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Current flood risk mapping, relying on historical observations, fails to account for increasing threat under climate change. Incorporating recent developments in inundation modelling, here we show a 26.4% (24.1–29.1%) increase in US flood risk by 2050 due to climate change alone under RCP4.5. Our national depiction of comprehensive and high-resolution flood risk estimates in the United States indicates current average annual losses of US$32.1 billion (US$30.5–33.8 billion) in 2020’s climate, which are borne disproportionately by poorer communities with a proportionally larger White population. The future increase in risk will disproportionately impact Black communities, while remaining concentrated on the Atlantic and Gulf coasts. Furthermore, projected population change (SSP2) could cause flood risk increases that outweigh the impact of climate change fourfold. These results make clear the need for adaptation to flood and emergent climate risks in the United States, with mitigation required to prevent the acceleration of these risks.

The flooding brought about by compound coastal flooding events can be devastating. Before, during, and immediately following these events, flood inundation maps (FIMs) can provide essential information to emergency management. However, there are a number of frameworks capable of estimating FIMs during flood events. In this article, we evaluate FIMs derived from three such frameworks in the context of Hurricane Harvey. Our analysis reveals that each of the three FIM frameworks provides different FIMs that differ in their level of accuracy. Each of the three FIMs also produces different exposure and consequence estimates because of their spatial differences. This investigation highlights the need for a centralized means of vetting and adjudicating multiple FIMs during compound flood events empowered by the ability to distribute FIMs as geographic information system (GIS) services and coalesce FIMs into a common operating picture. Furthermore, we provide evidence that the ability to produce multi-model estimates of FIMs to create probabilistic FIMs may provide a better product than the use of a lone FIM.

Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and census tract socio-economic data, we then describe the socio-spatial characteristics associated with these climate change-induced impacts. We show that 30 to 50% of the flooded properties would not have flooded without climate change. Climate change-attributed impacts were particularly felt in Latina/x/o neighborhoods, and especially so in Latina/x/o neighborhoods that were low-income and among those located outside of FEMA’s 100-year floodplain. Our focus is thus on climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.

In this paper we seek to understand the nature of flood spatial dependence over the conterminous United States. We extend an existing conditional multivariate statistical model to enable its application to this large and heterogenous region and apply it to a 40-year data set of ~2,400 U.S. Geological Survey gauge series records to simulate 1,000 years of U.S. flooding comprising more than 63,000 individual events with realistic spatial dependence. A continental-scale hydrodynamic model at 30 m resolution is then used to calculate the economic loss arising from each of these events. From this we are able to compute the probability that different values of U.S. annual total economic loss due to flooding are exceeded (i.e., a loss-exceedance curve). Comparing these data to an observed flood loss-exceedance curve for the period 1988–2017 shows a reasonable match for annual losses with probability below 10% (e.g., >1 in 10-year return period). This analysis suggests that there is a 1% chance of U.S. annual fluvial flood losses exceeding $78Bn in any given year, and a 0.1% chance of them exceeding $136Bn. Analysis of the set of stochastic events and losses yields new insights into the nature of flooding and flood risk in the United States. In particular, we confirm the strong relationship between flood affected area and event peak magnitude, but show considerable variability in this relationship between adjacent U.S. regions. The analysis provides a significant advance over previous national flood risk analyses as it gives the full loss-exceedance curve instead of simply the average annual loss.

A national depiction of high-resolution flood risk estimates has previously been thought to be beyond the grasp of reasonable computational capabilities. However, recent developments in inundation modelling now permit the first comprehensive national flood risk assessment of the US, which indicates an expected annual direct damage to property of 27 billion USD in 2020’s climate. Current flood risk is disproportionately borne by poorer and more White communities, and is concentrated on the Atlantic and Gulf coasts, the Northeast through Appalachia, and the Pacific Northwest. Under a medium-case concentration pathway (RCP4.5), we project a 37% increase in risk by 2050 due to climate change alone. This climate signal appears to disproportionately impact Black communities, with risk increases concentrated again on the Atlantic and Gulf coasts. Medium-case (SSP2) projections of population change cause flood risk increases that dwarf the impact of climate change by 4:1, illustrating the need for a holistic view on changes in risk with consideration of all its constituent causes. These results make clear the desperate need for adaptation to flood and emergent climate risks in the US, with mitigation required to prevent acceleration of this risk into the latter half of the century. These results can and should inform zoning, regulations, and targeted adaptation policies, as well as motivate wide reaching reforms in how flood risk and emergencies are managed.

This talk reports a new and significantly enhanced analysis of US flood hazard at 30m spatial resolution. For the first time we consider pluvial, fluvial and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centred on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high quality local models and the entire catalogue of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69-0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near future time horizon we project clear patterns of changing flood hazard (3σ changes in 100yr inundated area of -3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defence protection may become compromised by this time.

