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    Hierarchical structure of data for Senegal 2001–2002. Level 1 = Plasmodium falciparum densities; level 2 = children; level 3 = districts. Di.j.k is the kth measurement of P. falciparum density taken on the jth child living in the ith district.

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COINFECTION WITH PLASMODIUM FALCIPARUM AND SCHISTOSOMA HAEMATOBIUM: PROTECTIVE EFFECT OF SCHISTOSOMIASIS ON MALARIA IN SENEGALESE CHILDREN?

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  • 1 Institut de Recherche pour le Développement, Unité de Recherche Santé de la Mère et d’Enfant en Milieu Tropical (Unité 010), Faculté de Pharmacie, Université Paris V, Paris, France; Institut National de la Santé et de la Recherche Médicale, Unité d’Epidemiologie et de Biostatistiques (Unite 472), Villejuif, France

Studies with animal models have suggested the possibility of interactions between parasites during concurrent infections and have raised the question of a similar phenomenon in humans. The present survey was undertaken to assess the impact of urinary schistosomiasis on the susceptibility of children to malaria. It was carried out in Senegal between September 2001 and March 2002 among 523 children 3–15 years of age. We tested the association between Plasmodium falciparum densities and the load of Schistosoma haematobium egg excretion using a linear mixed model because data were not independent. After controlling for age, sex, and season, we showed that children lightly infected with S. haematobium (1–9 eggs/10 mL of urine) had lower P. falciparum densities than those not infected (β = −0.34, 95% confidence interval = −0.85, −0.10), suggesting a negative interaction between both parasites.

INTRODUCTION

In inter-tropical areas, multiple parasitic infections are common.13 Epidemiologic, clinical, or biologic outcomes are more often studied considering each parasite separately. Nevertheless, studies on animal models have shown that concurrent infections by two or more parasite species could affect the pathogenesis of each other.4,5 They have suggested the possibility of antagonistic or synergistic interactions between parasites, and have raised the question of a similar phenomenon in humans.

Malaria and helminth infections are the major parasitic diseases in developing countries and their epidemiologic coexistence is frequently observed, particularly in Africa. The implications of concomitant malaria and helminth infections have been mainly explored in animals under laboratory conditions.68 In human populations, only few studies have been conducted, with contradictory results. Some of them showed a protective role of helminths.911 For example, Nacher and others10 found that a helminth infection was associated with a protection from cerebral malaria, and Murray and others9 showed that treatment of severe ascariasis was accompanied by recrudescence of malarial attacks in children. Conversely, other studies suggested a deleterious effect of coinfection.12,13

The purpose of this study was to investigate coinfection with malaria and urinary schistosomiasis in a population of children in Senegal exposed to both diseases. We compared malaria parasite densities in children coinfected with Schistosoma haematobium with those not coinfected for increasing levels of infestation. We also studied intestinal helminth infections to observe their possible effect on malarial infection.

MATERIALS AND METHODS

Study area.

The study was conducted in Niakhar, Senegal, a rural area 135 km east of Dakar. This area is composed of 30 villages, with a population of approximately 30,000 persons, most of whom belong to the Sereer ethnic group. Each village is composed of several hamlets. Malaria and urinary schistosomiasis are endemic in the area. Their peak transmission occurs from July to October and low-level transmission continues through January. The predominant species of malaria-causing parasite is Plasmodium falciparum.14

Population study.

The study population was selected from a cohort of 1,129 subjects living in two villages of Niakhar (Diohine and Toucar) that have been followed since June 2001 for general epidemiologic purposes. A total of 523 children between 3 and 15 years of age (corresponding to the age group at risk for urinary schistosomiasis) were recruited in March 2002. To be selected into the study, children had to be present in the villages the day of enrollment, agreed to provide stool and urine samples, and their parents had to provide consent for their participation.

Study design.

Malaria investigations, consisting of obtaining a capillary blood sample for determination of parasite density, were done in September, October, and December 2001 and January 2002. In addition, at recruitment in March 2002, children were asked to provide single urine and stool samples for determination of helminth status. For all children, age, sex, village, and district of residence were recorded. The district was considered an indicator of the intensity of children exposed to malaria.

