Prevalence of intestinal parasitic infections among school children in capital areas of the Democratic Republic of São Tomé and Príncipe, West Africa

Background: Although the Democratic Republic of Sao Tome and Principe (DRSTP) has undertaken school children-based deworming programs against intestinal parasitic infections (IPIs) using a single dose of mebendazole annually since 2005, it remains unclear as to the outcome to date. The present study intends to  investigate the recent IPIs status among school children living in capital areas of the DRSTP.Methods: A total of 252 school children (121 boys and 131 girls) of grades 4 and 5 from 4 primary schools located in the capital areas participated in the present study and their fresh fecal specimens were examined for the presence of any parasites using the merthiolate- iodine-formaldehyde concentration method as conducted.Results: The overall prevalence of IPIs was 64.7% (163/ 252). No significant gender difference in prevalence between boys (67.8%) and girls (61.8%) was found (p = 0.3). The majority of school children were infected with a single species of parasite (55.8%). Altogether, 12 different intestinal parasite species were identified in DRSTP school children, of which 9 species were pathogenic and the remaining 3 were non-pathogenic.Conclusion: Improving the detection method, sanitation facilities and personal hygiene as well as utilizing combined drugs are all important measures to greatly reduce IPIs in DRSTP school children.Keywords: Democratic Republic of Sao Tome and Principe, school children, intestinal parasitic infection

HIV-1 na República Democrática de São Tomé e Príncipe: estudos sobre a situação actual

