Fig 3 -

Correlation between S. haematobium egg counts measured by the Schistoscope and S. haematobium egg counts measured by conventional microscopy (a, d, e), Ct-values determined by real-time PCR (b, f) and urine CAA concentration measured by UCP-LF CAA (c, g) in study A and B.</p

<i>Schistosoma haematobium</i> effects on <i>Plasmodium falciparum</i> infection modified by soil-transmitted helminths in school-age children living in rural areas of Gabon

<div><p>Background</p><p>Malaria burden remains high in the sub-Saharan region where helminths are prevalent and where children are often infected with both types of parasites. Although the effect of helminths on malaria infection is evident, the impact of these co-infections is not clearly elucidated yet and the scarce findings are conflicting. In this study, we investigated the effect of schistosomiasis, considering soil-transmitted helminths (STH), on prevalence and incidence of <i>Plasmodium falciparum</i> infection.</p><p>Methodology</p><p>This longitudinal survey was conducted in school-age children living in two rural communities in the vicinity of Lambaréné, Gabon. Thick blood smear light microscopy, urine filtration and the Kato-Katz technique were performed to detect malaria parasites, <i>S</i>. <i>haematobium</i> eggs and, STH eggs, respectively. <i>P</i>. <i>falciparum</i> carriage was assessed at inclusion, and incidence of malaria and time to the first malaria event were recorded in correlation with Schistosoma carriage status. Stratified multivariate analysis using generalized linear model was used to assess the risk of plasmodium infection considering interaction with STH, and survival analysis to assess time to malaria.</p><p>Main findings</p><p>The overall prevalence on subject enrolment was 30%, 23% and 9% for <i>S</i>. <i>haematobium</i>, <i>P</i>. <i>falciparum</i> infections and co-infection with both parasites, respectively. Our results showed that schistosomiasis in children tends to increase the risk of plasmodium infection but a combined effect with <i>Trichuris trichiura</i> or hookworm infection clearly increase the risk (aOR = 3.9 [_95%CI: 1.7–9.2]). The incidence of malaria over time was 0.51[_95%CI: 0.45–0.57] per person-year and was higher in the Schistosoma-infected group compared to the non-infected group (0.61 <i>vs</i> 0.43, <i>p</i> = 0.02), with a significant delay of time-to first-malaria event only in children aged from 6 to 10-years-old infected with <i>Schistosoma haematobium</i>.</p><p>Conclusions</p><p>Our results suggest that STH enhance the risk for <i>P</i>. <i>falciparum</i> infection in schistosomiasis-positive children, and when infected, that schistosomiasis enhances susceptibility to developing malaria in young children but not in older children.</p></div

S1 Raw Dataset -

Overall raw dataset containing data for Schistoscope validation on fresh urine samples (study A), Banked slides (study B) and quality control of banked slides. (XLSX)</p

Characteristics of study groups considered for longitudinal analysis regarding Schistosoma status (N = 586).

<p>Characteristics of study groups considered for longitudinal analysis regarding Schistosoma status (N = 586).</p

Comprehensive flow chart detailing the methodical sequence of urine sample collection, processing by the Schistoscope, conventional microscopy, real-time PCR and UCP-LF CAA and data analysis.

Comprehensive flow chart detailing the methodical sequence of urine sample collection, processing by the Schistoscope, conventional microscopy, real-time PCR and UCP-LF CAA and data analysis.</p

Diagnostic outcomes of the Schistoscope in comparison to conventional microscopy, real-time PCR and UCP-LF CAA in study A and B.

Diagnostic outcomes of the Schistoscope in comparison to conventional microscopy, real-time PCR and UCP-LF CAA in study A and B.</p

Malaria risk and malaria incidence among the 584 participants according to Schistosoma status and other risk factors.

<p>Malaria risk and malaria incidence among the 584 participants according to Schistosoma status and other risk factors.</p

Distribution of <i>P</i>. <i>falciparum</i> and <i>S</i>. <i>haematobium</i> infections among the 739 participants seen at baseline.

<p>Distribution of <i>P</i>. <i>falciparum</i> and <i>S</i>. <i>haematobium</i> infections among the 739 participants seen at baseline.</p

Diagnostic performance and pairwise level of agreement by Cohen’s Kappa statistics between the Schistoscope and conventional microscopy and the composite reference for the detection of <i>S</i>. <i>haematobium</i> infection in study A and B.

Diagnostic performance and pairwise level of agreement by Cohen’s Kappa statistics between the Schistoscope and conventional microscopy and the composite reference for the detection of S. haematobium infection in study A and B.</p

Depicts estimates of time to malaria after 52 weeks of follow-up.

<p>Depicted in the vertical axis the proportion of children who did not experience malaria and in the horizontal axis, the follow-up time in months. In red, children in <i>S</i>. <i>haematobium</i> non-infected group and in blue children in <i>S</i>. <i>haematobium</i> infected group. 2A) Kaplan Meier curve for time-to-first malaria case for overall study population. 2B) Kaplan Meier curve for time-to-first malaria case for children aged from 6 to 10 years old. 2C) Kaplan Meier curve for time-to-first malaria case for children aged from 11 to 16 years old.</p