Keywords : Malaria

A Data Mining based study on Dengue Fever: A Review

Kousik Bhattacharya; Avijit Kumar Chaudhuri; Anirban Das; Dilip K. Banerjee

International Research Journal on Advanced Science Hub, 2022, Volume 4, Issue 04, Pages 101-107
DOI: 10.47392/irjash.2022.025

Dengue fever (DF) is amosquitoborne disease spread by female Aedes mosquito. Dengue transmission depends on the changing of climatic parame- ters like temperature, humidity, rainfall, as well as the congestion in an area, i.e., where the population density is high. In this review, we have highlighted the reasons of the occurrence of DF and methods for early detection of the same. Symptoms are the key points to diagnose the dengue patients. Many diseases like Malaria, Chikungunia, Typhoid, COVID-19, etc. have the com- mon symptoms of fever, body pain, eye pain, diarrhoea, etc. Few rare symp- toms have been identified for diagnosing DF using machine learning predictive model. Rare symptoms are skin disease, headache, abdominal pain for early detection of dengue.

Incidents of Malaria in India using ARIMA Models

Sukanya K.; Suneetha T.; Sukeerthi T.; Vani A.

International Research Journal on Advanced Science Hub, 2020, Volume 2, Issue Special Issue ICIES 9S, Pages 120-133
DOI: 10.47392/irjash.2020.172

In India, the best embody of malaria occurred within the year 1950’s with associate calculable 75 million cases and 0.8 million deaths per Annum (World Health Organization, country office for India). The model was used for the forecasting of the year wise incidence of Malaria whereas Auto regressive integrated moving average (ARIMA) models was used for forecasting for the years 2020 and 2022 in Republic of India (Bharat) our study provides that of the ARIMA model was designated as best suited model to predict the longer term incidents of malaria cases within the fourth approaching period in India.