Optimizing community case management strategies to achieve equitable reduction of childhood pneumonia mortality:An application of Equitable Impact Sensitive Tool (EQUIST) in five low- and middle-income countries

BACKGROUND: The aim of this study was to populate the Equitable Impact Sensitive Tool (EQUIST) framework with all necessary data and conduct the first implementation of EQUIST in studying cost–effectiveness of community case management of childhood pneumonia in 5 low– and middle–income countries with relation to equity impact. METHODS: Wealth quintile–specific data were gathered or modelled for all contributory determinants of the EQUIST framework, namely: under–five mortality rate, cost of intervention, intervention effectiveness, current coverage of intervention and relative disease distribution. These were then combined statistically to calculate the final outcome of the EQUIST model for community case management of childhood pneumonia: US$ per life saved, in several different approaches to scaling–up. RESULTS: The current ‘mainstream’ approach to scaling–up of interventions is never the most cost–effective. Community–case management appears to strongly support an ‘equity–promoting’ approach to scaling–up, displaying the highest levels of cost–effectiveness in interventions targeted at the poorest quintile of each study country, although absolute cost differences vary by context. CONCLUSIONS: The relationship between cost–effectiveness and equity impact is complex, with many determinants to consider. One important way to increase intervention cost–effectiveness in poorer quintiles is to improve the efficiency and quality of delivery. More data are needed in all areas to increase the accuracy of EQUIST–based estimates

Computer aided data acquisition tool for high-throughput phenotyping of plant populations

<p>Abstract</p> <p>Background</p> <p>The data generated during a course of a biological experiment/study can be sometimes be massive and its management becomes quite critical for the success of the investigation undertaken. The accumulation and analysis of such large datasets often becomes tedious for biologists and lab technicians. Most of the current phenotype data acquisition management systems do not cater to the specialized needs of large-scale data analysis. The successful application of genomic tools/strategies to introduce desired traits in plants requires extensive and precise phenotyping of plant populations or gene bank material, thus necessitating an efficient data acquisition system.</p> <p>Results</p> <p>Here we describe newly developed software "<b>PHENOME" </b>for high-throughput phenotyping, which allows researchers to accumulate, categorize, and manage large volume of phenotypic data. In this study, a large number of individual tomato plants were phenotyped with the "PHENOME" application using a Personal Digital Assistant (PDA) with built-in barcode scanner in concert with customized database specific for handling large populations.</p> <p>Conclusion</p> <p>The phenotyping of large population of plants both in the laboratory and in the field is very efficiently managed using PDA. The data is transferred to a specialized database(s) where it can be further analyzed and catalogued. The "PHENOME" aids collection and analysis of data obtained in large-scale mutagenesis, assessing quantitative trait loci (QTLs), raising mapping population, sampling of several individuals in one or more ecological niches etc.</p

NEATTILL: A simplified procedure for nucleic acid extraction from arrayed tissue for TILLING and other high-throughput reverse genetic applications

<p>Abstract</p> <p>Background</p> <p>TILLING (Targeting Induced Local Lesions in Genomes) is a reverse genetics procedure for identifying point mutations in selected gene(s) amplified from a mutagenized population using high-throughput detection platforms such as slab gel electrophoresis, capillary electrophoresis or dHPLC. One essential pre-requisite for TILLING is genomic DNA isolation from a large population for PCR amplification of selected target genes. It also requires multiplexing of genomic DNA isolated from different individuals (pooling) in typically 8-fold pools, for mutation scanning, and to minimize the number of PCR amplifications, which is a strenuous and long-drawn-out work. We describe here a simplified procedure of multiplexing, NEATTILL (Nucleic acid Extraction from Arrayed Tissue for TILLING), which is rapid and equally efficient in assisting mutation detection.</p> <p>Results</p> <p>The NEATTILL procedure was evaluated for the tomato TILLING platform and was found to be simpler and more efficient than previously available methods. The procedure consisted of pooling tissue samples, instead of nucleic acid, from individual plants in 96-well plates, followed by DNA isolation from the arrayed samples by a novel protocol. The three variants of the NEATTILL procedure (<it>vast, in-depth </it>and <it>intermediate</it>) can be applied across various genomes depending upon the population size of the TILLING platform. The 2-D pooling ensures the precise confirmation of the coordinates of the positive mutant line while scanning complementary plates. Choice of tissue for arraying and nucleic acid isolation is discussed in detail with reference to tomato.</p> <p>Conclusion</p> <p>NEATTILL is a convenient procedure that can be applied to all organisms, the genomes of which have been mutagenized and are being scanned for multiple alleles of various genes by TILLING for understanding gene-to-phenotype relationships. It is a time-saving, less labour intensive and reasonably cost-effective method. Tissue arraying can cut costs by up to 90% and minimizes the risk of exposing the DNA to nucleases. Before arraying, different tissues should be evaluated for DNA quality, as the case study in tomato showed that cotyledons rather than leaves are better suited for DNA isolation. The protocol described here for nucleic acid isolation can be generally adapted for large-scale projects such as insertional mutagenesis, transgenic confirmation, mapping and fingerprinting which require isolation of DNA from large populations.</p

A Prospective Three-Year Cohort Study of the Epidemiology and Virology of Acute Respiratory Infections of Children in Rural India

Acute respiratory infection (ARI) is a major killer of children in developing countries. Although the frequency of ARI is similar in both developed and developing countries, mortality due to ARI is 10-50 times higher in developing countries. Viruses are common causes of ARI among such children, yet the disease burden of these infections in rural communities is unknown.A prospective longitudinal study was carried out in children enrolled from two rural Indian villages at birth and followed weekly for the development of ARI, classified as upper respiratory infection, acute lower respiratory infection (ALRI), or severe ALRI. Respiratory syncytial virus (RSV), influenza, parainfluenza viruses and adenoviruses in nasopharyngeal aspirates were detected by direct fluorescent antibody testing (DFA) and, in addition, centrifugation enhanced culture for RSV was done. 281 infants enrolled in 39 months and followed until 42 months. During 440 child years of follow-up there were 1307 ARIs, including 236 ALRIs and 19 severe ALRIs. Virus specific incidence rates per 1000 child years for RSV were total ARI 234, ALRI 39, and severe ALRI 9; for influenza A total ARI 141, ALRI 39; for INF B total ARI 37; for PIV1 total ARI 23, for PIV2 total ARI 28, ALRI 5; for parainfluenza virus 3 total ARI 229, ALRI 48, and severe ALRI 5 and for adenovirus total ARI 18, ALRI 5. Repeat infections with RSV were seen in 18 children.RSV, influenza A and parainfluenza virus 3 were important causes of ARI among children in rural communities in India. These data will be useful for vaccine design, development and implementation purposes