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Introduction: Submicroscopic Plasmodium infections are common in malaria endemic countries, but very little studies have been done in Senegal. This study investigates the genetic diversity and complexity of submicroscopic P. falciparum infections among febrile patients in low transmission areas in Senegal. Materials and methods: Hundred and fifty blood samples were collected from febrile individuals living in Dielmo and Ndiop (Senegal) between August 2014 and January 2015, tested for microscopic and sub-microscopic P. falciparum infections and characterized for their genetic diversity and complexity of infections using msp-1 and msp-2 genotyping. Results: Submicroscopic P. falciparum infections were 19.6% and 25% in Dielmo and Ndiop, respectively. K1 and 3D7 were the predominant msp-1 and msp-2 allelic types with respective frequencies of 67.36% and 67.10% in microscopic isolates and 58.24% and 78% in submicroscopic ones. Frequencies of msp-1 allelic types were statistically comparable between the studied groups (p>0.05), and were respectively 93.54% vs 87.5% for K1, 60% vs 54.83% for MAD20 and 41.93% vs 22.5% for RO33 while frequencies of msp-2 allelic types were significantly highest in the microscopy group for FC27 (41.93% vs 10%, Fisher’s Exact Test, p = 0.001) and 3D7 (61.29% vs 32.5%, Fisher’s Exact Test, p = 0.02). Multiplicities of infection were lowest in submicroscopic P. falciparum isolates. Conclusions: The study revealed a high submicroscopic P. falciparum carriage among patients in the study areas, and that submicroscopic P. falciparum isolates had a lower genetic diversity and complexity of malaria infections. [ABSTRACT FROM AUTHOR]

Background: In the progress towards malaria elimination, the accurate diagnosis of low-density asymptomatic infections is critical. Low-density asymptomatic submicroscopic malaria infections may act as silent reservoirs that maintain low-level residual malaria transmission in the community. Light microscopy, the gold standard in malaria diagnosis lacks the sensitivity to detect low-level parasitaemia. In this study, the presence and prevalence of submicroscopic Plasmodium carriage were investigated to estimate the parasites reservoir among asymptomatic individuals living in low transmission areas in Dielmo and Ndiop, Senegal during the dry season. Methods: A total of 2,037 blood samples were collected during cross-sectional surveys prior the malaria transmission season in July 2013 (N = 612), June 2014 (N = 723) and June 2015 (N = 702) from asymptomatic individuals living in Dielmo and Ndiop, Senegal. Samples were used to determine the prevalence of submicroscopic Plasmodium carriage by real time PCR (qPCR) in comparison to microscopy considered as gold standard. Results: The prevalence of submicroscopic Plasmodium carriage was 3.75% (23/612), 12.44% (90/723) and 6.41% (45/702) in 2013, 2014 and 2015, respectively. No Plasmodium carriage was detected by microscopy in 2013 while microscopy-based prevalence of Plasmodium carriage accounted for only 0.27% (2/723) and 0.14% (1/702) in 2014 and 2015, respectively. Plasmodium falciparum accounted for the majority of submicroscopic infections and represented 86.95% (20/23), 81.11% (73/90) and 95.55 (43/45) of infections in 2013, 2014 and 2015 respectively. Conclusion: Low-density submicroscopic asymptomatic Plasmodium carriage is common in the study areas during the dry season indicating that traditional measures are insufficient to assess the scale of parasite reservoir when transmission reaches very low level. Control and elimination strategies may wish to consider using molecular methods to identify parasites carriers to guide Mass screening and Treatment strategies. [ABSTRACT FROM AUTHOR]

