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Soil transmitted helminth (STH) infections are among the most common human infections worldwide with over 1 billion people affected. Many estimates of STH infection are often based on school-aged children (SAC). This study produced predictive risk-maps of STH on a more finite scale, estimated the number of people infected, and the amount of drug required for preventive chemotherapy (PC) in Ogun state, Nigeria. Georeferenced STH infection data obtained from a cross-sectional survey at 33 locations between July 2016 and November 2018, together with remotely-sensed environmental and socio-economic data were analyzed using Bayesian geostatistical modelling. Stepwise variable selection procedure was employed to select a parsimonious set of predictors to predict risk and spatial distribution of STH infections. The number of persons (pre-school ages children, SAC and adults) infected with STH were estimated, with the amount of tablets needed for preventive chemotherapy. An overall prevalence of 17.2% (95% CI 14.9, 19.5) was recorded for any STH infection. Ascaris lumbricoides infections was the most predominant, with an overall prevalence of 13.6% (95% CI 11.5, 15.7), while Hookworm and Trichuris trichiura had overall prevalence of 4.6% (95% CI 3.3, 5.9) and 1.7% (95% CI 0.9, 2.4), respectively. The model-based prevalence predictions ranged from 5.0 to 23.8% for Ascaris lumbricoides, from 2.0 to 14.5% for hookworms, and from 0.1 to 5.7% for Trichuris trichiura across the implementation units. The predictive maps revealed a spatial pattern of high risk in the central, western and on the border of Republic of Benin. The model identified soil pH, soil moisture and elevation as the main predictors of infection for A. lumbricoides, Hookworms and T. trichiura respectively. About 50% (10/20) of the implementation units require biannual rounds of mass drug administration. Approximately, a total of 1.1 million persons were infected and require 7.8 million doses. However, a sub-total of 375,374 SAC were estimated to be infected, requiring 2.7 million doses. Our predictive risk maps and estimated PC needs provide useful information for the elimination of STH, either for resource acquisition or identifying priority areas for delivery of interventions in Ogun State, Nigeria.

Additional file 1: Opportunities and Challenges of the new WHO recommendations.

Aim: This study investigated the prevalence of gastrointestinal helminth infections in ruminant livestock at DUFARMS holding of the Federal University of Agriculture Abeokuta, in Ogun State, southwestern Nigeria. Study Design: Cross sectional study. Place of Study: The study was conducted in Abeokuta, southwestern Nigeria between November 2013 and August 2014. Methodology: Faecal samples were collected directly from the rectum of 170 ruminant livestock and processed using ether-concentration method before examination for gastrointestinal helminth ova under the microscope. Data obtained were analyzed descriptively using SPSS 20.0 software and results were considered statistically significant at p

Peer reviewed: True, The ANOSPP amplicon panel is a genus-wide targeted sequencing panel to facilitate large-scale monitoring of Anopheles species diversity. Combining information from the 62 nuclear amplicons present in the ANOSPP panel allows for a more senstive and specific species assignment than single gene (e.g. COI) barcoding, which is desirable in the light of permeable species boundaries. Here, we present NNoVAE, a method using Nearest Neighbours (NN) and Variational Autoencoders (VAE), which we apply to k-mers resulting from the ANOSPP amplicon sequences in order to hierarchically assign species identity. The NN step assigns a sample to a species-group by comparing the k-mers arising from each haplotype's amplicon sequence to a reference database. The VAE step is required to distinguish between closely related species, and also has sufficient resolution to reveal population structure within species. In tests on independent samples with over 80% amplicon coverage, NNoVAE correctly classifies to species level 98% of samples within the An. gambiae complex and 89% of samples outside the complex. We apply NNoVAE to over two thousand new samples from Burkina Faso and Gabon, identifying unexpected species in Gabon. NNoVAE presents an approach that may be of value to other targeted sequencing panels, and is a method that will be used to survey Anopheles species diversity and Plasmodium transmission patterns through space and time on a large scale, with plans to analyse half a million mosquitoes in the next five years.