Balancing economic and epidemiological interventions in the early stages of pathogen emergence.

The global pandemic of COVID-19 has underlined the need for more coordinated responses to emergent pathogens. These responses need to balance epidemic control in ways that concomitantly minimize hospitalizations and economic damages. We develop a hybrid economic-epidemiological modeling framework that allows us to examine the interaction between economic and health impacts over the first period of pathogen emergence when lockdown, testing, and isolation are the only means of containing the epidemic. This operational mathematical setting allows us to determine the optimal policy interventions under a variety of scenarios that might prevail in the first period of a large-scale epidemic outbreak. Combining testing with isolation emerges as a more effective policy than lockdowns, substantially reducing deaths and the number of infected hosts, at lower economic cost. If a lockdown is put in place early in the course of the epidemic, it always dominates the "laissez-faire" policy of doing nothing.

Public parks and the pandemic: How park usage has been affected by COVID-19 policies.

Public parks serve an important societal function as recreational spaces for diverse communities of people, with well documented physical and mental health benefits. As such, parks may be crucial for how people have handled effects of the COVID-19 pandemic, particularly the increasingly limited recreational opportunities, widespread financial uncertainty, and consequent heightened anxiety. Despite the documented benefits of parks, however, many states have instituted park shutdown orders due to fears that public parks could facilitate SARS-CoV-2 transmission. Here we use geotagged social media data from state, county, and local parks throughout New Jersey to examine whether park visitation increased when the COVID-19 pandemic began and whether park shutdown orders were effective at deterring park usage. We compare park usage during four discrete stages of spring 2020: (1) before the pandemic began, (2) during the beginning of the pandemic, (3) during the New Jersey governor's state-wide park shutdown order, and (4) following the lifting of the shutdown. We find that park visitation increased by 63.4% with the onset of the pandemic. The subsequent park shutdown order caused visitation in closed parks to decline by 76.1% while parks that remained open continued to experience elevated visitation levels. Visitation then returned to elevated pre-shutdown levels when closed parks were allowed to reopen. Altogether, our results indicate that parks continue to provide crucial services to society, particularly in stressful times when opportunities for recreation are limited. Furthermore, our results suggest that policies targeting human behavior can be effective and are largely reversible. As such, we should continue to invest in public parks and to explore the role of parks in managing public health and psychological well-being.

Plant ecology: Macroparasitism in plant communities.

Mistletoes, lianas, vines, and epiphytes fulfill many of the population dynamic criteria of animal macroparasites. A new study illustrates elegant ways to quantify cost to the host and how this impacts competition between mistletoe species. It opens the door to a much fuller consideration of plant parasites as macroparasites.

Linking scaling laws across eukaryotes.

Scaling laws relating body mass to species characteristics are among the most universal quantitative patterns in biology. Within major taxonomic groups, the 4 key ecological variables of metabolism, abundance, growth, and mortality are often well described by power laws with exponents near 3/4 or related to that value, a commonality often attributed to biophysical constraints on metabolism. However, metabolic scaling theories remain widely debated, and the links among the 4 variables have never been formally tested across the full domain of eukaryote life, to which prevailing theory applies. Here we present datasets of unprecedented scope to examine these 4 scaling laws across all eukaryotes and link them to test whether their combinations support theoretical expectations. We find that metabolism and abundance scale with body size in a remarkably reciprocal fashion, with exponents near ±3/4 within groups, as expected from metabolic theory, but with exponents near ±1 across all groups. This reciprocal scaling supports "energetic equivalence" across eukaryotes, which hypothesizes that the partitioning of energy in space across species does not vary significantly with body size. In contrast, growth and mortality rates scale similarly both within and across groups, with exponents of ±1/4. These findings are inconsistent with a metabolic basis for growth and mortality scaling across eukaryotes. We propose that rather than limiting growth, metabolism adjusts to the needs of growth within major groups, and that growth dynamics may offer a viable theoretical basis to biological scaling.

Critical transitions in malaria transmission models are consistently generated by superinfection.

