Developing a forecasting model for cholera incidence in Dhaka megacity through time series climate data.

Cholera, an acute diarrheal disease spread by lack of hygiene and contaminated water, is a major public health risk in many countries. As cholera is triggered by environmental conditions influenced by climatic variables, establishing a correlation between cholera incidence and climatic variables would provide an opportunity to develop a cholera forecasting model. Considering the auto-regressive nature and the seasonal behavioral patterns of cholera, a seasonal-auto-regressive-integrated-moving-average (SARIMA) model was used for time-series analysis during 2000-2013. As both rainfall (r = 0.43) and maximum temperature (r = 0.56) have the strongest influence on the occurrence of cholera incidence, single-variable (SVMs) and multi-variable SARIMA models (MVMs) were developed, compared and tested for evaluating their relationship with cholera incidence. A low relationship was found with relative humidity (r = 0.28), ENSO (r = 0.21) and SOI (r = -0.23). Using SVM for a 1 °C increase in maximum temperature at one-month lead time showed a 7% increase of cholera incidence (p < 0.001). However, MVM (AIC = 15, BIC = 36) showed better performance than SVM (AIC = 21, BIC = 39). An MVM using rainfall and monthly mean daily maximum temperature with a one-month lead time showed a better fit (RMSE = 14.7, MAE = 11) than the MVM with no lead time (RMSE = 16.2, MAE = 13.2) in forecasting. This result will assist in predicting cholera risks and better preparedness for public health management in the future

Prevalence of Bacterial Lower Respiratory Tract Infections at a Tertiary Hospital in Jordan

Background: Lower respiratory tract infections (LRTI) are a major cause of morbidity and mortality globally. The World Health Organization (WHO) estimates that LRTI are the most common global cause of death from infectious diseases. &nbsp;However, the specific etiologic agent associated with LRTI is often unknown. Aims: We determined the bacterial infections and seasonal patterns associated with LRTI among hospitalized cases at Jordan University Hospital (JUH) for a period of five years. Methods: We conducted a multi-year study among hospitalized patients in Jordan on LRTI-associated bacterial etiology. Results: We found bacterial infections among 105 (21.1%) out of 495 LRTI patients. The most frequently identified bacteria in the LRTI patients were Staphylococcus aureus (7.7%) followed by Pseudomonas aeruginosa (5.1%). Most of the LRTI patients (95.2%) had at least one chronic disease and many were admitted to the Intensive Care Unit (16.8%). Of the 18 (3.64%) patients with LRTI who died at the hospital, 2 had a bacterial infection. We noticed a seasonal pattern of bacterial infections, with the highest prevalence during the winter months. Conclusions: Our findings suggest that early identification of bacterial agents and control of chronic disease may improve clinical management and reduce morbidity and mortality from LRTI

Changing species distribution and antimicrobial susceptibility pattern of Shigella over a 29-year period (1980-2008)

We studied changes in species distribution and antimicrobial resistance patterns of Shigella during 1980-2008, using the Diarrhoeal Diseases Surveillance system of Dhaka Hospital of ICDDR,B. In hospitalized patients Shigella prevalence decreased steadily from 8-12% in the 1980s to 3% in 2008. Endemic S. flexneri was the most commonly isolated species (54%). Epidemic S. dysenteriae type 1 had two peaks in 1984 and 1993, but was not found after 2000, except for one case in 2004. The therapeutic options are now limited: in 2008 a total of 33% of S. flexneri were resistant to ciprofloxacin and 57% to mecillinam. In the <5 years age group, severely underweight, wasted and stunted children were more at risk of shigellosis compared to well-nourished children (P<0·001). Although hospitalization for Shigella diarrhoea is decreasing, the high levels of antimicrobial resistance and increased susceptibility of malnourished children continue to pose an ongoing ris

Effects of Noise on Ecological Invasion Processes: Bacteriophage-mediated Competition in Bacteria

