Haplotype abundance barcharts for Lake Albert (A) and Lake Victoria (B).

<p>The main barcharts display haplotypes recovered during the baseline surveys and the inset barcharts display haplotypes isolated during the six-month follow up surveys. Dark grey bars indicate haplotypes identified in mothers whereas light grey bars represent haplotypes isolated from children. “Single” refers to unique haplotypes which were only identified once during the surveys.</p

Cumulative number of unique haplotypes identified at baseline plotted against the identification code of each sequentially sampled host from Lake Albert (A) and Lake Victoria (B).

<p>Cumulative number of unique haplotypes identified at baseline plotted against the identification code of each sequentially sampled host from Lake Albert (A) and Lake Victoria (B).</p

Genetic differentiation between surveys assessed by hierarchical AMOVA.

a<p>12 months for Walukuba and 18 months for Bugoto;</p>b<p>Φ_ST estimator of genetic differentiation;</p>c<p><i>P</i> value from permutation test of genetic differentiation (10000 permutations).</p

Neighbour joining tree based on the net mean genetic distances between individual infrapopulations sampled at baseline and in follow-up surveys.

<p>The red-dotted line indicates the almost-complete segregation between infrapopulations from Lake Albert and those from Lake Victoria. The red rectangle highlights one infrapopulation from Lake Victoria which clusters with infrapopulations from Lake Albert. BUG = Bugoigo; WAL = Walukuba; PIIDA = Piida; BUGT = Bugoto; BUK = Bukoba; LWA = Lwanika. 6 MO = 6 month follow-up; 12 MO = 12 month follow-up; 18 MO = 18 month follow-up. M* = identification code for a mother host; M*C1 or M*C2 = identification code for a child host.</p

Diagnostic performance of different diagnostic tests for <i>S. mansoni</i> infections before and after a treatment.

<p>This study was conducted in three epidemiological settings in Uganda in October/November 2009 (baseline) and 2010 (follow-up). For each stool sample, duplicate Kato-Katz thick smears were performed.</p

A neighbour joining tree based on Kimura-2-parameters representing phylogenetic relationships between haplotypes identified during the baseline surveys and selected haplotypes from across the globe.

<p>Black dots represent branches for which bootstrap support was over 75% (1000 replicates). Most haplotypes fall into lineage 2 as identified by Webster <i>et al. </i><a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002561#pntd.0002561-Webster2" target="_blank">[20]</a>. Haplotypes falling into lineages 1, 3, 4 and 5 are indicated using red oval outlines.</p

Relationship between infection intensity and genetic diversity at baseline.

<p>(A) Histogram displaying typical “overdispersed” distribution of <i>S. mansoni</i> infections at baseline. (B) Haplotype diversity of parasites isolated from individual hosts plotted against host infection intensity. (C) Nucleotide diversity of parasites isolated from individual hosts plotted against host infection intensity.</p

ROC curves of microscopy and the CCA using SEA-ELISA results as reference test.

<p>The receiver operating characteristic (ROC) curves and the area under the curve (AUC) of faecal microscopy (A) and CCA (B) are presented from either a low (green), moderate (orange) or high transmission (red) setting. Results are presented from baseline (above) and follow-up (below) surveys.</p

AMOVA results for two lake systems showing little evidence of genetic differentiation between mothers and children at baseline.

a<p>Φ_ST estimator of genetic differentiation;</p>b<p><i>P</i> value from permutation test of genetic differentiation (10000 permutations).</p

Precision mapping: An innovative tool and way forward to shrink the map, better target interventions, and accelerate toward the elimination of schistosomiasis - Fig 1

<p><b>Comparison of precision and conventional maps of schistosomiasis prevalence in the health districts of Edea (A) and Ndikinimeki (B), Cameroon.</b> The precision maps (A1 and B1) provide more accurate information on the distribution of schistosomiasis within districts and a clear precision on subdistricts or communities requiring preventive chemotherapy. Differences of subdistrict prevalence between 1985 and 2010 mappings further illustrate the limitations and uncertainties of the conventional mapping (A2 versus A3 and B2 versus B3). Produced with Esri ArcGIS Pro 2.0.</p