Background: African populations are considered to be particularly vulnerable to fever illnesses, including malaria, and acute respiratory disease, owing to limited resources and overcrowding. However, the overall burden of influenza in this context is poorly defined and incidence data for African countries are scarce. We therefore studied the fever syndrome incidence and more specifically influenza incidence in a cohort of inhabitants of Dielmo and Ndiop in Sokone district, Senegal. Methods: Daily febrile-illness data were prospectively obtained from January 2012 to December 2013 from the cohort of the villages of Dielmo and Ndiop, initially dedicated to the study of malaria. Nasopharyngeal swabs were collected from, and malaria diagnosis tests (thick blood smears) carried out on, every febrile individual during clinical visits; reverse transcriptase-polymerase chain reaction was used to identify influenza viruses in the samples. Binomial negative regression analysis was used to study the relationship between the monthly incidence rate and various covariates. Results: In Dielmo and Ndiop, the incidence of malaria has decreased, but fever syndromes remain frequent. Among the 1036 inhabitants included in the cohort, a total of 1,129 episodes of fever were reported. Influenza was present all year round with peaks in October-December 2012 and August 2013. The fever, ILI and influenza incidence density rates differed significantly between age groups. At both sites, the adjusted incidence relative risks for fever syndromes and ILI were significantly higher in the [6–24 months) than other age groups: 7.3 (95%CI: [5.7–9.3]) and 16.1 (95%CI: [11.1–23.3]) respectively. The adjusted incidence relative risk for influenza was significantly higher for the [0–6 months) than other age groups: 9.9 (95%CI: [2.9–33.6]). At both sites, incidence density rates were lowest among adults > = 50 years. Conclusions: In this rural setting in Senegal, influenza was most frequent among the youngest children. Preventive strategies targeting this population should be implemented. [ABSTRACT FROM AUTHOR]

Despite considerable success of genome wide association (GWA) studies in identifying causal variants for many human diseases, their success in unraveling the genetic basis to complex diseases has been more mitigated. Pathogen population structure may impact upon the infectious phenotype, especially with the intense short-term selective pressure that drug treatment exerts on pathogens. Rigorous analysis that accounts for repeated measures and disentangles the influence of genetic and environmental factors must be performed. Attempts should be made to consider whether pathogen diversity will impact upon host genetic responses to infection. We analyzed the heritability of two Plasmodium falciparum phenotypes, the number of clinical malaria episodes (PFA) and the proportion of these episodes positive for gametocytes (Pfgam), in a family-based cohort followed for 19 years, during which time there were four successive drug treatment regimes, with documented appearance of drug resistance. Repeated measures and variance components analyses were performed with fixed environmental, additive genetic, intra-individual and maternal effects for each drug period. Whilst there was a significant additive genetic effect underlying PFA during the first drug period of study, this was lost in subsequent periods. There was no additive genetic effect for Pfgam. The intra-individual effect increased significantly in the chloroquine period. The loss of an additive genetic effect following novel drug treatment may result in significant loss of power to detect genes in a GWA study. Prior genetic analysis must be a pre-requisite for more detailed GWA studies. The temporal changes in the individual genetic and the intra-individual estimates are consistent with those expected if there were specific host-parasite interactions. The complex basis to the human response to malaria parasite infection likely includes dominance/epistatic genetic effects encompassed within the intra-individual variance component. Evaluating their role in influencing the outcome of infection through host genotype by parasite genotype interactions warrants research effort. [ABSTRACT FROM AUTHOR]

Complex, high-dimensional data sets pose significant analytical challenges in the post-genomic era. Such data sets are not exclusive to genetic analyses and are also pertinent to epidemiology. There has been considerable effort to develop hypothesis-free data mining and machine learning methodologies. However, current methodologies lack exhaustivity and general applicability. Here we use a novel non-parametric, non-euclidean data mining tool, HyperCube®, to explore exhaustively a complex epidemiological malaria data set by searching for over density of events in m-dimensional space. Hotspots of over density correspond to strings of variables, rules, that determine, in this case, the occurrence of Plasmodium falciparum clinical malaria episodes. The data set contained 46,837 outcome events from 1,653 individuals and 34 explanatory variables. The best predictive rule contained 1,689 events from 148 individuals and was defined as: individuals present during 1992-2003, aged 1-5 years old, having hemoglobin AA, and having had previous Plasmodium malariae malaria parasite infection ≤10 times. These individuals had 3.71 times more P. falciparum clinical malaria episodes than the general population. We validated the rule in two different cohorts. We compared and contrasted the HyperCube® rule with the rules using variables identified by both traditional statistical methods and non-parametric regression tree methods. In addition, we tried all possible sub-stratified quantitative variables. No other model with equal or greater representativity gave a higher Relative Risk. Although three of the four variables in the rule were intuitive, the effect of number of P. malariae episodes was not. HyperCube® efficiently sub-stratified quantitative variables to optimize the rule and was able to identify interactions among the variables, tasks not easy to perform using standard data mining methods. Search of local over density in m-dimensional space, explained by easily interpretable rules, is thus seemingly ideal for generating hypotheses for large datasets to unravel the complexity inherent in biological systems. [ABSTRACT FROM AUTHOR]