The execution of large-scale (i.e., continental or global) hydraulic modeling is nowadays a reality thanks to the increasing computational capacity, data availability, as well as understanding of essential physical dynamics. Such achievements are typically associated to a compromise in terms of model resolutions (the finer being of few tens of meters, with a coarsened representation of the terrain) and, thus, accuracy on representing the topographic peculiarities of the flood-prone areas. Nevertheless, the experience gained observing the dynamics of past inundations highlights the role of small-scale topographic features (e.g., minor embankments, road deck, railways, etc.) in driving the flow paths. Recent advances on automated identification of flood defense from high resolution digital elevation model paved the way to include hydraulically relevant features (e.g., main levees) while preserving the model resolution suitable for large-scale applications (Wing et al, 2020). The present study extends this approach to flood-prone areas by investigating how the automatic detection of minor topographic discontinuities can enhance the estimation of flood dynamics of large-scale models. Taking advantage of high-resolution topographic data (i.e., 1-2 m) the approach automatically detects hydraulically relevant features and preserves their height while coarsening the resolution of the terrain used into the hydraulic model. The impact of such approach on the inundation dynamic is tested referring to three different case-studies that recently experienced riverine flooding: Secchia and Enza rivers (2014, 2017, respectively; Italy), Des Moines (Iowa, USA). The results confirm the relevance of small-scale topographic features, which, when considered, ensure a high correspondence to observations and local models. The element of strength of the presented approach is that such performances are ensured without requiring the adoption of high grid resolutions, and thus, not affecting the overall computational costs.

This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel depth, more rigorous flood frequency analysis, output downscaling to property tract level, and inclusion of the impact of local interventions in the flooding system. For the first time, we consider pluvial, fluvial, and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centered on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high-quality local models and the entire catalog of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69–0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high-frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national-scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near-future time horizon, we project clear patterns of changing flood hazard (3σ changes in 100 years inundated area of −3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defense protection may become compromised by this time.

Precipitation extremes are increasing globally due to anthropogenic climate change. However, there remains uncertainty regarding impacts upon flood occurrence and subsequent population exposure. Here, we quantify changes in population exposure to flood hazard across the contiguous United States. We combine simulations from a climate model large ensemble and a high-resolution hydrodynamic flood model—allowing us to directly assess changes across a wide range of extreme precipitation magnitudes and accumulation timescales. We report a mean increase in the 100-year precipitation event of ~20% (magnitude) and >200% (frequency) in a high warming scenario, yielding a ~30-127% increase in population exposure. We further find a non-linear increase for the most intense precipitation events—suggesting accelerating societal impacts from historically rare or unprecedented precipitation events in the 21st century.

Continental–global scale flood hazard models simulate design floods: theoretical flood events of a given probability. Since they output phenomena unobservable in reality, large-scale models are typically compared to more localised engineering models to evidence their accuracy. However, both types of model may share the same biases and so not validly illustrate predictive skill. Here, we adapt an existing continental-scale design flood framework of the contiguous US to simulate historical flood events. 35 discrete events are modelled and compared to observations of flood extent, water level, and inundated buildings. Model performance was highly variable depending on the flood event chosen and validation data used. While all events were accurately replicated in terms of flood extent, some modelled water levels deviated substantially from those measured in the field. In spite of this, the model generally replicated the observed flood events in the context of terrain data vertical accuracy, extreme discharge measurement uncertainties, and observational field data errors. This analysis highlights the continually improving fidelity of large-scale flood hazard models, yet also evidences the need for considerable advances in the accuracy of routinely collected field and high river flow data in order to interrogate flood inundation models more comprehensively.

This paper reports a new and significantly enhanced analysis of US flood hazard at 30m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel d...

Hurricanes and flood-related events cause more direct economic damage than any other type of natural disaster. In the United States, that damage totals more than USD 1 trillion in damages since 1980. On average, direct flood losses have risen from USD 4 billion annually in the 1980s to roughly USD 17 billion annually from 2010 to 2018. Despite flooding&rsquo, s tremendous economic impact on US properties and communities, current estimates of expected damages are lacking due to the fact that flood risk in many parts of the US is unidentified, underestimated, or available models associated with high quality assessment tools are proprietary. This study introduces an economic-focused Environmental Impact Assessment (EIA) approach that builds upon an our existing understanding of prior assessment methods by taking advantage of a newly available, climate adjusted, parcel-level flood risk assessment model (First Street Foundation, 2020a and 2020b) in order to quantify property level economic impacts today, and into the climate adjusted future, using the Intergovernmental Panel on Climate Change&rsquo, s (IPCC) Representative Concentration Pathways (RCPs) and NASA&rsquo, s Global Climate Model ensemble (CMIP5). This approach represents a first of its kind&mdash, a publicly available high precision flood risk assessment tool at the property level developed completely with open data sources and open methods. The economic impact assessment presented here has been carried out using residential buildings in New Jersey as a testbed, however, the environmental assessment tool on which it is based is a national scale property level flood assessment model at a 3m resolution. As evidence of the reliability of the EIA tool, the 2020 estimated economic impact (USD 5481 annual expectation) was compared to actual average per claim-year NFIP payouts from flooding and found an average of USD 5540 over the life of the program (difference of less than USD 100). Additionally, the tool finds a 41.4% increase in average economic flood damage through the year 2050 when environmental change is included in the model.

