the 95% confidence interval for these estimates. A '-' means that this parameter is not considered and thus has the value 0. * In Hypothesis I the drug has only transient effects. In Hypothesis IIa treatment results in an irreversible productivity reduction in each parasite. Under Hypothesis IIb, treatment causes a certain fraction of the parasites to loose fecundity totally. 18 Fig. 1 Frequency distributions of microfilarial counts for the pre-treatment survey and the post- treatment surveys of cohorts 1 (a) and 2 O). Dark bars represent the observations. The white bars denote the predictions for the assumption that treatment causes a permanent productivity reduction of 357o (Hypothesis IIa of Table 1). The numbers at the horizontal il(es represent the lower boundaries of skin-snip count classes. The numbers in the graphs of Fig. la (1 to 8) correspond to those in Fig. 2. pre-treatmenl cohort 1 o 2 4 0 i6 32 64 124256 No. ol ml per skin snip prs-lroatmenl cohorl 2 4-5 months alter treatment 1 1-12 monlhs alter treatmenl o o.5 2 I a tr€atment round round 1 round 2 round 3 round 4/5 2 E o sJo o a. ! =o o s 50 40 30 20 'to o 50 40 30 20 10 o 40 30 20 10 o 40 30 20 10 o o O5 2 .t 6 16 32 64124 o o.5 2 4 A 16 32 6112A o o.5 2 I a o o5 2 3 16 32 64 124 5 8 4 16 32 64 128 6 c o ! Jo oo E =o o s 40 30 20 10 o o.5 2 4 A 16 32 61129 o o.5 2 4 A 18 32 6412e o 05 2 I a 16 32 64 126 7 50 40 30 20 10 o 50 40 30 10 o o 2 No. ol ml per skin snip c o g J e oe !f o o a o 16 32 64 12a256 24 months arter lreatment O 2 /i A 16 32 61 126256 No. ol ml per skin snip t9 .g Eq c =an L o o- E c;c c(I, o = Fig. 2 Observed (dots) and predicted (ines) geometric mean skin-snip counts of study cohort 1. The solid lines represent predictions based on the hypothesis of a productivity reduction of 35Vo (Hyp.IIa). The dashed line is based on the hypothesis of no irreversible effects (Hyp.I). The peaks in the predicted trends (excluding the pre-treatment survey) have been connected with an exponential curve $=a.e-b'*). The times of the five treatments are in- dicated below the horizontal axis 100 95 30 20 10 0 \ '88 T1 \ '89 \ '90 \ '91 \ '92 T2 T3 T4 Calendar year T5 8 20 5 Part II 2t Eradication of onchocerciasis infection by vector control and annual ivermectin treatment. Introduction The objective of the Onchocerciasis Control Programme in West Africa (OCP) is to eliminate onchocerciasis as a public health problem in the area covered by the progralnme and to ensure that no recrudescence of the infection and the disease will occur. Initially, the only measure of control was aerial larviciding of the river basins, the breeding places of Simulium damnosum ssp., in order to eradicate the vector and block the transmission of Onchocercavolvulus. Since the vector control operations are extremely costly, an important question is after how many years they could be ceased without running unacceptable risks of fatal transmission levels when the blackflies return. In a previous study, we have applied the ONCHOSIM simulation model to assess the risk of recrudescence after several years of successful larviciding. Taking into account the differences in pre-control endemicity of the disease and several risk factors favouring recrudescence, we concluded that 14 years should be suffrcient to reduce the risk to less than l Vo even in the most afflicted areas @laisier et al., L99la). This has since been adopted :rs a general guideline. In developing this guideline, it was assumed that, given the limited treatment coverage and the presumed limited impact on the adult parasites, the microfilaricidal drug ivermectin - registred in 1987 - would not play a significant role in controlling the transmission and that eradication of the parasite should be accomplished by vector control alone. In large parts of the original OCP area (where larviciding started between 1975 and 1977) OCP has discontinued large scale larviciding and replaced it by a programme of entomological and epidemiological surveillance in order to detect unforflrnate occurrences of recrudescence of infection. For two reasons, the initially adopted guideline has to be reconsidered for the extension arqm of OCP where vector control started later as well as the areas where vector control was less sucessful during the first years. The first reason is that financial resources become more and more limited, pressing OCP to speed up the process of devolution, i.e. the transfer of responsibilities to the participating countries. The second - forfirnate - reason is the growing evidence that ivermectin is not only a very effective