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covid_model

A mechanistic population balance model to evaluate the impact of interventions on infectious disease outbreaks: Case for COVID19

covid_modelling

Using SEIR models to investigate the effects of a vaccine on COVID-19 cases.

cs61b-sp21

CS 61B, Spring 2021

cs61b-sp21-1

cvsim_multicountry

COVID-19 modelling

cyprus-seir-covid19-model

Cyprus-SEIR-Covid19-Model

epidemic-simulator

City-Scale simulator for Epidemic spread in Indian conditions

epidemicmodeling

Mathematical Modeling of Epidemic Diseases

eswatini-covasim

Adapting the Covasim model to Eswatini

final_project

git_learning

gitlet

Berkeley CS61B project 2 Gitlet

ije_2021_covid19agestructuredseir

java_assignments

jenkins

learning-area

MDN 学习区示例中文版

learning-area-1

Github repo for the MDN Learning Area.

matsim-episim-libs

Epidemic simulation for MATSim

model_covid_19

In this work we define a modified SEIR model that accounts for the spread of infection during the latent period, infections from asymptomatic or pauci-symptomatic infected individuals, potential loss of acquired immunity, people’s increasing awareness of social distancing and the use of vaccination as well as non-pharmaceutical interventions like social confinement. We estimate model parameters in three different scenarios - in Italy, where there is a growing number of cases and re-emergence of the epidemic, in India, where there are significant number of cases post confinement period and in Victoria, Australia where a re-emergence has been controlled with severe social confinement program. Our result shows the benefit of long term confinement of 50\% or above population and extensive testing. With respect to loss of acquired immunity, our model suggests higher impact for Italy. We also show that a reasonably effective vaccine with mass vaccination program can be successful in significantly controlling the size of infected population. We show that for India, a reduction in contact rate by 50\% compared to a reduction of 10\% in the current stage can reduce death from 0.0268\% to 0.0141\% of population. Similarly, for Italy we show that reducing contact rate by half can reduce a potential peak infection of 15\% population to less than 1.5\% of population, and potential deaths from 0.48\% to 0.04\%. With respect to vaccination, we show that even a 75\% efficient vaccine administered to 50\% population can reduce the peak number of infected population by nearly 50\% in Italy. Similarly, for India, a 0.056\% of population would die without vaccination, while 93.75\% efficient vaccine given to 30\% population would bring this down to 0.036\% of population, and 93.75\% efficient vaccine given to 70\% population would bring this down to 0.034\%.

modelado-y-control-covid19

Modelado de la transmisión del COVID19 empleando el modelo epidemiológico SEIRQP. Se presentan dos tipos de simulaciones, una estocástica (dependiente de factores aleatorios) y una determinística (sin aleatoriedad). Parte de la clase de sistemas de Control II. Realizado junto a Gabriela Iriarte.

n-blog

《一起学 Node.js》

novel-coronavirus-pneumonia-seir-lstm

本项目实现2019新型冠状病毒肺炎预测，分别采用经典传染病动力学模型SEIR和LSTM神经网络实现，通过控制模型参数来改变干预程度，体现防控的意义。

nr-abm-population

Database of New Rochelle, NY, US and code for its conversion into an agent-based computational model

openabm-covid19

OpenABM-Covid19: an agent-based model for modelling the spread of SARS-CoV-2 (coronavirus) and control interventions for the Covid-19 epidemic

python_corona_simulation

An agent-based simulation of corona and other viruses in python

reina-model

Agent-based simulation model for COVID-19 spread in society and patient outcomes

seir-covid19

Use SEIR to model COVID 19

seir-dit

Deterministic SEIR-like model aimed to study the effect of DIT strategy (Detect symptoms, isolate and trace contacts) as an alternative to COVID-19 control.

seir-model-for-covid19

This is a biology project assigned by IIT Goa to model and fit a epidemic model for COVID 19

seird

Compartmental model for tracking spread of COVID-19