Cross-species pathogen spillover across ecosystem boundaries: mechanisms and theory

Pathogen spillover between different host species is the trigger for many infectious disease outbreaks and emergence events, and ecosystem boundary areas have been suggested as spatial hotspots of spillover. This hypothesis is largely based on suspected higher rates of zoonotic disease spillover and emergence in fragmented landscapes and other areas where humans live in close vicinity to wildlife. For example, Ebola virus outbreaks have been linked to contacts between humans and infected wildlife at the rural-forest border, and spillover of yellow fever via mosquito vectors happens at the interface between forest and human settlements. Because spillover involves complex interactions between multiple species and is difficult to observe directly, empirical studies are scarce, particularly those that quantify underlying mechanisms. In this review, we identify and explore potential ecological mechanisms affecting spillover of pathogens (and parasites in general) at ecosystem boundaries. We borrow the concept of ‘permeability’ from animal movement ecology as a measure of the likelihood that hosts and parasites are present in an ecosystem boundary region. We then discuss how different mechanisms operating at the levels of organisms and ecosystems might affect permeability and spillover. This review is a step towards developing a general theory of cross-species parasite spillover across ecosystem boundaries with the eventual aim of improving predictions of spillover risk in heterogeneous landscapes

Big-data-driven modeling unveils country-wide drivers of endemic schistosomiasis

Schistosomiasis is a parasitic infection that is widespread in sub-Saharan Africa, where it represents a major health problem. We study the drivers of its geographical distribution in Senegal via a spatially explicit network model accounting for epidemiological dynamics driven by local socioeconomic and environmental conditions, and human mobility. The model is parameterized by tapping several available geodatabases and a large dataset of mobile phone traces. It reliably reproduces the observed spatial patterns of regional schistosomiasis prevalence throughout the country, provided that spatial heterogeneity and human mobility are suitably accounted for. Specifically, a fine-grained description of the socioeconomic and environmental heterogeneities involved in local disease transmission is crucial to capturing the spatial variability of disease prevalence, while the inclusion of human mobility significantly improves the explanatory power of the model. Concerning human movement, we find that moderate mobility may reduce disease prevalence, whereas either high or low mobility may result in increased prevalence of infection. The effects of control strategies based on exposure and contamination reduction via improved access to safe water or educational campaigns are also analyzed. To our knowledge, this represents the first application of an integrative schistosomiasis transmission model at a whole-country scale

The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

AbstractSchistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations

Solitary wave trains in granular chains: Experiments, theory and simulations

The features of solitary waves observed in horizontal monodisperse chain of barely touching beads not only depend on geometrical and material properties of the beads but also on the initial perturbation provided at the edge of the chain. An impact of a large striker on a monodisperse chain, and similarly a sharp decrease of bead radius in a stepped chain, generates a solitary wave train containing many single solitary waves ordered by decreasing amplitudes. We find, by simple analytical arguments, that the unloading of compression force at the chain edge has a nearly exponential decrease. The characteristic time is mainly a function involving the grains' masses and the striker mass. Numerical calculations and experiments corroborate these findings.Comment: The original publication is available at http://www.springerlink.com (related papers at http://www.supmeca.fr/perso/jobs

Reframing Optimal Control Problems for Infectious Disease Management in Low-Income Countries

Optimal control theory can be a useful tool to identify the best strategies for the management of infectious diseases. In most of the applications to disease control with ordinary differential equations, the objective functional to be optimized is formulated in monetary terms as the sum of intervention costs and the cost associated with the burden of disease. We present alternate formulations that express epidemiological outcomes via health metrics and reframe the problem to include features such as budget constraints and epidemiological targets. These alternate formulations are illustrated with a compartmental cholera model. The alternate formulations permit us to better explore the sensitivity of the optimal control solutions to changes in available budget or the desired epidemiological target. We also discuss some limitations of comprehensive cost assessment in epidemiology

Ecological interventions to prevent and manage zoonotic pathogen spillover

Spillover of a pathogen from awildlife reservoir into a human or livestock host requires the pathogen to overcome a hierarchical series of barriers. Interventions aimed at one or more of these barriers may be able to prevent the occurrence of spillover. Here, we demonstrate how interventions that target the ecological context in which spillover occurs (i.e. ecological interventions) can complement conventional approaches like vaccination, treatment, disinfection and chemical control. Accelerating spillover owing to environmental change requires effective, affordable, durable and scalable solutions that fully harness the complex processes involved in cross-species pathogen spillover. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’

Gene drives for schistosomiasis transmission control.