microfilaricide, but also has considerable effecs on the viability of female worms @uke et al., 1992; Kager et al., 1993). In a recent model-based analysis of data from a community trial of annual treatments in the Asubende area (Ghana) we have found that, 22 \l following each treatment, female worms are considerably delayed in their mf-production and that the ultimate fecundity level stabilizes around 70% of pre-treatment @laisier et al., submitted). Such strong effects put a new light on the potential of community treatment for controlling transmission and, hence, for shortening the required duration of vector control. This potential of the drug is the subject of the present paper. We will use the ONCHOSIM simulation model to investigate the extent to which annual ivermectin treatment can lead to earlier cessation of vector control. We will show how this depends on the attainable treatment coverage, the pre-control endemicity in the area, alternative assumptions on the effect of ivermectin on adult worms, and the timing of the start of ivermectin treatment. Methods Basic assumptions Vector control operations are assumed to be 100% effective, i.e. to reduce the biting rate to zero. Flies are assumed to return immediately after cessation of larviciding, giving rise to a biting rate equal to the pre-control level. With respect to the effect of ivermectin treatment we use the following assumptions: following treatment (1) all microfilariae are eliminated, Q) female worms recover from total loss of fecundity during,l0.to..11 months and (3) reach a new stable mf- production level rvhich is permanently 35Vo lower than before tr.eatlUgg! (Plaisier et al., sub- mitted). Both the period needed to recover and the permanent impact of the drug vary between persons and between treatments (var. coeff. a;|!L An alternative assumption we test is that the irreversible reduction of fecundity is not 35% but only 25Vo per treatment. This lower percentage can be justified from the confidence interval for the estimate of this parameter. The coverage of treatment (Vo of persons getting the drug) is one of the variables in the present analysis. This coverage is not equivalent to the probability to be treated for each individual in the population: depending on age and sex and some persons have a higher chance, others a lower. For example, children below 5 are not treated. Women in the fertile ages have a lower probability since pregnancy and lactation are exclusion criteria. Furthermore, persons can differ considerably in their compliance with treatment. The age- and sex-specific variation in treatment coverage has been taken from the results of the Asubende-trial (Alley et al., in press). In the Annex we explain how, given a mean population-coverage, for each individual the probability to be treated is calculated. 23 The assumptions have been incorporated into the stochastic microsimulation model ONCHOSIM which has subsequently been used to simulate the control strategies. A complete description of the model and parameter quantification is provided in Habbema et al. (in press). We simulate human populations of around 300 persons (natural growth of the population is compen- sated by migration) which show a pre-control endemicity level similar to the villages Tiercoura and Folonzo (both Burkina Faso) with a CMFLI of 70 and 30 mf per skin-snip respectively @laisier et al., 1991b). Observations of pre-control fly biting rates are lacking for this area. Using observations in the Pru-river, close to the highly endemic Asubende region in Ghana (Remme et d., 1989) we estimate the Annual Biting Rate within Tiercoura at27, (for adult men) and within Folonzo at I The maximum $osrre to fly-bites is, in both villages, reached at the age of 15 years. Women are, on average, 30% less exposed than men. The variation coefficient of bites/person within a specific age and sex group is estimated at 0.39 for Tiercoura and 0.54 for Folonzo. Since we have previously found that the (age- and sex-indepen- dent) exposure heterogeneity is an important risk factor for recrudescence, we will also simulate a 'Tiercoura-like' village (called Tiercoura*) with an exposure variation coefficient of 0.58. Simulation of control strategies A control strategy is completely described by the number of years of (l00Vo successful) vector control (v), the number of annual ivermectin treatments (i), the treatment coverage (Vo treated, c) assuming that this will be constant for the whole period, and the time-lag between the start of vector control and the start of ivermectin treatment (d), assuming