Open Access

Long term study on the effect of mollusciciding with niclosamide in streamhabitats on the transmission of schistosomiasis mansoni after community-basedchemotherapy in Makueni District, Kenya

  • Henry C Kariuki1,
  • Henry Madsen2Email author,
  • John H Ouma3,
  • Anthony E Butterworth4,
  • David W Dunne5,
  • Mark Booth6,
  • Gachuhi Kimani7,
  • Joseph K Mwatha7,
  • Eric Muchiri8 and
  • Birgitte J Vennervald2
Parasites & Vectors20136:107

DOI: 10.1186/1756-3305-6-107

Received: 15 December 2012

Accepted: 12 April 2013

Published: 18 April 2013

Abstract

Background

Schistosoma mansoni infection is a persistent public health problemin many Kenyan communities. Although praziquantel is available, re-infectionafter chemotherapy treatment is inevitable, especially among children.Chemotherapy followed by intermittent mollusciciding of habitats ofBiomphalaria pfeifferi, the intermediate host snail, may havelonger term benefits, especially if timed to coincide with naturalfluctuations in snail populations.

Methods

In this cohort study, the Kambu River (Intervention area) was molluscicidedintermittently for 4 years, after mass chemotherapy with praziquantelin the adjacent community of Darajani in January 1997. The nearby ThangeRiver was selected as a control (Non-intervention area), and its adjacentcommunity of Ulilinzi was treated with praziquantel in December 1996. Snailnumbers were recorded monthly at 9–10 sites along each river, whilerainfall data were collected monthly, and annual parasitological surveyswere undertaken in each village. The mollusciciding protocol was adapted tolocal conditions, and simplified to improve prospects for widespreadapplication.

Results

After the initial reduction in prevalence attributable to chemotherapy, therewas a gradual increase in the prevalence and intensity of infection in thenon-intervention area, and significantly lower levels of re-infectionamongst inhabitants of the intervention area. Incidence ratio between areasadjusted for age and gender at the first follow-up survey, 5 weeksafter treatment in the non-intervention area and 4 months aftertreatment in the intervention area was not significant (few people turnedpositive), while during the following 4 annual surveys these ratios were0.58 (0.39-0.85), 0.33 (0.18-0.60), 0.14 (0.09-0.21) and 0.45 (0.26-0.75),respectively. Snail numbers were consistently low in the intervention areaas a result of the mollusciciding. Following termination of themollusciciding at the end of 2000, snail populations and infections insnails increased again in the intervention area.

Conclusion

The results of this study demonstrate that in the Kenyan setting acombination of chemotherapy followed by intermittent mollusciciding can havelonger term benefits than chemotherapy alone.

Keywords

Bayluscide Schistosoma mansoni Re-infection Biomphalaria pfeifferi Molluscicide

Background

Chemotherapy with praziquantel, directed at Schistosoma mansoni infectedprimary school children, is an effective way of causing a rapid reduction inmorbidity and in prevalence and intensity of infection. However, it has relativelylittle effect on transmission and regular re-treatment at intervals of one to threeyears is therefore usually necessary [14]. The intensity of re-infection after treatment in some cases may reach50% of pre-treatment levels by about one year after treatment, especially in theyounger age groups [5, 6]. Even low-level recurring reinfection is likely to be associated withsubtle but persistent morbidities such as anemia, undernutrition and diminishedperformance status [7]. One potential improvement to the strategy of regular chemotherapy may beto combine chemotherapy with mollusciciding of exposure sites. Such an approach hasbeen successfully used in several studies. In St. Lucia in the West Indies, acommunity based chemotherapy programme resulted in a rapid reduction in prevalenceand intensity of infection, and focal snail control delayed or prevented theexpected resurgence of transmission [8]. A combination of chemotherapy and focal mollusciciding in Brazil reducedthe prevalence of S. mansoni infection from between 12.5-40% to below 9% [9], while in the late 1950’s a combination of chemotherapy andmollusciciding helped to achieve the control of S. mansoni on ViequesIsland in Puerto Rico [10]. In Burundi, however, focal snail control produced disappointing results [11]. This approach has not been attempted in Kenya, and has not beenundertaken anywhere in comparison with chemotherapy alone at the same time and undersimilar environmental conditions.

