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BackgroundKnowledge of urogenital schistosomiasis can empower individuals to limit surface water contact and participate in mass drug administration campaigns, but nothing is currently known about the schistosomiasis knowledge that schoolchildren have in Ghana. We developed and implemented a survey tool aiming to assess the knowledge of urogenital schistosomiasis (treatment, transmission, prevention, symptoms) among science teaches and primary and junior high school students in the Eastern Region of Ghana.MethodsWe developed a 22-question knowledge survey tool and administered it to 875 primary and 938 junior high school students from 74 schools in 37 communities in the Eastern Region of Ghana. Teachers (n = 57) answered 20 questions matched to student questions. We compared knowledge scores (as percent of correct answers) across topics, gender, and class year and assessed associations with teacher's knowledge scores using t-tests, chi-squared tests, univariate, and multivariate linear regression, respectively.ResultsStudents performed best when asked about symptoms (mean±SD: 76±21% correct) and prevention (mean±SD: 69±25% correct) compared with transmission (mean±SD: 50±15% correct) and treatment (mean±SD: 44±23% correct) (pConclusionsOur survey parsed four components of student and teacher knowledge. We found strong knowledge in several realms, as well as knowledge gaps, especially on transmission and treatment. Addressing relevant gaps among students and science teachers in UGS-endemic areas may help high-risk groups recognize risky water contact activities, improve participation in mass drug administration, and spark interest in science by making it practical.

Despite availability of high quality medical records, health care systems often do not have the resources or tools to utilize these data efficiently. Yet, hospital-based, laboratory-confirmed records may pave the way for building reliable surveillance systems capable of monitoring temporal trends of emerging infections. In this communication, we present a new tool to compress and visualize medical records with a local population profile (LPP) approach, which transforms information into statistically comparable patterns. We provide a step-by-step tutorial on how to build, interpret, and expand the use of LPP using hospitalization records of laboratory-confirmed cholera. We abstracted case information from the databases maintained by the Department of Clinical Microbiology at Christian Medical College in Vellore, India. We used a single-year age distribution to construct LPPs for O1, O139, and non O1/O139 serotypes of Vibrio cholerae. Disease counts and hospitalization rates were converted into fitted kernel-based probability densities. We formally compared LPPs with the Kolmogorov-Smirnov test, and created multi-panel visuals to depict temporal trend, age distribution, and hospitalization rates simultaneously. Our first implementation of LPPs revealed information that is typically gathered from surveillance systems such as: i) estimates of the demographic distribution of diseases and identification of a population at risk, ii) changes in the dominant pathogen presence; and iii) trends in disease occurrence. The LPP demonstrated the benefit of increased resolution in pattern detection of disease for different Vibrio cholerae serotypes and two demographic categories by showing patterns and anomalies that would be obscured by traditional methods of analysis and visualization. LPP can be used effectively to compile basic patient information such as age, sex, diagnosis, location, and time into compact visuals. Future development of the proposed approach will allow public health researchers and practitioners to broadly utilize and efficiently compress large volumes of medical records without loss of information.

Stunting or reduced linear growth is very prevalent in low-income countries. Recent studies have demonstrated a causal relationship between alterations in the gut microbiome and moderate or severe acute malnutrition in children in these countries. However, there have been no primary longitudinal studies comparing the intestinal microbiota of persistently stunted children to that of non-stunted children in the same community. In this pilot study, we characterized gut microbial community composition and diversity of the fecal microbiota of 10 children with low birth weight and persistent stunting (cases) and 10 children with normal birth weight and no stunting (controls) from a birth cohort every 3 months up to 2 years of age in a slum community in south India. There was an increase in diversity indices (P