Pathogen-mediated competition, through which an invasive species carrying and transmitting a pathogen can be a superior competitor to a more vulnerable resident species, is one of the principle driving forces influencing biodiversity in nature. Using an experimental system of bacteriophage-mediated competition in bacterial populations and a deterministic model, we have shown in [Joo et al 2005] that the competitive advantage conferred by the phage depends only on the relative phage pathology and is independent of the initial phage concentration and other phage and host parameters such as the infection-causing contact rate, the spontaneous and infection-induced lysis rates, and the phage burst size. Here we investigate the effects of stochastic fluctuations on bacterial invasion facilitated by bacteriophage, and examine the validity of the deterministic approach. We use both numerical and analytical methods of stochastic processes to identify the source of noise and assess its magnitude. We show that the conclusions obtained from the deterministic model are robust against stochastic fluctuations, yet deviations become prominently large when the phage are more pathological to the invading bacterial strain.Comment: 39 pages, 7 figure

Development of admixture mapping panels for African Americans from commercial high-density SNP arrays

<p>Abstract</p> <p>Background</p> <p>Admixture mapping is a powerful approach for identifying genetic variants involved in human disease that exploits the unique genomic structure in recently admixed populations. To use existing published panels of ancestry-informative markers (AIMs) for admixture mapping, markers have to be genotyped <it>de novo </it>for each admixed study sample and samples representing the ancestral parental populations. The increased availability of dense marker data on commercial chips has made it feasible to develop panels wherein the markers need not be predetermined.</p> <p>Results</p> <p>We developed two panels of AIMs (~2,000 markers each) based on the Affymetrix Genome-Wide Human SNP Array 6.0 for admixture mapping with African American samples. These two AIM panels had good map power that was higher than that of a denser panel of ~20,000 random markers as well as other published panels of AIMs. As a test case, we applied the panels in an admixture mapping study of hypertension in African Americans in the Washington, D.C. metropolitan area.</p> <p>Conclusions</p> <p>Developing marker panels for admixture mapping from existing genome-wide genotype data offers two major advantages: (1) no <it>de novo </it>genotyping needs to be done, thereby saving costs, and (2) markers can be filtered for various quality measures and replacement markers (to minimize gaps) can be selected at no additional cost. Panels of carefully selected AIMs have two major advantages over panels of random markers: (1) the map power from sparser panels of AIMs is higher than that of ~10-fold denser panels of random markers, and (2) clusters can be labeled based on information from the parental populations. With current technology, chip-based genome-wide genotyping is less expensive than genotyping ~20,000 random markers. The major advantage of using random markers is the absence of ascertainment effects resulting from the process of selecting markers. The ability to develop marker panels informative for ancestry from SNP chip genotype data provides a fresh opportunity to conduct admixture mapping for disease genes in admixed populations when genome-wide association data exist or are planned.</p

Urinary and Dietary Analysis of 18,470 Bangladeshis Reveal a Correlation of Rice Consumption with Arsenic Exposure and Toxicity

Background: We utilized data from the Health Effects of Arsenic Longitudinal Study (HEALS) in Araihazar, Bangladesh, to evaluate the association of steamed rice consumption with urinary total arsenic concentration and arsenical skin lesions in the overall study cohort (N=18,470) and in a subset with available urinary arsenic metabolite data (N=4,517). Methods: General linear models with standardized beta coefficients were used to estimate associations between steamed rice consumption and urinary total arsenic concentration and urinary arsenic metabolites. Logistic regression models were used to estimate prevalence odds ratios (ORs) and their 95% confidence intervals (CIs) for the associations between rice intake and prevalent skin lesions at baseline. Discrete time hazard models were used to estimate discrete time (HRs) ratios and their 95% CIs for the associations between rice intake and incident skin lesions. Results: Steamed rice consumption was positively associated with creatinine-adjusted urinary total arsenic (β=0.041, 95% CI: 0.032-0.051) and urinary total arsenic with statistical adjustment for creatinine in the model (β=0.043, 95% CI: 0.032-0.053). Additionally, we observed a significant trend in skin lesion prevalence (P-trend=0.007) and a moderate trend in skin lesion incidence (P-trend=0.07) associated with increased intake of steamed rice. Conclusions: This study suggests that rice intake may be a source of arsenic exposure beyond drinking water