This paper describes both operational and research aspects of introducing seasonaland focal mollusciciding with niclosamide (Bayluscide®) in a river in MakueniDistrict, Kenya. A nearby community using a similar river and with intensetransmission was selected for chemotherapy alone. Mollusciciding activities wereundertaken to coincide with the natural fluctuations in snail numbers associatedwith rainfall patterns. The study was undertaken to elucidate the efficacy ofmollusciciding after chemotherapy for long-term maintenance of low re-infectionrates, and to develop a streamlined and simple procedure for use in Kenya andelsewhere endemic for schistosome infections.

Methods

Ethical clearance

This project was conducted as an integrated part of 4 other projects for whichapproval was obtained from the ethical committee at the Kenya Medical ResearchInstitute, Nairobi, Kenya on August 11, 1992, January, 6, 1994, October 1, 1998and July 7, 1999. For ethical reasons we decided to not return routinelycollected Biomphalaria pfeifferi to the sites, either those with patentinfection or those without because they might have prepatent infections.

Study area

The general features of the study area have been described in previouspublications [12, 13]. The current study was carried out in the context of two rivers andtheir surrounding communities (Figure 1), i.e. the KambuRiver, where community chemotherapy was followed by mollusciciding(Intervention), and the Thange River, which served as a control with nomollusciciding but chemotherapy of a local community only(Non-intervention).
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Figure 1

The two study streams. The stippled line indicates theNairobi–Mombasa road and stars the sampling sites. Sites werenumbered consequtively from T1 (S2° 28′ 24.96″;E38° 3′ 12.12″) to T11 (S2° 23′54.00″; E38° 9′ 20.64″) in the Thange stream(Non-intervention) and from K1 (S2° 34′ 1.17″ E38°7′ 3.46″) to K11 (S2° 35′ 56.71″; E38°9′ 47.14″) in the Kambu stream (Intervention). Ulilinzi andDarajani show the approximate position of schools in the twocommunities.

Transmission of Schistosoma mansoni in Makueni District and in manyother endemic areas in Kenya frequently occurs in streams, some of which may dryup during the dry season or be flushed by floods during heavy rains. There aretwo main annual transmission seasons in Makueni; these occur after the March/Maylong rains and November/December short rains [14].

The Kambu River passes close to Kambu Market on the Nairobi-Mombasa highway andclose to Darajani Market some 5 km downstream. In an earlier study,examination for S. mansoni infection and associated morbidityat a nearby primary school (Nzoila Primary School) observed prevalence ofinfection among the school children of 90%, with 40% of these childrendisplaying evidence of hepatosplenic disease [15]. Examination at other nearby primary schools in the Kambu area alsoindicated high prevalence of infection [12]. The source of infection in this area was Kambu River. Darajanivillage was selected for evaluation of S. mansoni transmission aftermollusciciding.

Kambu River emerges about 7 km upstream from the study area as a series ofsprings originating from the nearby Kyulu Hills. The river, which on average isabout 3 m wide and 0.2 m deep, flows through some rocky areas butmainly has a sandy bed often overlain with silt. Various types of emergent andfloating vegetation suitable for snail proliferation are abundant. Kambu Riveris heavily used by humans for their domestic and personal activities and forwatering their livestock from as far away as 10 km on either bank. Alongits upper areas, where the present study was carried out, the river does not dryout completely during any time of the year.

Thange River was selected as the non-molluscicided control river, and Ulilinzivillage, through which it flows, was used for comparative parasitologicalevaluation. The Thange River is similar in description to the Kambu, has itsorigins in the Kyulu Hills and flows in a parallel valley towards the Athi River(Figure 1). In both rivers transmission sites werenumbered consecutively downstream from the source.

Parasitology

A cohort of people was selected in both areas on the basis of the proximity oftheir households to the water contact sites (less than one kilometre fromtransmission sites). Ulilinzi was sparsely populated as opposed to the highlypopulated Darajani area. A baseline survey for S. mansoni infection wasconducted in October 1996; 208 individuals aged 5 to 60 years fromUlilinzi, and 630 individuals aged 5 to 60 years from Darajani wereexamined. A stool sample was taken from each individual on three consecutivedays, and from each sample two 50 mg thick smears were prepared using theKato-Katz method [16]. The number of S. mansoni eggs per sample was counted. A fewpeople who did not provide 3 samples were kept in the analyses. No systematictreatment with antischistosomal drugs had been given in the Thange area beforethese studies began but there had been annual treatments of children in someKambu schools prior to 1996 and some of these were residents of the Darajanicommunity. All infected people from the cohorts were treated with 40 mgpraziquantel per kg body weight, while all other members of the two communitieswere offered free treatment using the same dosage. Neighbouring communities werenot treated.