Antibiotic pressure contributes to rising antibiotic resistance. Policy guidelines encourage rational prescribing behavior, but effectiveness in containing antibiotic use needs further assessment. This study therefore assessed the patterns of antibiotic use over a decade and analyzed the impact of different modes of guideline development and dissemination on inpatient antibiotic use.Antibiotic use was calculated monthly as defined daily doses (DDD) per 100 bed days for nine antibiotic groups and overall. This time series compared trends in antibiotic use in five adjacent time periods identified as 'Segments,' divided based on differing modes of guideline development and implementation: Segment 1--Baseline prior to antibiotic guidelines development; Segment 2--During preparation of guidelines and booklet dissemination; Segment 3--Dormant period with no guidelines dissemination; Segment 4--Booklet dissemination of revised guidelines; Segment 5--Booklet dissemination of revised guidelines with intranet access. Regression analysis adapted for segmented time series and adjusted for seasonality assessed changes in antibiotic use trend.Overall antibiotic use increased at a monthly rate of 0.95 (SE = 0.18), 0.21 (SE = 0.08) and 0.31 (SE = 0.06) for Segments 1, 2 and 3, stabilized in Segment 4 (0.05; SE = 0.10) and declined in Segment 5 (-0.37; SE = 0.11). Segments 1, 2 and 4 exhibited seasonal fluctuations. Pairwise segmented regression adjusted for seasonality revealed a significant drop in monthly antibiotic use of 0.401 (SE = 0.089; p

We outline a framework for evaluating food- and water-borne surveillance systems using hospitalization records, and demonstrate the approach using data on salmonellosis, campylobacteriosis and giardiasis in persons aged ≥65 years in Massachusetts. For each infection, and for each reporting jurisdiction, we generated smoothed standardized morbidity ratios (SMR) and surveillance to hospitalization ratios (SHR) by comparing observed surveillance counts with expected values or the number of hospitalized cases, respectively. We examined the spatial distribution of SHR and related this to the mean for the entire state. Through this approach municipalities that deviated from the typical experience were identified and suspected of under-reporting. Regression analysis revealed that SHR was a significant predictor of SMR, after adjusting for population age-structure. This confirms that the spatial "signal" depicted by surveillance is in part influenced by inconsistent testing and reporting practices since municipalities that reported fewer cases relative to the number of hospitalizations had a lower relative risk (as estimated by SMR). Periodic assessment of SHR has potential in assessing the performance of surveillance systems.

The absence or deficiency of melanin as in albinos, has detrimental effects on retinal development that include aberrant axonal projections from eye to brain and impaired vision. In pigmented retinal pigment epithelium (RPE), dihydroxyphenalanine (L-Dopa), an intermediate in the synthetic path for melanin, has been hypothesized to regulate the tempo of neurogenesis. The time course of expression of retinal L-Dopa, whether it is harbored exclusively in the RPE, the extent of deficiency in albinos compared to isogenic controls, and whether L-Dopa can be restored if exogenously delivered to the albino have been unknown.L-Dopa and catecholamines including dopamine extracted from retinas of pigmented (C57BL/6J) and congenic albino (C57BL/6J-tyr(c2j) ) mice, were measured throughout development beginning at E10.5 and at maturity. L-Dopa, but not dopamine nor any other catecholamine, appears in pigmented retina as soon as tyrosinase is expressed in RPE at E10.5. In pigmented retina, L-Dopa content increases throughout pre- and postnatal development until the end of the first postnatal month after which it declines sharply. This time course reflects the onset and completion of retinal development. L-Dopa is absent from embryonic albino retina and is greatly reduced in postnatal albino retina compared to pigmented retina. Dopamine is undetectable in both albino and pigmented retinas until after the postnatal expression of the neuronal enzyme tyrosine hydroxylase. If provided to pregnant albino mothers, L-Dopa accumulates in the RPE of the fetuses.L-Dopa in pigmented RPE is most abundant during development after which content declines. This L-Dopa is not converted to dopamine. L-Dopa is absent or at low levels in albino retina and can be restored to the RPE by administration in utero. These findings further implicate L-Dopa as a factor in the RPE that could influence development, and demonstrate that administration of L-Dopa could be a means to rescue developmental abnormalities characteristic of albinos.

Understanding the temporal patterns in disease occurrence is valuable for formulating effective disease preventive programs. Cohort studies present a unique opportunity to explore complex interactions associated with emergence of seasonal patterns of infectious diseases.We used data from 452 children participating in a birth cohort study to assess the seasonal patterns of rotavirus diarrhea by creating a weekly time series of rotavirus incidence and fitting a Poisson harmonic regression with biannual peaks. Age and cohort effects were adjusted for by including the weekly counts of number of children in the study and the median age of cohort in a given week. Weekly average temperature, humidity and an interaction term to reflect the joint effect of temperature and humidity were included to consider the effects of meteorological variables.In the overall rotavirus time series, two significant peaks within a single year were observed--one in winter and the other in summer. The effect of age was found to be the most significant contributor for rotavirus incidence, showing a strong negative association. Seasonality remained a significant factor, even after adjusting for meteorological parameters, and the age and cohort effects.The methodology for assessing seasonality in cohort studies is not yet developed. This is the first attempt to explore seasonal patterns in a cohort study with a dynamic denominator and rapidly changing immune response on individual and group levels, and provides a highly promising approach for a better understanding of the seasonal patterns of infectious diseases, tracking emergence of pathogenic strains and evaluating the efficacy of intervention programs.