Hydraulic modelling at large spatial scales is a field of enquiry approaching a state of maturity, with the flood maps produced beginning to inform wide-area planning decisions, insurance pricing and emergency response. These maps, however, are typically ‘static’; that is, are a spatially homogeneous representation of a given probability flood. Actual floods vary in their extremity across space: if a given location is extreme, you may expect proximal locations to be similarly extreme and distal locations to be decreasingly extreme. Methods to account for this stochastically can, broadly speaking, be split into: (i) continuous simulation via a meteorological-hydrological-hydraulic model cascade and (ii) fitting statistical dependence models to samples of river gauges, generating a synthetic event set of streamflows and simulating the hydraulics from these. The former has the benefit of total spatial coverage, but the drawbacks of high computational cost and the low skill of large-scale hydrological models in simulating absolute river discharge. The latter enables higher-fidelity hydraulics in simulating the extremes only and with more accurately defined boundary conditions, yet it is only possible to execute (ii) in gauge-rich regions – excluding most of the planet.In this work, we demonstrate that a hybrid approach of (i) & (ii) offers a promising path forward for stochastic flood modelling in gauge-poor areas. Inputting simulated streamflows from large-scale hydrological models to a conditional exceedance model which characterises the spatial dependence of discharge extremes produces a very different set of plausible flood events than when observed flows are used as boundary conditions. Yet, if the relative exceedance probability of simulated flows – internal to the hydrological model – are used in place of their absolute values (i.e. a return period instead of a value in m3s-1), the observation- and model-based dependence models produce similar events in terms of the spatial distribution of return periods. In the context of flood losses, when using Fathom-US CAT (a state-of-the-art large-scale stochastic flood loss model), the risk of an example portfolio is indistinguishable between the gauge- and model-driven framework given the uncertainty in vulnerability alone. This is providing the model-based event return period is matched up with a hydraulic model of the same return period, yet where the latter is characterised via a gauge-based approach.

Vulnerability functions are applied in flood risk models to calculate the losses incurred when a flood interacts with the built environment. Typically, these take the form of relative depth–damage relationships: flood depths at the location of a particular asset translate to a damage expressed as a certain percentage of its value. Vulnerability functions are a core component of risk and insurance industry catastrophe (CAT) models, permitting physical models of flood inundation under different scenarios (e.g. certain probabilities) to be translated to more tangible and useful estimates of loss. Much attention is devoted to the physical hazard component of flood risk models, but the final vulnerability component has historically received less attention — despite quantifications of risk being highly sensitive to these uncertain depth–damage functions. For the case of US flood risk models, ‘off-the-shelf’ functions from the US Army Corps of Engineers (USACE) are commonly used. In an analysis of roughly 2 million flood claims under the US National Flood Insurance Programme (NFIP), we find these ubiquitous USACE functions are not reflective of real damages at specified flood depths experienced by policy holders of the NFIP. Particularly for smaller flood depths (90% of building values, with the proportion of >90% damages increasing with water depth. The NFIP data also reveal that newer buildings tend to be more resilient (lower damages for a given depth), surface water flooding to be more damaging than fluvial flooding for a given depth, vulnerability to vary dramatically across space, and even the concept of a relative damage to be untenable in its application to expensive properties (e.g. even for depths >1m, properties worth >$250k rarely experience losses >20% of their value). The findings of this study have significant implications for developers of flood risk models, suggesting current estimates of US flood risk (in $ terms) may be substantial over-estimates.

Flood-related events are the most damaging natural hazard in the United States, yet many households at risk do not have flood insurance. Using detailed policy- and claims-level data from the National Flood Insurance Program (NFIP), we conduct a holistic analysis of the market for publicly provided flood insurance in the U.S., focusing on not only high-risk areas subject to an incomplete mandate requiring the purchase of insurance, but also lower risk areas where no such mandate exists. We are able to better understand determinants of demand for insurance in a setting with voluntary purchase and low take-up and therefore provide a more complete analysis of the market for flood insurance in the U.S. than previous work. In addition to exploring correlates of demand for flood insurance, this paper provides quasi-experimental estimates of households’ willingness-to-pay for flood insurance and finds strong evidence to suggest the NFIP failing to utilize full information on flood risk leads to adverse selection in the program.

This paper reports the development of a ∼30 m resolution two-dimensional hydrodynamic model of the conterminous U.S. using only publicly available data. The model employs a highly efficient numerical solution of the local inertial form of the shallow water equations which simulates fluvial flooding in catchments down to 50 km2 and pluvial flooding in all catchments. Importantly, we use the U.S. Geological Survey (USGS) National Elevation Dataset to determine topography; the U.S. Army Corps of Engineers National Levee Database to explicitly represent known flood defenses; and global regionalized flood frequency analysis to characterize return period flows and rainfalls. We validate these simulations against the complete catalogue of Federal Emergency Management Agency (FEMA) Special Flood Hazard Area (SFHA) maps and detailed local hydraulic models developed by the USGS. Where the FEMA SFHAs are based on high-quality local models, the continental-scale model attains a hit rate of 86%. This correspondence improves in temperate areas and for basins above 400 km2. Against the higher quality USGS data, the average hit rate reaches 92% for the 1 in 100 year flood, and 90% for all flood return periods. Given typical hydraulic modeling uncertainties in the FEMA maps and USGS model outputs (e.g., errors in estimating return period flows), it is probable that the continental-scale model can replicate both to within error. The results show that continental-scale models may now offer sufficient rigor to inform some decision-making needs with dramatically lower cost and greater coverage than approaches based on a patchwork of local studies.