A follow up survey was conducted 5 weeks after treatment in both areas butit was found that in Darajani the initial treatment was less than satisfactoryand all infected people were given a second treatment in January 1997 to reduceintensity of infection to a level comparable to that in Ulilinzi. The reason forthe treatment failure most likely was that mainly children (up to teen age) didnot swallow the tablets due to rumours about bad taste and severe side effectsof the drug. In all subsequent treatments we were very careful to ensure thatall swallowed the tablets. A 5 weeks follow-up survey was carried out afterthe second treatment in Darajani but this was based on only one stool sample andis therefore not included here. Another follow-up sampling was done in Darajaniin May 1997 and this one was used for the analysis. Therefore, the follow upsurveys were from December 1996 (5 weeks after treatment) at Ulilinzi andMay 1997 at Darajani (about 4 months after the second treatment).Thereafter, annual surveys (Survey 1 – Survey 4) were conducted in eacharea, generally in November in Darajani (Intervention) and January the followingyear in Ulilinzi (Non-intervention). There was no other treatment forschistosomiasis infection in these areas except possibly by health centres.Praziquantel was available at the nearby Kibwezi health centre where infectedindividuals would be referred to. Most other clinics did not have praziquantelat that time.

Snail sampling

Initially 11 sites on the Kambu and Thange rivers respectively (Figure 1), were purposively identified based on previous(unpublished) observations on extent of human water contact. During thepre-intervention all sites were sampled regularly but during the follow-up, only9 sites on the Kambu river and 10 sites on the Thange river were sampledregularly. Each site was sampled for B. pfeifferi twice per month fromJanuary 1993 to December 2005. Sampling was carried out as described in [17], by one man searching each site for 15 minutes, using a standardflat, wire-mesh scoop (mesh size 2 mm). Snails were brought to a fieldlaboratory in each area and examined for schistosome infection by cercarialshedding. Biomphalaria pfeifferi snails were placed individually inflat-bottomed glass vials (7.5 cm by 2.5 cm in height and diameter)containing clear filtered stream water and exposed to indirect sunlight for amaximum duration of 4 hours (900 h - 1300 h). The cercariae werecategorized either as those of human schistosomes (S. mansoni) or othertrematodes [18]. Snails were not returned to their sites after examination; theimpact of this on snail population dynamics would probably be minor as snaildensity was high also in sections outside our sampling stations and drift ofsnails along the stream was significant (we did not quantify this).

Rainfall

Rainfall was recorded daily at each field laboratory and presented as rainfall inmm per month.

Mollusciciding

Bayluscide® WP 70% (niclosamide is the active molluscicidal ingredient) wasused at the manufacturers recommended dose of 1 ppm for 8 hours [19]. The Kambu stream was treated at a concentration of1 mg l-1 for 8 hours using a dispenser made of a200-litre metal oil drum with a bottom siphoning mechanism (i.e. drip-feedapplication). At the same time, marginal water, small effluents and side pondswith no flow along the entire target stretch of the river, were treated withmolluscicide applied with a 10-litre compression sprayer containing 50 g ofmolluscicide to give an estimated concentration of2 mg l-1.

Mollusciciding began in August 1995, i.e. before the baseline parasitologicalsurvey, to ensure that the chosen methods were working. An attempt was made totarget snails at the very source of the stream, which served as a refuge forsnails, but this proved time consuming and too expensive in terms of chemicalconsumption. In February 1996, a routine for major, area-wide mollusciciding wasadopted of one drip-feed application at a point about 2 km downstream fromthe main source (c. 3 km upstream from the first snail study-site) and abooster application at the middle of the study area, plus supplementaryhand-spraying of marginal water along the target stretch of the river. Thismajor mollusciciding was carried out twice a year, as snail populations began torecover from the preceding rainy seasons, in about February/March andAugust/September. In between these area-wide treatments, focal molluscicidingwas carried out along the target stretch of the river with backpack sprayers inand around sites where snails were found.

