jms5151/SEI-SEIR_Arboviruses

Climate-based mechanistic model of arbovirus transmission in Ecuador and Kenya. # Software All codes were created and run using R statistical software version 3.5.3 and Rstudio version 1.1.383. # About SEI-SEIR_Arboviruses This repository provides code to run climate-based mechanistic models of arboviral transmission. The models support of the manuscript "Climate predicts geographic and temporal variation in mosquito-borne disease dynamics" by Caldwell et al. Nature Communications (nature.com). # models Temperature-, rainfall-, and humidity-dependent model: SEI-SEIR_model_THR.R Temperature-, rainfall-, and humidity-dependent model with trait variation: SEI-SEIR_model_with_trait_variation.R Code to set up simulations: SEI-SEIR_simulation_setup.R # data Initial conditions (proportion of population in each compartment): LHS_inputs.csv Posterior distribution of c, T0, Tmax for temperature-dependent traits: Random_sample_of_posterior_traits.csv Epidemic characteristics datasets: (1) Duration_intensity_outbreaks.csv and (2) Number_outbreaks.csv Time series of temperature, humidity, and rainfall for study sites: climate_data.RData Time series of vector data for study sites: vector_data.csv. Only adult Ae. aegypti data was collected at Ecuador sites. Time serires of arboviral data for study sites: arbovirus_data.csv. Data is only available for Kenya sites. # simulations A single code is provided to run each model with appropriate data. # analyses Compare model output with observational data: pairwise_correlation.R Compare model output with different socio-ecological characteristics: socio_ecological_relationships.R Compare predictions and observations for different epidemic characteristics: epidemic_characteristics.R