The “dilution effect” implies that where species vary in susceptibility to infection by a pathogen, higher diversity often leads to lower infection prevalence in hosts. For directly transmitted pathogens, non-host species may “dilute” infection directly (1) and indirectly (2). Competitors and predators may (1) alter host behavior to reduce pathogen transmission or (2) reduce host density. In a well-studied system, we tested the dilution of the zoonotic Puumala hantavirus (PUUV) in bank voles (Myodes glareolus) by two competitors and a predator. Our study was based on long-term PUUV infection data (2003–2013) in northern Sweden. The field vole (Microtus agrestis) and the common shrew (Sorex araneus) are bank vole competitors and Tengmalm’s owl (Aegolius funereus) is a main predator of bank voles. Infection probability in bank voles decreased when common shrew density increased, suggesting that common shrews reduced PUUV transmission. Field voles suppressed bank vole density in meadows and clear-cuts and indirectly diluted PUUV infection. Further, Tengmalm’s owl decline in 1980–2013 may have contributed to higher PUUV infection rates in bank voles in 2003–2013 compared to 1979–1986. Our study provides further evidence for dilution effect and suggests that owls may have an important role in reducing disease risk.

Residents of urban slums suffer from a high burden of zoonotic diseases due to individual, socioeconomic, and environmental factors. We conducted a cross-sectional sero-survey in four urban slums in Salvador, Brazil, to characterize how poverty and sanitation contribute to the transmission of rat-borne leptospirosis. Sero-prevalence in the 1,318 participants ranged between 10.0 and 13.3%. We found that contact with environmental sources of contamination, rather than presence of rat reservoirs, is what leads to higher risk for residents living in areas with inadequate sanitation. Further, poorer residents may be exposed away from the household, and ongoing governmental interventions were not associated with lower transmission risk. Residents at higher risk were aware of their vulnerability, and their efforts improved the physical environment near their household, but did not reduce their infection chances. This study highlights the importance of understanding the socioeconomic and environmental determinants of risk, which ought to guide intervention efforts.

Human encroachment on wildlife habitats has contributed to the emergence of several zoonoses. Pathogenic hantaviruses are hosted by rodents and cause severe diseases in the Americas and Eurasia. We reviewed several factors that potentially drive prevalence (the proportion of infected rodents) in host populations. These include demography, behavior, host density, small mammal diversity, predation, and habitat and landscape characteristics. This review is the first to include a quantitative summary of the literature investigating hantavirus prevalence in rodents. Demographic structure and density were investigated the most and predation the least. Reported effects of demographic structure and small mammal diversity were consistent, whereby reproductive males were most likely to be infected and prevalence decreased with small mammal diversity. The influences of habitat and landscape properties are often complex and indirect. The relationship between density and prevalence merits more investigation. Most hantavirus hosts are habitat generalists and their control is challenging. Incorporating all potential factors and their interactions is essential to understanding and controlling infection in host populations.

Pathogenic hantaviruses (family Bunyaviridae, genus Hantavirus) are rodent-borne viruses causing hemorrhagic fever with renal syndrome (HFRS) in Eurasia. In Europe, there are more than 10,000 yearly cases of nephropathia epidemica (NE), a mild form of HFRS caused by Puumala virus (PUUV). The common and widely distributed bank vole (Myodes glareolus) is the host of PUUV. In this study, we aim to explain and predict NE incidence in boreal Sweden using bank vole densities. We tested whether the number of rainy days in winter contributed to variation in NE incidence. We forecast NE incidence in July 2013–June 2014 using projected autumn vole density, and then considering two climatic scenarios: 1) rain-free winter and 2) winter with many rainy days. Autumn vole density was a strong explanatory variable of NE incidence in boreal Sweden in 1990–2012 (R2 = 79%, p<0.001). Adding the number of rainy winter days improved the model (R2 = 84%, p<0.05). We report for the first time that risk of NE is higher in winters with many rainy days. Rain on snow and ground icing may block vole access to subnivean space. Seeking refuge from adverse conditions and shelter from predators, voles may infest buildings, increasing infection risk. In a rainy winter scenario, we predicted 812 NE cases in boreal Sweden, triple the number of cases predicted in a rain-free winter in 2013/2014. Our model enables identification of high risk years when preparedness in the public health sector is crucial, as a rainy winter would accentuate risk.