Initially, flow was estimated by means of a V-notch weir but later we estimatedaverage water flow using a floating wine bottle cork, with satisfactory results.The cork was dropped at point 0 and the time it took to reach the 10-m marktaken. The average width and depth of the 10-metre section were also taken. Theflow rate was then calculated as shown in [19].

The efficacy of the molluscicide was estimated by exposing caged sentinel snailsdownstream at various points. Control snails were also placed upstream in areaswhere the molluscicide was not introduced. The snails were introduced in10 × 10 × 10 cm cubic cages surroundedwith plastic mosquito netting that was not large enough to allow for snails tocrawl out. Ten snails were placed in each cage, and one cage placed at intervalsof one km.

Training

Five persons from the local community were trained in mollusciciding, evaluationof snail population sizes and identification of infected snails.

Analysis

Infection status at baseline (infected/not infected) and egg counts were comparedbetween the two areas after adjusting for age class and gender using generalizedlinear models, i.e. logistic regression using a logit link function forinfection status and negative binomial regression using a log link function foregg counts. Egg counts from the three (for some samples less) consecutivesamples were summed and the total amount of faeces actually examined was used asan offset in these analyses. The ancillary parameter (α) in the variancefunction (μ + αμ2) was estimated usingfull maximum likelihood estimation as described by [20]. Model fit was checked by assessing over-dispersion using thechi-square based dispersion statistics and standardized deviance residuals werechecked to identify potential outliers [20].

For comparison between areas of pre-intervention snail counts (monthly counts insites for two years i.e. 1993 and 1994), population averaged generalizedestimating equations [21] were used. For infections in snails a logit link was used. Differentcorrelation structures were tried and the one chosen was based on the QICstatistic [21]. The best was an autoregressive correlation structure with a lag of1.

Since infections in people differed between the two areas at baseline, theevaluation of treatment (mollusciciding) effects would need to adjust for thisdifference. Data were arranged as panel data (a panel is a person or a snailsampling site) where each panel was examined once a year. For infections inpeople, generalized estimating equations on the yearly survey data adjusting forbaseline infection status or intensity of infection (eggs per g faeces) usinglogistic regression or negative binomial regression in population averagedgeneralized estimating equations were used. For snail data, the total number ofsnails sampled per site was calculated for each year and comparison of treatmenteffect was adjusted for snail counts during the two pre-treatment years.Incidence rate ratios (relative risk) between the two areas were calculatedbetween successive surveys after adjusting for age group, gender and baselineinfection status if significant and interval between surveys was entered as theexposure using a generalized linear model with binomial distribution and alog-link function. P-values below 0.05 were taken to indicate significantdifferences.

Results

Snails –pre-intervention

Pre-intervention snail sampling in 1993 and 1994 is shown in Figure 2. Rainfall followed the expected pattern of a short periodwith high rainfall in November/December of each year, and a longer period oflower rainfall between March and May. Density of B. pfeifferi increasedfrom about May to November when density declined markedly. These trends,however, were not the same in both years and thus a significant interaction wasfound between season and year (p < 0.001) and between year andarea (p < 0.001). Also for the number of S. mansoniinfected snails interactions between season and year (p < 0.001)and between year and area (p < 0.001) were significant.
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Figure 2

Numbers of Biomphalaria pfeifferi (open columns) and Schistosoma mansoni infected snails (black columns) per month per site in two streams,Thange a) and Kambu b), during the pre-intervention years (1993 and1994) and the first year of mollusciciding, together with rainfallc).

There was considerable variation in both the number of snails collected and thepercentage of snails that shed S. mansoni cercariae within and betweensites along both rivers (Figure 3). Sites 1–3 in thenon-intervention area and site 10 in the intervention area were not sampledregularly during the follow-up period and were therefore excluded from thefollowing analysis. The highest recorded number of snails at any site visitalong the non-intervention river was 992 in 1993 and along the interventionstream it was 1024 at one site in 1994. In the non-intervention river, sites 4,5 and 8 had the highest snail counts and jointly these sites accounted for 68.6%of all snails found in this area during the two pre-intervention years. In theintervention area, there was less variation among sites; lowest counts werefound in sites 2 and 11 and highest counts in sites 4, 6 and 7. The latter threesites accounted for 43.5% of all snails found during the pre-interventionyears.
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Figure 3

Total number of Biomphalaria pfeifferi collected in each site (Figure1) during the two pre-intervention years, 1993 and1994. A few of these sites were excluded from the follow-upanalysis.