Flooding is the costliest form of natural disaster and impacts are expected to increase, in part, due to exposure of new development to flooding. However, these costs could be reduced through the acquisition and conservation of natural land in floodplains. Here we quantify the benefits and costs of reducing future flood damages in the United States by avoiding development in floodplains. We find that by 2070, cumulative avoided future flood damages exceed the costs of land acquisition for more than one-third of the unprotected natural lands in the 100-yr floodplain (areas with a 1% chance of flooding annually). Large areas have an even higher benefit–cost ratio: for 54,433 km2 of floodplain, avoided damages exceed land acquisition costs by a factor of at least five to one. Strategic conservation of floodplains would avoid unnecessarily increasing the economic and human costs of flooding while simultaneously providing multiple ecosystem services. Flooding is the costliest natural disaster. Focusing on the United States, this analysis finds that by 2070 avoided damages exceed land acquisition costs for more than one-third of unprotected natural lands in the 100-year floodplain.

Forecasts of tropical cyclones have seen rapid improvements in recent years as expanding computational capacity permits more runs of finer resolution meteorological models with increasing representation of physical processes. However, the utilization of a hydrodynamic component in these models is often neglected, meaning flood forecasts typically output point water levels that give little indication of a projected inundation extent on the ground. Here, we append this critical component to the forecast cascade by coupling Fathom-US, a continental-scale hydraulic model which employs the LISFLOOD-FP numerical scheme, to forecasts of streamflow, rainfall and coastal surge height from the National Oceanic and Atmospheric Administration (NOAA). Medium-term (2–15 days) flood inundation forecasts, as well as hindcasts driven by real-time observations, were executed for Hurricane Harvey by rapidly simulating pluvial and coastal flood hazard and extracting fluvial flood maps from an existing US-wide simulation library. The resultant ~30 m resolution depth grids were then validated against post-event observations collated by the US Geological Survey. Across the disaster zone, the hindcast (forecast) model captured, on average, 78% (75%) of the benchmark flood extent, obtained a Critical Success Index of 0.66 (0.57) and deviated from observed high water marks by ~1 m (~1.2 m). When compared to a simpler GIS-based approach, the hydraulic model exhibited much higher skill in replicating observations. This study shows that fully hydrodynamic approaches can be practicably employed in large-scale forecast frameworks at high resolution to produce skillful projections of inundation extent without significantly affecting the forecast lead time. Keywords: Flooding, Hydrodynamic modeling, Flood forecasting, Hurricane Harvey, Large-scale modeling, Validation

Current estimates of global flood exposure are made using datasets that distribute population counts homogenously across large lowland floodplain areas. When intersected with simulated water depths, this results in a significant mis-estimation. Here, we use new highly resolved population information to show that, in reality, humans make more rational decisions about flood risk than current demographic data suggest. In the new data, populations are correctly represented as risk-averse, largely avoiding obvious flood zones. The results also show that existing demographic datasets struggle to represent concentrations of exposure, with the total exposed population being spread over larger areas. In this analysis we use flood hazard data from a ~90 m resolution hydrodynamic inundation model to demonstrate the impact of different population distributions on flood exposure calculations for 18 developing countries spread across Africa, Asia and Latin America. The results suggest that many published large-scale flood exposure estimates may require significant revision., Flood risk modelling neglects the location of people and assets. Here the authors applied machine learning techniques and high-resolution population data to reinvestigate the impact of population distributions on flood exposure and showed that populations are generally represented as risk-averse and largely avoiding obvious flood zones.

A frequent barrier to addressing some of our world’s most pressing environmental challenges is a lack of funding. Currently, environmental project funding largely comes from philanthropic and public sources, but this does not meet current needs. Increased coordination and collaboration between multiple levels and sectors of government, in addition to private sector funding, can help address the environmental funding challenge. New financial tools and strategies can enable this transition and facilitate uptake of innovative solutions. One such mechanism, the Environmental Impact Bond (EIB), is an emerging financial tool with the potential to transform the environmental funding landscape. However, these financial instruments are not well understood or recognized beyond those actively involved in EIB projects or in the field of conservation finance. As EIBs gain momentum, there is a clear need for a common framework, including definitions and nomenclature, research needs, and outlook for the future. In this paper, we define EIB mechanics, elucidate the difference between EIBs and Green Bonds, and propose a common vocabulary for the field. Drawing on first-hand experience with the few EIBs which have been deployed, we review and assess lessons learned, trends, and paths for the future. Finally, we propose a set of future targets and discuss research goals for the field to unify around. Through this work, we identify a concrete set of research gaps and objectives, providing evidence for EIBs as one important tool in the environmental finance toolbox.

