Progressive invasion of Aedes albopictus in Northern Spain in the period 2013–2018 and a possible association with the increase in insect bites

1) Background: Aedes albopictus has rapidly expanded throughout Europe, becoming a public health concern in the Mediterranean Basin. 2) Methods: Following the detection of Ae. albopictus in the southwestern French region of Aquitaine in 2012, an entomological surveillance programme was implemented in the Basque Country (Northern Spain) in 2013. 3) Results: Ae. albopictus eggs were first detected in 2014 in a transited parking area in the northeastern sampling point, 22 km away from the nearest French site with recorded presence of tiger mosquito. At this site, eggs were found throughout the study (2014–2018). Other western and southern municipalities became positive in 2017 and 2018. Ae. albopictus adults were first captured in 2018 by aspiration of the vegetation in an area where eggs had been detected since 2015, suggesting a progressive establishment of a self-sustained population. Incidence of insect bites in humans was roughly constant over the study period except for a significant increase in 2018 in the Health County where eggs had been detected since 2014. Densities of Ae. albopictus eggs in positive areas remained at similar levels over the years. 4) Conclusion: Multiple approaches and standardized methods are necessary to successfully control this vector

Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle

14 Pág. Departamento de Mejora Genetica AnimalMitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions.This research was financed by RTA2015-00022-C03-02 (METALGEN) project from the National Plan of Research, Development and Innovation 2013–2020 and the Department of Economic Development and Competitiveness (Madrid, Spain). A.L.G. was funded by FPI-INIA grant with reference FPI-SGIT2016-06.Peer reviewe

Successes and challenges in optimizing the viral load cascade to improve antiretroviral therapy adherence and rationalize second-line switches in Swaziland.

INTRODUCTION: As antiretroviral therapy (ART) is scaled up, more patients become eligible for routine viral load (VL) monitoring, the most important tool for monitoring ART efficacy. For HIV programmes to become effective, leakages along the VL cascade need to be minimized and treatment switching needs to be optimized. However, many HIV programmes in resource-constrained settings report significant shortfalls. METHODS: From a public sector HIV programme in rural Swaziland, we evaluated the VL cascade of adults (≥18 years) on ART from the time of the first elevated VL (>1000 copies/mL) between January 2013 and June 2014 to treatment switching by December 2015. We additionally described HIV drug resistance for patients with virological failure. We used descriptive statistics and Kaplan-Meier estimates to describe the different steps along the cascade and regression models to determine factors associated with outcomes. RESULTS AND DISCUSSION: Of 828 patients with a first elevated VL, 252 (30.4%) did not receive any enhanced adherence counselling (EAC). Six hundred and ninety-six (84.1%) patients had a follow-up VL measurement, and the predictors of receiving a follow-up VL were being a second-line patient (adjusted hazard ratio (aHR): 0.72; p = 0.051), Hlathikhulu health zone (aHR: 0.79; p = 0.013) and having received two EAC sessions (aHR: 1.31; p = 0.023). Four hundred and ten patients (58.9%) achieved VL re-suppression. Predictors of re-suppression were age 50 to 64 (adjusted odds ratio (aOR): 2.02; p = 0.015) compared with age 18 to 34 years, being on second-line treatment (aOR: 3.29; p = 0.003) and two (aOR: 1.66; p = 0.045) or three (aOR: 1.86; p = 0.003) EAC sessions. Of 278 patients eligible to switch to second-line therapy, 120 (43.2%) had switched by the end of the study. Finally, of 155 successfully sequenced dried blood spots, 144 (92.9%) were from first-line patients. Of these, 133 (positive predictive value: 92.4%) had resistance patterns that necessitated treatment switching. CONCLUSIONS: Patients on ART with high VLs were more likely to re-suppress if they received EAC. Failure to re-suppress after counselling was predictive of genotypically confirmed resistance patterns requiring treatment switching. Delays in switching were significant despite the ability of the WHO algorithm to predict treatment failure. Despite significant progress in recent years, enhanced focus on quality care along the VL cascade in resource-limited settings is crucial

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding

17 Pág.  Departamento de ​Mejora Genética Animal (INIA)The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.This research was financed by the METALGEN project (RTA2015-00022-C03) from the national plan for research, development, and innovation 2013–2020 and the Department of Economic Development and Competitiveness (Madrid, Spain).Peer reviewe

Modelling the spatial risk of malaria through probability distribution of Anopheles maculipennis s.l. and imported cases