Este projecto de investigação aborda três aspectos da infecção por HIV na República Democrática de São Tomé e Príncipe (STP), nomeadamente: (i) epidemiologia dos vírus circulantes; (ii) subtipos de HIV-1 e sua filogenia; (iii) resistência a fármacos antirretrovirais. Após a aprovação pela Comissão de Ética local, a epidemiologia dos vírus circulantes foi estudada numa amostragem efectuada nos distritos de Água Grande e Mé Zóchi, em 2007. Envolveu 1018 participantes de ambos os sexos dos 14 aos 65 anos, e consistiu num questionário anónimo com colheita de amostras aleatorizadas de sangue venoso. Estas foram testadas com “Determine™ HIV ½” (Abbott Diagnostics Il., USA) e, quando positivo, retestadas com “VIDAS™ HIV DUO” (BioMérieurx SA). Só cinco casos foram positivos em ambos os testes, quatro de sexo masculino e um feminino. Os subtipos de HIV-1 e a sua filogenia foram estudados no plasma de 93 amostras de conveniência de pessoas entre os 7 e os 63 anos, de ambos os sexos. Estas amostras foram colhidas em diferentes instituições de Saúde do país, de 2004 a 2007. Dois fragmentos do gene da polimerase (pol) – um sendo a totalidade da protease (PR, codões 1-99) e o outro, parte da transcriptase reversa (RT, codões 1-335) – foram amplificados e sequenciados com “ViroSeq HIV-1 System” e o sequenciador “ABI 3100”. As sequências cDNA resultantes da PR e da RT foram analisadas com os algoritmos de subtipagem “HIVSeq” e “REGA Subtyping Tool”. Foram desenhadas árvores filogenéticas por comparação com as sequências de referência do grupo M. As discrepâncias encontradas entre os dois algoritmos foram analisadas com o software Simplot v3.2. Algumas amostras foram classificadas como subtipos puros (A, C, D, F, G, H, J) mas nenhum subtipo B foi encontrado. As amostras, na sua maioria (56%), eram recombinantes (CRF02_AG, CRF02_AG/G, CRF02_AG/H, A/CRF02_AG, K/CRF02_AG, CRF01_AE/CRF02_AG), sugerindo transmissão local. Os subtipos A, G e os seus recombinantes representaram mais do que ¾ do total. Em pessoas infectadas, nas mesmas sequências de cDNA quer de doentes nunca tratados quer de doentes sob tratamento, o padrão de resistências genotípicas aos ARVs foi avaliado com o “Stanford HIV Drug Resistance Algorithm” (beta test). As mutações de resistência encontradas foram: uma de tipo PIs (primária – F53L), oito de tipo NRTIs (M41L, T69N/S, M184I/V, T215Y/S e K219Q) e seis de tipo NNRTIs (A98G, K103N/S, V179E, Y181C, G190A). Foram também encontrados vários polimorfismos nos sítios da PR e da RT.Embora a prevalência do HIV-1 fosse ainda relativamente baixa (0,5%), a grande diversidade genética dos vírus de subtipos não-B em circulação em STP, pode comprometer quer a fiabilidade dos testes serológicos quer a eficácia de hipotéticas futuras vacinas para os países da África Central e da costa Ocidental.This research project aims to study three aspects of HIV infection in the Democratic Republic of São Tomé e Príncipe (STP), namely: (i) the epidemiology of circulating viruses; (ii) HIV-1 subtypes and their phylogeny; (iii) antiretroviral drug resistance patterns. The circulating viruses’ epidemiology was studied, after the local Ethics Committee approval, by way of a survey in the districts of Agua Grande and Mé Zóchi, during 2007. It involved 1018 participants of both genders from 14 to 65 years old, and consisted in a randomized anonymous questionnaire and venous blood sampling. The latter were screened with “DetermineTM HIV ½” (Abbott Diagnostics, Il., USA) and, if positive, tested with “VIDAS® HIV DUO” (BioMérieurx SA). Only five cases (0.5 %) were positive on both tests four from males and one from a female. The HIV-1 subtypes and their phylogeny were studied in 93 convenience blood samples of people aged 7 to 63 of both genders. These samples were collected in the country’s different Health institutions from 2004 to 2007. Two fragments of polymerase gene (pol) - one consisting of the full protease (PR, codons 1-99) and the other, part of the reverse transcriptase (RT, codons 1-335) - were amplified and sequenced with “ViroSeq HIV-1 System” and “ABI 3100” sequencer. The resulting cDNA from PR and RT were analyzed with the subtyping algorithms “HIVSeq” and “REGA Subtyping Tool”. Phylogenetic trees were designed using as comparison the reference’s sequences of group M. The discrepancies found between the two algorithms were analyzed with software Simplot v3.2. Some samples were classified as pure subtypes (A, C, D, F, G, H, J) while no subtype B was found. The majority (56%) of the samples were recombinants (CRF02_AG, CRF02_AG/G, CRF02_AG/H, A/CRF02_AG, K/CRF02_AG, CRF01_AE/CRF02_AG), suggesting regional transmission. Subtypes A, G and their recombinants represent more than ¾ of the total. In the same cDNA sequences, from both treated and treatment-naïve infected people, the genotypic ARVs resistance profile was assessed using “Stanford HIV Drug Resistance Algorithm” (beta test). The resistance mutations found were: one PIs type (primary – F53L), eight NRTIs type (M41L, T69N/S, M184I/V, T215Y/S and K219Q) and six NNRTIs type (A98G, K103N/S, V179E, Y181C, G190A). Several polymorphisms on the PR and RT sites were also found. Although HIV-1 prevalence was still relatively low (0,5%), the great genetic diversity of the non-B subtypes viruses circulating in STP may compromise both the reliability of the serological tests and the effectiveness of hypothetical future vaccines for the Central Africa and West coast

Prevalence of intestinal parasitic infections among school children in capital areas of the Democratic Republic of S\ue3o Tom\ue9 and Pr\uedncipe, West Africa.

Background: Although the Democratic Republic of Sao Tome and Principe (DRSTP) has undertaken school children-based deworming programs against intestinal parasitic infections (IPIs) using a single dose of mebendazole annually since 2005, it remains unclear as to the outcome to date. The present study intends to investigate the recent IPIs status among school children living in capital areas of the DRSTP. Methods: A total of 252 school children (121 boys and 131 girls) of grades 4 and 5 from 4 primary schools located in the capital areas participated in the present study and their fresh fecal specimens were examined for the presence of any parasites using the merthiolate- iodine-formaldehyde concentration method as conducted. Results: The overall prevalence of IPIs was 64.7% (163/ 252). No significant gender difference in prevalence between boys (67.8%) and girls (61.8%) was found (p = 0.3). The majority of school children were infected with a single species of parasite (55.8%). Altogether, 12 different intestinal parasite species were identified in DRSTP school children, of which 9 species were pathogenic and the remaining 3 were non-pathogenic. Conclusion: Improving the detection method, sanitation facilities and personal hygiene as well as utilizing combined drugs are all important measures to greatly reduce IPIs in DRSTP school children

Variables selected for this study.