Long‐term decline and depression of density in cyclic small rodents is a recent widespread phenomenon. These observed changes at the population level might have cascading effects at the ecosystem level. Here, we assessed relationships between changing boreal landscapes and biodiversity changes of small mammal communities. We also inferred potential effects of observed community changes for increased transmission risk of Puumala virus (PUUV) spread, causing the zoonotic disease nephropatica epidemica in humans. Analyses were based on long‐term (1971–2013) monitoring data of shrews and voles representing 58 time series in northern Sweden. We calculated richness, diversity, and evenness at alpha, beta, and gamma level, partitioned beta diversity into turnover (species replacement) and nestedness (species addition/removal), used similarity percentages (SIMPER) analysis to assess community structure, and calculated the cumulated number of PUUV‐infected bank voles and average PUUV prevalence (percentage of infected bank voles) per vole cycle. Alpha, beta, and gamma richness and diversity of voles, but not shrews, showed long‐term trends that varied spatially. The observed patterns were associated with an increase in community contribution of bank vole (Myodes glareolus), a decrease of gray‐sided vole (M. rufocanus) and field vole (Microtus agrestis) and a hump‐shaped variation in contribution of common shrew (Sorex araneus). Long‐term biodiversity changes were largely related to changes in forest landscape structure. Number of PUUV‐infected bank voles in spring was negatively related to beta and gamma diversity, and positively related to turnover of shrews (replaced by voles) and to community contribution of bank voles. The latter was also positively related to average PUUV prevalence in spring. We showed that long‐term changes in the boreal landscape contributed to explain the decrease in biodiversity and the change in structure of small mammal communities. In addition, our results suggest decrease in small mammal diversity to have knock‐on effects on dynamics of infectious diseases among small mammals with potential implications for disease transmission to humans.

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.

Abstract. Zoonoses are major contributors to emerging infectious diseases globally. Hemorrhagic fever with renal syndrome (HFRS) is a zoonosis caused by rodent-borne hantaviruses. In Europe, Puumala hantavirus (PUUV) carried and shed by the bank vole (Myodes glareolus), is the most common cause of HFRS. We explore the relationship of PUUV infection in bank voles, as measured by PUUV antibody detection, with habitat and landscape scale properties during two successive vole cycles in boreal Sweden. Our analysis revealed that PUUV infection in the population was not uniform between cycles and across different landscapes. The mean density index of PUUV antibody positive and negative bank voles were highest in old forest, second highest in cut-over forest (approx. 0-30 years old) and lowest on mires. Most importantly, old forest was the core habitat, where PUUV antibody positive bank voles were found through the low density phase and the transition between successive vole cycles. In spring, occurrence of antibody positive voles was negatively related to the proportion of cut-over forest in the surrounding landscape, suggesting that large scale human induced land-use change altered the occurrence of PUUV infection in voles which has not been shown before. Dependence of PUUV infection on habitat and landscape structure, and the variation in infection load within and between cycles are of importance for human risk assessment.

Predicting risk of zoonotic diseases, i.e., diseases shared by humans and animals, is often complicated by the population ecology of wildlife host(s). We here demonstrate how ecological knowledge of a disease system can be used for early prediction of human risk using Puumala hantavirus (PUUV) in bank voles (Myodes glareolus), which causes Nephropathia epidemica (NE) in humans, as a model system. Bank vole populations at northern latitudes exhibit multiannual fluctuations in density and spatial distribution, a phenomenon that has been studied extensively. Nevertheless, existing studies predict NE incidence only a few months before an outbreak. We used a time series on cyclic bank vole population density (1972–2013), their PUUV infection rates (1979–1986; 2003–2013), and NE incidence in Sweden (1990–2013). Depending on the relationship between vole density and infection prevalence (proportion of infected animals), either overall density of bank voles or the density of infected bank voles may be used to predict seasonal NE incidence. The density and spatial distribution of voles at density minima of a population cycle contribute to the early warning of NE risk later at its cyclic peak. When bank voles remain relatively widespread in the landscape during cyclic minima, PUUV can spread from a high baseline during a cycle, culminating in high prevalence in bank voles and potentially high NE risk during peak densities.