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2 results for “disease spread model”
Replication files for: Integrative modeling of the spread of serious infectious diseases and corresponding wastewater dynamics
<p>This repository contains the inputs used and outputs produced by the urban water management modelling software ++SYSTEMS for the paper Integrative Modeling of the Spread of Serious Infectious Diseases and Corresponding Wastewater Dynamics. It includes the following files:</p> <ol> <li>simulation_output.zip:</li> <ol> <li>In the subfolder infection_model, .csv and .txt files containing the agent-based model outputs for 250 simulations with homogeneous infection initialisation (2024_09_17) or localised infection initialisation (2024_10_15). These files were used as inputs for ++SYSTEMS.</li> <li>In the subfolder wastewater_model, .txt files containing the flow rates by pipe and the viral concentrations by sampling location for each combination of ABM simulation and rain/decay scenario. These files were the outputs of ++SYSTEMS.</li> </ol> <li>S1_INSIDe_Demonstrator_AreaList.txt: .txt file defining the area types and number of inhabitants for each surface area within the synthetic neighbourhood used in the paper. This file was also used as an input for ++SYSTEMS.<span> </span></li> <li>S2_systems_model_files.zip: .csv files defining the characteristics of the sewage system for the synthetic neighbourhood as well as the rain scenarios used in the paper. These file were also used as inputs for ++SYSTEMS.<span> </span></li> </ol>
Codes: An early warning indicator trained on stochastic disease-spreading models with different noises
<p>This dataset contains the training data (Version V1) and all the codes (Version V2) of the paper entitled "An early warning indicator trained on stochastic disease-spreading models with different noises." </p> <p>Time series and corresponding residuals from white noise (equation 2.5), environmental noise (equation 2.8), and demographic noise (equation 2.9) are stored in the training_data_WhiteN, training_data_EnvN, and training_data_DemN folders, respectively. All residuals of the time series are contained in the training_resids folder, which also includes labels and groups of the training data. For details on the data generation process, please refer to section 3.1 in the paper. </p>
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