Laboratory studies.

Malarial infection was determined by a Giemsa-stained thick smear made from capillary blood. Parasite count was estimated on 200 microscope fields, and the average number of leukocytes per field was estimated in 30 fields. Asexual-stage parasite densities were reported as parasite count per 100 leukocytes.

Urine and stool samples were processed within 24 hours of collection. Schistosomiasis status (infected or not infected) was determined by the detection of S. haematobium eggs using a urine filtration technique (Nytrel®filter; Vestergaard Frandsen Group, Kolding, Denmark). The load of S. haematobium egg excretion was determined per 10 mL of urine. In addition, hematuria was detected with a reagent strip, and was expressed as negative or in levels of positivity (trace, +, ++, or +++). Stools were screened for helminths by microscopic examination, and helminth number and species were recorded.

Statistical analysis.

We examined malaria parasite density in relation to the load of S. haematobium egg excretion. Only P. falciparum density was studied. To determine the influence of coexisting infections of P. malariae and/or P. ovale on P. falciparum density, we compared mixed infections with nonmixed infections, with regard to P. falciparum densities. Since these densities were similar in both groups, we analyzed all children infected with P. falciparum, whether or not infected with another plasmodial species.

Plasmodium falciparum density was transformed by computing the log +1 value and was considered a continuous variable (0 for noninfected children). Normality was checked using the Shapiro test and graphic methods.

The intensity of schistosomiasis was divided into four categories with slight modifications of World Health Organization recommendations15: no infection, light infection (1–9 eggs per 10 mL of urine), moderate infection (10–49 eggs/10 mL), and heavy infection (≥ 50 eggs/10 mL). Egg load was not considered when children had microscopic hematuria (≥ 1+) in the absence of eggs.

Intestinal helminth status was expressed qualitatively (as infected or not infected). Age was treated as a continuous variable. We considered the season during which P. falciparum density was measured as a binary variable: a high transmission season in September or November, and a moderate transmission season in December or January.

Since measurements of malaria parasite density were repeated (four per child) and children originated from various districts (17 districts in which malaria exposure intensity was considered homogeneous), our data were not independent. Data presented a hierarchical structure where malaria parasite densities were level 1 units, and children were level 2 units clustered within districts that were level 3 units (Figure 1).

To test the association between malaria parasite density and the load of S. haematobium egg excretion, statistical analysis was performed with a linear mixed model that took into account the hierarchical structure.16 We used a random intercept model as specified in the equation

where Yijk is the kth log (P. falciparum density +1) for child j living in district i for k = 1,2, . ,4, i = 1,2, . ,17 and j = 1,2, .,14; bi ~ N (0, σ2b) where σ2b = district-to-district variation, aj|bi ~ N (0, σ2a) where σ2a = child-to-child variation, and eijk ~ N (0, σ2e) where σ2e residual variation.

We assumed that random coefficients (bi, aj, eijk) were independent of each other. The child and district variance components were estimated by restricted maximum likelihood method and the fixed effects parameters were estimated by the maximum likelihood method. For analysis, we used the PROC MIXED SAS® procedure (SAS Institute, Cary, NC).

We carried out a univariate analysis using the abovementioned linear mixed model to study the same dataset as in the multivariate analysis to search for potential confounders. Variables studied included age, sex, intestinal helminth infection status, and season. A multivariate analysis was then performed that included variables with P ≤ 0.20 in univariate analysis. We first took into account all children, and then considered only those who had at least one positive P. falciparum density during their follow-up to have a more homogeneous population regarding malaria exposure and possibly genetic susceptibility or immunity. Finally, we performed a stratified analysis on age of the child to search for a possible interaction between load of S. haematobium eggs and age. For this analysis only, we considered three age groups (3–7, 8–10, and 11–15 years old) in which we tested the association between P. falciparum density and the load of S. haematobium eggs after adjusting for variables included in the multivariate model. The Kruskall-Wallis test was used to compare non-Gaussian variables. Statistical analysis was performed by using the SAS system software (SAS Institute).