Rotavirus infection causes a significant proportion of diarrhea in infants and young children worldwide leading to dehydration, hospitalization, and in some cases death. Rotavirus infection represents a significant burden of disease in developing countries, such as those in South Asia.We conducted a meta-analysis to examine how patterns of rotavirus infection relate to temperature and precipitation in South Asia. Monthly rotavirus data were abstracted from 39 published epidemiological studies and related to monthly aggregated ambient temperature and cumulative precipitation for each study location using linear mixed-effects models. We also considered associations with vegetation index, gathered from remote sensing data. Finally, we assessed whether the relationship varied in tropical climates and humid mid-latitude climates.Overall, as well as in tropical and humid mid-latitude climates, low temperature and precipitation levels are significant predictors of an increased rate of rotaviral diarrhea. A 1°C decrease in monthly ambient temperature and a decrease of 10 mm in precipitation are associated with 1.3% and 0.3% increase above the annual level in rotavirus infections, respectively. When assessing lagged relationships, temperature and precipitation in the previous month remained significant predictors and the association with temperature was stronger in the tropical climate. The same association was seen for vegetation index; a seasonal decline of 0.1 units results in a 3.8% increase in rate of rotavirus.In South Asia the highest rate of rotavirus was seen in the colder, drier months. Meteorological characteristics can be used to better focus and target public health prevention programs.

Visual analytics, a technique aiding data analysis and decision making, is a novel tool that allows for a better understanding of the context of complex systems. Public health professionals can greatly benefit from this technique since context is integral in disease monitoring and biosurveillance. We propose a graphical tool that can reveal the distribution of an outcome by time and age simultaneously.We introduce and demonstrate multi-panel (MP) graphs applied in four different settings: U.S. national influenza-associated and salmonellosis-associated hospitalizations among the older adult population (≥65 years old), 1991-2004; confirmed salmonellosis cases reported to the Massachusetts Department of Public Health for the general population, 2004-2005; and asthma-associated hospital visits for children aged 0-18 at Milwaukee Children's Hospital of Wisconsin, 1997-2006. We illustrate trends and anomalies that otherwise would be obscured by traditional visualization techniques such as case pyramids and time-series plots.MP graphs can weave together two vital dynamics--temporality and demographics--that play important roles in the distribution and spread of diseases, making these graphs a powerful tool for public health and disease biosurveillance efforts.

In temperate regions, influenza epidemics occur annually with the highest activity occurring during the winter months. While seasonal dynamics of the influenza virus, such as time of onset and circulating strains, are well documented by the Centers for Disease Control and Prevention Influenza Surveillance System, an accurate prediction of timing, magnitude, and composition of circulating strains of seasonal influenza remains elusive. To facilitate public health preparedness for seasonal influenza and to obtain better insights into the spatiotemporal behavior of emerging strains, it is important to develop measurable characteristics of seasonal oscillation and to quantify the relationships between those parameters on a spatial scale. The objectives of our research were to examine the seasonality of influenza on a national and state level as well as the relationship between peak timing and intensity of influenza in the United States older adult population.A total of 248,889 hospitalization records were extracted from the Centers for Medicare and Medicaid Services for the influenza seasons 1991-2004. Harmonic regression models were used to quantify the peak timing and absolute intensity for each of the 48 contiguous states and Washington, DC. We found that individual influenza seasons showed spatial synchrony with consistent late or early timing occurring across all 48 states during each influenza season in comparison to the overall average. On a national level, seasons that had an earlier peak also had higher rates of influenza (r(s) = -0.5). We demonstrated a spatial trend in peak timing of influenza; western states such as Nevada, Utah, and California peaked earlier and New England States such as Rhode Island, Maine, and New Hampshire peaked later.Our findings suggest that a systematic description of influenza seasonal patterns is a valuable tool for disease surveillance and can facilitate strategies for prevention of severe disease in the vulnerable, older adult population.