The odds of finding S. mansoni infections in snails in thenon-intervention area were higher in sites 5, 10 and 11 than in the other sitescombined (p < 0.001) and infections were more commonly found in1993 than in 1994. Infected snails were found in all sites, but site 10accounted for 77.0% of all infected snails in the non-intervention area duringthe pre-intervention period and sites 4, 5 and 10 accounted for 91.5% of allinfected snails. In the intervention area, the odds of finding infections insnails was lower in sites 5 and 8 than in the other sites but differences amongthe other sites were also significant (p < 0.001). Especially,sites 1, 3 and 4 had high odds of infections. Infections were more commonlyfound in 1994 than in 1993 (p < 0.001). Also in the interventionarea, infected snails were found in all sites and variation between sites wasless than in the non-intervention area. Thus sites 3, 4 and 7 accounted for57.8% of all infected snails during the pre-intervention period.

A freak storm during the short rainy season from November to December 1994 washedaway B. pfeifferi populations and caused adverse alteration of snailhabitats in the Kambu River by washing out vegetation and depositing largeamounts of silt; the storm did not affect the Thange River. As a consequence,and in addition to the effects of the rains that fell between February andApri11995, no snails were found in the Kambu sites until June 1995 when a smallnumber of snails were found.

Mollusciciding

The first mollusciciding in August 1995 consumed a total of 6.1 kg ofBayluscide, while subsequent routine applications consumed 10 kg of themolluscicide per treatment (i.e. 2 per year), including the supplementary handspraying. In between these area-wide treatments, focal mollusciciding wascarried out with backpack sprayers in and around sites where snails were found,using an average of 3 kg per year. Caged snails were taken to Darajanifield laboratory and placed in clean stream water for 24 hours forrecovery. All caged snails exposed in the molluscicided section were found deadup to a distance of 10 kilometres downstream, but those exposed 13 kmdownstream survived. There was no mortality in the snails exposed upstream inthe untreated section of the stream.

Snails –during intervention

The climatic phenomenon El Nino occurred in 1997, and this was associated with adisruption of normal rainfall patterns in both study areas. Abnormally highrainfall was measured during the period November 1997- January 1998, and therains did not completely abate until June 1998. Prior to El Nino, snailpopulations at sites along the non-intervention river typically crashed with theonset of the November rains, and recovered after the March-May rains. During1997 and 1998 there was a population crash that lasted from November to Novemberof the following year, after which the previously observed fluctuations in snailpopulations was resumed. Population averaged modelling with a autoregressive 1correlation structure showed that baseline snail count was a significantpredictor of follow-up counts (p < 0.001). Rainfall was asignificant predictor and a 100 mm increase was associated with a reductionin snail counts by 27% (p < 0.001). An increase in the baselinecount of 100 snails was associated with a 43% increase in follow-up counts. Theinteraction between baseline count and area was not significant and was excludedfrom the final model. Area (Intervention/non-intervention) was a significantpredictor (p < 0.001) of follow-up snail count and so was year(p < 0.001), and the interaction between these two predictors wassignificant (p < 0.001). Thus counts in the intervention area was1.5, 25.1, 6.4, 6.7, 1.2 and 1.6% of that in the non-intervention area duringyears 1995, 1996 1997, 1998, 1999 and 2000, respectively when adjusting forbaseline snail counts and rainfall. Mollusciciding was terminated at the end of2000 and during subsequent years snail density in the intervention streamincreased although not to the same level as pre-intervention (Figure 4).
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Figure 4

Mean total number of Biomphalaria pfeifferi (a)and number of infected B. pfeifferi (b)collected per site per year during 1994 to 2005, together withrainfall (c). Error bars represents 95% CL.