The study was reviewed and approved by the ethics committee of the Senegalese Ministry of Public Health. In March 2002, children who had S. haematobium infection or intestinal helminth infection were identified and treated with praziquantel and levamisole, respectively. All children who had fever and visited the clinic during the study period received a presumptive antimalarial treatment (chloroquine).

RESULTS

Description of the study population.

Some of the 3–15-year-old children in the Niakhar cohort were not selected for the study because they were absent on the day of recruitment, urine or stool samples were not obtained, or consent of the parents was not obtained. These children were similar with regard to sex and malaria parasite density compared with the 523 children selected, but they were slightly older. Thus, there was no bias in the selection of the study group. Of the 523 children recruited, 55% (285 of 523) lived in Diohine and 54% (284 of 523) were boys. The mean age of this population was nine years (Table 1).

Malarial infection.

Most (95%) children had at least three measurements of malaria parasite density during the follow-up. The prevalence of malarial infection ranged from 50% to 56% (Table 2). It was highest in September and November during the high malaria transmission period (56% and 55%, respectively), and then decreased in December and January, when malaria transmission was moderate (52% and 50%, respectively). More boys were infected than girls. Approximately 90% of the infections were P. falciparum. Between 5% and 10% of the children had mixed plasmodial infections each month. The mean P. falciparum density was estimated only in malaria infected children. It was highest in September and November, and then decreased in December and January (arithmetic mean = 86, 69, 25, and 19/100 leukocytes, respectively). Over the study period, 287 children received antimalarial treatment. A total of 199 were treated once, 63 twice, 20 three times, and 5 four times. There was no difference in antimalarial treatment distribution between S. haematobium-infected children and noninfected children.

Helminth infection.

Five hundred five (97%) children were tested for S. haematobium infection (Table 3). The results of urinary filtration and hematuria (microscopic hematuria and absence of eggs) were discordant for 18 children, and the load of S. haematobium egg excretion was not taken into account. Three hundred thirty-six children (67%) were infected, and more than half (54%) had an egg load ≥50/10 mL of urine. The prevalence and intensity of S. haematobium infection increased with age and was higher in boys than in girls. There was no difference in the prevalence between intestinal helminth-infected and noninfected children.

Information on intestinal helminth status was available for 474 children. One hundred forty-seven (31%) were infected with intestinal helminths. There were 119 infections with Ascaris lumbricoides, 25 with Hymenolepis nana, 9 with Strongyloides stercoralis, and 1 with Trichuris trichiura. Only seven children were infected with two different parasite species (six with A. lumbricoides and H. nana and one with A. lumbricoides and S. stercoralis).

Malaria parasite density and its relationship with S. haematobium infection.

Univariate analysis. As shown in Table 4, age, sex, and season were significantly associated with P. falciparum parasite density. Parasite density decreased with age (P < 0.001), and was lower in girls than in boys and when malaria transmission was moderate (both P < 0.001). We found that children lightly infected with S. haematobium (1–9 eggs/10 mL of urine) had significantly lower P. falciparum densities than those who were not infected. No significant association was found for higher loads of eggs. We did not observe any association between intestinal helminth infection and P. falciparum density.

Multivariate analysis.

Age, sex, and season were included in the final model (Table 5). Adjustment for these factors did not change the association between P. falciparum density and age, sex, or season. Similar to the findings with univariate analysis, children lightly infected with S. haematobium had lower P. falciparum densities than noninfected children (β = −0.34, 95% confidence interval = −0.58, −0.10, P = 0.07, by global test for all S. haematobium egg loads). A mixed model approach allowed us to estimate that child-to-child variation in P. falciparum density was 70-fold more important than district-to-district variation. When we considered only children who had at least one P. falciparum parasitemia during the follow-up, the association between low intensity of S. haematobium eggs and low malaria parasite density persisted. In addition, stratified analysis suggested that this relationship varied according to the age of the child; it was stronger in children 11–15 years of age. However, we did not find any significant interaction between age and load of S. haematobium eggs (P = 0.76).

