Time series methods. Granger causality Wald testing was used to determine whether influenza A and B (combined), influenza A, and influenza B seasons can be used to forecast peaks in pneumococcal infections [20] . Originally, Granger methods were used in econometrics to evaluate the directionality of relationships between closely correlated time series; a causal exposure to an independent variable should be associated with a lagged change in the dependent variable, and this relationship should be absent when the temporal sequence of exposure and response is reversed. In other words, Granger ''causality'' can be used to postulate causality in linear prediction only if one thing happens before another, and not vice versa. It cannot be used to prove causation, but does provide important evidence that can support or refute causality.