HEALTHDOC
ENDEMIC SIMULATION
Explore different mathematical models to simulate disease spread and endemic patterns
The SIR model divides the population into three compartments: Susceptible (S), Infected (I), and Recovered (R). The model simulates how individuals move between these compartments over time based on infection and recovery rates.
Equations:
dS/dt = -β × S × I
dI/dt = β × S × I - γ × I
dR/dt = γ × I
Where β is the transmission rate and γ is the recovery rate.
LSTM is a type of recurrent neural network that can learn long-term dependencies in time series data. In disease modeling, LSTM can capture complex patterns and dependencies that may not be captured by traditional compartmental models.
Our simulation implements a simplified version of LSTM behavior using a time-dependent function with memory effects.
Prophet is a forecasting procedure developed by Facebook that works well with time series data that have strong seasonal effects and multiple seasons of historical data. For endemic diseases, Prophet can model seasonal patterns, holidays, and trend changes.
Our simulation implements a simplified version of Prophet's approach using trend, seasonality, and holiday components.
ARIMA is a classical time series forecasting model that combines autoregressive (AR), differencing (I), and moving average (MA) components. ARIMA is particularly useful for modeling diseases with cyclic patterns and trends.
Our simulation implements a simplified ARIMA process with customizable parameters for AR, MA components, and differencing.
Learn about the different mathematical approaches to modeling disease spread
A compartmental model that divides the population into Susceptible, Infected, and Recovered groups.
A deep learning approach that can capture complex patterns and long-term dependencies in time series data.
A forecasting tool that excels at handling seasonality, holidays, and multiple trend changes.
A statistical model that combines autoregression, differencing, and moving average components.
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View Endemic SimulationDesigned by Jayachandiran K