Novel Methods for Efficient Surveillance and Monitoring

Résumé du livre

The third paper presents Large Country-Lot Quality Assurance Sampling (LC-LQAS), a method to obtain information at the local level, with sufficient accuracy to aid program managers, while also providing central policy makers with the information they need. This is achieved by aggregating local LQAS data to provide regional or national level estimates via cluster sampling methodology. The method is exemplified with a program evaluation of the HAMSET project in Eritrea. The fourth and final paper addresses the biases inherent in estimators based on a convenience sample, which precludes the legitimate use of powerful inferential tools associated with a random sample. As an alternative to a full random sample to infer the values of an indicator for the whole population, we present an annealing methodology that combines a relatively small, and presumably less expensive, random sample with the convenience sample. Using this additional information allows us to not only take advantage of inferential tools, but also, by combining with information from the convenience sample, provides more accurate information than from just using data from the random sample alone.