The execution of hydraulic models at large spatial scales has yielded a step change in our understanding of flood risk. Yet their necessary simplification through the use of coarsened terrain data results in an artificially smooth digital elevation model with diminished representation of flood defense structures. Current approaches in dealing with this, if anything is done at all, involve either employing incomplete inventories of flood defense information or making largely unsubstantiated assumptions about defense locations and standards based on socioeconomic data. Here, we introduce a novel solution for application at scale. The geomorphometric characteristics of defense structures are sampled, and these are fed into a probabilistic algorithm to identify hydraulically relevant features in the source digital elevation model. The elevation of these features is then preserved during the grid coarsening process. The method was shown to compare favorably to surveyed U.S. levee crest heights. When incorporated into a continental-scale hydrodynamic model based on LISFLOOD-FP and compared to local flood models in Iowa (USA), median correspondence was 69% for high-frequency floods and 80% for low-frequency floods, approaching the error inherent in quantifying extreme flows. However, improvements versus a model with no defenses were muted, and risk-based deviations between the local and continental models were large. When simulating an event on the Po River (Italy), built and tested with higher quality data, the method outperformed both undefended and even engineering-grade models. As such, particularly when employed alongside model components of commensurate quality, the method here generates improved-accuracy simulations of flood inundation.

A different modeling approach fills large gaps in the U.S. government's flood risk estimates, revealing previously overlooked at-risk areas often surrounding small flood-prone streams.

Hepatocytes constitute the principal site of listerial replication in the livers of mice infected i.v. CD8+ T lymphocytes play a predominant role in the host defenses to Listeria monocytogenes. In vitro experiments by others undertaken to delineate the functions of CD8+ T lymphocytes have focused primarily on their interaction with Listeria-infected macrophages. Such experiments do not address directly the role of CD8+ T lymphocytes in eliminating the bulk of Listeria replicating within the liver. Here, we report that immune CD8+ T cells at an E:T cell ratio > or = 10:1 lysed Listeria-infected hepatocytes as judged by the following two criteria. Aspartate aminotransferase activity in the culture supernatants, indicative of hepatocyte damage, increased significantly. Conversely, infected hepatocytes cocultured with immune CD8+ T cells exhibited a marked reduction in viable intracellular Listeria assessed by CFUs. Neither immune CD4+ T cells nor nonimmune CD8+ T cells caused a similar increase in aspartate aminotransferase activity released or a decrease in intracellular bacteria. Immune CD8+ T cell-mediated lysis of infected hepatocytes was restricted by classical MHC class I (H-2Kb) molecules and was inhibited by the presence of either brefeldin A or mAb specific for CD8. These results suggest that the predominant role of CD8+ T lymphocytes in host resistance to listerial infections of the liver may be due to their capacity to lyse infected hepatocytes.

The critical role of the liver in the resolution of systemic bacterial infections is well documented. In the case of Listeria monocytogenes, approximately 60% of bacteria inoculated i.v. into mice are recovered in the liver at 10 min after infection. Here we report that the Listeria recovered at 10 min were distributed equally among the hepatocyte and nonparenchymal liver cell populations. The majority (>/= 75%) of these organisms were bound extracellularly as judged by their sensitivity to gentamicin. In contrast, >/= 93% of Listeria recovered in the liver at 6 h were located within hepatocytes. The listerial burden of the liver decreased 0.5 to 1.0 log, between 10 min and 6 h after infection. This decrease correlated with a sevenfold increase in the percentage of neutrophils that constituted the nonparenchymal cell population. Mice rendered neutrophil deficient by pretreatment with anti-granulocyte (RB6-8C5) mAb exhibited a significant increase (>300%) rather than a decrease in liver Listeria and a marked increase in hepatocyte damage. Similarly, neutrophil-deficient mice exhibited a reduced capacity to eliminate Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus that were cleared by the liver and bound extracellularly to hepatocytes and nonparenchymal cells. These findings document the crucial role of immigrating neutrophils in nonspecific host defenses to systemic bacterial infections expressed within the liver.

We previously reported that the bulk of Listeria monocytogenes injected intravenously into mice is taken up in the liver and replicates within the parenchymal cells (hepatocytes). Although IFN-gamma is known to play an important role in host defenses to listerial infections of the liver, the mechanism(s) that underlies this role remains to be fully delineated. In the initial experiments presented here, we demonstrated the elevated expression of IFN-gamma message in the livers of mice during primary listerial infections. Subsequent experiments showed that the listerial burden of the hepatocyte population was increased significantly in mice administered monoclonal anti-IFN-gamma. Conversely, the administration of murine rIFN-gamma resulted in a marked (2 log10) decrease in the number of hepatocyte-associated Listeria. In vitro, IFN-gamma stimulated the listericidal activity of purified hepatocytes. Infected hepatocytes incubated in the presence of > 0.1 U/ml murine rIFN-gamma exhibited a significant reduction in intracellular Listeria. The elevated antilisterial activity of IFN-gamma-treated hepatocytes in culture was abrogated by the presence of compounds that scavenged or inhibited the production of reactive oxygen intermediates. Taken together, these findings suggest that activation of the oxygen-dependent, antimicrobial activity of hepatocytes may constitute a principal effector function of IFN-gamma in host defenses to listerial infections of the liver.