that treatment always starts later. We have tested many combinations of y (range: 0 to 15 years), i (range: 0-30), c (range: 35-75%), and, d (0, 8, and 16 years). The result of each simulated strategy is summarized as 'recrudescence' (l) or 'no recrudescence' (0). Recrudescence is defined as the occurence of increasing mf-loads after total withdrawal vector control, ivermectin or both Statistical analysis of simulatton results The purpose of the analysis is to estimate the recrudescence risk as a function of the strategy- variables. Previously @laisier et al., l99la) we have achieved this by performing many simula- tions for one particular strategy (number of years vector control) and counting the number of simulations resulting in recrudescence. By choosing an appropriate range of durations of vector control, those durations where the risk approaches zero (e.g. 0.01) could be identified. However, I Community Microfilarial Load; i.e. the geometric mean mf-load in adults 24 -tr.9^?lT:€I!i logistic regress t----\l c, and d)[+ with four strategy-variables involved this approach is not suitable: the range of vector control- durations where the risk changes from - 1 to - 0 is different for each ivermectin treatment strategy. In the present analysis we have applied another method which comprises the following two steps: (1) for a large number of ivermectin treatment strategies, an iterative procedure is used to flnd the duration of vector control where the risk changes most rapidly; Q) the technique of ion is applied to estimate the risk for each ftrategy (which is a combination of v, i, An example of the iterative procedure is given in Fig. 1. In this example we use the parame- ters representative for Tiercoura. The ivermectin strategy consists of 10 years of treatment, starting in the same ye:tr as vector control and covering 65Vo of the population. The initial duration of vector control is 10 years which results in eradication of the parasite. The initial iteration step is 4 years and hence the next attempt is 6 years vector control. This is (far too) short and results in recrudescence. Now, the iteration step is halved and 8 years vector control is tested. This is still too short and again try 10 years is tested, again resulting in eradication. Since we are especially interested in low recrudescence risks (e.g. 1%) we take one-third of the iteration step when a "1" (recrudescence) is followed by a "0" (eradication). Hence, the new tested value is 9.33 years (nine years and four months). Here recrudescence is encountered and we subsequently test 9.67 years (halving the interval). A total of 10 iteration steps is done in this way. The smallest interval allowed is one month. Note that 9.67 years is tested three times, successively resulting in "0", "1", and "0". Apparently, around this value the risk is changing most rapidly. All iteration-steps for all tested combinations are accumulated in a data-file for use in the regression analysis. Tentative regression results are used to repeat the procedure using other starting values and other (as a rule smaller) initial iteration intervals. We have used SPSS to calculate logistic regression equations for the risk of recrudescence (ref.). Separate equations are calculated for the different area-conditions: Tiercoura, Tiercoura*, and Folonzo, as well as for the different values for the delay between the start of the two control methods (d=0, 8, or 16 yqrs; only for Tiercoura) and the effectiveness of ivermectin (35% vs. 25% permanent effect; only for Tiercoura). The independent variables of the regression equations are the duration of vector control (v), the number of annual treatments (i), the treatment coverage (c), and linear, quadratic and cubic combinations of v, i and c. Since neither i nor c has a meaning on its own, they are always combined in the regression equations. In the procedure for estimating regression coeffrcients we have used a combination of backward and forward selection. Each procedure is started with the strategy variables (v and i. c) and their linear and quadratic combinations (interaction terms, e.g. i2.c.l). Coefficients that are not significant (P=0.05, 25 according to the Wald-statistic; ref.) are eliminated while the significant coefficienS for the cubic terms (e.g. r/; anA interaction terms with a cubic component are included (e.g. i'C'rl;. nn example of estimated regression coefficients is provided in Table 1. Form the resulting regression equations the risk of recrudescence for a given v, i, and c can be easily calculated. However, they are too complicated