Cross Walking

Leveraging Low-Quality Data

Facility data is the most abundant source of information about malaria, but since it is collected passively, it is not representative of the whole population. It can be useful for malaria policy if we understand and can quantify the biases.

The statistics we would like to have include the prevalence of infection in a well-designed cross-sectional blood survey. Such data are collected routinely as part of many studies, and they are among the most abundant research data, but the data are far too sparse to be used to manage malaria.

Cross-walking is an attempt to rigorously quantify the biases in clinical data through statistical modeling. We let \(X\) denote the prevalence of malaria in a population, and we \(Y\) the test positivity rate.