Malaria remains one of the most important infectious diseases globally due to its high incidence and mortality rates. The influx of infected cases from endemic to non-endemic malaria regions like Europe has resulted in a public health concern over sporadic local outbreaks. This is facilitated by the continued presence of competent Anopheles vectors in non-endemic countries. We modelled the potential distribution of the main malaria vector across Spain using the ensemble of eight modelling techniques based on environmental parameters and the Anopheles maculipennis s.l. presence/absence data collected from 2000 to 2020. We then combined this map with the number of imported malaria cases in each municipality to detect the geographic hot spots with a higher risk of local malaria transmission. The malaria vector occurred preferentially in irrigated lands characterized by warm climate conditions and moderate annual precipitation. Some areas surrounding irrigated lands in northern Spain (e.g. Zaragoza, Logroño), mainland areas (e.g. Madrid, Toledo) and in the South (e.g. Huelva), presented a significant likelihood of A. maculipennis s.l. occurrence, with a large overlap with the presence of imported cases of malaria. While the risk of malaria re-emergence in Spain is low, it is not evenly distributed throughout the country. The four recorded local cases of mosquito-borne transmission occurred in areas with a high overlap of imported cases and mosquito presence. Integrating mosquito distribution with human incidence cases provides an effective tool for the quantification of large-scale geographic variation in transmission risk and pinpointing priority areas for targeted surveillance and prevention

AIMSurv: First pan-European harmonized surveillance of Aedes invasive mosquito species of relevance for human vector-borne diseases

Human and animal vector-borne diseases, particularly mosquito-borne diseases, are emerging or re-emerging worldwide. Six Aedes invasive mosquito (AIM) species were introduced to Europe since the 1970s: Aedes aegypti, Ae. albopictus, Ae. japonicus, Ae. koreicus, Ae. atropalpus and Ae. triseriatus. Here, we report the results of AIMSurv2020, the first pan-European surveillance effort for AIMs. Implemented by 42 volunteer teams from 24 countries. And presented in the form of a dataset named “AIMSurv Aedes Invasive Mosquito species harmonized surveillance in Europe. AIM-COST Action. Project ID: CA17108”. AIMSurv2020 harmonizes field surveillance methodologies for sampling different AIMs life stages, frequency and minimum length of sampling period, and data reporting. Data include minimum requirements for sample types and recommended requirements for those teams with more resources. Data are published as a Darwin Core archive in the Global Biodiversity Information Facility- Spain, comprising a core file with 19,130 records (EventID) and an occurrences file with 19,743 records (OccurrenceID). AIM species recorded in AIMSurv2020 were Ae. albopictus, Ae. japonicus and Ae. koreicus, as well as native mosquito species

Field Evaluation of a Rapid Immunochromatographic Assay for Detection of Trypanosoma cruzi Infection by Use of Whole Blood▿

Laboratory and clinical diagnostic classification of seropositive individuals, followed by treatment and supportive therapy, is an established component of Chagas' disease control in areas where this disease is endemic. However, most Chagas' disease patients live in remote areas where neither equipped laboratories nor skilled human resources are widely available. Employing a rapid diagnostic test (RDT), when using whole blood samples, is the best option for Chagas' disease control. A high sensitivity and specificity for the Chagas Stat-Pak RDT (Chembio Diagnostic Systems, Inc., Medford, NY) has been reported for assays using serum and plasma, but its validity for the detection of antibodies to Trypanosoma cruzi infection in whole blood is unknown. This cross-sectional study measured the sensitivity and specificity of the Chagas Stat-Pak with whole blood, using conventional serological assays for comparison. The interobserver reliability in the interpretation of the Chagas Stat-Pak results and “ease-of-use” criterion needed to perform the Chagas Stat-Pak and conventional assays were also measured. The Chagas Stat-Pak yielded a high specificity (99.0%, 95% confidence interval [CI] = 98.4 to 99.4%) but a relatively low sensitivity (93.4%, 95% CI = 87.4 to 97.1%). The interobserver reliability was excellent (kappa [n = 1,913] = 0.999, P < 0.0001), and the quantified ease-of-use criterion suggested that the RDT is simple to perform. Despite the attributes of the Chagas Stat-Pak, it is not an ideal diagnostic test for the population investigated in the present study due to its relatively low sensitivity and high cost. The RDT manufacturer is called upon to improve the test if the international community hopes to make progress in controlling Chagas infections in areas where this disease is endemic

Rumen eukaryotes are the main phenotypic risk factors for larger methane emissions in dairy cattle