to calculate the duration of vector control which corresponds with a given recrudescence risk (given the values of i and c). This is done iteratively, using the routine available in the Borland Quattro-Pro spreadsheet progr:Im. Results Fig. 2 shows the trend in the recrudescence risk for several combinations of the number of annual ivermectin treatments and the duration of vector control in a Tiercouralike village. It is assumed that the average treatment coverage is 65% and that both control methods start at the same moment. The lines in the figure represent 'iso-risk' lines, connecting those strategies that result in equal risks (0.01, 0.1, 0.5, and 0.99). Below (less vector control) and left of the line (less annual treatments) the risk is higher than indicated, otherwise it is lower. In the absence of ivermectin treatment (points on the Y-axis) approximately 13 years of vector control are required to reduce the recrudescence risk to 1%. This duration reduces to 11 years when ten years of annual ivermectin treatment is added. With the same ivermectin strategy the risk increases to 0.1 when vector control is stopped already after 10 years. Recrudescence is certain (risk > 0.99) with only less than 6.5 years of vector control. The iso-risk lines diverge considerably as the number of treatments increase. With 16 treatments risks of less than 0.99 are achieved in the absence of vector control, while still9.3 years of vector control are needed to reduce the risk to 0.01. The effect of alternative coveragelevels is shown in Fig. 3a. In this figure only the 0.01 iso- risk lines are shown. Especially for longer periods of treatment the impact of higher or lower coverages is considerably. When treatment is continued for 15 yqlrs, then each 10% decrease in coverage corresponds with approximately 9 months more vector control to maintain a recrudes- cence risk of 0.01; with l0 years of treatment the gain or loss is only 2-4 months. Fig. 3b demonstrates that the effectiveness of control strategies is highly dependent on the pre-control endemicity of the area. With a treatment coverage of 65Vo, in a village like Folonzo, 20 years of annual treatment are sufficient to eradicate the parasite without the help of vector control. Shorter periods of treatment (10 - 15 years) allow considerable reductions in the duration of vector control. 26 The predicted implications of a delay between the start of vector control and the start of annual treatment is shown in Fig.4. The results apply to Tiercoura and a coverage level of 65%. Up to 20 years of annual treatment, with a delay of 8 years less vector control is required to reduce the risk to 0.01 than with an equal start. For example, with a period of ten years of annual treatment, [0 years of vector control are sufficient; this was almost 11 years when both methods started synchronous. For periods of 20 years of treatment or more, a delay of 8 years is slightly less favourable in terms of reducing larviciding. Such long durations correspond with less than 8 years of larviciding, and this implias a short period without any means of control (treatment starts after cessation of larviciding). This is the major problem with a long delay like 16 years. Now treatment always starts when larviciding has stopped, which implies that in many cases ivermectin treatment is used for the control instead of the prevention of recrudescence. A summary of the results is provided in Table 2. For each of the circumstances and four different coverage levels, the required duration of vector control which reduces the recrudescence risk to l% ue shown for four different durations of annual treatment (5, 10, 15, and 20 years). The numbers in the table are obtained from the regression equations. 27 Table 1. Ivermectin treatment ixc ix* ixc i2xc i3xc Estimates of the coefficients for the variables (row x column) of the logistic regression equation for the recrudescence risk Tiercoura (d = 0). Prior to estima- tion, the variables are transformed as follows: i = no. of ivermectin treatments + 10; v = no. of years vector control + 10; c = coverage (Vo) + 50. The resulting equation has the form: tn(r/1-r)=fi.6 + 22.7.v - 28.3.i + 5.71.i.c - 25.1.i. c,v + ..etc., with r being the recrudescence risk. Vector control v f 22.71 i n.s 12.g* 5.71 -t2.5 3.86 n.s. n.s. -25.1$ 4.47 n.s. 4.86 n.s. -28.3 13.6 n.s -1.79 -0.576 n.s.