Pilot Audit of Trichiasis Surgery Outcomes Using a Mobile App in the Republic of Chad.

Purpose: The purpose of the study was to assess the feasibility of a mobile data collection app for use in trichiasis surgical audits in the Melfi and Mangalme districts of the Guera region of the Republic of Chad and to perform a cost analysis to determine if the auditing mechanism could be implemented nationally.

Materials And Methods: Patients who underwent trichiasis surgery 6 months prior and who had follow-up 7-14 days after surgery were included in the study. Each surgeon had a sample of 20% of operated eyelids; nine surgeons with data for ≥20 eyelids were included.

Prevalence of trachoma in the Republic of Chad: results of 41 population-based surveys.

Purpose: To estimate the prevalence of trachoma in suspected-endemic areas of Chad, and thereby determine whether trachoma is a public health problem requiring intervention.

Methods: We divided the suspected-endemic population living in secure districts into 46 evaluation units (EUs), and used the standardized methodologies of the Global Trachoma Mapping Project. A two-stage cluster-sampling procedure was adopted.

A Population-Based Trachoma Prevalence Survey Covering Seven Districts of Sangha and Likouala Departments, Republic of the Congo.

Purpose: We set out to estimate the prevalence of trachoma and access to water and sanitation in seven suspected-trachoma-endemic districts of northern Congo, surveyed as a single evaluation unit.

Methods: From a complete list of rural villages in the seven districts, we systematically selected 22 with probability proportional to village size. In selected villages, we included all households where there were fewer than 25 in total, or used compact segment sampling to select a group of approximately 20 households by random draw.

Predicting organic loading in natural water using spectral fluorescent signatures.

Spectral fluorescent signature (SFS) is a rapid, reagent free and inexpensive technique, which has great potential for environmental monitoring of aqueous systems, especially for predicting dissolved organic carbon (DOC) along natural waters. This technical note aimed to examine the possibility to use SFS associated with partial least squares regression (PLS) to assess the organic loading in natural water. A model was built using samples of water collected between October 1999 and February 2002 on the Passaic River at Little Falls, NJ, USA.

Modified dissolved organic matter fractionation technique for natural water.

A technique to fractionate dissolved organic materials (DOMs) from low DOM water (<5mg/l) was developed by using triple columns of DAX-8 adsorption resin, one column of AG-MP-50 cationic resin, and another column of WA 10 weak anionic resin in sequence. The procedure was then applied to fractionate water samples obtained at various sampling locations throughout two surface water treatment plants (WTPs) in central New Jersey to study its effectiveness, DOM occurrence, and variation along treatment units. The treatment plants utilize different treatment methods, hence producing variability in DOM fractions suitable for examining the procedure's effectiveness.

Using principal component analysis to monitor spatial and temporal changes in water quality.

Chemical, biological and physical data monitored at 12 locations along the Passaic River, New Jersey, during the year 1998 are analyzed. Principal component analysis (PCA) was used: (i) to extract the factors associated with the hydrochemistry variability; (ii) to obtain the spatial and temporal changes in the water quality. Solute content, temperature, nutrients and organics were the main patterns extracted.

Comparison of spectral fluorescent signatures-based models to characterize DOM in treated water samples.

Statistical procedures enable a multivariate analysis of the measurements to identify specific characteristics of the dissolved organic matter (DOM) fractions in raw natural water, including the concentrations. In this work, three already established models were used to predict the concentrations of fractions of DOM from spectral fluorescent signatures (SFSs): a general linear regression (GLR), loadings and scores of a principal components analysis (PCA), and a partial least squares regression (PLS). Details about the method undertaken to prepare the fractions were given.

Spectral fluorescence signatures and partial least squares regression: model to predict dissolved organic carbon in water.

Spectro-fluorescence signature (SFS) of water samples contains information that may be used to quantify dissolved organic carbon (DOC) if combined with multivariate analyses. A model was built through SFS and partial least squared (PLS) regression. The SFSs of 219 samples of natural water along the Raritan River and Millstone River watersheds located in central New Jersey, and their corresponding DOC concentrations were used to build the model.