%0 Journal Article %A Anwar, Mohammad %A Lewnard, Joseph %A Parikh, Sunil %A Pitzer, Virginia %D 2016 %T MOESM8 of Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence %U https://springernature.figshare.com/articles/journal_contribution/MOESM8_of_Time_series_analysis_of_malaria_in_Afghanistan_using_ARIMA_models_to_predict_future_trends_in_incidence/4415480 %R 10.6084/m9.figshare.c.3628256_D7.v1 %2 https://ndownloader.figshare.com/files/7141898 %K Malaria %K Prediction %K Afghanistan %K Environment %K Autoregressive model %X Additional file 8: Annex 3. Approximate estimation of malaria suspects expected up to December 2016, based on Model 2 with 2-Lag Vegetation. This estimate may be taken with following considerations: 1- Assuming linear trend of malaria stays the same as the Model predict. 2- Incidences not reported to the system remain small or negligible. The numbers calculated are incidence rate per 10 000 of service users in the country %I figshare