Albeit pregnancy-associated malaria (PAM) poses a potential risk for over 125 million women each year, an accurate review assessing the impact on malaria in infants has yet to be conducted. In addition to an effect on low birth weight (LBW) and prematurity, PAM determines foetal exposure to Plasmodium falciparum in utero and is correlated to congenital malaria and early development of clinical episodes during infancy. This interaction plausibly results from an ongoing immune tolerance process to antigens in utero, however, a complete explanation of this immune process remains a question for further research, as does the precise role of protective maternal antibodies. Preventive interventions against PAM modify foetal exposure to P. falciparum in utero, and have thus an effect on perinatal malaria outcomes. Effective intermittent preventive treatment in pregnancy (IPTp) diminishes placental malaria (PM) and its subsequent malaria-associated morbidity. However, emerging resistance to sulphadoxine-pyrimethamine (SP) is currently hindering the efficacy of IPTp regimes and the efficacy of alternative strategies, such as intermittent screening and treatment (IST), has not been accurately evaluated in different transmission settings. Due to the increased risk of clinical malaria for offspring of malaria infected mothers, PAM preventive interventions should ideally start during the preconceptual period. Innovative research examining the effect of PAM on the neurocognitive development of the infant, as well as examining the potential influence of HLA-G polymorphisms on malaria symptoms, is urged to contribute to a better understanding of PAM and infant health.

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In areas with regular fishing coastal fleets seabirds may benefit from the predictability of discards from fishing vessels, but it is not clear to what extent birds rely on this predictable resource and whether foraging is synchronized with the diel availability of discards. In this paper we investigate if a typical scavenger species, the yellow‐legged gull Larus michahellis, takes advantage of the temporal and spatial predictability of fish discards in the western Mediterranean Sea. The activity and distribution of the trawling fleet in this area is regulated and very predictable in time and space. We gathered aerial survey data across a relatively large area close to the coast to study the spatial distribution and density of L. michahellis, and modelled the density distribution of the species in relation to several oceanographic, ecological and temporal variables, using two different modelling approaches: MARS (multivariate adaptative regression splines) and GLM (generalized linear models). Our models suggest that the spatial density of trawlers at sea and the time of the day are the best explanatory variables of gull distribution, and that gulls concentrate in areas with vessels mainly during fish discarding time, supporting the hypothesis that gulls optimize time foraging to take advantage of fishery waste predictability. Additional surveys from the main gull roosting sites inshore support this hypothesis, as gulls start leaving to the sea just before fishing is completed and vessels begin discarding fish scraps when back to the harbour. This study represents one of the few examples of applying MARS to density distribution modelling, although its application to marine ecosystems should be conducted with caution because of large areas with real absence data. GLMs have shown to be more adaptable to such kind of data. Our data confirm the importance of fishery waste for L. michahellis, not only as a food resource but also as a major driver of their activity and distribution patterns. The ability of seabirds to predict accurately when a food resource will be available implies that modelling their distribution at sea needs to include such variables, both in spatial and temporal dimensions.

We investigate the use of a partial likelihood for estimation of the parameters of interest in spatio-temporal point-process models. We identify an important distinction between spatially discrete and spatially continuous models. We focus our attention on the spatially continuous case, which has not previously been considered. We use an inhomogeneous Poisson process and an infectious disease process, for which maximum-likelihood estimation is tractable, to assess the relative efficiency of partial versus full likelihood, and to illustrate the relative ease of implementation of the former. We apply the partial-likelihood method to a study of the nesting pattern of common terns in the Ebro Delta Natural Park, Spain.