Smoking cessation is an important public health policy worldwide. However, as far as we know, there is a lack of screening of variables related to the success of therapeutic intervention (STI) in Brazilian smokers by machine learning (ML) algorithms. To address this gap in the literature, we evaluated the ability of eight ML algorithms to correctly predict the STI in Brazilian smokers who were treated at a smoking cessation program in Brazil between 2006 and 2017. The dataset was composed of 12 variables and the efficacies of the algorithms were measured by accuracy, sensitivity, specificity, positive predictive value (PPV) and area under the receiver operating characteristic curve. We plotted a decision tree flowchart and also measured the odds ratio (OR) between each independent variable and the outcome, and the importance of the variable for the best model based on PPV. The mean global values for the metrics described above were, respectively, 0.675±0.028, 0.803±0.078, 0.485±0.146, 0.705±0.035 and 0.680±0.033. Supporting vector machines performed the best algorithm with a PPV of 0.726±0.031. Smoking cessation drug use was the roof of decision tree with OR of 4.42 and importance of variable of 100.00. Increase in the number of relapses also promoted a positive outcome, while higher consumption of cigarettes resulted in the opposite. In summary, the best model predicted 72.6% of positive outcomes correctly. Smoking cessation drug use and higher number of relapses contributed to quit smoking, while higher consumption of cigarettes showed the opposite effect. There are important strategies to reduce the number of smokers and increase STI by increasing services and drug treatment for smokers.</div

Decision tree flowchart.

Smoking cessation is an important public health policy worldwide. However, as far as we know, there is a lack of screening of variables related to the success of therapeutic intervention (STI) in Brazilian smokers by machine learning (ML) algorithms. To address this gap in the literature, we evaluated the ability of eight ML algorithms to correctly predict the STI in Brazilian smokers who were treated at a smoking cessation program in Brazil between 2006 and 2017. The dataset was composed of 12 variables and the efficacies of the algorithms were measured by accuracy, sensitivity, specificity, positive predictive value (PPV) and area under the receiver operating characteristic curve. We plotted a decision tree flowchart and also measured the odds ratio (OR) between each independent variable and the outcome, and the importance of the variable for the best model based on PPV. The mean global values for the metrics described above were, respectively, 0.675±0.028, 0.803±0.078, 0.485±0.146, 0.705±0.035 and 0.680±0.033. Supporting vector machines performed the best algorithm with a PPV of 0.726±0.031. Smoking cessation drug use was the roof of decision tree with OR of 4.42 and importance of variable of 100.00. Increase in the number of relapses also promoted a positive outcome, while higher consumption of cigarettes resulted in the opposite. In summary, the best model predicted 72.6% of positive outcomes correctly. Smoking cessation drug use and higher number of relapses contributed to quit smoking, while higher consumption of cigarettes showed the opposite effect. There are important strategies to reduce the number of smokers and increase STI by increasing services and drug treatment for smokers.</div

Flowchart of supervised and classificatory machine learning algorithms performance evaluation and best model selection.

Flowchart of supervised and classificatory machine learning algorithms performance evaluation and best model selection.</p

Flowchart of medical records selected for descriptive and predictive analysis.

Flowchart of medical records selected for descriptive and predictive analysis.</p

Mean and standard deviation of the predictive values of machine learning models evaluated.

Mean and standard deviation of the predictive values of machine learning models evaluated.</p

Forest plot of odds ratio and confidence interval of variables according to smoking cessation.

Forest plot of odds ratio and confidence interval of variables according to smoking cessation.</p

Image of therapeutic intervention success probability equator prototype.

Image of therapeutic intervention success probability equator prototype.</p