+ n.s n.s n.s n.s n.s * the constant of the equation t coeffrcient for covariable v + not significant $ coefficient for covariable i. c. v (interaction term) 28 Table 2 Village Treatment coveruge (%) tr.9 10.8 9.r 10.0 9.3 8.4 9.8 8.7 r .0 No. of years vector control required to reduce the recrudescence risk to less than 0.01 Number of annual treatments: 5 10 15 20 r2.2 11.6 11 .0 10.3 tz.r 11.3 10.3 9.2 r2.0 11.0 9.6 7.9 6.5 Tiercoura Tiercoura Tiercoura Tiercoura Folonzo Folonzo Folonzo Folonzo Tiercoura * Tiercoura + Tiercoura * Tiercoura * Tiercoura, delay treatment 8 years Tiercoura, delay 16 years Tiercoura, less effective ivermectin 45 55 65 75 45 55 65 75 45 55 65 75 65 65 65 7.6 4.6 9.6 7.9 0 09.3 6.9 0 13.1 12.5 11.8 11.1 r3.0 t2.2 tt.2 to.2 12.9 rl.9 10.6 9.1 12.9 11.8 10.0 7.9 tL.4 10.0 8.9 8.0 tz.t 11.5 11.1 10.6 12.2 tt.4 10.4 9.2 29 Fig. 1 and 2 Tiercoura varying recrudescence risk 12 10 \ \ 10 15 No. of annual treatments 14 {- risk=0.01 + 0.1 -E- 0.5 + 0.99 8 6 4 2 6 c o o o oo ot-(u o o ciz 0 50 v=6 v=8 v=1 0 1 0 1 0 1 ---+ r€ 0 1 o€ 20 25 Fig. 3a and 3b 6 c o o o oo a (U o o ciz 14 12 10 6 14 12 10 Tiercoura varying coverage 10 2 0 50 15 20 25 Folonzo varying coverage k*.*- \ \ \ 10 15 No. of annual treatments + 45% -f 557o + 650h * 75% I 6 4 2 0 o c oo o oo U' (U o o oz 50 + 45% 55"/o + 65% + 75/" 20 25 Fig. 4 14 12 2 Tiercoura varying delay 10 15 No. of annual treatments -+ 0 + I -)<- 16 I 6 4 1 6 c o o o oo o (U o o c;z 0 50 20 25 32 Part III 33 Recrudescence of onchocerciasis infection after cessation of control The potential of ivermectin in the prevention and control of recrudescence 1. Introduction The major objective of OCP is to eliminate onchocerciasis as a public health problem in the area covered by the programme and to ensure that no recrudescence of the infection and the disease will occur. Initially, the only tool to achieve these targets was aerial larviciding of the river basins in order to eradicate the vector and block the transmission. Since the vector control operations are extremely costly, an important question is after how many years they could be ceased without running unacceptable risks of fatal transmission levels when the blackflies return. In a previous study, we have applied the ONCHOSIM simulation model to assess the risk of recrudescence after several years of successful larviciding. Taking into account the differences in pre-control endemicity of the disease and several other risk factors favouring recrudescence, we concluded that 14 years should be sufficient to reduce the risk to less than I Vo ayan in the most afflicted areas. This has since been adopted as a general guideline. However, there has always been the awareness that such a guideline cannot be applied uncritically. In particular in areas where vector control was less successful or where there has been significant invasions of flies, additional considerations are needed for decision making. In particular the consequences of human migration have to be considered in this respect. The registration and field testing of ivermectin (MectizanR) have increased the possibilities for control enormously. Its microfilaricidal efficacy has proven to be a major weapon in the fight against ocular disease and blindness. Regular administration (at annual or semi annual intervals) to the population also causes a significant reduction in the level of transmission. However, mainly due to the ability of the blackflies to transmit the infection at low skin microfilarial densities, one should be cautious in designating ivermectin as an equally powerful alternative of larviciding and, as a consequence, stop vector control. Preliminary simulations with ONCHOSIM have shown that, in the absence of supplementary vector control, ivermectin treatment will most likely not eradicate the infection from an area. On the other hand, simulation results suggested that a strong treatment regime might be an efficious measure to stop recrudescence if it, unfortunately, occurs after cessation of vector control. An important condition is that such recrudescence is detected timely. In the present report we aim at giving an in-depth analysis of the potential of ivermectin as a tool for transmission control. The most important reason to carry out such an analysis is that, in the period since our preliminary simulations, additional data from field studies became available. Initial clinical trials did already show that the immediate elimination of microfilariae in most of the patients was followed by a considerable delay in the repopulation of the skin. A thorough model-based analysis of the results of the Asubende trial not only confirmed these findings but also provided strong evidence that treatment induces an irreversible reduction of the fecundity of adult female