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Background Aedes spp. are responsible for the transmission of many arboviruses, which contribute to rising human morbidity and mortality worldwide. The Aedes aegypti mosquito is a main vector for chikungunya, dengue and yellow fever infections, whose incidence have been increasing and distribution expanding. This vector has also driven the emergence of the Zika virus (ZIKV), first reported in Africa which spread rapidly to Asia and more recently across the Americas. During the outbreak in the Americas, Cape Verde became the first African country declaring a Zika epidemic, with confirmed cases of microcephaly. Here we investigate the prevalence of ZIKV and dengue (DENV) infected Ae. aegypti mosquitoes in the weeks following the outbreak in Cape Verde, and the presence of insecticide resistance in the circulating vector population. Genetic diversity in the mosquito population was also analysed. Methods From August to October 2016, 816 Ae. aegypti mosquitoes were collected in several locations across Praia, Cape Verde, the major hot spot of reported ZIKV cases in the country. All mosquitoes were screened by reverse transcription PCR for ZIKV and DENV, and a subset (n = 220) were screened for knockdown insecticide resistance associated mutations in the voltage gated sodium channel (VGSC) gene by capillary sequencing. The mitochondrial NADH dehydrogenase subunit 4 (nad4) gene was sequenced in 100 mosquitoes. These data were compared to 977 global sequences in a haplotype network and a phylogenetic tree analysis. Results Two Ae. aegypti mosquitoes were ZIKV positive (0.25%). There were no SNP mutations found in the VGSC gene associated with insecticide resistance. Analysis of the nad4 gene revealed 11 haplotypes in the Cape Verdean samples, with 5 being singletons. Seven haplotypes were exclusive to Cape Verde. Several of the remaining haplotypes were frequent in the global dataset, being present in several countries (including Cape Verde) across five different continents. The most common haplotype in Cape Verde (50.6 %) was also found in Africa and South America. Conclusions There was low-level Zika virus circulation in mosquitoes from Praia shortly after the outbreak. The Ae. aegypti population did not appear to have the kdr mutations associated with pyrethroid resistance. Furthermore, haplotype and phylogenetic analyses revealed that Cape Verde Ae. aegypti mosquitoes are most closely related to those from other countries in Africa and South America.

Background Sri Lanka achieved the WHO certificate as a malaria free country in September 2016, thus monitoring of malaria transmission using sensitive and effective tools is an important need. Use of age-specific antibody prevalence as a serological tool to predict transmission intensity is proven to be a cost effective and reliable method under elimination settings. This paper discusses the correlation of four anti-malarial antibodies against vivax and falciparum malaria with the declining transmission intensities in two previously high malaria endemic districts i.e. Kurunegala and Moneragala of Sri Lanka. Methods Sera was collected from 1,186 individuals from the two districts and were subjected to standard ELISA together with control sera from non-immune individuals to obtain Optical Density (OD) values for four anti-malarial antibodies i.e. anti-MSP1 and anti-AMA1 for both Plasmodium vivax and Plasmodium falciparum. The sero-positive samples were determined as mean OD + 3SD of the negative controls. The sero-prevalence was analyzed against the demographic characteristics of the population. A simple reversible catalytic model was fitted into sero-prevalence data to predict the sero-conversion and sero-reversion rates. Results Over 60% of the population was sero-positive for one or more antibodies except young children (

Background Malaria morbidity and mortality has declined in recent years in a number of settings. The ability to describe changes in malaria transmission associated with these declines is important in terms of assessing the potential effects of control interventions, and for monitoring and evaluation purposes. Methods Data from five cross-sectional surveys conducted in Farafenni and surrounding villages on the north bank of River Gambia between 1988 and 2011 were compiled. Antibody responses to MSP-119 were measured in samples from all surveys, data were normalized and expressed as seroprevalence and seroconversion rates (SCR) using different mathematical models. Results Results showed declines in serological metrics with seroprevalence in children aged one to 5 years dropping from 19 % (95 % CI 15–23 %) in 1988 to 1 % (0–2 %) in 2011 (p value for trend in proportions

BACKGROUND: The advent of next generation sequencing technology has accelerated efforts to map and catalogue copy number variation (CNV) in genomes of important micro-organisms for public health. A typical analysis of the sequence data involves mapping reads onto a reference genome, calculating the respective coverage, and detecting regions with too-low or too-high coverage (deletions and amplifications, respectively). Current CNV detection methods rely on statistical assumptions (e.g., a Poisson model) that may not hold in general, or require fine-tuning the underlying algorithms to detect known hits. We propose a new CNV detection methodology based on two Poisson hierarchical models, the Poisson-Gamma and Poisson-Lognormal, with the advantage of being sufficiently flexible to describe different data patterns, whilst robust against deviations from the often assumed Poisson model. RESULTS: Using sequence coverage data of 7 Plasmodium falciparum malaria genomes (3D7 reference strain, HB3, DD2, 7G8, GB4, OX005, and OX006), we showed that empirical coverage distributions are intrinsically asymmetric and overdispersed in relation to the Poisson model. We also demonstrated a low baseline false positive rate for the proposed methodology using 3D7 resequencing data and simulation. When applied to the non-reference isolate data, our approach detected known CNV hits, including an amplification of the PfMDR1 locus in DD2 and a large deletion in the CLAG3.2 gene in GB4, and putative novel CNV regions. When compared to the recently available FREEC and cn.MOPS approaches, our findings were more concordant with putative hits from the highest quality array data for the 7G8 and GB4 isolates. CONCLUSIONS: In summary, the proposed methodology brings an increase in flexibility, robustness, accuracy and statistical rigour to CNV detection using sequence coverage data.