DISCUSSION

Since polyparasitism is common among populations in developing countries and there may be interactions between parasites, as suggested by previous studies,4,5 we studied the effect of urinary schistosomiasis on the susceptibility of children to malaria. We observed that children lightly infected with S. haematobium had significantly lower P. falciparum densities than those not infected, suggesting a negative interaction between the two parasites.

To our knowledge, only two studies have explored coinfection with malaria and schistosomiasis in human populations, and these were interested mainly in immunologic implications.17,18 However, a recent study of the incidence of malarial attacks in children in relation to the intensity of their S. mansoni egg load showed that those lightly infected with S. mansoni had fewer malaria attacks than those not infected (Le Hesran JY and others, unpublished data).

We are confident that the association observed was not ecologically determined. Indeed, even if malaria and schistosomiasis are water-associated diseases, their modes of transmission (place and time) are different, suggesting an independent risk of contamination. In addition, for schistosomiasis, studies have shown that in small areas children are infected independently of their place of residence and distance from bathing areas.19 We identified the area in which cases of schistosomiasis were found and observed that their distribution did not follow any systematic pattern and were not situated near bodies of water. If simultaneous transmission of malaria and schistosomiasis occurred, we would have observed a positive correlation between P. falciparum density and S. haematobium egg load. Thus, our results are compatible with a negative interaction between the two parasites.

No association was found between intestinal helminth infection (mainly ascariasis) and P. falciparum parasite density. Explanations for this may be that there is no effect of intestinal helminth infection on parasitemia, as suggested by Nacher and others,10 or that the number of infected children was not sufficient to observe a significant association. In a previous study, Ashford and others2 showed a positive correlation between egg load of Ascaris lumbricoides and Plasmodium density, but no adjustment was made for age or malarial exposure.

As expected, we observed that malaria parasite density decreased with age. It may be related to specific anti-malarial immunity that develops in disease-endemic areas with repeated infections. Moreover, we found that P. falciparum density was significantly lower in girls. When we considered only children with positive blood smears, since boys were infected more often than girls, the association remained (β = − 0.26, 95% confidence interval = −0.48, −0.04).

We found that schistosomiasis was more prevalent and intense in boys than in girls and in older children. These age and sex effects are well known and are associated with the number and type of water contacts. It has been shown that boys are more exposed than girls because they take more baths,19,20 and that the level of infestation increases with age because schistosomiasis is a chronic affection and children have repeated episodes.21

Schistosomiasis status was determined from a single urine sample in March 2002. We believed that the probability of a change in this status between September 2001 and March 2002, and throughout the entire follow up, was very low. Because our study was conducted in a disease-endemic area among relatively older children (most > 5 years old), most of those infected had probably contracted the infection several years ago. With regard to uninfected children, we verified that none had received antihelminthic treatment before urine samples were collected.

Single urine and blood samples were used to classify children as infected and to determine their parasitic loads (malaria parasite density and S. haematobium egg load). Examinations were made using thick blood smear and urine filtration techniques, which have high specificities but lower sensitivities.22,23 This lack of sensitivity is due not only to the limitations of the techniques, but also to fluctuations in parasite counts in peripheral blood (for malaria) or urine (for schistosomiasis) in an individual during the course of a day. In our study, even if there were misclassifications (false-negative or underestimated parasitic loads) we believe that they did not modify the results. Indeed, schistosomiasis and malaria status were established independent of each other. We also compared malaria and schistosomiasis prevalences in our study with those of previous studies conducted in the Niakhar area. The prevalence of S. haematobium infection was consistent with the results of one study (Hamour S and others, unpublished data). We estimated that 56% of the children were infected with P. falciparum in November 2001, while Robert and others found an infection rate of 82% in November 1995.14 An explanation for this difference may be the particularly heavy rainfalls during 1995, thus causing higher transmission.

We adjusted for the main confounders (age and level of exposure to malaria). The latter confounder depends on environmental and behavioral factors. We considered only environmental exposure (adjusting for the district of residence) because it was shown in a study performed in 2002 in the same area that only 8% of the families used prophylaxis or bed nets (Rouget F, unpublished data).

