Performance of Small Cluster Surveys and the Clustered LQAS Design to estimate Local-level Vaccination Coverage in Mali

<p>Abstract</p> <p>Background</p> <p>Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required.</p> <p>Methods</p> <p>We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A.</p> <p>Results</p> <p>VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans.</p> <p>Conclusions</p> <p>Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.</p

Absence of system xc⁻ on immune cells invading the central nervous system alleviates experimental autoimmune encephalitis

Background: Multiple sclerosis (MS) is an autoimmune demyelinating disease that affects the central nervous system (CNS), leading to neurodegeneration and chronic disability. Accumulating evidence points to a key role for neuroinflammation, oxidative stress, and excitotoxicity in this degenerative process. System x(c)- or the cystine/glutamate antiporter could tie these pathological mechanisms together: its activity is enhanced by reactive oxygen species and inflammatory stimuli, and its enhancement might lead to the release of toxic amounts of glutamate, thereby triggering excitotoxicity and neurodegeneration. Methods: Semi-quantitative Western blotting served to study protein expression of xCT, the specific subunit of system x(c)-, as well as of regulators of xCT transcription, in the normal appearing white matter (NAWM) of MS patients and in the CNS and spleen of mice exposed to experimental autoimmune encephalomyelitis (EAE), an accepted mouse model of MS. We next compared the clinical course of the EAE disease, the extent of demyelination, the infiltration of immune cells and microglial activation in xCT-knockout (xCT(-/-)) mice and irradiated mice reconstituted in xCT(-/-) bone marrow (BM), to their proper wild type (xCT(+/+)) controls. Results: xCT protein expression levels were upregulated in the NAWM of MS patients and in the brain, spinal cord, and spleen of EAE mice. The pathways involved in this upregulation in NAWM of MS patients remain unresolved. Compared to xCT(+/+) mice, xCT(-/-) mice were equally susceptible to EAE, whereas mice transplanted with xCT(-/-) BM, and as such only exhibiting loss of xCT in their immune cells, were less susceptible to EAE. In none of the above-described conditions, demyelination, microglial activation, or infiltration of immune cells were affected. Conclusions: Our findings demonstrate enhancement of xCT protein expression in MS pathology and suggest that system x(c)- on immune cells invading the CNS participates to EAE. Since a total loss of system x(c)- had no net beneficial effects, these results have important implications for targeting system x(c)- for treatment of MS

Observation of an Excited Bc+ State

Using pp collision data corresponding to an integrated luminosity of 8.5 fb-1 recorded by the LHCb experiment at center-of-mass energies of s=7, 8, and 13 TeV, the observation of an excited Bc+ state in the Bc+π+π- invariant-mass spectrum is reported. The observed peak has a mass of 6841.2±0.6(stat)±0.1(syst)±0.8(Bc+) MeV/c2, where the last uncertainty is due to the limited knowledge of the Bc+ mass. It is consistent with expectations of the Bc∗(2S31)+ state reconstructed without the low-energy photon from the Bc∗(1S31)+→Bc+γ decay following Bc∗(2S31)+→Bc∗(1S31)+π+π-. A second state is seen with a global (local) statistical significance of 2.2σ (3.2σ) and a mass of 6872.1±1.3(stat)±0.1(syst)±0.8(Bc+) MeV/c2, and is consistent with the Bc(2S10)+ state. These mass measurements are the most precise to date

Immobilization of the white-rot fungus Anthracophyllum discolor to degrade the herbicide atrazine

Herbicides cause environmental concerns because they are toxic and accumulate in the environment, food products and water supplies. There is a need to develop safe, efficient and economical methods to remove them from the environment, often by biodegradation. Atrazine is such herbicide. White-rot fungi have the ability to degrade herbicides of potential utility. This study formulated a novel pelletized support to immobilize the white-rot fungus Anthracophyllum discolor to improve its capability to degrade the atrazine using a biopurification system (BS). Different proportions of sawdust, starch, corn meal and flaxseed were used to generate three pelletized supports (F1, F2 and F3). In addition, immobilization with coated and uncoated pelletized supports (CPS and UPS, respectively) was assessed. UPS-F1 was determined as the most effective system as it provided high level of manganese peroxidase activity and fungal viability. The half-life (t1/2) of atrazine decreased from 14 to 6 days for the control and inoculated samples respectively. Inoculation with immobilized A. discolor produced an increase in the fungal taxa assessed by DGGE and on phenoloxidase activity determined. The treatment improves atrazine degradation and reduces migration to surface and groundwater.Grant CONICYT/FONDAP/15130015Grant FONDECYT 112096

An evidence-based framework for predicting the impact of differing autotroph-heterotroph thermal sensitivities on consumer-prey dynamics

