Designing a framework for implementing CUSUM algorithms for Climate change detection for relative diseases

Big data have long predicted widespread irresistible infections as large-scale reactions to seasonal climate change,
polarising discussion, and a particularly dreadful human virus for which financial motives and control techniques might
restrict the disclosure of atmospheric intervention changes. The majority of the time, seasonal climate change illnesses are no
longer common because of modifications to rural land practises, isolated incidents, changes in human conduct, and
management of vectors. Most vector-borne illnesses only seldom show symptoms, and they are climate sensitive. The
Cumulative Sum (CUSUM) algorithms are used in Big Data Analytics to identify climate change. The recommended CUSUM
algorithm produces better results for the climate change algorithm.