Abrupt events and population synchrony in the dynamics of Bovine Tuberculosis

Aristides Moustakas,Ioannis N Daliakopoulos,Yannis Markonis,Matthew R Evans

doi:10.1038/s41467-018-04915-0

Abstract

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.

Highlights

Disease control strategies can have both intended and unintended effects on the dynamics of infectious diseases
From December 2002 to September 2015, New Herd Incidents (NHI) increased at a lower rate than during the period in which testing was interrupted, but the number of NHI were at least an order of magnitude higher than prior to January 2001 (Fig. 1a)
The empirical probability distribution of NHI/Tests on Herds (TTH) is similar before and after testing interruption, the mean of the distribution is considerably higher after the testing interruption; (Fig. 1d)

Summary

Introduction

Disease control strategies can have both intended and unintended effects on the dynamics of infectious diseases. After annual testing was introduced in some GB regions, new infections have become more de-synchronised, a result 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. We analyse a monthly data set on New Herd Incidents (NHI; herds that were detected to contain at least one infected individual having previously been bTB-free) normalised by the number of Total Tests on Herds (TTH) from January 1996 to August 201611 Using this data set, we sought to quantify patterns of the disease spread over space and time. We examined the impact of epidemiological changes due to the period during which disease controls were suspended indicated by the interruption to cattle testing, an abrupt short-lasting event, on disease prevalence, temporal cycles of infections, and spatial population synchrony. This study shows that amendments in the epidemiological parameters lead to chaotic patterns and that abrupt events synchronise disease dynamics

Methods

Results

Conclusion