B-SHADE Estimation and Sampling Manual

B-SHADE Theory

Sampling is a method to investigate and understand the population using a sample. It has been widely applied in various disciplines such as natural resources, environmental pollution, and public health. With the sample data collected, some parameters of the population (for example, mean and sum) is estimated using an appropriate model. Usually, a best and unbiased estimation is expected. However, if the samples were not carefully selected under the model's assumption, then the estimated result is biased from the population's real value. For example, when setting sentinels to estimate a disease's prevalence or incidence in a city, hospitals with good equipment and doctors are more likely to be selected by planners. Then the sentinels' average visitor number would be much higher than the real average visitor number of all hospitals. By considering the correlation between samples and their population, the B-SHADE (Biased Sentinel Hospital based Area Disease Estimation) model can generate an unbiased estimation of the population with biased samples. Although originally designed for biased sentinel hospitals' patient number/incidence estimation, it is a common method for biased samples’ population estimation.

Software Functionality

1. Pop estimation

(1) Menu bar

Wizard: including two main functions, Pop estimation and Samples selection.

Help: showing the manual, demo and about of the system.

(2) Data input area

Input the sample data and historical data, choose total or mean population to estimate.

(3) Result output area

Result is shown in a table, including Date, the estimated total (or mean) population and the variance. Export the result in CSV format.

2. Samples selection

(1) Data input area

Input historical data and the required number of sample stations.

Advanced options about the simulated anealing optimisation can be setted by click the "Options" buttun.

(2) Result output area

System displays the best sample combination in a grid.