We did not obtain any information on nutritional status or existence of hemoglobinopathies (sickle cell trait, thalassemias, glucose-6-phosphate dehydrogenase deficiency), which are known to influence malarial infection. We believe that even if they had been taken into account, they would not have affected the results. The impact of nutritional status has been reported for severe malaria, but not for parasitemia.24 Moreover, the sickle cell trait would have been a confounder in our study only if it influenced not only malaria parasite density (as was shown in recent studies25), but also the load of S. haematobium eggs, which has never been observed previously.

Our understanding of the mechanisms by which interactions between parasites occur is still limited. Recent studies have proposed an immunologic hypothesis based upon the T cell dichotomy.6 If one considers that for each parasite or pathogen, there is a corresponding protective T cell/cytokine response, concomitant infection could lead to synergistic or antagonistic T cell responses, dependent upon what kind of response (Th1 or Th2) was induced by each parasite. Synergistic responses could decrease the pathologic impact of the infections, whereas antagonistic responses could exacerbate the diseases. In humans, the immune responses induced during malaria and schistosomiasis are complex and not well known. As a result, what occurs during coinfection is more difficult to understand. The nature of immune responses may vary according to the stage and intensity of infections.26,27 This could explain the non-linear relationship we observed between malaria parasite densities and S. haematobium egg loads.

Parasitic coinfection and interaction phenomena are complex. Until now, they have been investigated mainly in animal models. However, the underlying problem is whether observations made under controlled laboratory conditions are relevant in human populations. In humans, these phenomena require further study to understand their mechanisms and public health implications. Community therapy programs usually focus on a single parasitic disease, such as control of schistosomiasis in school age children. Since several diseases may co-exist in the same individuals and affect the severity of each other, it could be worthwhile to implement integrated control programs that deliver multiple treatments against several parasitic infections simultaneously. In coinfected individuals, such programs could avoid possible deleterious effects of a single-targeted treatment on other diseases.

Table 1

General characteristics of the 523 children included in data analysis in Senegal, 2001–2002

No. of subjects%
Sex
    Male28454
    Female23946
Village
    Diohine28555
    Toucar23845
Age (years)
    3–4153
    5–717033
    8–1016030
    11–1312724
    14–155110
Table 2

Rate of malarial infection, species of malaria-causing parasite, and mean Plasmodium falciparum density, according to month of follow-up in Senegal, 2001–2002

September % (n)November % (n)December % (n)January % (n)
* Infection by P. falciparum and/or P. ovale and/or P. malariae.
† Arithmetic mean P. falciparum/100 leukocytes among infected children. CI = 95% confidence interval.
Malarial infection*56 (262)55 (275)52 (249)50 (232)
    Males62 (163)57 (157)55 (138)59 (138)
    Females38 (99)43 (118)45 (111)41 (94)
Plasmodium sp.
    P. falciparum90 (236)85 (234)79 (197)85 (198)
    P. falciparum plus (P. ovale and/or P. malariae)5 (13)8 (22)10 (24)6 (13)
    P. ovale and/or P. malariae5 (13)7 (19)11 (28)9 (21)
Mean P. falciparum density (CI)†86 (65, 107)69 (44, 93)25 (19, 32)19 (14, 25)
Table 3

Prevalence of urinary schistosomiasis and distribution of the load of Schistosoma haematobium egg excretion, according to sex, age and village of residence in Senegal, 2001–2002

S. haematobium egg loadUrinary schistosomiasis prevalence
1–9 % (n)10–49 % (n)≥50 % (n)P% (n)P
Sex
    Male52 (49)56 (34)64 (115)0.1659 (198)0.001
    Female48 (45)44 (27)36 (66)41 (138)
Age (years)
    3–44 (4)2 (1)0 (0)2 (5)
    5–742 (39)21 (13)18 (32)25 (84)
    8–1023 (22)34 (21)36 (66)< 10−332 (109)< 10−3
    11–1323 (22)31 (19)32 (57)29 (98)
    14–158 (7)12 (7)14 (26)12 (40)
Village
    Diohine64 (60)43 (26)60 (109)0.0258 (195)0.001
    Toucar36 (34)57 (35)40 (72)42 (141)
Total28 (94)18 (61)54 (181)67 (336)
Table 4

