R

Case Study of the evolution of Daptomycin in SEpi following prolonged antibiotic exposure

Estimating the prevalence of antimalarial mutations in Ethiopia across time and space

Estimating the COVID-19 first wave IFR using serologic data accounting for seroreversion

An algorithm for detecting deme inbreeding spatial coefficients from recombining pathogen genetic data

Determing who was being infected, where infections were occuring, and where they originated

Bayesian statistical model for estimating age-based infection fatality ratios from serologic data

Spatial Structured Wright Fisher Model for Malaria Population Genetic Simulations

Exploring population structure attributed to antimalarial resistance in the Democratic Republic of the Congo

Coupling epidemiologic analysis with relatedness metrics (identity by descent) and population dynamics, we show that there is active transmission between Tanzania and Zanzibar

Below, you will find code for creating a shiny flex-dashboard for simple SIR open and closed population models. --- title: "Simulating SIR Models in a Closed and Open Population" date: "`r format(Sys.time(), '%B %d, %Y')`" editor_options: chunk_output_type: console output: flexdashboard::flex_dashboard runtime: shiny --- {r setup, include=FALSE} knitr::opts_chunk$set(echo = F, warning = F, message = F, fig.align = 'center', results = 'hide', fig.keep = 'all') library(tidyverse) library(cowplot) # https://rmarkdown.rstudio.com/flexdashboard/layouts.html#multiple_pages {r} #.............................................................. # Open Model #.