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Leptospirosis is a zoonosis caused by pathogenic species of bacteria belonging to the genus Leptospira. Most studies infer the epidemiological patterns of a single serogroup or aggregate all serogroups to estimate overall seropositivity, thus not exploring the risks of exposure to distinct serogroups. The present study aims to delineate the demographic, socioeconomic and environmental factors associated with seropositivity of Leptospira serogroup Icterohaemorraghiae and serogroup Cynopteri in an urban high transmission setting for leptospirosis in Brazil. We performed a cross-sectional serological study in five informal urban communities in the city of Salvador, Brazil. During the years 2018, 2020 2021, we recruited 2.808 residents and collected blood samples for serological analysis using microagglutination assays. We used a fixed-effect multinomial logistic regression model to identify risk factors associated with seropositivity for each serogroup. Seropositivity to Cynopteri increased with each year of age (OR 1.03; 95% CI 1.01-1.06) and was higher in those living in houses with unplastered walls (exposed brick) (OR 1.68; 95% CI 1.09-2.59) and where cats were present near the household (OR 2.00; 95% CI 1.03-3.88). Seropositivity to Icterohaemorrhagiae also increased with each year of age (OR 1.02; 95% CI 1.01-1.03) and was higher in males (OR 1.51; 95% CI 1.09-2.10), in those with work-related exposures (OR 1.71; 95% CI 1.10-2.66) or who had contact with sewage (OR 1.42; 95% CI 1.00-2.03). Spatial analysis showed differences in distribution of seropositivity to serogroups Icterohaemorrhagiae and Cynopteri within the five districts where study communities were situated. Our data suggest distinct epidemiological patterns associated with the Icterohaemorrhagiae and Cynopteri serogroups in the urban environment at high risk for leptospirosis and with differences in spatial niches. We emphasize the need for studies that accurately identify the different pathogenic ser

Apicomplexans are a protozoan phylum of obligate parasites which may be highly viru-lent during acute infections, but may also persist as chronic infections which appear tohave little fitness cost. Babesia microti is an apicomplexan haemoparasite that, in im-munocompromised individuals, can cause severe, potentially fatal disease. However,in its natural host, wild field voles (Microtus agrestis), it exhibits chronic infections thathave no detectable impact on survival or female fecundity. How is damage minimized,and what is the impact on the host's immune state and health? We examine the dif-ferences in immune state (here represented by expression of immune-related genesin multiple tissues) associated with several common chronic infections in a populationof wild field voles. While some infections show little impact on immune state, wefind strong associations between immune state and B. microti. These include indi-cations of clearance of infected erythrocytes (increased macrophage activity in thespleen) and activity likely associated with minimizing damage from the infection (anti-inflammatory and antioxidant activity in the blood). By analysing gene expressionfrom the same individuals at multiple time points, we show that the observed changesare a response to infection, rather than a risk factor. Our results point towards con-tinual investment to minimize the damage caused by the infection. Thus, we shed lighton how wild animals can tolerate some chronic infections, but emphasize that thistolerance does not come without a cost., Natural Environment Research Council, Depto. de Biodiversidad, Ecología y Evolución, Fac. de Ciencias Biológicas, TRUE, pub

A key requirement in studies of endemic vector-borne or zoonotic disease is an estimate of the spatial variation in vector or reservoir host abundance. For many vector species, multiple indices of abundance are available, but current approaches to choosing between or combining these indices do not fully exploit the potential inferential benefits that might accrue from modelling their joint spatial distribution. Here, we develop a class of multivariate generalized linear geostatistical models for multiple indices of abundance. We illustrate this novel methodology with a case study on Norway rats in a low-income urban Brazilian community, where rat abundance is a likely risk factor for human leptospirosis. We combine three indices of rat abundance to draw predictive inferences on a spatially continuous latent process, rattiness, that acts as a proxy for abundance. We show how to explore the association between rattiness and spatially varying environmental factors, evaluate the relative importance of each of the three contributing indices and assess the presence of residual, unexplained spatial variation, and identify rattiness hotspots. The proposed methodology is applicable more generally as a tool for understanding the role of vector or reservoir host abundance in predicting spatial variation in the risk of human disease.