worms. We have estimated this permanent reduction at average of around 30% per treatment. L 2. Methodology We will discuss three strategies for the use of ivermectin in the context of OCP and assess the risk of recrudescence associated with these strategies: (1) Ivermectin treatment and vector control are applied jointly during a certain period. The two control measures will start and stop at the same moments. {!)Like strategy (1), but vector control is only applied during the first part of the control period (e.g. the first 8 years) after which (annual) treatment with ivermectin will continue alone (e.g. for 10 years). Q) Vector control is initially used as the only control strategy (central OCP il%), but after stopping vector control an ivermectin treatment campaign is used to stop recrudescence if it occurs. When discussing this latter strategy, we will try to develop guidelines for the detection of recrudescence on the basis of both entomological and epidemiological indices. An important outcome will be an assessment of the critical period between the cessation of larviciding (and the possible onset of the recrudescence) and the start of the ivermectin treatment campaign. For each of these 'families' of strategies we will carry out a large number of simulations with the ONCHOSIM model. Important independent variables in the sen- sitivity analysis are the duration of a control strategy and (for ivermectin) the coverage of treatment. Furthermore, we will use four different sets of assumptions, which we will denote model 1 through 4: Model 1: This is the standard model quantification which we estimated for a hyper-endemic village like Tiercoura (Burkina Faso). In this model we use those values for the parameters of the working of ivermectin that resulted in the best agreement with the data from the Asubende trial. It is assumed that each treatment results in an irrever- sible reduction of the mf-production of adult female worms of 35% on average. Model 2: In this model we assume less permanent effect of ivermectin on the fecundity of worms: 25% instead of 35 %. The value of 25% appeared to be the lower confidence limit for the estimate of this parameter. Model 3: In this model we have increased the variability between persons in the exposure to blackfly bites. From previous analyses we have noticed that this is an important risk factor for recrudescence. Model 4: This model is quantified like model 1. The difference is that at a given moment during the simulated strategies a given number of infected immigrants enter the area. 3. Results INOTE: OnIy part of the analysis is finished. New results will be sent as soon as they are availablel 3.1 Strategy (1) The results for strategies where vector control and ivermectin treatment are applied jointly (same starting moment, same moment of cessation) are summarized in Table I and Fig. 1[at present only for models 1 to :1. Each row in Table 1 represents a given coverage of treatment (fraction of population treated). The numbers in the Table represent the risk of recrudescence after a given duration of control and with a given model. For example, 11 years of successful vector control together with 11 years of annual ivermec- tin treatment with a coverage of on average 25% gives rise to an (unacceptable) risk of recrudescence of 0.48 when we use the assumptions of the standard model 1. When we Z assume that ivermectin causes less permanent effect to adult worms (model 2), then this risk increases to 0.56. Finally, when there is a larger heterogeneity in exposure (which implies that there exists a sub-population of very frequently bitten persons when vector control stops) the risk of recrudescence is estimated at 0.9. The recrudescence risk is calculated by carrying out 50 simulations with a particular model and for a particular strategy and counting the simulations that lead to recrudescence (e.9. a risk of 0.48 means that24 out of 50 simulations showed a recrudescence). From the simulation results we can conclude that a duration of 10 years of combined control is too short to prevent recrudescence, even at high treatment coverages of 0.65 and more. The two 'high-risk' models (2 and 3) resulted in considerable risks of 0.4 when the coverage of treatment is around 0.65 (a coverage which was attained during the Asubende trial). One additional year of control results in a major improvement. Eleven years of combined control with a treatment coverage of 0.65 corresponds with a recrudescence risk of slightly more than 5Vo (model 3) to around zero (model 1). The conclusion seems justified that 