Schistosomiasis is one of the most important and widespread neglected tropical diseases (NTD), with over 200 million people infected in more than 70 countries; the disease has nearly 800 million people at risk in endemic areas. Although mass drug administration is a cost-effective approach to reduce occurrence, extent, and severity of the disease, it does not provide protection to subsequent reinfection. Interventions that target the parasites' intermediate snail hosts are a crucial part of the integrated strategy required to move toward disease elimination. The recent revolution in gene drive technology naturally leads to questions about whether gene drives could be used to efficiently spread schistosome resistance traits in a population of snails and whether gene drives have the potential to contribute to reduced disease transmission in the long run. Responsible implementation of gene drives will require solutions to complex challenges spanning multiple disciplines, from biology to policy. This Review Article presents collected perspectives from practitioners of global health, genome engineering, epidemiology, and snail/schistosome biology and outlines strategies for responsible gene drive technology development, impact measurements of gene drives for schistosomiasis control, and gene drive governance. Success in this arena is a function of many factors, including gene-editing specificity and efficiency, the level of resistance conferred by the gene drive, how fast gene drives may spread in a metapopulation over a complex landscape, ecological sustainability, social equity, and, ultimately, the reduction of infection prevalence in humans. With combined efforts from across the broad global health community, gene drives for schistosomiasis control could fortify our defenses against this devastating disease in the future

Averting wildlife-borne infectious disease epidemics requires a focus on socio-ecological drivers and a redesign of the global food system.

A debate has emerged over the potential socio-ecological drivers of wildlife-origin zoonotic disease outbreaks and emerging infectious disease (EID) events. This Review explores the extent to which the incidence of wildlife-origin infectious disease outbreaks, which are likely to include devastating pandemics like HIV/AIDS and COVID-19, may be linked to excessive and increasing rates of tropical deforestation for agricultural food production and wild meat hunting and trade, which are further related to contemporary ecological crises such as global warming and mass species extinction. Here we explore a set of precautionary responses to wildlife-origin zoonosis threat, including: (a) limiting human encroachment into tropical wildlands by promoting a global transition to diets low in livestock source foods; (b) containing tropical wild meat hunting and trade by curbing urban wild meat demand, while securing access for indigenous people and local communities in remote subsistence areas; and (c) improving biosecurity and other strategies to break zoonosis transmission pathways at the wildlife-human interface and along animal source food supply chains

Women, but not men, have prolonged QT interval if depressed after an acute coronary syndrome

Aims Depression is a mortality risk marker for acute coronary syndrome (ACS) patients. We hypothesized that the QT interval, a predictor for risk of sudden cardiac death, was related to depressive symptoms in ACS. Methods and results We performed an analysis of admission electrocardiograms from hospitalized patients with unstable angina or non-ST elevation myocardial infarction from two prospective observational studies of depression in ACS. Depressive symptoms were assessed with the Beck Depression Inventory (BDI), and depression was defined as BDI score ≥10, compared with <5. Patients with QRS duration ≥120 ms and/or who were prescribed antidepressants were excluded. QT intervals were adjusted for heart rate by two methods. Our analyses included 243 men (40.0% with BDI ≥10) and 139 women (62.0% with BDI ≥ 10). Among women, average QT corrected by Fridericia's method (QTcF) was 435.4 ± 26.6 ms in the depressed group, vs. 408.6 ± 24.3 ms in the non-depressed group (P< 0.01). However, among men, average QTcF was not significantly different between the depressed and non-depressed groups (415.4 ± 23.6 vs. 412.0 ± 25.8 ms, P= 0.29). In multivariable analyses that included hypertension, diabetes, ACS type, left ventricular ejection fraction <0.40, and use of QT-prolonging medication, there was a statistically significant interaction between depressive symptoms and gender (P< 0.001). Conclusions In this ACS sample, prolongation of the QT interval was associated with depressive symptoms in women, but not in men. Further investigation of the mechanism of the relationship between depression and abnormal cardiac repolarization, particularly in women, is warranted to develop treatment strategies

Predictive Power of Air Travel and Socio-Economic Data for Early Pandemic Spread

Controlling the pandemic spread of newly emerging diseases requires rapid, targeted allocation of limited resources among nations. Critical, early control steps would be greatly enhanced if the key risk factors can be identified that accurately predict early disease spread immediately after emergence.Here, we examine the role of travel, trade, and national healthcare resources in predicting the emergence and initial spread of 2009 A/H1N1 influenza. We find that incorporating national healthcare resource data into our analyses allowed a much greater capacity to predict the international spread of this virus. In countries with lower healthcare resources, the reporting of 2009 A/H1N1 cases was significantly delayed, likely reflecting a lower capacity for testing and reporting, as well as other socio-political issues. We also report substantial international trade in live swine and poultry in the decade preceding the pandemic which may have contributed to the emergence and mixed genotype of this pandemic strain. However, the lack of knowledge of recent evolution of each H1N1 viral gene segment precludes the use of this approach to determine viral origins.We conclude that strategies to prevent pandemic influenza virus emergence and spread in the future should include: 1) enhanced surveillance for strains resulting from reassortment in traded livestock; 2) rapid deployment of control measures in the initial spreading phase to countries where travel data predict the pathogen will reach and to countries where lower healthcare resources will likely cause delays in reporting. Our results highlight the benefits, for all parties, when higher income countries provide additional healthcare resources for lower income countries, particularly those that have high air traffic volumes. In particular, international authorities should prioritize aid to those poorest countries where both the risk of emerging infectious diseases and air traffic volume is highest. This strategy will result in earlier detection of pathogens and a reduction in the impact of future pandemics