Mitigation of methane emissions from dairy cattle is a relevant strategy to reduce environmental impact from livestock as well as to increase farm profitability through improvement of energy usage. The objective of this study was to compare how microbiome composition determines methane concentration (MET) and methane intensity (MI, ppm CH4/kg Milk) with other traditional proxies (e.g. milk yield and conformation traits). A total of 1359 Holstein cows from 17 herds in 4 northern regions of Spain were included in this study. Microbiome data came from a subset of 437 cows from 14 herds. Cows were classified in quartiles for MET and MI, according to individual records of methane measurements during the cow's visit to the automatic milking system unit. A probit approach under a Markov chain Monte Carlo (McMC) Bayesian framework was used to determine risk factors for high MET and high MI. Reducing MET and MI genetic merit by unit of standard deviation (SD) reduced the probability of being classified in the upper quartile by 35.2% (33.9% to 36.4%) and 28.8% (27.6% to 29.6%), respectively. Increasing the relative abundance of most bacteria reduced the probability of a cow to be classified as high emitter (e.g., Firmicutes 9.9% (8.3 to 11.3) for MET and 7.1% (6.2 to 8.2) for MI, per unit of SD). An opposite effect was observed for the relative abundance of Eukaryotes. Larger abundance of most eukaryote caused larger risk for a cow to be classified as a high emitter animal (e.g., Oomycetes 14.2% (11.7% to 16.4%) for MET and 11.8% (9.4% to 14.0%) for MI, per unit of SD). One more unit of milk yield SD increased the probability of being classified in the upper quartile for MET by 3.7% (2.3% to 4.2%) and reduced the probability for MI by 12.6% (12.2% to 13.3%). Structure and capacity traits were not main drivers of being classified in the higher quartile of methane emission and intensity, with risk odds lower than 2% per unit of SD. Cow genetic merit for methane concentration and her microbiome composition (86 phylum and 1240 genus) were the main drivers for a cow to be classified as high MET or MI. This study suggests that mitigation of MET and MI could be addressed through animal breeding programs including genetic merits and strategies that modulate the microbiome.This research was financed by RTA2015-00022-C03 (METALGEN) project from the national plan of research, development, and innovation 2013-2020. The first author of this paper was granted a scholarship from Universidad de Costa Rica for course doctorate studies which partially conducted to the progress of this study.Peer reviewe

Rumen eukaryotes are the main phenotypic risk factors for larger methane emissions in dairy cattle

Mitigation of methane emissions from dairy cattle is a relevant strategy to reduce environmental impact from livestock as well as to increase farm profitability through improvement of energy usage. The objective of this study was to compare how microbiome composition determines methane concentration (MET) and methane intensity (MI, ppm CH4/kg Milk) with other traditional proxies (e.g. milk yield and conformation traits). A total of 1359 Holstein cows from 17 herds in 4 northern regions of Spain were included in this study. Microbiome data came from a subset of 437 cows from 14 herds. Cows were classified in quartiles for MET and MI, according to individual records of methane measurements during the cow’s visit to the automatic milking system unit. A probit approach under a Markov chain Monte Carlo (McMC) Bayesian framework was used to determine risk factors for high MET and high MI. Reducing MET and MI genetic merit by unit of standard deviation (SD) reduced the probability of being classified in the upper quartile by 35.2% (33.9% to 36.4%) and 28.8% (27.6% to 29.6%), respectively. Increasing the relative abundance of most bacteria reduced the probability of a cow to be classified as high emitter (e.g., Firmicutes 9.9% (8.3 to 11.3) for MET and 7.1% (6.2 to 8.2) for MI, per unit of SD). An opposite effect was observed for the relative abundance of Eukaryotes. Larger abundance of most eukaryote caused larger risk for a cow to be classified as a high emitter animal (e.g., Oomycetes 14.2% (11.7% to 16.4%) for MET and 11.8% (9.4% to 14.0%) for MI, per unit of SD). One more unit of milk yield SD increased the probability of being classified in the upper quartile for MET by 3.7% (2.3% to 4.2%) and reduced the probability for MI by 12.6% (12.2% to 13.3%). Structure and capacity traits were not main drivers of being classified in th higher quartile of methane emission and intensity, with risk odds lower than 2% per unit of SD. Cow genetic merit for methane concentration and her microbiome composition (86 phylum and 1240 genus) were the main drivers for a cow to be classified as high MET or MI. This study suggests that mitigation of MET and MI could be addressed through animal breeding programs including genetic merits and strategies that modulate the microbiome.This research was financed by RTA2015-00022-C03 (METALGEN) project from the national plan of research, development, and innovation 2013-2020.UCR::Vicerrectoría de Docencia::Ciencias Agroalimentarias::Facultad de Ciencias Agroalimentarias::Escuela de ZootecniaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Agroalimentarias::Centro de Investigación en Nutrición Animal (CINA