Time series analysis of malaria in pregnancy using Wavelet transform and ARIMA models: Preprocessed Dataset

The processed dataset was cleaned for outliers, missing values handled using Kalman smoothen imputation and formatted into structured time-series entries of original data collected from Nigerian Malaria Data Repository (NMDR). It was used in the work to i) examine the variability of monthly Malaria confirmed pregnant women cases (dataMIP) and the general confirmed uncomplicated malaria cases (datam) across Nigeria 6 geopolitical zones, ii) evaluate temporal trends, leading to the short-term forecast of MIP incidence. The monthly periods per location (yearSORT, LGAsort) of each State for each region are also included in the data. This dataset was derived from third-party data under institutional agreement. The dataset has been anonymized and made publicly available in accordance with institutional and ethical guidelines. All identifying information has been transformed to ensure anonymity.This dataset is shared under a CC BY-NC 4.0 license. Reuse must cite the original source and comply with ethical standards. The data has been anonymized and processed to protect confidentiality. Commercial use is not permitted.State-level identifiers (e.g., Cross, Niger) were retained to support regional analysis. These are broad geographic references and do not contain facility-level or individual-level data. LGAs were numerically coded, and no mapping schema has been shared.The dataset reflects aggregated, anonymized trends at the state and LGA level. It does not include facility names, GPS coordinates, or any data that could reasonably be used to identify individuals or institutions. Data use complies with ethical and institutional guidelines.