Big Data Analytics Framework for Childhood Infectious Disease Surveillance and Response System using Modified MapReduce Algorithm

Tanzania, like most East African countries, faces a great burden from the spread of preventable infectious childhood diseases. Diarrhea, acute respiratory infections (ARI), pneumonia, malnutrition, hepatitis, and measles are responsible for the majority of deaths amongst children aged 0-5 years. Infectious disease surveillance and response is the foundation of public healthcare practices, and it is increasingly being undertaken using information technology. Tanzania however, due to challenges in information technology infrastructure and public health resources, still relies on paper-based disease surveillance. Thus, only traditional clinical patient data is used. Nontraditional and pre-diagnostic infectious disease report case data are excluded. In this paper, the development of the Big Data Analytics Framework for Childhood Infectious Disease Surveillance and Response System is presented. The framework was designed to guide healthcare professionals to track, monitor, and analyze infectious disease report cases from sources such as social media for prevention and control of infectious diseases affecting children. The proposed framework was validated through use-cases scenario and performance-based comparison.

@article{Mwamnyange2021,
  title     = {Big Data Analytics Framework for Childhood Infectious Disease Surveillance and Response System using Modified MapReduce Algorithm},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {3},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Mdoe Mwamnyange and Edith Luhanga and Sanket R. Thodge},
  doi       = {10.14569/IJACSA.2021.0120345},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120345}
}