Parasitological observations at baseline

Odds of S. mansoni infection at baseline among people in theintervention area were lower than that in the non-intervention area(OR = 0.27; p < 0.001) when adjusted for the effectsof age group and gender, i.e. males had higher odds of infection than females(OR = 1.87; p < 0.001). Age group was not significantbut was retained in the model. Similarly, odds of heavy infection(epg > =400) were lower in the intervention than in thenon-intervention area (OR = 0.16; p < 0.001), whenadjusted for the effects of age group and sex. Effect of gender was notsignificant while age group was significant (p < 0.001). Therewas, however, a significant interaction between age group and area(p < 0.05); especially school aged children who had higherprevalence of heavy infection in the non-intervention area than in theintervention area (Figure 5a).
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Figure 5

Prevalence (a) of Schistosoma mansoni infectionand heavy infections (black bars) and intensity of infection (b) byage group in the intervention and non-intervention area at baseline. Error bars represents 95% CL.

Egg counts modelled as a Poisson distribution were significantly over-dispersed,wherefore we used negative binomial regression. The ancillary parameter wasestimated to be 3.4231 and a model including area, gender, age group and theinteraction between area and gender showed no signs of over-dispersion(dispersion statistics = 1.01). Egg counts were lower in theintervention area than in the non-intervention area (p < 0.01),males had on average 36% higher egg counts than females, and age group was asignificant predictor (<0.01) as well. There was, however, a significantinteraction between area and age group (p < 0.05).

Parasitological observations during follow-up

In the follow-up survey after treatment and the following 3 annual surveys acumulative total of 261 infections were recorded in the non-intervention areaand 224 in the intervention area. Of these, 78 (29.9%) and 73 (32.6%) in thenon-intervention and intervention area, respectively were negative in the surveythat followed the one where they were detected indicating that some people weretreated, presumably at health centers although this could also be a randomvariation in sensitivity at low egg counts. A total of 23 (88%) and 29 (73%) ofthe people found positive during the follow-up survey after treatment were alsopositive in the last survey in the non-intervention and intervention arearespectively and of these 8 and 15, respectively, were found positive during allsurveys. The maximum observed egg count during the various follow-up surveys was557 and 750 eggs g-1 in the non-intervention and intervention area,respectively (Table  1). Maximum egg-counts forpeople who were also positive during the preceding survey were higher but thesehigh intensities of infection were found in only a few people.
Table 1

Number of people found infected, maximum intensity of infection andgeometric mean intensity of infection in the non-intervention andintervention areas in Makueni District, Kenya

 

Number of cases

Maximum intensity (eggs g-1)

Geometric mean intensity (eggs g-1) (95% CL)

 

Non-intervention

Intervention

Non-intervention

Intervention

Non-intervention

Intervention

Baseline survey (October 1996)

      

 Negative

22

194

    

 Positive

154

380

1440

3340

90 (70–117)

77 (65–92)

 Positive also at follow-up

32

56

1403

1303

179 (101–318)

99 (68–145)

Follow-up survey*

      

 New cases

1

5

420

25

420

11 (4–26)

 Positive pre-treatment

32

56

300

1000

29 (20–42)

20 (13–29)

Survey 1 (1997/1998)

      

 New cases

63

43

470

750

20 (14–30)

11 (6–18)

 Positive at follow-up

24

31

407

1103

24 (13–45)

21 (12–38)

Survey2 (1998/1999)

      

 New cases

18

32

397

525

8 (4–14)

11 (7–17)

 Positive at survey 1

36

35

1333

655

8 (5–13)

20 (11–34)

Survey 3 (1999/2000)

      

 New cases

94

36

557

303

22 (17–28)

9 (6–15)

 Positive at survey 2

45

40

1380

417

26 (16–42)

21 (13–32)

Survey 4 (2000/2001)

      

 New cases

17

47

523

743

15 (7–32)

9 (7–13)

 Positive at survey 3

78

45

2527

833

48 (32–72)

29 (17–47)

*) treatment was given in October 1996 and this survey was conducted5 weeks post-treatment in the non-intervention area, while asecond treatment was given in January 1997 in the intervention areaand the survey data presented here are from 4 monthspost-treatment.