Reactive nitrogen intermediates (RNI), e.g., nitric oxide derived from a terminal guanido nitrogen atom of L-arginine, exhibit potent antimicrobial activity in vitro. The function of these intermediates in host defenses in vivo, however, is presently unclear. Experiments were undertaken to determine the role of RNI in the resolution of primary listerial infections of the liver. Serum RNI levels were elevated significantly in mice infected with Listeria monocytogenes. Moreover, a marked increase in RNI production was found in cultures of the parenchymal, as well as the nonparenchymal, liver cells obtained from Listeria-infected mice. RNI did not kill Listeria treated directly, however, nor were they a factor in the listericidal activity exhibited by hepatic cells. Rather, the elevated production of RNI during primary infection appeared to promote the replication of Listeria in vivo. Mice administered NG-monomethyl-L-arginine, a competitive inhibitor of RNI production, exhibited a 10- and a 100-fold reduction in the number of Listeria in their lives on days 3 and 7 postinfection, respectively. In vitro, NG-monomethyl-L-arginine stimulated the Ag-specific proliferation of T lymphocytes derived from Listeria-infected mice at concentrations that inhibited RNI production. These latter findings suggest that the elevated production of RNI during primary listerial infections suppresses host defenses by diminishing the proliferation and, consequently, the biologic response of immune cell populations.

The serum and tissue levels of macrophage colony-stimulating factor (M-CSF) are elevated in mice during a primary immunologic response to infection by Listeria monocytogenes. Experiments were performed to determine the specific role of M-CSF in the resolution of listerial infections. The bulk of Listeria injected into a mouse i.v. is deposited in the liver. The expression of M-CSF mRNA in the liver increased markedly within 2 h postinfection. Maximum expression was dependent upon the dose of Listeria inoculated. The administration of anti-M-CSF mAb reduced the percentage of Mac-1+ mononuclear phagocytes subsequently found in the livers of infected animals. This reduction correlated inversely with an increase in the number of Listeria associated with both the parenchymal and NPC populations. These results suggest that M-CSF may play an important role in the primary immunologic response to Listeria in the liver by stimulating the production, mobilization, and/or biologic activity of Mac-1+ mononuclear phagocytes.

Kupffer cells were the principal source of IL-6 produced in the livers of mice following i.v. inoculation of Listeria monocytogenes. IL-6 mRNA expression and the production of IL-6 were reduced drastically within the nonparenchymal liver cell population derived from mice rendered Kupffer cell depleted by pretreatment with liposome-encapsulated dichloromethylene diphosphonate. A sharp increase in the appearance of activated STAT3 occurred in extracts of purified hepatocytes derived from normal mice infected i.v. with Listeria. Remarkably, the kinetics of this increase overlapped IL-6 mRNA expression by Kupffer cells; each peaked at approximately 30 min postinfection. No increase in STAT3 activation was observed in IL-6-deficient or Kupffer cell-depleted animals. The results of these experiments indicate that the synthesis of IL-6 and the activation of STAT3 within hepatocytes are critical functions of Kupffer cells occurring very early during the course of systemic listerial infections.

The colony-stimulating factors (CSFs) are cytokines involved in the production, differentiation, and activation of host phagocytes. During murine infection with Chlamydia trachomatis (MoPn), plasma CSF levels increased in euthymic (nu/+) and athymic (nu/nu) BALB/c mice. Levels declined later in infection, with the nu/+ mice resolving the infection but the nu/nu mice succumbing by day 16. Either live or heat-killed Chlamydia organisms could induce CSF increases on day 7 postchallenge in nu/+ mice; however, by day 14, only mice challenged with live organisms maintained high plasma levels. CSFs were also produced by spleen cells of nu/+ and nu/nu mice in response to Chlamydia antigen. Spleen cell CSF production was detectable by days 3 to 5 postinfection. In nu/+ mice, spleen cell CSF production was elevated throughout the rest of the time course but in nu/nu mice fell significantly at day 14. Like the plasma CSF activity (CSA) production, spleen cell CSA production on day 7 was seen in mice challenged with either live or heat-killed Chlamydia organisms, but on day 14 only nu/+ mice challenged with live organisms maintained significant CSA production. To further characterize the T-cell dependence of CSA production, spleen cells of nu/+ mice were depleted of T cells or T-cell subsets before producing supernatants. On day 14 postinfection, the CD4+ lymphocyte was the major producer of CSFs. Additionally, there were different types of CSFs secreted by nu/+ and nu/nu mice as determined by the ability of spleen cell supernatants to support the granulocyte-macrophage CSF/interleukin 3-dependent cell line FDCP-1. Supernatants from nu/+ mice had 4 to 8 times the level of FDCP-1 CSF activity of the supernatants from nu/nu mice. These results support the evidence that nu/+ mice were producing some CSFs by T-cell-dependent mechanisms. This is the first report of CSF production in vivo during Chlamydia infection. Furthermore, we show that CSFs are produced by both T-cell-dependent and T-cell-independent mechanisms. The capacity of the CSFs to increase the production and effector function of phagocytes may be important to host defenses.