Increased temperature accelerates vital rates, influencing microbial population and wider ecosystem dynamics, for example, the predicted increases in cyanobacterial blooms associated with global warming. However, heterotrophic and mixotrophic protists, which are dominant grazers of microalgae, may be more thermally sensitive than autotrophs, and thus prey could be suppressed as temperature rises. Theoretical and meta-analyses have begun to address this issue, but an appropriate framework linking experimental data with theory is lacking. Using ecophysiological data to develop a novel model structure, we provide the first validation of this thermal sensitivity hypothesis: increased temperature improves the consumer’s ability to control the autotrophic prey. Specifically, the model accounts for temperature effects on auto- and mixotrophs and ingestion, growth and mortality rates, using an ecologically and economically important system (cyanobacteria grazed by a mixotrophic flagellate). Once established, we show the model to be a good predictor of temperature impacts on consumer–prey dynamics by comparing simulations with microcosm observations. Then, through simulations, we indicate our conclusions remain valid, even with large changes in bottom-up factors (prey growth and carrying capacity). In conclusion, we show that rising temperature could, counterintuitively, reduce the propensity for microalgal blooms to occur and, critically, provide a novel model framework for needed, continued assessment

A Machine Learning Trainable Model to Assess the Accuracy of Probabilistic Record Linkage

Record linkage (RL) is the process of identifying and linking data that relates to the same physical entity across multiple heterogeneous data sources. Deterministic linkage methods rely on the presence of common uniquely identifying attributes across all sources while probabilistic approaches use non-unique attributes and calculates similarity indexes for pair wise comparisons. A key component of record linkage is accuracy assessment — the process of manually verifying and validating matched pairs to further refine linkage parameters and increase its overall effectiveness. This process however is time-consuming and impractical when applied to large administrative data sources where millions of records must be linked. Additionally, it is potentially biased as the gold standard used is often the reviewer’s intuition. In this paper, we present an approach for assessing and refining the accuracy of probabilistic linkage based on different supervised machine learning methods (decision trees, naïve Bayes, logistic regression, random forest, linear support vector machines and gradient boosted trees). We used data sets extracted from huge Brazilian socioeconomic and public health care data sources. These models were evaluated using receiver operating characteristic plots, sensitivity, specificity and positive predictive values collected from a 10-fold cross-validation method. Results show that logistic regression outperforms other classifiers and enables the creation of a generalized, very accurate model to validate linkage results

Diarrhoea in a large prospective cohort of European travellers to resource-limited destinations

BACKGROUND: Incidence rates of travellers' diarrhoea (TD) need to be updated and risk factors are insufficiently known. METHODS: Between July 2006 and January 2008 adult customers of our Centre for Travel Health travelling to a resource-limited country for the duration of 1 to 8 weeks were invited to participate in a prospective cohort study. They received one questionnaire pre-travel and a second one immediately post-travel. First two-week incidence rates were calculated for TD episodes and a risk assessment was made including demographic and travel-related variables, medical history and behavioural factors. RESULTS: Among the 3100 persons recruited, 2800 could be investigated, resulting in a participation rate of 89.2%. The first two-weeks incidence for classic TD was 26.2% (95%CI 24.5-27.8). The highest rates were found for Central Africa (29.6%, 95% CI 12.4-46.8), the Indian subcontinent (26.3%, 95%CI 2.3-30.2) and West Africa (21.5%, 95%CI 14.9-28.1). Median TD duration was 2 days (range 1-90). The majority treated TD with loperamide (57.6%), while a small proportion used probiotics (23.0%) and antibiotics (6.8%). Multiple logistic regression analysis on any TD to determine risk factors showed that a resolved diarrhoeal episode experienced in the 4 months pre-travel (OR 2.03, 95%CI 1.59-2.54), antidepressive comedication (OR 2.11, 95%CI 1.17-3.80), allergic asthma (OR 1.67, 95%CI 1.10-2.54), and reporting TD-independent fever (OR 6.56, 95%CI 3.06-14.04) were the most prominent risk factors of TD. CONCLUSIONS: TD remains a frequent travel disease, but there is a decreasing trend in the incidence rate. Patients with a history of allergic asthma, pre-travel diarrhoea, or of TD-independent fever were more likely to develop TD while abroad

How good is probabilistic record linkage to reconstruct reproductive histories? Results from the Aberdeen children of the 1950s study

BACKGROUND: Probabilistic record linkage is widely used in epidemiology, but studies of its validity are rare. Our aim was to validate its use to identify births to a cohort of women, being drawn from a large cohort of people born in Scotland in the early 1950s. METHODS: The Children of the 1950s cohort includes 5868 females born in Aberdeen 1950–56 who were in primary schools in the city in 1962. In 2001 a postal questionnaire was sent to the cohort members resident in the UK requesting information on offspring. Probabilistic record linkage (based on surname, maiden name, initials, date of birth and postcode) was used to link the females in the cohort to birth records held by the Scottish Maternity Record System (SMR 2). RESULTS: We attempted to mail a total of 5540 women; 3752 (68%) returned a completed questionnaire. Of these 86% reported having had at least one birth. Linkage to SMR 2 was attempted for 5634 women, one or more maternity records were found for 3743. There were 2604 women who reported at least one birth in the questionnaire and who were linked to one or more SMR 2 records. When judged against the questionnaire information, the linkage correctly identified 4930 births and missed 601 others. These mostly occurred outside of Scotland (147) or prior to full coverage by SMR 2 (454). There were 134 births incorrectly linked to SMR 2. CONCLUSION: Probabilistic record linkage to routine maternity records applied to population-based cohort, using name, date of birth and place of residence, can have high specificity, and as such may be reliably used in epidemiological research