The intricacies of compartmental models (SIR, SEIR) and their role in understanding and predicting disease dynamics: 1/ Understanding disease dynamics is crucial for predicting outbreaks and implementing effective public health measures. Compartmental models like SIR and SEIR are fundamental tools used by epidemiologists for this purpose. Let's delve deeper into how they work. #Epidemiology 2/ The SIR model divides the population into three compartments: Susceptible (S), Infected (I), and Recovered (R). It assumes that everyone in the population belongs to one of these compartments. #SIRmodel #DiseaseDynamics 3/ The SEIR model adds another compartment, Exposed (E), to the SIR model. Individuals in the Exposed compartment have been infected but are not yet infectious. This accounts for the incubation period of the disease. #SEIRmodel #IncubationPeriod 4/ The transition of individuals between compartments is represented by parameters: beta (infection rate), gamma (recovery rate), and in the case of the SEIR model, sigma (rate of progression from exposed to infectious). #Parameters #InfectionRate #RecoveryRate 5/ These parameters are crucial because they determine the dynamics of the disease. For example, 'R0', the basic reproduction number, is calculated as beta/gamma in the SIR model. It represents the average number of people an infected person will infect. But this is a simplification, and actual calculations may vary based on the disease and model specifics. #R0 #ReproductionNumber 6/ The parameters (beta, gamma, sigma) may vary over time and between different populations. More advanced models can incorporate this variability to provide more accurate predictions. 7/ The models can be further refined by adding more compartments, such as a compartment for deceased individuals, or by dividing the population into different age groups or geographical locations. #ModelRefinement #PopulationDynamics 8/ Compartmental models are usually fitted to real-world data to estimate the parameters and make predictions. This involves using statistical methods to find the values of the parameters that best explain the observed data. #ModelFitting #Predictions 9/ It is important to note that these models make several assumptions, such as homogeneous mixing of the population and constant parameters over time. In reality, these assumptions may not hold, and more complex models may be needed. #ModelAssumptions #ComplexModels 10/ There are several R packages available for fitting and analyzing compartmental models. Some popular ones include 'EpiModel', 'epimdr ' and 'deSolve'. #Rpackages #DataAnalysis 11/ Understanding the intricacies of compartmental models is key to interpreting their results and using them to inform public health decisions. Compartmental models like SIR and SEIR can be used to estimate the impact of interventions like social distancing or vaccination. This helps policymakers make informed decisions to control the spread of the disease. #PublicHealth #ModelInterpretation 12/ While SIR and SEIR models are valuable tools for understanding and predicting disease dynamics, they are simplifications of reality. They should be used with caution and in conjunction with other forms of analysis and expert opinion. #epidemiology #publichealth #DataScience

The basic confihuration of convolutional neural network #CNN ,#DeepLearning #modelfitting #neurons #hiddenlayer #probability #classification #output

Specific topics related to data science: #regression, #clustering, #neuralnetworks, #deeplearning, #decisiontrees, #ensembles, #correlation, #Python, #R, #Tensorflow, #SVM, #datareduction, #featureselection, #experimentaldesign, cross-validation, #modelfitting, and many more

If you figure out how to do modelfitting using Microsoft word, please let me know!

What tests should you be using for model fitting? Here are some relatively obscure ones: | bit.ly/2Zkwp9V #DataQuality #DeepLearning #keras #Algorithm #DataScience #Kubernetes #DataTeams #Automation #ExplainableAI #Business #ModelFitting

#NeuromatchAcademy starts today - if you, like me, can't participate live bc of other engagements: All their course material is available for free on github! 🤩 #ModelFitting #MachineLearning #BayesianStatistics #DecisionMaking @neuromatch github.com/NeuromatchAcademy…

Gene and Kylo have been invited on for a fitting for a great Boutique company! #boutique #fitting #modelfitting #welldone #babymodels #teamta

#modelfitting with @Toubaalp getting ready for the fashion show with @fgequality at @techupforwomen Nov 19th. #roboticdress in collaboration with @aninanet & #360fashionnetwork #360fash tech kits. #fashiontech #wearabletech #wearabletechnology #roboticsc… instagram.com/p/B4xshUvHe4q/

Scientists: she means *narrative*. Not #data gathering #modelfitting #errorreduction, #hypothesis testing - not even hypothesis formation. Just: understanding things better purely out of the attempt to put thoughts in words. i.e. Proze. i.e. Non-quantified reflective thingies.

Combining a violin plot & a boxplot for quick data visualisation #plot #R #violinplot #boxplot #Datavisualisation #Modelfitting

ABC not easy as 123? @MikeAIrvine can help - his Python code for fitting epidemic models "does not require significant theoretical background" - as simple as do re mi! doi.org/10.1016/j.epidem.201… #ModelFitting #Epidemics @ubcmath @IDAdvance @ParasitologyELS @bdi_oxford @NtdModelling

This is a great Python library for neuronal simulation. Still I miss the modelfitting module from Brian1, useful for implementing ML tasks.

#Working #modelfitting #personalstylist #frommetoyoulovee #artmeso #fashionshow instagram.com/p/BZ9mXbqnD4P/

14 #GreatArticles About #Cross-Validation, #ModelFitting and Selection #DataScience buff.ly/2w2HIqX

Loved seeing this lot again 👍🤗 @freeportessex #modelfitting #fashion #models melissa.steven… instagram.com/p/BYbLjZBg_dZ/

Day One of Model fittings!!! 2 Days until the Atlanta Fashion Showcase!!! #stormdorris #couture #modelfitting #sneakpeek #atlfashionshowcase

Informative reads on #regression #analysis, #deeplearning, #Python, #datareduction, #modelfitting and more! | via @analyticbridge

I cringe every time I see a plot that just joins the dots | #data #datascience #statistics #modelfitting 🙄😞😔

We even included some #modelfitting advice on our #marchforscience poster!

This looks like it could be useful! #stats #modelfitting #disease lshtm.ac.uk/study/cpd/infect…