12 years of combined control is sufficient, unless the coverage of treatment decreases to below 60% (model 3). The results are also plotted in Fig.1. In this figure we have, in addition, fitted a logistic curve through the observations: _r=1- 1 -/ x-a\t+e\t) with a being the treatment coverage where the recrudescence risk is 0.5. The factor b is proportional to the range of coverages which lead to risks intermediate to 0 and 1. Table 1 Recrudescence risks for several durations of control, for several values of the treatment coverage and based on 3 different model assumptions. cov. Standard model (1) 10yr l|yr Less perm. effect iverm. (2)10yr llyr 12yr More exposure variation (3) 10yr llyr 12yr 0 0.0s 0.1 0.15 0.2 0.2s 0.3 0.35 0.4 0.4s 0.5 0.s5 0.6 0.6s o.7 0.75 1 1 1 1 1 1 1 0.92 0.76 o.82 0,5 0.38 o.14 0.1 0.08 0.04 1 0.96 o.82 o.74 0.76 0.48 o.24 o.22 0.1 0.04 0.02 0 0 0 0 0 1 1 1 1 1 1 0.98 1 0.96 0.88 0.8 0.68 0.54 o.4 0.28 0.32 0.94 0.92 0.9 0.8 0.8 0.56 0.s2 0.38 0.32 0.08 0.1 0.1 0.04 0.02 0 o.o2 o.22 0.16 0.18 0.04 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0.98 0.98 0.98 0.98 0.84 0.64 0.48 0.38 o.42 o.32 1 0.98 0.96 0.94 0.9 0.9 0.78 0.62 0.s2 0.26 0.3 o.12 0.04 0.06 0.08 0 0.6 o.42 0.38 0.34 0.28 0.08 0.1 0 0.04 0.02 0.02 0 0.02 0 0 0 3 Duration of strategy: a 10 yr o 11yr I 12yr Model 1 Model 2 Model 3 o oc o o o o!3 o o o = .o (U l, o (L 1.0 0.8 0.6 o.4 o.2 0.0 1.0 0.8 0.6 0.4 0.2 0.0 1.0 0.8 0.6 o.4 0.2 0.0 A Q A A A a \a A A Ot.o a a A? A\o \ a -t - o - a ao L, A A 10 I I A 'N"-- \- a 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 ?- 7 r- A q A a e \a ol o a a\ Average fraction treated -5 -. \ Centre lor Declslon rclencesm ln Troplcal Disease Control ERASMUS UNIVERSITY ROTTERDAM Centre for Decision Sciences in Tropical Disease Control Department of Public Health P.O. Box 1738 3000 DR Rotterdam The Netherlands Tel. (10) 40877 t4 Fax. (10) 436 68 3l DATE TO NAME DEPT ADDRESS COUNTRY TELEFAX I June 1994 Mr. E. Soumbey-Alley Onchocerciasis Control Programme in West Africa (BIS) B.P. 549 OUAGADOUGOU Burkina Faso 00 226 302 147 FROM A.P. Plaisier (emf no. 5165) NUMBER OF PAGES (incl. frontpage) 6 NOTES : Dear William, Attached some first results t (very brief) explanation. I will send you more on friday. As a background document see: "Recrude.scence of onchocerciasis infection - simulation of risks, detection and control". The anached figures provide a first indication of the potential value of entomological criteria for detecting recrudescence. In each of the graphs we have simulated a hyper-endemic village like Tiercoura a 300 times, leading to recrudescence in 110 (Fig I and 2) and ll2 (Fig 3 and 4) of the cases. To detect recrudescence we use the ratio between the post-control and pre-control ATP. The graphs show the situation 30 years after cessation of vector control as a function of the ATP*r,:ATPo,rl value used as a criterion for detecting recrudescence. In Fig 1 we have tested such ratio's between 0.005 (0.5%) and 0.05 (5%) assuming that the ATP*., is determined each 3 yea9. The solid line shows the number of recrudescence cases that has been detected and where an ivermectin treatment campaign has started. In Fig. la this campaign consists of l0 years of annual treatment with a mean coverage of 65%. For the range of tested ratio's, the large majority of recrudescence qNes have been detected after 30 years. However, when a ratio of 0.035 is used (3.5%) a few recrudescence cases have been detected too late (dashed, t*') to be controlled by ivermectin. In Fig. lb the campaign after detection consists of 15 years of annual treatment and a coverage decreasing from 65 in the first to 35% in the final year. This graph is highly comparable to Fig. la. In Fig. lc we assume a campaign of only 10 years with a coverage decreasing from 65 to 35%. With such a campaign, some recrudescence cases are detected too late when a ratio of only 0.025 Q.SVo) is used. In Fig. 2 (a, b, and c) the interval between successive entomological surveys is 4 years. Fig. 3 is comparable with Fig. 1, except that it is assumed that ivermectin is a less effective drug (25% permanent effect on adult worms instead of 35%). In Fig. 4 we assume less effective ivermectin and a survey interval of 4 years. Note that, when the most pessimistic assumptions hold true (Fig. ac) then the detection of one recrudescence case will always be tool late (irrespective of the ratio used). The dashed line with'+'denotes the number of false alarmes (i.e. the cases where recrudescence is presumed uniustly).J In conclusion: When the ATP is determined at intervals of 3 to 4 years, then a ratio of ATP*r,:ATPrr" of 0.02 (zVo) as a criterion for detection is a good balance between detecting too early (too much false alarmes) and detecting too late. I Under the assumption that the mean ABR and the mean parous rate before vector control is exactly the same as after vector control. 