Assessing the predictive causality of individual based models using Bayesian inference intervention analysis: an application in epidemiology

Disease control strategies can have both intended and unintended effects on the dynamics of infectious diseases. Routine testing for the harmful pathogen Bovine Tuberculosis (bTB) was suspended briefly during the foot and mouth disease epidemic of 2001 in Great Britain. Here we utilize bTB incidence data and mathematical models to demonstrate how a lapse in management can alter epidemiological parameters, including the rate of new infections and duration of infection cycles. Testing interruption shifted the dynamics from annual to 4-year cycles, and created long-lasting shifts in the spatial synchrony of new infections among regions of Great Britain. After annual testing was introduced in some GB regions, new infections have become more de-synchronised, a result also confirmed by a stochastic model. These results demonstrate that abrupt events can synchronise disease dynamics and that changes in the epidemiological parameters can lead to chaotic patterns, which are hard to be quantified, predicted, and controlled.

show abstract

Internet Search Effort on Covid-19 and the Underlying Public Interventions and Epidemiological Status

Moustakas

2021

Preprint

Self Cite

View full text Add to dashboard Cite

This study aimed to quantify the relative importance of indices of personal freedom, economy, and epidemiology on the public interest on Covid-19 expressed by internet searches on the topic. The relationship between the effective reproduction rate Rt, news media cover, and web search effort was also quantified. Data of online search in Greece on Covid-19 topic for one year were analyzed using indices of social distancing, financial measures, and epidemiological variables using machine learning. Temporal autocorrelation of web search effort was quantified and control charts of web search, Rt, new cases and new deaths were employed. Results indicated that the trained model exhibited a fit of R2 = 91% between the actual and predicted web search effort. The top five variables for predicting web search effort were new deaths, the opening of international borders to non-Greek nationals, new cases, testing policy, and restrictions in internal movements. Web search had negligible temporal autocorrelation between weeks. Web search peaked during the same weeks that the Rt was peaking although new deaths or new cases were not peaking during those dates. The extent to which online searches may reflect the actual epidemiological situation is discussed.

show abstract

Assessing the predictive causality of individual based models using Bayesian inference intervention analysis: an application in epidemiology

Cited by 3 publications

References 70 publications

Environmental impact of Karkheh Dam in the southern part of Iran on groundwater quality by intervention and trend analysis

Environmental impact of Karkheh Dam in the southern part of Iran on groundwater quality by intervention and trend analysis

Abrupt events and population synchrony in the dynamics of Bovine Tuberculosis

Internet Search Effort on Covid-19 and the Underlying Public Interventions and Epidemiological Status

Contact Info

Product

Resources

About