Modelling dynamic change of malaria transmission in holoendemic setting (Dielmo, Senegal) using longitudinal measures of antibody prevalence to Plasmodium falciparum crude schizonts extract.

BACKGROUND: Evaluation of local Plasmodium falciparum malaria transmission has been investigated previously using the reversible catalytic model based on prevalence of antibody responses to single antigen to estimate seroconversion rates. High correlations were observed between seroconversion rates and entomological inoculation rates (EIR). However, in this model, the effects of malaria control interventions and clinical episodes on serological measurements were not assessed. This study monitors the use of antibody responses to P. falciparum crude extracts for assessing malaria transmission, compares seroconversion rates estimated from longitudinal data to those derived from cross-sectional surveys and investigates the effects of malaria control interventions on these measures in an area of declining malaria transmission. In addition, the validity of this model was evaluated by comparison with the alternative model. METHODS: Five cross-sectional surveys were carried out at the end of the wet season in Dielmo, a malaria-endemic Senegalese rural area in 2000, 2002, 2008, 2010 and 2012. Antibodies against schizonts crude extract of a local P. falciparum strain adapted to culture (Pf 07/03) were measured by ELISA. Age-specific seroprevalence model was used both for cross-sectional surveys and longitudinal data (combined data of all surveys). RESULTS: A total of 1504 plasma samples obtained through several years follow-up of 350 subjects was used in this study. Seroconversion rates based on P. falciparum schizonts crude extract were estimated for each cross-sectional survey and were found strongly correlated with EIR. High variability between SCRs from cross-sectional and longitudinal surveys was observed. In longitudinal studies, the alternative catalytic reversible model adjusted better with serological data than the catalytic model. Clinical malaria attacks and malaria control interventions were found to have significant effect on seroconversion. DISCUSSION: The results of the study suggested that crude extract was a good serological tool that could be used to assess the level of malaria exposure in areas where malaria transmission is declining. However, additional parameters such as clinical malaria and malaria control interventions must be taken into account for determining serological measurements for more accuracy in transmission assessment.

High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype.

This work addresses the problem of supervised classification for highly correlated high-dimensional data describing non-independent observations to identify SNPs related to a phenotype. We use a general penalized linear mixed model with a single random effect that performs simultaneous SNP selection and population structure adjustment in high-dimensional prediction models. Specifically, the model simultaneously selects variables and estimates their effects, taking into account correlations between individuals. Single nucleotide polymorphisms (SNPs) are a type of genetic variation and each SNP represents a difference in a single DNA building block, namely a nucleotide. Previous research has shown that SNPs can be used to identify the correct source population of an individual and can act in isolation or simultaneously to impact a phenotype. In this regard, the study of the contribution of genetics in infectious disease phenotypes is of great importance. In this study, we used uncorrelated variables from the construction of blocks of correlated variables done in a previous work to describe the most related observations of the dataset. The model was trained with 90% of the observations and tested with the remaining 10%. The best model obtained with the generalized information criterion (GIC) identified the SNP named rs2493311 located on the first chromosome of the gene called PRDM16 ((PR/SET domain 16)) as the most decisive factor in malaria attacks.

Impact of different heat wave definitions on daily mortality in Bandafassi, Senegal.

OBJECTIVE: The aim of this study is to find the most suitable heat wave definition among 15 different ones and to evaluate its impact on total, age-, and gender-specific mortality for Bandafassi, Senegal. METHODS: Daily weather station data were obtained from Kedougou situated at 17 km from Bandafassi from 1973 to 2012. Poisson generalized additive model (GAM) and distributed lag non-linear model (DLNM) are used to investigate the effect of heat wave on mortality and to evaluate the nonlinear association of heat wave definitions at different lag days, respectively. RESULTS: Heat wave definitions, based on three or more consecutive days with both daily minimum and maximum temperatures greater than the 90th percentile, provided the best model fit. A statistically significant increase in the relative risk (RRs 1.4 (95% Confidence Interval (CI): 1.2-1.6), 1.7 (95% CI: 1.5-1.9), 1.21 (95% CI: 1.08-1.3), 1.2 (95% CI: 1.04-1.5), 1.5 (95% CI: 1.3-1.8), 1.4 (95% CI: 1.2-1.5), 1.5 (95% CI: 1.07-1.6), and 1.5 (95% CI: 1.3-1.8)) of total mortality was observed for eight definitions. By using the definition based on the 90th percentile of minimum and maximum temperature with a 3-day duration, we also found that females and people aged ≥ 55 years old were at higher risks than males and other different age groups to heat wave related mortality. CONCLUSION: The impact of heat waves was associated with total-, age-, gender-mortality. These results are expected to be useful for decision makers who conceive of public health policies in Senegal and elsewhere. Climate parameters, including temperatures and humidity, could be used to forecast heat wave risks as an early warning system in the area where we conduct this research. More broadly, our findings should be highly beneficial to climate services, researchers, clinicians, end-users and decision-makers.