26 research outputs found

    Analysis of pfhrp2 genetic diversity in Senegal and implications for use of rapid diagnostic tests

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    Background: The Senegalese National Malaria Control Programme has recommended use of rapid diagnostic tests (RDTs) that target the histidine-rich protein 2 (HRP2), specific to Plasmodium falciparum, to diagnose malaria cases. The target antigen has been shown to be polymorphic, which may explain the variability in HRP2-based RDT results reported in field studies. The genetic diversity of the pfhrp2 gene has not been investigated in depth in many African countries. The goal of this study is to determine the extent of polymorphism in pfhrp2 among Senegal, Mali and Uganda parasite populations, and discuss the implications of these findings on the utility of RDTs that are based on HRP2 detection. Methods: Sequencing data from the pfhrp2 locus were used to analyze the genetic diversity of this gene among three populations, with different transmission dynamics and malaria parasite ecologies. Nucleotide diversity (π) and non-synonymous nucleotide diversity (πNS) were studied in the pfhrp2 gene from isolates obtained in Senegal. Amino acid repeat length polymorphisms in the PfHRP2 antigen were characterized and parameters of genetic diversity, such as frequency and correlation between repeats in these populations, were assessed. Results: The diversity survey of the pfhrp2 gene identified 29 SNPs as well as insertion and deletion polymorphisms within a 918 bp region. The Senegal pfhrp2 exhibited a substantial level of diversity [π = 0.00559 and πNS = 0.014111 (πS = 0.0291627)], similar to several polymorphic genes, such as msp1, involved in immune responses, and the gene encoding the SURFIN polymorphic antigen, which are surface exposed parasite proteins. Extensive repeat length polymorphisms in PfHRP2, as well as similar patterns in the number, organization and the type of predicted amino acid repeats were observed among the three populations, characterized by an occurrence of Type 2, Type 4 and Type 7 repeats. Conclusions: These results warrant deeper monitoring of the RDT target antigen diversity and emphasize that development of other essential genes as a target for diagnostic tools is critical

    Allelic diversity of MSP1 and MSP2 repeat loci correlate with levels of malaria endemicity in Senegal and Nigerian populations.

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    BACKGROUND: Characterizing the genetic diversity of malaria parasite populations in different endemic settings (from low to high) could be helpful in determining the effectiveness of malaria interventions. This study compared Plasmodium falciparum parasite population diversity from two sites with low (pre-elimination) and high transmission in Senegal and Nigeria, respectively. METHODS: Parasite genomic DNA was extracted from 187 dried blood spot collected from confirmed uncomplicated P. falciparum malaria infected patients in Senegal (94) and Nigeria (93). Allelic polymorphism at merozoite surface protein 1 (msp1) and merozoite surface protein- 2 (msp2) genes were assessed by nested PCR. RESULTS: The most frequent msp1 and msp2 allelic families are the K1 and IC3D7 allelotypes in both Senegal and Nigeria. Multiplicity of infection (MOI) of greater that 1 and thus complex infections was common in both study sites in Senegal (Thies:1.51/2.53; Kedougou:2.2/2.0 for msp1/2) than in Nigeria (Gbagada: 1.39/1.96; Oredo: 1.35/1.75]). The heterozygosity of msp1 gene was higher in P. falciparum isolates from Senegal (Thies: 0.62; Kedougou: 0.53) than isolates from Nigeria (Gbagada: 0.55; Oredo: 0.50). In Senegal, K1 alleles was associated with heavy than with moderate parasite density. Meanwhile, equal proportions of K1 were observed in both heavy and moderate infection types in Nigeria. The IC3D7 subtype allele of the msp2 family was the most frequent in heavily parasitaemic individuals from both countries than in the moderately infected participants. CONCLUSION: The unexpectedly low genetic diversity of infections high endemic Nigerian setting compared to the low endemic settings in Senegal is suggestive of possible epidemic outbreak in Nigeria

    West Africa International Centers of Excellence for Malaria Research: Drug Resistance Patterns to Artemether-Lumefantrine in Senegal, Mali, and The Gambia.

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    In 2006, artemether-lumefantrine (AL) became the first-line treatment of uncomplicated malaria in Senegal, Mali, and the Gambia. To monitor its efficacy, between August 2011 and November 2014, children with uncomplicated Plasmodium falciparum malaria were treated with AL and followed up for 42 days. A total of 463 subjects were enrolled in three sites (246 in Senegal, 97 in Mali, and 120 in Gambia). No early treatment failure was observed and malaria infection cleared in all patients by day 3. Polymerase chain reaction (PCR)-adjusted adequate clinical and parasitological response (ACPR) was 100% in Mali, and the Gambia, and 98.8% in Senegal. However, without PCR adjustment, ACPR was 89.4% overall; 91.5% in Mali, 98.8% in Senegal, and 64.3% in the Gambia (the lower value in the Gambia attributed to poor compliance of the full antimalarial course). However, pfmdr1 mutations were prevalent in Senegal and a decrease in parasite sensitivity to artesunate and lumefantrine (as measured by ex vivo drug assay) was observed at all sites. Recrudescent parasites did not show Kelch 13 (K13) mutations and AL remains highly efficacious in these west African sites

    Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

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    In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

    Towards Resilient Agriculture to Hostile Climate Change in the Sahel Region: A Case Study of Machine Learning-Based Weather Prediction in Senegal

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    To ensure continued food security and economic development in Africa, it is very important to address and adapt to climate change. Excessive dependence on rainfed agricultural production makes Africa more vulnerable to climate change effects. Weather information and services are essential for farmers to more effectively survive the increasing occurrence of extreme weather events due to climate change. Weather information is important for resource management in agricultural production and helps farmers plan their farming activities in advance. Machine Learning is one of the technologies used in agriculture for weather forecasting and crop disease detection among others. The objective of this study is to develop Machine Learning-based models adapted to the context of daily weather forecasting for Rainfall, Relative Humidity, and Maximum and Minimum Temperature in Senegal. In this study, we made a comparison of ten Machine Learning Regressors with our Ensemble Model. These models were evaluated based on Mean Absolute Error, Mean Squared Error, Root Mean Squared Error and Coefficient of Determination. The results show that the Ensemble Model performs better than the ten base models. The Ensemble Model results for each parameter are as follows; Relative Humidity: Mean Absolute Error was 4.0126, Mean Squared Error was 29.9885, Root Mean Squared Error was 5.4428 and Coefficient of Determination was 0.9335. For Minimum Temperature: Mean Absolute Error was 0.7908, Mean Squared Error was 1.1329, Root Mean Squared Error was 1.0515 and Coefficient of Determination was 0.9018. For Maximum Temperature: Mean Absolute Error was 1.2515, Mean Squared Error was 2.8038, Root Mean Squared Error was 1.6591 and Coefficient of Determination was 0.8205. For Rainfall: Mean Absolute Error was 0.2142, Mean Squared Error was 0.1681, Root Mean Squared Error was 0.4100 and Coefficient of Determination was 0.7733. From the present study, it has been observed that the Ensemble Model is a feasible model to be used for Rainfall, Relative Humidity, and Maximum and Minimum Temperature forecasting

    Malaria prevalence, prevention and treatment seeking practices among nomadic pastoralists in northern Senegal

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    Abstract Background Malaria transmission in Senegal is highly stratified, from low in the dry north to moderately high in the moist south. In northern Senegal, along the Senegal River Valley and in the Ferlo semi-desert region, annual incidence is less than five cases per 1000 inhabitants. Many nomadic pastoralists have permanent dwellings in the Ferlo Desert and Senegal River Valley, but spend dry season in the south with their herds, returning north when the rains start, leading to a concern that this population could contribute to ongoing transmission in the north. Methods A modified snowball sampling survey was conducted at six sites in northern Senegal to determine the malaria prevention and treatment seeking practices and parasite prevalence among nomadic pastoralists in the Senegal River Valley and the Ferlo Desert. Nomadic pastoralists aged 6 months and older were surveyed during September and October 2014, and data regarding demographics, access to care and preventive measures were collected. Parasite infection was detected using rapid diagnostic tests (RDTs), microscopy (thin and thick smears) and polymerase chain reaction (PCR). Molecular barcodes were determined by high resolution melting (HRM). Results Of 1800 participants, 61% were male. Sixty-four percent had at least one bed net in the household, and 53% reported using a net the night before. Only 29% had received a net from a mass distribution campaign. Of the 8% (142) who reported having had fever in the last month, 55% sought care, 20% of whom received a diagnostic test, one-third of which (n = 5) were reported to be positive. Parasite prevalence was 0.44% by thick smear and 0.50% by PCR. None of the molecular barcodes identified among the nomadic pastoralists had been previously identified in Senegal. Conclusions While access to and utilization of malaria control interventions among nomadic pastoralists was lower than the general population, parasite prevalence was lower than expected and sheds doubt on the perception that they are a source of ongoing transmission in the north. The National Malaria Control Program is making efforts to improve access to malaria prevention and case management for nomadic populations

    Lack of artemisinin resistance in Plasmodium falciparum in northwest Benin after 10 years of use of artemisinin-based combination therapy

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    Aim: In Benin, artemisinin-based combination therapy (ACT) has been recommended as the first-line treatment for uncomplicated Plasmodium falciparum malaria since 2004. The emergence in Southeast Asia of parasites that are resistant to artemisinins poses a serious threat to global control of this disease. The presence of artemisinin resistance genotypes in parasite populations in Benin is currently unknown. The present study investigated the prevalence of relevant K13-propeller gene polymorphisms in parasite isolates from the north-western region of Benin. Method: Plasmodium falciparum isolates were collected from children with a confirmed diagnosis of malaria aged 6 months to 5 years in two towns, Cobly and Djougou, in the north-western part of Benin. The study was conducted during the rainy season from July to November 2014 in local health facilities. The K13-propeller gene was amplified in parasite isolates using nested PCR and subsequently sequenced. Results: A total of 108 children were recruited into the study. The efficiency of amplification reactions was 72% (78/108). The propeller domain of the K13 gene was successfully sequenced in 78 P. falciparum isolates; all of them were wild type with no polymorphisms detectable. Conclusion: The absence of mutations in the K13 gene indicates that P. falciparum parasite populations in the study area are still fully susceptible to artemisinins
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