The European Nucleotide Archive

The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) is Europe’s primary nucleotide-sequence repository. The ENA consists of three main databases: the Sequence Read Archive (SRA), the Trace Archive and EMBL-Bank. The objective of ENA is to support and promote the use of nucleotide sequencing as an experimental research platform by providing data submission, archive, search and download services. In this article, we outline these services and describe major changes and improvements introduced during 2010. These include extended EMBL-Bank and SRA-data submission services, extended ENA Browser functionality, support for submitting data to the European Genome-phenome Archive (EGA) through SRA, and the launch of a new sequence similarity search service

Deep tubewell microbial water quality and access in arsenic mitigation programs in rural Bangladesh

The objective of this paper is to determine whether deep tubewells installed through arsenic mitigation efforts in rural Bangladesh provide better drinking water microbial quality compared to shallow tubewells. We conducted a stratified random cross-sectional survey of 484 households to assess microbial contamination of deep tubewell water at source and at point of use (POU) compared to shallow tubewell water using the Compartment Bag Test. In addition, we measured storage time, distance, travel time and ownership status among both sets of users to assess deep tubewell efficacy and under what conditions they offer poorer or better water quality. Differences in tubewell characteristics were compared using non-parametric Mann-Whitney U tests and two-proportion Z-tests. Prevalence ratios of microbial contamination stratified by water quality, storage time and distance to tubewells and ownership were estimated using unadjusted Mantel-Haenszel tests. There was no significant difference in microbial contamination between shallow and deep tubewells at source. The presence of POU water microbial contamination in storage containers in deep tubewell households was 1.11 times the prevalence in shallow tubewell storage containers (95% CI = 0.97–1.27). Deep tubewell users stored water longer and walked significantly farther to obtain water compared to shallow tubewell users. Among deep tubewell households, those residing farther away from the source were 1.24 times as likely to drink contaminated water from storage containers compared to those located nearby (95% CI = 1.04–1.48). Our findings suggest that deep tubewells have comparable water quality to shallow tubewells at source, but increasing distance from the household exacerbates risk of microbial contamination at POU

Land subsidence hazard in iran revealed by country-scale analysis of sentinel-1 insar

Many areas across Iran are subject to land subsidence, a sign of exceeding stress due to the over-extraction of groundwater during the past decades. This paper uses a huge dataset of Sentinel-1, acquired since 2014 in 66 image frames of 250×250km, to identify and monitor land subsidence across Iran. Using a two-step time series analysis, we first identify subsidence zones at a medium scale of 100m across the country. For the first time, our results provide a comprehensive nationwide map of subsidence in Iran and recognize its spatial distribution and magnitude. Then, in the second step of analysis, we quantify the deformation time series at the highest possible resolution to study its impact on civil infrastructure. The results spots the hazard posed by land subsidence to different infrastructure. Examples of road and railways affected by land subsidence hazard in Tehran and Mashhad, two of the most populated cities in Iran, are presented in this study

Compositional analysis of chalcopyrite using calibration-free laser-induced breakdown spectroscopy

Thisarticlepresentselementalanalysisofaneconomicallyimportantmineral(chalcopyrite) oflocalorigin. Calibration-freelaser-inducedbreakdownspectroscopy(CF-LIBS)methodologybased on the assumption of optically thin plasma and local thermodynamic equilibrium was employed for quantitative analysis. Plasma on the surface of the chalcopyrite target was generated by an Nd:YAG laser beam of wavelength 532 nm, pulse width 5 ns, and operated at repetition rate of 10 Hz. A LIBS2000+ detection system, comprised of five spectrometers, covering the spectral range from 200–720 nm, was used to record the signal of the optical emission from the chalcopyrite plasma. Recorded optical spectrum revealed the presence of Cu and Fe as the major elements while Ca and Na were recognized as the minor elements in the target sample. Quantitative analysis has shown that the relative concentrations of Cu, Fe, and Ca in the sample under study were 58.9%, 40.2%, and 0.9% by weight respectively. However, Na was not quantified due to the unavailability of suitable spectral lines, required for CF-LIBS analysis. Results obtained by CF-LIBS were validated by X-ray fluorescence (XRF) analysis, which showed the presence of five compositional elements viz. Cu, Fe, Si, Se and Ag with weight percentages of 58.1%, 35.4%, 5.7%, 0.7%, and 0.1% respectively. These results endorse the effectiveness of the CF-LIBS technique for quantitative analysis of major elements, however, its usefulness in case of minor and trace elements needs further improvement