Final Project for a Mathematical Biology course
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Updated
Aug 4, 2017 - TeX
Final Project for a Mathematical Biology course
Source code of paper "Rare Events of Host Switching for Diseases using a SIR Model with Mutations"
Network spread models developed in R.
COVID-19 Case Modelling in Julia completed as part of the MIT Math 6S083 Course.
supplementary code and data to Diehl et al, 2016 (Cell)
Scripts used in the publication "Continent-wide recent emergence of a global pathogen in African amphibians" by Ghose et al. (2023)
Analysis of core Chronic Diseases in Northern Nigeria is a group project demo performed by trainees at GIZ sponsored Data Science training program by COVEN LABS. The Data was gotten from kaggle.com and was prepared by Emmanuel Odelanmi who was trying to predict Meningitis occurrence in individuals using Machine Learning. The project is to advice…
Covid-19 Tracker application using React, Material UI, Disease.sh API, chart.js and firebase hosting
This is a repository for storing calculation scribbles, code and temporary script files of Wetland Environmental Mathematics assignment.
An implementation of a primitive SIR model to simulate the propagation of a disease with a limited set of variables.
An examination of predictive disease saliency in social networks and the potential application of network analysis in locating disease spread
A collection of MATLAB scripts used for a research project at the Mathematical and Theoretical Biology Institute (MTBI) 2011 Summer program.
Solve a stochastic SEIR model for disease progression
A framework written in Python to create and run simulations on compartmental epidemiological models.
This is an implementation of the SIERD model in C using Euler's explicit method
Data used to perform the analyses published in Transboundary and Emerging Diseases, DOI: 10.1111/tbed.14679
A report and relevant scripts detailing how quarantining has affected the spread of COVID-19 using ECDC data and an SIR model.
A tool for identifying cooling towers from satellite and aerial imagery, for tracking sources of Legionnaire's disease.
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