Conceptualizing climate as a distinct variable limits our understanding of the synergies and interactions between climate change and the range of abiotic and biotic factors, which influence animal health. Frameworks such as eco-epidemiology and the epi-systems approach, while more holistic, view climate and climate change as one of many discreet drivers of disease. Here, I argue for a new paradigmatic framework: climate-change syndemics. Climate-change syndemics begins from the assumption that climate change is one of many potential influences on infectious disease processes, but crucially is unlikely to act independently or in isolation; and as such, it is the inter-relationship between factors that take primacy in explorations of infectious disease and climate change. Equally importantly, as climate change will impact a wide range of diseases, the frame of analysis is at the collective rather than individual level (for both human and animal infectious disease) across populations.

An eco-epidemiological model of susceptible Tilapia fish, infected Tilapia fish and Pelicans is investigated by several author based upon the work initiated by Chattopadhyay and Bairagi (Ecol. Model., 136, 103–112, 2001). In this paper, we investigate the dynamics of the same model by considering different parameters involved with the model as bifurcation parameters in details. Considering the intrinsic growth rate of susceptible Tilapia fish as bifurcation parameter, we demonstrate the period doubling route to chaos. Next we consider the force of infection as bifurcation parameter and demonstrate the occurrence of two successive Hopf-bifurcations. We identify the existence of backward Hopf-bifurcation when the death rate of predators is considered as bifurcation parameter. Finally we construct a stochastic differential equation model corresponding to the deterministic model to understand the role of demographic stochasticity. Exhaustive numerical simulation of the stochastic model reveals the large amplitude fluctuation in the population of fish and Pelicans for certain parameter values. Extinction scenario for Pelicans is also captured from the stochastic model.

In the field of molecular and epidemiological parasitology, characterization of fast evolving genetic markers appears as an important challenge to consider the diversity and genetic structure of parasites. The study of respective populations can help us to understand their adaptive strategies to survive and perpetuate the species within different host populations, all trying to resist infection. In the past, the relative monomorphic features of Echinococcus multilocularis, the causative agent of alveolar echinococcosis and a severe human parasitic disease, did not stimulate studies dealing with the genetic variability of Echinococcus species or respective populations. A recently developed, characterized and validated original multilocus microsatellite, named EmsB, tandemly repeated in the genome, offered an additional opportunity for this line of investigation. We have compiled in this review new insights brought by this molecular tracker on the transmission activity of Echinococcus among different hosts and at different geographical scales.

Urinary schistosomiasis is an important source of human morbidity in Msambweni, Kenya, where the intermediate host snail, Bulinus nasutus is found in ponds and water pools. In the past, aquatic habitats in the area have been studied separately; however, recent collections of B. nasutus snails and shells indicated that many of these ponds are in fact connected during and following sufficient rains. Satellite imagery and a geographical information system (GIS) were used to survey the main water courses and potential drainage routes, to locate potential source populations of snails and to determine probable snail dispersal routes. The 2 water bodies implicated as being the most important Schistosoma haematobium transmission foci in the area were found to differ in their degree of connectivity to other B. nasutus source habitats. One pond becomes connected even after normal rains, while the other pond requires prolonged rains or flooding to become connected with source habitats. Consequently, the transmission foci differ in their susceptibility to snail population control measures. Spatially explicit dispersal models that consider the spatial and temporal patterns of connectivity between aquatic habitats will contribute to improved snail surveillance and more focused control for urinary schistosomiasis at a local level.