Antimalarial Drugs for Pediatrics - Prescribing and Dispensing Practices in a Tanzanian City

Purpose: To assess dispensing and prescribing practices with regard to antimalarial drugs for pediatrics in private pharmacies and public hospitals in Dar es Salaam, Tanzania.Methods: This was a cross-sectional, descriptive study that assessed the knowledge and practice of 200 drug dispensers in the private community pharmacies in Dar es Salaam. Two hundred (200) parents of children seeking malaria treatment were also interviewed at the public hospitals.Results: A majority of drug dispensers had moderate (63.3 %) to low knowledge (36.7 %) regarding antimalarial drug use in pediatrics. Parents had moderate (67 %) to low (33 %) level of understanding of the instructions given to them by the prescribers regarding administration of antimalarial drugs to pediatrics at home. Most children were not weighed, and there were indications of wrong calculations of doses of antimalarials in pediatrics.Conclusion: Overall, there were irrational dispensing and prescribing of antimalarial drugs to pediatrics. Since malaria is a major killer disease in Tanzania, especially in children under five years of age, there is a need to institute measures to ensure rational prescribing, dispensing and use of antimalarial drugs in pediatrics.Keywords: Antimalarials, Dispensing, Knowledge, Pediatrics, Pharmacies, Prescribin

The pattern of infections among under-fives: a call for actions

INTRODUCTION Infectious diseases are by far the most frustrating challenges in the health systems of most tropical nations. Unlike other challenges, infections have their causes known and solutions at hand. Paediatric world is the most important victim of infectious ailments. Various models, interventions for reduction/elimination of infectious diseases have been put forth but the strategies (in most tropical nations) have not bore the anticipated fruits. OBJECTIVES To assess the pattern of infections and its association with nutritional status among under-five years population of Dodoma in August – September 2007. METHODOLOGY A descriptive, cross-sectional community based study was done at Makulu ward of Dodoma district involving 396 under five year population derived from 322 different families. Data was collected using a standard structured questionnaire and analysed using epi-info 6 software. RESULTS Among 396 children studied, 52.3% were females. Maximum representation was found in the age range of 12-23 months (mode at age of 14.0 months). More than half (50.8%) of all children surveyed were found to have fever (at the time of the survey) and 58.8% were reported to have had fever within a period of 1 month prior to conduction of the study. Among children with fever, 52.3% had a normal weight to age ratio. More than 90% of surveyed children were reported to have been weaned before 6 months of age. CONCLUSION The prevalence of fever was found to be high (reflecting infectious nature) in this study. RECOMMENDATIONS More analytical studies are needed in this area to explain for the nature and causes of fever in this age group at Makulu ward

Cluster-Seeking James-Stein Estimators

This paper considers the problem of estimating a high-dimensional vector of parameters $\boldsymbol{\theta} \in \mathbb{R}^n$ from a noisy observation. The noise vector is i.i.d. Gaussian with known variance. For a squared-error loss function, the James-Stein (JS) estimator is known to dominate the simple maximum-likelihood (ML) estimator when the dimension $n$ exceeds two. The JS-estimator shrinks the observed vector towards the origin, and the risk reduction over the ML-estimator is greatest for $\boldsymbol{\theta}$ that lie close to the origin. JS-estimators can be generalized to shrink the data towards any target subspace. Such estimators also dominate the ML-estimator, but the risk reduction is significant only when $\boldsymbol{\theta}$ lies close to the subspace. This leads to the question: in the absence of prior information about $\boldsymbol{\theta}$, how do we design estimators that give significant risk reduction over the ML-estimator for a wide range of $\boldsymbol{\theta}$? In this paper, we propose shrinkage estimators that attempt to infer the structure of $\boldsymbol{\theta}$ from the observed data in order to construct a good attracting subspace. In particular, the components of the observed vector are separated into clusters, and the elements in each cluster shrunk towards a common attractor. The number of clusters and the attractor for each cluster are determined from the observed vector. We provide concentration results for the squared-error loss and convergence results for the risk of the proposed estimators. The results show that the estimators give significant risk reduction over the ML-estimator for a wide range of $\boldsymbol{\theta}$, particularly for large $n$. Simulation results are provided to support the theoretical claims.Marie Curie Career Integration Grant; 10.13039/501100004815-Early Career Grant from the Isaac Newton Trus

Empirical Bayes Estimators for Sparse Sequences.

