Seasonality and Seasonal Decomposition Analysis of hMPV
We evaluated the number and incidence of weekly hMPV cases and hMPV-associated ALRI cases from 2011–2016. We used R’s23 (R Version 4.0.4) decompose (part of the stats package) and forecast package 24 to assess the temporal dynamics of hMPV cases and specifically isolate the trend, seasonal, and error components. Since the magnitude of the seasonal fluctuations and the variation around the trend-cycle do not vary proportionally with time, we used an additive time-series decomposition approach to isolate the temporal trend, seasonality, and error components. In additive decomposition we assume:
\(y\)t = St + Tt + Rt
Where \(y\)t is the data, St is the seasonal component, Tt is the trend component, and Rt is the remainder component.