Prevalence of infection and heavy infection recorded at each survey in eachcommunity is shown in Figure 6. Since prevalence ofinfection differed between areas at the baseline survey, adjustment of follow-upeffects was made for infection status of each person at baseline. In a GEEmodel, the odds of infection during follow-up was higher among those who werepositive at baseline than among those who were originally negative(OR = 2.84, p < 0.001). There was a significanteffect of age group (p < 0.001) and of area(OR = 0.20; p < 0.001), while there was nointeraction between age group and area and this interaction term was excludedfrom the final model. Males had higher odds of infection than females(OR = 1.44, p < 0.01). Year was a significantpredictor (p < 0.001) but there was a significant interactionbetween year and area. Thus the odds of infection in the intervention area were0.65, 0.24, 0.41, 0.08 and 0.20 of that in the non-intervention area during thefollow-up survey and the 4 subsequent annual surveys, respectively.
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Figure 6

Prevalence (a) of Schistosoma mansoni infectionand heavy infections (black bars) and intensity of infection (b) asgeometric mean by year in the intervention and non-interventionareas. Error bars represents 95% CL. The baseline was fromOctober 1996, while surveys 1–4 were from November in theIntervention area and the following January in the Non-intervention areaduring the years 1997/1998, 1998/1999, 1999/2000 and 2000/2001,respectively.

Incidence ratio between areas adjusted for age group and gender at the follow-upsurvey after chemotherapy was not significant, while during the following 4annual surveys these ratios (95% CL) were 0.58 (0.39-0.85), 0.33 (0.18-0.60),0.14 (0.09-0.21) and 0.45 (0.26-0.75), respectively. Few heavy infections wereobserved during the post-treatment surveys, 25 in the non-intervention area (20of these during 2000) and 14 in the intervention area.

The effect of treatment on egg counts was more marked. The first treatmentachieved a reduction of over 95%, rising to 99.15% after the supplementarytreatment given 3 months later. Intensity of infection at baseline was asignificant predictor of follow up egg count (p < 0.001) whenadjusting for gender, age group, year, interaction between area and age groupand between area and year; a 100 eggs increase in baseline epg was associatedwith a 9.8% increase in follow-up egg count. Males had higher egg counts thanfemales (count ratio: 3.08, p < 0.001). Also age group(p < 0.001) and year (p < 0.001) were significantpredictors, but both had significant interaction with area(p < 0.001 for both terms). Ratios between egg count inintervention and non-intervention area were 0.43, 0.17, 0.45, 0.13 and 0.18during the follow-up and the 4 annual surveys, respectively. Thus egg countswere lower in the intervention area than in the non-intervention area during allyears of mollusciciding when adjusted for baseline differences.

Discussion

Schistosomiasis continues to exert a burden on public health in many communities ofthe tropics and sub-tropics even where National Control Programmes operate. This isdue to the fact that chemotherapy alone does not prevent re-infection. Wehypothesized at the outset of this project that mollusciciding, using localknowledge of snail breeding sites, could lead to an additional benefit to thepopulations at risk of infection. Mollusciciding is no longer a feature of manyschistosomiasis control programmes but our results press home the fact thatadditional measures against the snail population can have measurable benefits. Themajor observations of this study are that the snail numbers were reducedsignificantly at all sites along the Kambu River (Intervention area), and that bothprevalence and intensity of infection after chemotherapy remained lower in theDarajani community, close to Kambu river, than in the non-intervention area,Ulilinzi village, close to Thange River during the follow-up period. The combinationof chemotherapy followed by intermittent mollusciciding, therefore, had asignificant protective effect not only for the Darajani community but also forneighbouring communities also relying on the Kambu River for their waterrequirements, i.e. an estimated population of over 30,000 [22].

In an area where environmental conditions favour the proliferation of intermediatehost snails, Biomphalaria pfeifferi, complete elimination of snails may beimpossible to achieve, especially in stream habitats. Further, after molluscicidingsome snails may be found at some habitats, especially where suitable ponds or poolsform. Formation of such pools is usually caused by fast currents during rains thatwash away sand at some points along the riverbed, leaving deep furrows. The locationof such pools may change from one rainy season to the next. It is thereforenecessary to identify such sites and check for snails regularly. This is in markedcontrast to a study in the Gambia, where mollusciciding of seasonal rainwater poolsprogressively reduced snail population density and markedly reduced transmission ofS. haematobium[23].

