Impact of tuberculosis treatment length and adherence under different transmission intensities.

Tuberculosis (TB) is a leading cause of human mortality due to infectious disease. Treatment default is a relevant factor which reduces therapeutic success and increases the risk of resistant TB. In this work we analyze the relation between treatment default and treatment length along with its consequence on the disease spreading. We use a stylized model structure to explore, systematically, the effects of varying treatment duration and compliance. We find that shortening treatment alone may not reduce TB prevalence, especially in regions where transmission intensity is high, indicating the necessity of complementing this action with increased compliance. A family of default functions relating the proportion of defaulters to the treatment length is considered and adjusted to a particular dataset. We find that the epidemiological benefits of shorter treatment regimens are tightly associated with increases in treatment compliance and depend on the epidemiological background.

Mycobacterial ecology as a modulator of tuberculosis vaccine success.

Natural infection with Mycobacterium tuberculosis, as well as cross-immune reactions with the constituent of standard vaccines, attenuated M. bovis, and other species of mycobacteria confer partial immunity to subsequent M. tuberculosis infection. It has been shown in the past that the immune response to mycobacteria found naturally in the environment reduces the benefit of vaccination as assessed by means of vaccine efficacy. In this paper we show that efficacy is a poor measure of the potential success of new anti-tuberculous vaccines due to its inability to account for the relative weight of reinfection in disease dynamics. We advocate instead the use of vaccine effectiveness when evaluating the impact of new control methods against infections that confer partial immunity. Through the study of a simple model that incorporates cross-reactive responses to environmental mycobacteria (EM) and reinfection, we show how the particulars of the relation between EM abundance and vaccine effectiveness depend on the degree of protection conferred respectively by natural infection, vaccination and EM. The relative importance of reinfection as a transmission mechanism comes up as the most important source of variability in vaccine effectiveness. Our results suggest that control efforts should be placed in reducing the importance of reinfection through diminishing transmission rates. Vaccines that overcome preexisting immunity to other mycobacteria will still have varying degrees of success depending on the underlying rate of TB transmission.

Understanding the transmission dynamics of respiratory syncytial virus using multiple time series and nested models.

The nature and role of re-infection and partial immunity are likely to be important determinants of the transmission dynamics of human respiratory syncytial virus (hRSV). We propose a single model structure that captures four possible host responses to infection and subsequent reinfection: partial susceptibility, altered infection duration, reduced infectiousness and temporary immunity (which might be partial). The magnitude of these responses is determined by four homotopy parameters, and by setting some of these parameters to extreme values we generate a set of eight nested, deterministic transmission models. In order to investigate hRSV transmission dynamics, we applied these models to incidence data from eight international locations. Seasonality is included as cyclic variation in transmission. Parameters associated with the natural history of the infection were assumed to be independent of geographic location, while others, such as those associated with seasonality, were assumed location specific. Models incorporating either of the two extreme assumptions for immunity (none or solid and lifelong) were unable to reproduce the observed dynamics. Model fits with either waning or partial immunity to disease or both were visually comparable. The best fitting structure was a lifelong partial immunity to both disease and infection. Observed patterns were reproduced by stochastic simulations using the parameter values estimated from the deterministic models.

Gripenet: an internet-based system to monitor influenza-like illness uniformly across Europe.

Gripenet has been monitoring the activity of influenza-like-illness (ILI) with the aid of volunteers via the internet in the Netherlands and Belgium since 2003 and in Portugal since 2005. In contrast with the traditional system of sentinel networks of mainly primary care physicians coordinated by the European Influenza Surveillance Scheme (EISS), Gripenet obtains its data directly from the population. Any resident of the three countries can participate in Gripenet by completing an application form on the appropriate websites (http://www.griepmeting.nl for the Netherlands and Belgium, http://www.gripenet.pt for Portugal), which contains various medical, geographic and behavioural questions. Participants report weekly on the website any symptoms they have experienced since their last visit. ILI incidence is determined on the basis of a uniform case definition. In the 2006/2007 season, 19,623 persons participated in Gripenet in the Netherlands, 7,025 in Belgium and 3,118 in Portugal. The rise, peak and decline of ILI activity occurred at similar times according to Gripenet and EISS. However, ILI attack rates in the Netherlands (6.6%), Belgium (6.1%) and Portugal (5.6%) were remarkably more similar in Gripenet than in EISS (0.8%, 3.9%, and 0.6% respectively). Monitoring ILI activity with the direct participation of volunteers provides similar incidence curves compared to the traditional system coordinated by EISS. Whereas EISS provides an established system whose data is validated by virology tests, Gripenet is a fast and flexible monitoring system whose uniformity allows for direct comparison of ILI rates between countries. A current objective of Gripenet is to engage more European countries.

Localized contacts between hosts reduce pathogen diversity.

We investigate the dynamics of a simple epidemiological model for the invasion by a pathogen strain of a population where another strain circulates. We assume that reinfection by the same strain is possible but occurs at a reduced rate due to acquired immunity. The rate of reinfection by a distinct strain is also reduced due to cross-immunity. Individual based simulations of this model on a 'small-world' network show that the proportion of local contacts in the host contact network structure significantly affects the outcome of such an invasion, and as a consequence will affect the patterns of pathogen evolution. In particular, hosts interacting through a 'small-world' network of contacts support lower prevalence of infection than well-mixed populations, and the region in parameter space for which an invading strain can become endemic and coexist with the circulating strain is smaller, reducing the potential to accommodate pathogen diversity. We discuss the underlying mechanisms for the reported effects, and we propose an effective mean-field model to account for the contact structure of the host population in 'small-world' networks.

Dynamical behaviour of epidemiological models with sub-optimal immunity and nonlinear incidence.

In this paper we analyze the dynamics of two families of epidemiological models which correspond to transitions from the SIR (susceptible-infectious-resistant) to the SIS (susceptible-infectious-susceptible) frameworks. In these models we assume that the force of infection is a nonlinear function of density of infectious individuals, I. Conditions for the existence of backwards bifurcations, oscillations and Bogdanov-Takens points are given.