Spatial scales in human movement between reservoirs of infection

Measuring heterogeneities in soil-transmitted helminth transmission and control

The global effort over the past decade to control soil-transmitted helminths (STH) has resulted in communities with endemic infection reaching low prevalence levels suitable for the validation of elimination as a public health problem (EPHP), defined by the World Health Organisation (WHO) as <2% of infections classified as moderate or heavy intensity. The spatial scale in which this is validated is currently undefined. As the burden of STH infection decreases, the degree of aggregation of infection within individuals in a population increases. Identifying these remaining pockets of infection requires fine-scale monitoring and evaluation (M&E) programmes that are rarely implemented within current national neglected tropical disease (NTD) control. This review examines various heterogeneities that characterise the epidemiology of STH infections, and discusses their impact on control policy formulation.

On Spatiotemporal Overdispersion and Macroparasite Accumulation in Hosts Leading to Aggregation: A Quantitative Framework

In many host-parasite systems, overdispersion in the distribution of macroparasites leads to parasite aggregation in the host population. This overdispersed distribution is often characterized by the negative binomial or by the power law. The aggregation is shown by a clustering of parasites in certain hosts, while other hosts have few or none. Here, I present a theory behind the overdispersion in complex spatiotemporal systems as well as a computational analysis for tracking the behavior of transmissible diseases with this kind of dynamics. I present a framework where heterogeneity and complexity in host-parasite systems are related to aggregation. I discuss the problem of focusing only on the average parasite burden without observing the risk posed by the associated variance; the consequences of under- or overestimation of disease transmission in a heterogenous system and environment; the advantage of including the network of social interaction in epidemiological modeling; and the implication of overdispersion in the management of health systems during outbreaks.