Neighbor-net constructed on SplitsTree software employing the chord distance values among the <i>Leishmania infantum</i> genotypes.

<p>Identical genotypes for the 14 microsatellite markers were grouped and are represented by “TYPEs” (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036242#pone.0036242.s003" target="_blank">Table S1</a>). The distribution of the splits shows the same populations that were determined by the STRUCTURE analysis (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036242#pone-0036242-g002" target="_blank">Figure 2</a>); some genotypes from POP2 are closer to POP1, and others are closer to POP3.</p

The distribution of MLMT genotypes shared among <i>Leishmania infantum</i> strains by hosts and geographic origins.

<p>POP1, ‘TYPE1’ to ‘TYPE14’; POP2, ‘TYPE15’ to ‘TYPE19’; POP3, ‘TYPE20’ to ‘TYPE22’. Brazilian States: AM, Amazonas; BA, Bahia; CE, Ceará; DF, Distrito Federal; ES, Espírito Santo; MA, Maranhão; MG, Minas Gerais; MT, Mato Grosso; MS, Mato Grosso do Sul; PA, Pará; PE, Pernambuco; PI, Piauí; RJ, Rio de Janeiro; RN, Rio Grande do Norte; RS, Rio Grande do Sul; SE, Sergipe; SP, São Paulo. Paraguay: ASU, Asunción.</p><p>The number of strains per state for each genotype is shown in brackets.</p><p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036242#pone.0036242.s003" target="_blank">Table S1</a> for more details.</p

<i>Leishmania infantum</i> populations inferred from STRUCTURE analysis based on profiles of 14 microsatellites.

<p>The barplot was generated in Excel using the results of the aligned distribution of Q values from 10 for <i>K</i> = 3, which was generated using CLUMPP software. Evanno's method predicted that three was the most likely number of populations (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036242#pone.0036242.s001" target="_blank">Figure S1</a>). The POP1 (n = 111) is composed of strains from all of the foci (with the exception of PA), and most of the strains contain traces from POP2. POP2 (n = 31) includes strains from 10 states, but it is predominantly observed in MT. POP3 (n = 31) is composed primarily of MS strains and of four strains from other states of Northeast Brazil. Abbreviations: AM, Amazonas; BA, Bahia; CE, Ceará; DF, Distrito Federal; ES, Espírito Santo; MA, Maranhão; MG, Minas Gerais; MT, Mato Grosso; MS, Mato Grosso do Sul; PA, Pará; PE, Pernambuco; PI, Piauí; RJ, Rio de Janeiro; RN, Rio Grande do Norte; RS, Rio Grande do Sul; SE, Sergipe; SP, São Paulo; PY, Paraguay.</p

Factorial correspondence analysis (FCA) of the <i>Leishmania infantum</i> genotypes.

<p>Spacial distribution of strains after FCA of microsatellite genotypes. Blue dots, POP1; yellow dots, POP2; grey dots, POP3.</p

The geographic origin of <i>Leishmania infantum</i> strains and populations of STRUCTURE analysis.

<p>The yellow dots represent the locations of the collections of each analyzed strain. The graphics indicate the proportion numbers of the strains (Y axis) in each population (X axis). The assignment of the strains to a population was performed in the STRUCTURE analysis that was based on the profiles of 14 microsatellite markers. POP1 is a widespread population, and it is predominant in most of the foci. POP2 and POP3 are predominant in Central West Brazil where <i>Lutzomyia longipalpis</i> and <i>Lutzomyia cruzi</i> are involved in the transmission cycle of Visceral Leishmaniasis. The abbreviations for the Brazilian states are as follows (in bold): AM, Amazonas; BA, Bahia; CE, Ceará; DF, Distrito Federal; ES, Espírito Santo; MA, Maranhão; MG, Minas Gerais; MT, Mato Grosso; MS, Mato Grosso do Sul; PA, Pará; PE, Pernambuco; PI, Piauí; RJ, Rio de Janeiro; RN, Rio Grande do Norte; RS, Rio Grande do Sul; SE, Sergipe; SP, São Paulo. International country codes: AR, Argentina; BO, Bolivia; CL, Chile; CO, Colômbia; GF, French Guiana; GY, Guyana; PY, Paraguay; PE, Peru; SR, Suriname; UR, Uruguay; VE, Venezuela. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036242#pone.0036242.s003" target="_blank">Table S1</a> for more details.</p

Prevalence of intestinal parasites among inmates in Midwest Brazil

<div><p>Background</p><p>Intestinal parasitic infections constitute a public health issue in developing countries, with prevalence rates as high as 90%, a figure set to escalate as the socioeconomic status of affected populations deteriorates. Investigating the occurrence of these infections among inmates is critical, since this group is more vulnerable to the spread of a number of infectious illnesses.</p><p>Methods</p><p>This cross-sectional, analytical, quantitative study was conducted in July 2015 at prison facilities located in Midwest Brazil to estimate the prevalence of parasitic infection among inmates. For detection of parasites, 510 stool samples were examined by ether centrifugation and spontaneous sedimentation.</p><p>Results</p><p>Eight parasitic species were detected, with an overall prevalence of 20.2% (103/510). <i>Giardia lamblia</i> and <i>Entamoeba histolytica</i>/<i>dispar</i> were the most frequent pathogenic parasites. <i>Endolimax nana</i> was the predominant non-pathogenic species. Nearly half of the subjects (53/103; 51.4%) were positive for mixed infection. Logistic regression revealed that inmates held in closed conditions were more likely to contract parasitic infections than those held in a semi-open regime (OR = 1.97; 95% CI = 1.19–3.25; <i>p</i> = 0.0085). A higher prevalence of parasitic infections was observed among individuals who had received no prophylactic antiparasitic treatment in previous years (OR = 10.2; 95% CI = 5.86–17.66; <i>p</i> < 0.001). The other factors investigated had no direct association with the presence of intestinal parasites.</p><p>Conclusion</p><p>Infections caused by directly transmissible parasites were detected. Without adequate treatment and prophylactic guidance, inmates tend to remain indefinitely infected with intestinal parasites, whether while serving time in prison or after release.</p></div

Logistic regression analysis of structural, social, and behavioral factors associated with prevalence of intestinal parasitic infection among inmates.

<p>Mato Grosso do Sul, Midwest Brazil.</p

Symptoms reported by inmates with positive parasitological stool tests.

<p>Mato Grosso do Sul, Midwest Brazil (<i>n</i> = 103).</p

Cases of single- and mixed-species intestinal infection among positively diagnosed inmates, by prison facility.

<p>Mato Grosso do Sul, Midwest Brazil (<i>n</i> = 103).</p