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The authors develop a multi-type branching process model of the 2014 Liberian Ebola outbreak that incorporates the impacts of changes in behavior on potential transmission scenarios, thereby informing the path to containment of the epidemic.

BackgroundYellow fever virus is a mosquito-borne flavivirus that persists in an enzoonotic cycle in non-human primates (NHPs) in Brazil, causing disease in humans through spillover events. Yellow fever (YF) re-emerged in the early 2000s, spreading from the Amazon River basin towards the previously considered low-risk, southeastern region of the country. Previous methods mapping YF spillover risk do not incorporate the temporal dynamics and ecological context of the disease, and are therefore unable to predict seasonality in spatial risk across Brazil. We present the results of a bagged logistic regression predicting the propensity for YF spillover per municipality (administrative sub-district) in Brazil from environmental and demographic covariates aggregated by month. Ecological context was incorporated by creating National and Regional models of spillover dynamics, where the Regional model consisted of two separate models determined by the regions’ NHP reservoir species richness (high vs low).ResultsOf the 5560 municipalities, 82 reported YF cases from 2001 to 2013. Model accuracy was high for the National and low reservoir richness (LRR) models (AUC = 0.80), while the high reservoir richness (HRR) model accuracy was lower (AUC = 0.63). The National model predicted consistently high spillover risk in the Amazon, while the Regional model predicted strong seasonality in spillover risk. Within the Regional model, seasonality of spillover risk in the HRR region was asynchronous to the LRR region. However, the observed seasonality of spillover risk in the LRR Regional model mirrored the national model predictions.ConclusionsThe predicted risk of YF spillover varies with space and time. Seasonal trends differ between regions indicating, at times, spillover risk can be higher in the urban coastal regions than the Amazon River basin which is counterintuitive based on current YF risk maps. Understanding the spatio-temporal patterns of YF spillover risk could better inform allocation of public health services.Electronic supplementary materialThe online version of this article (10.1186/s13071-018-3063-6) contains supplementary material, which is available to authorized users.

Microbial populations can be dispersal limited. However, microorganisms that successfully disperse into physiologically ideal environments are not guaranteed to establish. This observation contradicts the Baas-Becking tenet: ‘Everything is everywhere, but the environment selects’. Allee effects, which manifest in the relationship between initial population density and probability of establishment, could explain this observation. Here, we experimentally demonstrate that small populations of Vibrio fischeri are subject to an intrinsic demographic Allee effect. Populations subjected to predation by the bacterivore Cafeteria roenbergensis display both intrinsic and extrinsic demographic Allee effects. The estimated critical threshold required to escape positive density-dependence is around 5, 20 or 90 cells ml −1 under conditions of high carbon resources, low carbon resources or low carbon resources with predation, respectively. This work builds on the foundations of modern microbial ecology, demonstrating that mechanisms controlling macroorganisms apply to microorganisms, and provides a statistical method to detect Allee effects in data.

White-nose syndrome (WNS) is an emerging infectious disease that has resulted in severe declines of its hibernating bat hosts in North America. The ongoing epidemic of white-nose syndrome is a multi-scale phenomenon becau.se it causes hibernaculum-level extirpations, while simultaneously spreading over larger spatial scales. We investigate a neglected topic in ecological epidemiology: how local pathogen-driven extirpations impact large-scale pathogen spread. Previous studies have identified risk factors for propagation of WNS over hibernaculum and landscape scales but none of these have tested the hypothesis that separation of spatial scales and disease-induced mortality at the hibernaculum level might slow or halt its spread. To test this hypothesis, we developed a mechanistic multi-scale model parameterized using white-nose syndrome.county and site incidence data that connects hibernaculum-level susceptible-infectious-removed (SIR) epidemiology to the county-scale contagion process. Our key result is that hibernaculum-level extirpations will not inhibit county-scale spread of WNS. We show that over 80% of counties of the contiguous USA are likely to become infected before the current epidemic is over and that geometry of habitat connectivity is such that host refuges are exceedingly rare. The macroscale spatiotemporal infection pattern that emerges from local SIR epidemiological processes falls within a narrow spectrum of possible outcomes, suggesting that recolonization, rescue effects, and multi-host complexities at local scales are not important to forward propagation of WNS at large spatial scales. If effective control measures are not implemented, precipitous declines in bat populations are likely, particularly in cave-dense regions that constitute the main geographic corridors of the USA, a serious concern for bat conservation.