Endemic persistence or disease extinction: The effect of separation into sub-communities

Using lattice SIS epidemiological model with clustered treatment to investigate epidemic control

In epidemic control, how the size of treatment blocks influences the disease is a very interesting problem. Here, we construct an SIS model with spatially clustered treatment blocks using cellular automata and pair approximation to investigate the disease control and optimal arrangement of treatment blocks. On a same treatment intensity, the treatment blocks are built randomly and the individuals in the treatment blocks are cured in the next interval. The migration and neighboring structures are also considered in this model. We find that the size of treatment blocks will influence the control of disease. The bigger size of treatment blocks is more effective in epidemic control. The results obtained by lattice simulations and pair approximation respectively are consistent. On the same treatment arrange, higher migration rate has completely different influence on the epidemic depending on different neighboring structures. Besides, in different neighboring structures, both infected and susceptible populations will get clustered under the treatment blocks. Meanwhile, the neighboring structures can influence the degree of aggregation and the bigger treatment blocks can promote the aggregation compared to the smaller ones. The results here are significant for the control of epidemic diseases, especially when available medical resources are limited.

Costs and benefits of group living with disease: a case study of pneumonia in bighorn lambs (Ovis canadensis)

Group living facilitates pathogen transmission among social hosts, yet temporally stable host social organizations can actually limit transmission of some pathogens. When there are few between-subpopulation contacts for the duration of a disease event, transmission becomes localized to subpopulations. The number of per capita infectious contacts approaches the subpopulation size as pathogen infectiousness increases. Here, we illustrate that this is the case during epidemics of highly infectious pneumonia in bighorn lambs (Ovis canadensis). We classified individually marked bighorn ewes into disjoint seasonal subpopulations, and decomposed the variance in lamb survival to weaning into components associated with individual ewes, subpopulations, populations and years. During epidemics, lamb survival varied substantially more between ewe-subpopulations than across populations or years, suggesting localized pathogen transmission. This pattern of lamb survival was not observed during years when disease was absent. Additionally, group sizes in ewe-subpopulations were independent of population size, but the number of ewe-subpopulations increased with population size. Consequently, although one might reasonably assume that force of infection for this highly communicable disease scales with population size, in fact, host social behaviour modulates transmission such that disease is frequency-dependent within populations, and some groups remain protected during epidemic events.

Epidemiological implications of mobility between a large urban centre and smaller satellite cities

An SIR infectious disease propagation model is considered that incorporates mobility of individuals between a large urban centre and smaller satellite cities. Because of the difference in population sizes, the urban centre has standard incidence and satellite cities have mass action incidence. It is shown that the general basic reproduction number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {R}}_{0}$$\end{document}R0 acts as a threshold between global asymptotic stability of the disease free equilibrium and disease persistence. The case of Winnipeg (MB, Canada) and some neighbouring satellite communities is then considered numerically to complement the mathematical analysis, highlighting the importance of taking into account not only \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {R}}_{0}$$\end{document}R0 but also other measures of disease severity. It is found that the large urban centre governs most of the behaviour of the general system and control of the spread is better achieved by targeting it rather than reducing movement between the units. Also, the capacity of a satellite city to affect the general system depends on its population size and its connectivity to the main urban centre.

Organisational immunity in social insects

Selection for disease control is believed to have contributed to shape the organisation of insect societies-leading to interaction patterns that mitigate disease transmission risk within colonies, conferring them 'organisational immunity'. Recent studies combining epidemiological models with social network analysis have identified general properties of interaction networks that may hinder propagation of infection within groups. These can be prophylactic and/or induced upon pathogen exposure. Here we review empirical evidence for these two types of organisational immunity in social insects and describe the individual-level behaviours that underlie it. We highlight areas requiring further investigation, and emphasise the need for tighter links between theory and empirical research and between individual-level and collective-level analyses.

Divide and conquer? Persistence of infectious agents in spatial metapopulations of hosts

Persistence of an infectious agent in a population is an important issue in epidemiology. It is assumed that spatially fragmenting a population of hosts increases the probability of persistence of an infectious agent and that movement of hosts between the patches is vital for that. The influence of migration on persistence is however often studied in mean-field models, whereas in reality the actual distance travelled can be limited and influence the movement dynamics. We use a stochastic model, where within- and between-patch dynamics are coupled and movement is modelled explicitly, to show that explicit consideration of movement distance makes the relation between persistence of infectious agents and the metapopulation structure of its hosts less straightforward than previously thought. We show that the probability of persistence is largest at an intermediate movement distance of the host and that spatially fragmenting a population of hosts is not necessarily beneficial for persistence.

Influence of infection rate and migration on extinction of disease in spatial epidemics

Extinction of disease can be explained by the patterns of epidemic spreading, yet the underlying causes of extinction are far from being well understood. To reveal a mechanism of disease extinction, a cellular automata model with both birth, death rate and migration is presented. We find that, in single patch, when the infection rate is small or large enough, the disease will disappear for a long time. When the invasion form is in the coexistence of stable spiral and turbulent wave state, the disease will persist. Also, we find that the migration has dual effects on the epidemic spreading. On one hand, in the extinction region of single patch, if the migration rate is large enough, there is a phase transition from the disease free to endemic state in two patches. On the other hand, migration will induce extinction in the regime, which can ensure the persistence of the disease in single patch, due to emergence of anti-phase synchrony. The results obtained well reveal the effect of infection rate and migration on the extinction of the disease, which enriches the finding in the filed of epidemiology and may provide some new ideas to control the disease in the real world.