Data from: Modeling the potential of introducing different Wolbachia–infected mosquitoes to control Aedes-borne arboviral infections

Full description

Description of Dataset

This dataset contains the results and outputs generated from model simulations conducted in MATLAB and R programming languages for the research project titled "Modeling the Potential of Introducing Different Wolbachia–Infected Mosquitoes to Control Aedes-Borne Arboviral Infections."

The objective of this study was to explore the effectiveness of introducing various strains of Wolbachia-infected mosquitoes as a means of controlling Aedes-borne arboviral infections, such as dengue, Zika, and chikungunya.

Dataset Overview: The dataset encompasses various components that provide valuable insights into the modeling simulations conducted during the research project. The dataset includes:

1. Model Parameters:
   • Values and specifications of the input parameters used in the mathematical models, such as disease transmission rates, recovery rates, mosquito population dynamics, and Wolbachia infection dynamics.
   • Details on the assumptions and calibration techniques employed in determining model parameters.
    
2. Model Implementation:
   • Code files written in MATLAB and R programming languages used to implement the mathematical models.
   • Information on the software versions and packages utilized in executing the simulations.
    
3. Simulated Data:
   • Numerical outputs generated from the simulations, such as disease incidence, prevalence, and mosquito population dynamics.
   • Model-generated predictions of disease transmission patterns, impact of Wolbachia introduction, and associated changes in arboviral infection dynamics.
    
4. Sensitivity Analyses:
   • Outputs from sensitivity analyses, investigating the influence of key model parameters on the outcomes of the simulations.
   • Results of parameter variation and uncertainty analyses to understand the robustness and reliability of the model predictions.
    
5. Graphs and Visualizations:
• Plots, graphs, and visual representations of the simulation results, aiding in the interpretation and visualization of the model outputs.
• Figures depicting the trends, patterns, and dynamics of disease transmission and mosquito population dynamics under different scenarios.
 

Data Format: The dataset is organized into folders, with each folder containing relevant files associated with the modeling simulations and analyses. The code files are presented as text files or script files with the .m (MATLAB) or .R (R) file extensions. Simulated data and analysis outputs are provided in CSV (Comma-Separated Values) or Excel spreadsheet format.

The dataset also contains the Wolbachia field trials in 32 suburbs in the city of Townsville, which is one of the largest cities in North Queensland, Australia with a population of approximately 187,500. From October 2014, wMel-Wolbachia-infected mosquitoes were continually released for a 28-month period. Releases were carried out using mosquito release containers—Mozzie boxes and BioGents Sentinel mosquito traps, set up for subsequent mosquito capture.

The dataset (Townsville dengue case notifications data (for locally acquired and imported cases)) used for this analysis were extracted from O’Neill et al. Originally, the information regarding all laboratory confirmed and clinically probable diagnosis of symptomatic dengue from the beginning of the year 2001 to the first quarter of 2019 was supplied by the Communicable Disease Branch of Queensland Health. These data described the dengue case notifications in Townsville by month of illness onset and history of recent foreign travel by individuals in the 3–12 days before illness onset.

Overall, the dataset for the project "Modeling Simulations for 'Modeling the Potential of Introducing Different Wolbachia–Infected Mosquitoes to Control Aedes-Borne Arboviral Infections'" comprises the model parameters, implementation code, simulated outcomes, sensitivity analyses, and visualizations from the research project. By making this comprehensive dataset available, it will facilitate further research and exploration into the potential of using Wolbachia-infected mosquitoes for managing Aedes-borne arboviral infections.