The problem of estimating a high-dimensional sparse vector θ ∈ ℝ n from an observation in i.i.d. Gaussian noise is considered. An empirical Bayes shrinkage estimator, derived using a Bernoulli-Gaussian prior, is analyzed and compared with the well-known soft-thresholding estimator using squared-error loss as a measure of performance. We obtain concentration inequalities for the Stein's unbiased risk estimate and the loss function of both estimators. Depending on the underlying θ, either the proposed empirical Bayes (eBayes) estimator or soft-thresholding may have smaller loss. We consider a hybrid estimator that attempts to pick the better of the soft-thresholding estimator and the eBayes estimator by comparing their risk estimates. It is shown that: i) the loss of the hybrid estimator concentrates on the minimum of the losses of the two competing estimators, and ii) the risk of the hybrid estimator is within order 1/√n of the minimum of the two risks. Simulation results are provided to support the theoretical results

Study for Design of Magneto Rheological Damper

Semi-active isolation system have received attention over the active and passive isolation system for vibration, mitigation of vibration in industrial application is the essential development. Magneto rheological damper quick response to sudden maneuvers with less power consumption leads to many research and design of MR damper for different design parameters and variable current input, in this present work designed a MR damper with all the requisite design parameter information compiled from earlier work., number of coils required to generate the effective magnetic flux field has been calculated to design the magneto rheological damper and to arrive maximum magnetic flux density vs dc current with proper proportion percentage of ferrite particles in MR fluid which further leads to calculate shear stress and damper force can produce by the designed MR damper at variable current input

Implementation of MAD and Mean Absolute Deviation based Smoothing Algorithm for Displacement Data in Digital Image Correlation Technique

This study aims at obtaining smoothed strain fields from digital image correlation technique (DIC), by smoothing the displacement fields prior to strain computation. Both median absolute deviation (MAD) and mean absolute deviation based smoothing algorithms are implemented for data smoothing. On implementation of these algorithms, the noise levels in the strain fields are found to be reduced to a greater extent. For executing the whole field smoothing algorithm, an accurate boundary encoding algorithm is also developed

Material Characterization of Carbon Fiber Reinforced Polymer Laminate Using Virtual Fields Method

Material Characterization of Carbon Fiber Reinforced Polymer Laminate Using Virtual Fields Metho

Fetal growth in low-risk Indian population at a tertiary centre and its comparison with INTERGROWTH-21 standards: a prospective cohort study

Background: The objective of this study was to compare the fetal growth pattern in low risk Indian population with the INTERGROWTH-21 standards.Methods: Low risk women were enrolled at 10 to 20 weeks of gestation and followed up until delivery. An experienced operator performed abdominal ultrasound every 5±1 week and measured biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC) and femur length (FL) of the fetus. Newborn anthropometric measurements were taken within 12 hours of childbirth.Results: A total of 126 healthy women, enrolled at mean gestation of 16.8±1.6 weeks, completed the follow up until delivery. None of the participants developed any major obstetric or medical morbidity. The study subjects showed lower mean z scores for BPD (-0.7±1.3), HC (-0.4±1.3) and AC (-0.4±1.3) but a higher mean z-score for FL (0.3±1.7) as compared to INTERGROWTH-21 standards. From 1st through 5th visit, the z scores for BPD and HC improved whereas declined for AC and FL.Conclusions: The fetal growth in non-affluent healthy Indian women had a lower fetal growth compared to INTERGROWTH-21 standards