Neither the presence nor the specific role of secretory cytokines in in vivo allograft rejection has been extensively studied. We quantitated the levels of colony-stimulating factors, tumor necrosis factor, and interleukin 1 within the rejecting allograft. BALB/c (H-2d) mice were implanted with polyurethane sponges containing either allogeneic C57BL/6 (H-2b) or syngeneic splenocytes, or splenocyte-free media. At various days postgrafting, the sponges were harvested, and the cells infiltrating the grafts were analyzed for specific antidonor cytolytic activity, while IL-1, TNF, and CSF levels were measured in the graft exudate fluid. Allogeneic grafts had significantly higher concentrations of CSF, TNF, and IL-1 than syngeneic of splenocyte-free grafts. A specific radioimmunoassay revealed that macrophage colony-stimulating factor (M-CSF) is the primary CSF produced in the grafts. Peak TNF levels preceded peak M-CSF and IL-1 levels, which coincided with the initial appearance of allospecific cytotoxic T lymphocytes. Maximal CTL activity was seen on day 13, when the levels of these cytokines had already begun to fall. Specific bioassays for multi-CSF (IL-3), granulocyte CSF, granulocyte-macrophage CSF, IL-2, and IL-4 failed to detect these cytokines in the sponge fluid at any time. We hypothesize that TNF, M-CSF, and IL-1 probably play regulatory roles in the immunologic events at the site of allograft challenge.

Since the discovery of Legionella pneumophila in the late 1970s, this organism and other Legionella sp have been an important cause of pneumonia in solid organ transplant recipients. Legionella sp are obligate aerobes that require a source of amino acids, iron, and L-cystine. Growth is enhanced in a 5% CO2 atmosphere at 37 degrees C in the presence of charcoal. Legionella sp reside in water supplies and hospital outbreaks associated with contaminated water have been described. Transplant recipients are particularly susceptible to Legionella infection. Legionella pneumonia tends to occur within several weeks after transplantation and frequently coincides with episodes of rejection. A prodrome of influenza-like symptoms is followed by a sometimes "explosive" pneumonia with patchy lobular or interstitial infiltrates on chest radiograph. High fever, abdominal pain, and mental status changes are sometimes seen. Diagnosis is made by examination of respiratory secretions by the direct fluorescent antibody technique or culture of the organism. Intravenous erythromycin is the treatment of choice. Rifampin is added if there is a lack of response. Both erythromycin and rifampin have important and opposite effects on cyclosporine metabolism, which may result, respectively, in increased cyclosporine toxicity or graft loss. Patients who must continue cyclosporine will, therefore, require frequent monitoring of cyclosporine levels.

Samples obtained from plumbing systems of hospitals, nonhospital institutions and homes were cultured for Legionella spp. by plating the samples directly on a selective medium. Swab samples were taken from the inner surfaces of faucet assemblies (aerators, spouts, and valve seats), showerheads, and shower pipes. Water and sediment were collected from the bottom of hot-water tanks. Legionella pneumophila serogroups 1, 5, and 6 were recovered from plumbing fixtures of the hospitals and nonhospital institutions and one of five homes. The legionellae (7 to 13,850 colony-forming units per ml) were also present in water and sediment from hot-water tanks maintained at 30 to 54 degrees C, but not in those maintained at 71 and 77 degrees C. Legionella micdadei was isolated from one tank. Thus legionellae are present in hot-water tanks which are maintained at warm temperatures or whose design results in warm temperatures at the bottom of the tanks. We hypothesize that hot-water tanks are a breeding site and a major source of L. pneumophila for the contamination of plumbing systems. The existence of these bacteria in the plumbing systems and tanks was not necessarily associated with disease. The extent of the hazard of this contamination needs to be delineated.

The colony-stimulating factors (CSFs) promote the proliferation and differentiation of hematopoietic precursors and more recently have been shown to amplify the functions of mature phagocytes in vitro. In this study recombinant human granulocyte/macrophage colony-stimulating factor (rGM-CSF) was administered to cancer patients to determine whether the cytotoxic and secretory activity of their blood monocytes could be enhanced. Patients with refractory neoplastic disease were treated with rGM-CSF either as a single bolus or as a constant infusion for 14 days at either 100 or 500 micrograms/m2 per day. As has been reported by others, the number of peripheral blood monocytes and granulocytes rose markedly in a dose-response fashion during infusion with rGM-CSF. The functional capacity of monocytes was increased by rGM- CSF, since the cytotoxicity of monocytes against antibody-coated xenogeneic cells was increased during the constant infusion compared to baseline. In addition, monocytes harvested during the constant infusion and stimulated with lipopolysaccharide (LPS) in vitro secreted increased quantities of tumor necrosis factor alpha (TNF-alpha) and interferon (IFN). These data indicate that rGM-CSF can enhance both the number and the function of peripheral blood monocytes in vivo.

The capacity of macrophage colony-stimulating factor (M-CSF) to enhance respiratory burst activity in peritoneal macrophages was measured. Macrophages incubated for 48 hr or more with concentrated L cell-conditioned medium as a source of M-CSF released two to three times as much O2- in response to PMA as did unexposed macrophages. Stimulation was noted at concentrations of colony-stimulating activity from 0.1 to 2000 U/ml and was maximal at 10 to 100 U/ml. Purified, endotoxin-free CSF enhanced secretion to a similar degree as unpurified L cell-conditioned medium. Release of O2- by M-CSF macrophages occurred over 60 min and was triggered by opsonized zymosan as well as PMA. H2O2 release was also enhanced in macrophages exposed to both unpurified and purified M-CSF. These data indicate that M-CSF enhances the capacity of mature macrophages to release oxygen reduction products, and they are consistent with reports that CSF can stimulate the release of other secretory products.