Plasmodium falciparum density in relation to age, sex, Schistosoma haematobium egg load, and season by univariate analysis* in Senegal 2001–2002

No.β†95% CI‡P value§
* Study of the log (P. falciparum density +1). Analysis was carried out with a random intercept model with levels being child and district.
† Coefficient of regression.
‡ CI = confidence interval.
§ P value (for variables with more than two categories, the P value of the global test is given).
¶ Number of Schistosoma haematobium eggs per 10 mL of urine.
Age (years)1,916−0.06−0.09, −0.03< 10−3
Sex
    Male1,045
    Female871−0.35−0.53, −0.17< 10−3
S. haematobium egg load¶
    0623
    1–9349−0.33−0.58, −0.08
    10–49225−0.14−0.43, 0.150.10
    ≥ 50656−0.18−0.40, 0.04
Intestinal helminth infection
    No1,218
    Yes533−0.03−0.23, 0.170.76
Season
    December or January947
    September or November9690.520.38, 0.65< 10−3
Table 5

Relationship between Plasmodium falciparum density and Schistosoma haematobium egg load, multivariate analysis* in Senegal 2001–2002

Fixed effectsβ†95% CI‡P§
* N = 1853 measures (log (P. falciparum density +1)), on 505 children. Analysis was carried out with a random intercept model with levels being child and district. Adjustment was done for age, sex, and season.
† Coefficient of regression.
‡ CI = confidence interval.
§ P value (for variables with more than two categories, the P value of the global test is given).
¶ Number of Schistosoma haematobium eggs per 10 mL of urine.
Intercept1.79
Age (years)−0.06−0.09, −0.03< 10−3
Sex
    Male
    Female−0.36−0.54, −0.18< 10−3
S. haematobium egg load¶
    0
    1–9−0.34−0.58, −0.10
    10–49−0.09−0.38, 0.200.07
    ≥50−0.12−0.34, 0.10
Season
    December or January
    September or November0.520.38, 0.66< 10−3
Random effects
    Child-to-child variation (level 2)0.34
    District-to-district variation (level 3)0.01
    Residual variation2.41
Figure 1.
Figure 1.

Hierarchical structure of data for Senegal 2001–2002. Level 1 = Plasmodium falciparum densities; level 2 = children; level 3 = districts. Di.j.k is the kth measurement of P. falciparum density taken on the jth child living in the ith district.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 72, 6; 10.4269/ajtmh.2005.72.702

Authors’ addresses: Valérie Briand, Jean-Yves Le Hesran, André Garcia, and Michel Cot, Institut de Recherche pour le Développement, Unité de Recherche Santé de la Mère et d’Enfant en Milieu Tropical (Unité 010), Faculté de Pharmacie, Université Paris V, 4 Avenue de l’Observatoire, 75270 Paris Cedex 06, France, Telephone: 33-1-53-73-96-22, Fax: 33-1-53-73-96-17, E-mails: vale.briand@laposte.net, jean-yves.lehesran@ird.fr, andre.garcia@ird.sn, and michel.cot@ird.fr. Laurence Watier, Institut National de la Santé et de la Recherche Médicale, Unité d’Epidemiologie et de Biostatistiques (Unite 472), 16 Avenue Paul Vaillant-Couturier, 94807 Villejuif Cedex, France, Telephone: 33-1-45-59-50-58, Fax: 33-1-45-59-51-69, E-mail: watier@vjf.inserm.fr.

Acknowledgments: We thank the team of the Research Institute for Development in Dakar, and Daniel Couret (Research Institute for Development) for their assistance. We also thank Dr. Philippe Deloron and Jean-Philippe Chippaux (Research Institute for Development) for helpful discussions.

Financial support: This work was supported by a grant from the French Ministry of Research and Technology (Pal+ program) and by the Fondation pour la Recherche Médicale.

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