2 The first ATP has been determined between 2 and 3 years after cessation of control; the second ATP has been determined between 5 and 6 years after cessation of control, etc. \\........- Hyper-endemic village Survey interval 3 ([iercoura) years + -+- -r(- fig 1a o C _9 a5 .E , o c;z 10 years ivermectin constant coverage : 6596 15 years ivermectin coverage reducing lrom 65 to 35ol" 10 years ivermectin coverage reducing lrom 65 to 35% ATP post: ATP pre ATP post : ATP pre + -+- -x- f,g 1 -{' 1c oc .9 65 .Eo o c,z oc .9 c,5 .Eo o c;z + -+- -t(- fr3 I I l I ATP post : ATP pre \. ,."\........ -..........,-...--.' LHyper-endemic village Survey interval 4 (fiercoura) years + -+- -l(- 69 2a 6c .9 G l E , o c,z oc .9 6 f .Eo o ciz oc .9 a5 .Eq o oz ATP post : ATP pre ATP post : ATP pre + -+. -x- n3 1O years ivermectin constant coverage = 6596 2 15 years ivermectin coverage reducing from 65 to 35% 2c 10 years ivermectin coverage reducing from 65 to 35% -+ -+- .l(. n3 I t L I I ATP post : ATP pre - oc .9 6 = .Eo o ciz oc .9 -gf E ,6 o CJz o C .9 6 f .Eo o CJz Tiercoura - less effective ivermectin Survey interval 3 years ATP post : ATP pre ATP post : ATP pre + .+- -*- ne )a- 1O years ivermectin constanl coverage = 657o 15 years ivermectin coverage reducing from 65 to 35% 3c 10 years ivermectin coverage reducing from 65 to 35% + -+- -*- E3 3* + -+- -*- n3 + \ ATP post : ATP pre I6t .9 6 E .Eo o oz Tiercoura - less etfective ivermectin Survey interval 4 years ATP post: ATP prc ATP post: ATP pre + -+- -*- f,g ya 10 years ivermectin constant coverage : 657o 15 years ivermectin coverage reducing from 65 to 35% Llc 10 years ivermectin coverage reducing from 65 to 35% + -+- -)t(- C.1,9 1 ,l- oc .9 6 E .Eo o ciz + -+- -*- f9 ac o !f .Eo o oz I ATP post : ATP prc Centre for Decision sciences CDIDrc ln Troplcal Dlsease Control ERASMUS UNIVERSITY ROTTERDAM Centre for Decision Sciences in Tropical Disease Control Department of Public Health P.O. Box 1738 3000 DR Rotterdam The Netherlands Tel. (10) 40877 14 Fax. (10) 436 68 31 DATE TO NAME DEPT ADDRESS COUNTRY TELEFAX 3 June 1994 Mr. E. Soumbey-Alley Onchocerciasis Control Programme in West Africa (BIS) B.P. 549 OUAGADOUGOU Burkina Faso 00 226 302 147 FROM A.P. Plaisier (emf no. 5165) NUMBER OF PAGES (incl. frontpage) 3 Attached you will find an aggregation of the results for detection and control of recrudescence by the ATPro.,:ATPo." ratio. The bar-graphs show the distribution of the critical delays, i.e. the-maximuh period of time between cessation of vector control and the onset of ivermectin treatment allowed to sucessfully control recrudescence. NOTES : Dear William, Anton Threshold values for the ATPoor,:ATPo." ratio to detect and control rirudescerice Tiercoura - standard assumptions for ivermectin Survey interval (years) Optimall value for ivermectin scenario2: % unnec. treated for scenario A B C A B C I 4 5 4.25 83 31 68 2 2.75 3 ', )< 4 2 18 3 2.5 2.5 2.25 0 0 2 4 2.25 2 2 0 2 2 5 2.5 2.5 2 0 0 2 6 2 2 ,.a.3 0 0 n.a I Optimal value: 1. Detection comes never too late (within a period of 30 years after cessation of vector control) 2. The percentage of 'unnecessarily treated' situations is minimized 3. The recrudescence situations are detected as soon as possible.2 A = 10 years ivermectin, constant coverage of 65%; B = 15 years ivermeitin, coverage reduces from 65 to357o; C = l0 years ivermectin, coverage reduces from 65 to35%.3 I.e. irrespective of the threshold value, this interval will result in at least I case where recrudescence detection and control is too late. Tiercoura - less permanent effect of ivermectin Survey interval (years) Optimal value for ivermectin scenario: % unnec. treated for scenario: A B C A B C I 4 4.25 4 80 72 80 2 2.75 3.5 2 4 0 42 3 2.25 2.5 n.a. I 1 n.a 4 2 2.5 n.a. 2 0 n.a 5 1.5 2 n.a. 7 1 n.a 6 1.5 2.25 n.a. 6 0 n.a Tiercoura risk of recrudescence = 37"/" 30 ao3zso oo620oao O JF = lc t-oo E10 rOo\ 35 20 10 <6 5 0 6-1 0 1 1-15 16-20 21-25 26-30 critical delay (years) I 10 yrs; 65% 7- ls yrs;6$>35% VVZ 10 yrs; 65,>35% Tiercoura - less effective ivermectin risk of recrudescence : 37To >30 30 25 1 aoa(U o ooc oo @oof Lo oL o rOo\ 5 0 6-10 1 1-15 16-20 21-25 26-30 critical delay (years) I 10 yrs; 65% 7- lS yrs; 6$>35% 72 lO yrs; 6$>35% <6 >30