Murine T lymphocyte clones sensitized to Listeria monocytogenes were developed to investigate specific mechanisms of T cell-mediated immunity. The clones were of the Thy-1.2+, L3T4+, Lyt-2- phenotype and proliferated in a dose response fashion to heat-killed Listeria. Cloned T lymphocytes injected intravenously protected nonimmune mice against L. monocytogenes challenge as determined by spleen and liver bacterial numbers. Supernatants, produced by stimulating clones with heat-killed Listeria for 48 h, also afforded protection against L. monocytogenes. The clonal supernatants contained significant quantities of IFN-gamma and CSF. IFN-gamma production was Ag specific and occurred within 24 h of stimulation. CSF production by clones was increased four- to sixfold over baseline as determined by a bone marrow colony-forming assay and was Ag specific. When the IFN-gamma in supernatants was neutralized with a specific mAb, protection afforded by the supernatants was lost. These data indicate that one mechanism for Ag-specific, T lymphocyte-mediated protection against L. monocytogenes is the release of IFN-gamma.

The effect of short-term nutritional deprivation on host defenses and on the parameters of macrophage production was determined in outbred mice. Confirming previous data from this laboratory, initial experiments demonstrated that starved mice were relatively resistant to infection by Listeria monocytogenes as determined by spleen and liver bacterial counts. The number of macrophage progenitor cells in bone marrow rose slightly during a 72-h starvation period and returned to normal during refeeding. By contrast, the number of progenitor cells in spleens fell to 12% of the base line during starvation. The concentration of the macrophage colony-stimulating factor in serum decreased during starvation and returned to normal during refeeding. Additional experiments were performed to determine whether starved mice had increased parameters of macrophage production during listerial infection. The number of progenitor cells in the bone marrow and spleens of starved mice had increased compared with that of fed mice early in infection. Macrophage colony-stimulating factor levels in starved mice rose early and remained elevated during infection but were not as high as in fed mice. These data document the changes in the parameters of monocyte production during starvation and suggest that the number of macrophage progenitor cells may be related to increased resistance to L. monocytogenes.

The effect of M-CSF-exposed macrophages on murine splenic lymphocyte responses was determined. Resident peritoneal macrophages incubated with purified M-CSF for 48 hr inhibited lymphocyte proliferation to Con A, PHA, and listerial antigen as determined by [3H]TdR uptake, and inhibited Con A-stimulated lymphocyte IL 2 production. The inhibition was similar to that observed with macrophages from BCG-infected mice. Maximal suppression occurred at M-CSF concentrations of 500 U/ml or greater and when the incubation time with M-CSF was 48 hr or more. M-CSF effect was specific because rabbit anti-M-CSF IgG blocked the suppression whereas control rabbit IgG did not. Secretory products of macrophages could not be implicated in this interaction. Catalase and indomethacin, alone or together, did not reverse the inhibition. In addition, putative suppressive factors were not detected in supernatants of M-CSF-stimulated macrophages. Lymphocytes that were removed from macrophage monolayers and were recultured in medium plus Con A were able to proliferate. Macrophages stimulated by M-CSF therefore appear to have inhibitory activity for proliferating lymphocytes, and may play a role in immunoregulatory mechanisms.

CSF have been postulated to be important mediators of host defenses. The current studies were undertaken to investigate the production of CSF by Listeria-specific, T cell clones and to assess the participation of CSF in anti-listerial host resistance. Listeria-specific L3T4+, Lyt-2- T cell clones were isolated and expanded by standard techniques. The clones themselves protected mice from listerial challenge when injected intravenously, and supernatants generated from Ag-stimulated clones were protective. In order to define factors important in the protection, supernatants from the clones were assayed for CSF by several in vitro assays. Total colony-stimulating activity was measured with a bone marrow colony-forming assay. T cell clones secreted 1000 to 2000 U/ml of colony-stimulating activity after 48 hours of stimulation with specific antigen. The relative amounts of the various CSF were determined by the capacity of supernatants to support proliferation of the factor-dependent cell lines FDCP-1 and 32D cl 3 in the presence and absence of specific anti-CSF antibodies. Results showed that most of the CSF activity was due to granulocyte-macrophage (GM)-CSF and IL-3. The role of GM-CSF in anti-listerial host resistance was assessed in two types of experiments. In one set of experiments GM-CSF activity was neutralized in the supernatants by addition of specific rabbit anti-GM-CSF antibodies. Treated and untreated supernatants were then tested for their capacity to protect nonimmune mice against listerial challenge. Neutralization of GM-CSF in the supernatants decreased the protective capacity of the supernatants by approximately 23%. In a second set of studies, the administration of recombinant murine GM-CSF was shown to protect mice from challenges of L. monocytogenes. Taken together, these experiments provide evidence that CSF are important mediators of immune T cell mediated host defenses.