Your data is here [![enter image description here][1]][1] . This is a cumulative series which wll have false autocorrleation due to the accumulation. The correct thing to do is to analyze the observed daily series which is here [![enter image description here][2]][2] which has a level shift , five pulses and an an model (1,0,0) . 

The Actual/Fit and Forecast for the observed series is here[![enter image description here][3]][3] with forecasts here [![enter image description here][4]][4]

Now to forecast the cumulative simply take your last value and sequentially add each forecasted value.

The cumulative series is a derived series ( by addition) and will not provide the clarity that you need.

What you are doing is a typical mistake of transforming the observations i.e.filtering them and then trying to create a model for the artificially summed series. 

Hope this helps you and others .


Build an ARIMA model like this one [![enter image description here][5]][5]


  [1]: https://i.sstatic.net/dP060.png
  [2]: https://i.sstatic.net/W8pH6.png
  [3]: https://i.sstatic.net/r5VN0.png
  [4]: https://i.sstatic.net/Ys6to.png
  [5]: https://i.sstatic.net/SzSWJ.png