Assessing the heterogeneity in the transmission of infectious diseases from time series of epidemiological data

Structural features and the heterogeneity of disease transmissions play an essential role in the dynamics of epidemic spread. But these aspects can not completely be assessed from aggregate data or macroscopic indicators such as the effective reproduction number. We propose in this paper an index of...

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Bibliographic Details
Published in:PloS one 2023-05, Vol.18 (5), p.e0286012
Main Authors: Schneckenreither, Günter, Herrmann, Lukas, Reisenhofer, Rafael, Popper, Niki, Grohs, Philipp
Format: Article
Language:English
Subjects:
Analysis
Austria
Biology and life sciences
Clusters
Communicable Diseases - epidemiology
Coronaviruses
COVID-19
COVID-19 - epidemiology
Data mining
Development and progression
Disease Outbreaks
Disease transmission
Diseases
Engineering and Technology
Epidemics
Epidemiologic methods
Epidemiology
Health aspects
Heterogeneity
Humans
Infections
Infectious diseases
Mathematical models
Medical research
Medicine and Health Sciences
Medicine, Experimental
Methods
Outbreaks
Pandemics
Phase transitions
Physical Sciences
Population
Registration
Reproduction
Risk factors
SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
Sociodemographics
Statistical models
Statistics
Stochasticity
Time Factors
Time series
Time-series analysis
Viral diseases
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Summary:Structural features and the heterogeneity of disease transmissions play an essential role in the dynamics of epidemic spread. But these aspects can not completely be assessed from aggregate data or macroscopic indicators such as the effective reproduction number. We propose in this paper an index of effective aggregate dispersion (EffDI) that indicates the significance of infection clusters and superspreading events in the progression of outbreaks by carefully measuring the level of relative stochasticity in time series of reported case numbers using a specially crafted statistical model for reproduction. This allows to detect potential transitions from predominantly clustered spreading to a diffusive regime with diminishing significance of singular clusters, which can be a decisive turning point in the progression of outbreaks and relevant in the planning of containment measures. We evaluate EffDI for SARS-CoV-2 case data in different countries and compare the results with a quantifier for the socio-demographic heterogeneity in disease transmissions in a case study to substantiate that EffDI qualifies as a measure for the heterogeneity in transmission dynamics.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0286012