Where snails occur in streams, as in the present study area, rainfall plays animportant role in reducing snail populations and the population “startsafresh” after each rainy season, but the effect is only temporary asre-population occurs rapidly. This is partly because close to the source of suchstreams several “snail pockets” may exist and some of them may be ofvery small size and yet support a thriving snail population. It may not be possibleto locate and treat all these reservoirs of snails. Thus after mollusciciding isstopped snail populations will soon recover. This study has shown that takingadvantage of rainfall by timed mollusciciding helps to keep snail populations lowfor a prolonged period. It may, however, not be straightforward to estimate whenrains may cause depletion of snails, since during this study the rainfall did notfollow the same pattern from year to year. During the March-May long rainy seasonsthe rains were generally low. The El Niño rains from November 1997 to January1998, in contrast, were devastating for snail habitats in both Kambu and Thangerivers, resulting in depletion of monthly snail recoveries in 1998 until August forKambu and September for Thange.

Focal mollusciciding using the compression sprayers hardly caused any noticeableeffect on non-target organisms, especially fish, but area-wide mollusciciding didkill some fish (data not included). Kambu River is not an important area for fishingnor does the community rely on fish as a source of food, but it joins a major river,the Athi, which is an important source of fish. Due to dilution, the molluscicideeffect was not felt in the Athi River during the area wide mollusciciding (the lateDr RF Sturrock, personal communication).

Several important questions are associated with the use of molluscicide to preventreinfection rather than relying on repeated treatment of exposed individuals tomaintain low reinfection levels. The cost effectiveness of the molluscicidingapproach is particularly important. In the present study, the cost of a single roundof chemotherapy of Darajani community was approximately 1.8 times higher than theannual mollusciciding cost (data not shown), but would obviously be different atpresent due to the reduction in praziquantel cost. Had all persons at risk beentreated annually, the relative cost would have been considerably higher, and such anapproach would not have prevented re-infection [2, 7]. It is also important to ask whether or not intermittent molluscicidingcan have a demonstrable effect on morbidity. In this context, it has been shown thatthe mollusciciding of the River Kambu was associated with both a lack of reinfectionamongst a cohort of school children from the nearby Mbeetwani community, and also aregression of hepatosplenomegaly over a three year period [24, 25]. A lack of re-infection amongst the Mbeetwani cohort led to observationsconcerning the effects of malaria exposure on hepatosplenic disease associated withschistosomiasis [26, 27]. Taken together, these two sets of studies indicate that whilst reductionin infection is clearly demonstrable through a combination of mollusciding andchemotherapy, any causally related effect on morbidity is likely to be a function ofvarious factors including the presence of co-infections of different species.Defining the nature of this ‘function’ will require a mixed-methodsapproach in future studies to ensure that a more complete understanding ofschistosome ecology is available to inform the development of optimised controlprogrammes. With some countries shifting schistosomiasis control strategy frommorbidity control to elimination [28, 29], transmission control becomes important and mollusciciding could becomeessential to achieve this and there is need to develop new molluscicide formulationsor new strategies of application adapted to the local conditions [29, 30].

Conclusion

This study has demonstrated that chemotherapy followed by intermittent molluscicidingcan have a significantly higher impact on re-infection than a single round ofchemotherapy, and may be more cost-effective than repeated mass treatments of thehuman beings. These results were obtained in a specific Kenyan setting, butnonetheless demonstrate that a combined approach to schistosome control is feasibleand has demonstrable benefits in terms of reducing infection and morbidity incommunities where transmission is high.

Declarations

Acknowledgements

We would like to recognize the contribution by late Dr. R. F. Sturrock, whoselong history of malacological studies in Kenya was very important for theinitiation of this study. The authors thank the communities of Ulilinzi andDarajani for their co-operation during this study. Acknowledgements are given toPeter Ayieko, Kanyi Gitonga and the local fieldworkers, who were involved indata collection over the whole study period. MB was supported by the WellcomeTrust. We are grateful to Bayer for donating the molluscicide used during thefirst 2 years. The study was partially supported by the DanishInternational Development Assistance, through its funding to the DBL Centre forHealth Research and Development, and by the Edna McConnell Clark Foundation.

Authors’ Affiliations

(1)
Division of Vector Borne Diseases, Kenya Ministry of Health
(2)
Kenya Methodist University, School of Medicine and Health Sciences
(3)
DBL Centre for Health Research and Development, Institute of Veterinary Disease Biology, University of Copenhagen
(4)
Maseno University, Kisumu
(5)
College of Medicine, University of Malawi
(6)
Department of Pathology, University of Cambridge
(7)
School of Medicine, Pharmacy and Health, Durham University
(8)
Kenya Medical Research Institute

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© Kariuki et al.; licensee BioMed Central Ltd. 2013

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