Predicting malaria dynamics in Burundi using deep Learning Models

by   Daxelle Sakubu, et al.

Malaria continues to be a major public health problem on the African continent, particularly in Sub-Saharan Africa. Nonetheless, efforts are ongoing, and significant progress has been made. In Burundi, malaria is among the main public health concerns. In the literature, there are limited prediction models for Burundi. We know that such tools are much needed for interventions design. In our study, we built machine-learning based models to estimates malaria cases in Burundi. The forecast of malaria cases was carried out at province level and national scale as well. Long short term memory (LSTM) model, a type of deep learning model has been used to achieve best results using climate-change related factors such as temperature, rainfal, and relative humidity, together with malaria historical data and human population. With this model, the results showed that at country level different tuning of parameters can be used in order to determine the minimum and maximum expected malaria cases. The univariate version of that model (LSTM) which learns from previous dynamics of malaria cases give more precise estimates at province-level, but both models have same trends overall at provnce-level and country-level


page 1

page 2

page 3

page 4


Hydroelectric Generation Forecasting with Long Short Term Memory (LSTM) Based Deep Learning Model for Turkey

Hydroelectricity is one of the renewable energy source, has been used fo...

Using Long Short-Term Memory (LSTM) and Internet of Things (IoT) for localized surface temperature forecasting in an urban environment

The rising temperature is one of the key indicators of a warming climate...

Impact analysis of recovery cases due to COVID19 using LSTM deep learning model

The present world is badly affected by novel coronavirus (COVID-19). Usi...

Obesity Prediction with EHR Data: A deep learning approach with interpretable elements

Childhood obesity is a major public health challenge. Obesity in early c...

A generalized forecasting solution to enable future insights of COVID-19 at sub-national level resolutions

COVID-19 continues to cause a significant impact on public health. To mi...

Predicting pregnancy using large-scale data from a women's health tracking mobile application

Predicting pregnancy has been a fundamental problem in women's health fo...

Predicting risk of delirium from ambient noise and light information in the ICU

Existing Intensive Care Unit (ICU) delirium prediction models do not con...

Please sign up or login with your details

Forgot password? Click here to reset