The history of modelling vector-borne infections essentially begins with the papers by Ross on malaria. His models assume that the dynamics of malaria can most simply be characterized by two equations that describe the prevalence of malaria in the human and mosquito hosts. This structure has formed the central core of models for malaria and most other vector-borne diseases for the past century, with additions acknowledging important aetiological details. We partially add to this tradition by describing a malaria model that provides for vital dynamics in the vector and the possibility of super-infection in the human host: reinfection of asymptomatic hosts before they have cleared a prior infection. These key features of malaria aetiology create the potential for break points in the prevalence of infected hosts, sudden transitions that seem to characterize malaria's response to control in different locations. We show that this potential for critical transitions is a general and underappreciated feature of any model for vector-borne diseases with incomplete immunity, including the canonical Ross-McDonald model. Ignoring these details of the host's immune response to infection can potentially lead to serious misunderstanding in the interpretation of malaria distribution patterns and the design of control schemes for other vector-borne diseases. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Managing marine disease emergencies in an era of rapid change.

Infectious marine diseases can decimate populations and are increasing among some taxa due to global change and our increasing reliance on marine environments. Marine diseases become emergencies when significant ecological, economic or social impacts occur. We can prepare for and manage these emergencies through improved surveillance, and the development and iterative refinement of approaches to mitigate disease and its impacts. Improving surveillance requires fast, accurate diagnoses, forecasting disease risk and real-time monitoring of disease-promoting environmental conditions. Diversifying impact mitigation involves increasing host resilience to disease, reducing pathogen abundance and managing environmental factors that facilitate disease. Disease surveillance and mitigation can be adaptive if informed by research advances and catalysed by communication among observers, researchers and decision-makers using information-sharing platforms. Recent increases in the awareness of the threats posed by marine diseases may lead to policy frameworks that facilitate the responses and management that marine disease emergencies require.

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases.

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination 'as a public health problem' when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models' predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020.

Climate change and Arctic parasites.

Climate is changing rapidly in the Arctic. This has important implications for parasites of Arctic ungulates, and hence for the welfare of Arctic peoples who depend on caribou, reindeer, and muskoxen for food, income, and a focus for cultural activities. In this Opinion article we briefly review recent work on the development of predictive models for the impacts of climate change on helminth parasites and other pathogens of Arctic wildlife, in the hope that such models may eventually allow proactive mitigation and conservation strategies. We describe models that have been developed using the metabolic theory of ecology. The main strength of these models is that they can be easily parameterized using basic information about the physical size of the parasite. Initial results suggest they provide important new insights that are likely to generalize to a range of host-parasite systems.

Yellowstone wolves and the forces that structure natural systems.

Since their introduction in 1995 and 1996, wolves have had effects on Yellowstone that ripple across the entire structure of the food web that defines biodiversity in the Northern Rockies ecosystem. Ecological interpretations of the wolves have generated a significant amount of debate about the relative strength of top-down versus bottom-up forces in determining herbivore and vegetation abundance in Yellowstone. Debates such as this are central to the resolution of broader debates about the role of natural enemies and climate as forces that structure food webs and modify ecosystem function. Ecologists need to significantly raise the profile of these discussions; understanding the forces that structure food webs and determine species abundance and the supply of ecosystem services is one of the central scientific questions for this century; its complexity will require new minds, new mathematics, and significant, consistent funding.

A walk on the tundra: Host-parasite interactions in an extreme environment.

Climate change is occurring very rapidly in the Arctic, and the processes that have taken millions of years to evolve in this very extreme environment are now changing on timescales as short as decades. These changes are dramatic, subtle and non-linear. In this article, we discuss the evolving insights into host-parasite interactions for wild ungulate species, specifically, muskoxen and caribou, in the North American Arctic. These interactions occur in an environment that is characterized by extremes in temperature, high seasonality, and low host species abundance and diversity. We believe that lessons learned in this system can guide wildlife management and conservation throughout the Arctic, and can also be generalized to more broadly understand host-parasite interactions elsewhere. We specifically examine the impacts of climate change on host-parasite interactions and focus on: (I) the direct temperature effects on parasites; (II) the importance of considering the intricacies of host and parasite ecology for anticipating climate change impacts; and (III) the effect of shifting ecological barriers and corridors. Insights gained from studying the history and ecology of host-parasite systems in the Arctic will be central to understanding the role that climate change is playing in these more complex systems.

The impact of community organization on vector-borne pathogens.

Vector-borne zoonotic disease agents, which are known to often infect multiple species in the wild, have been identified as an emerging threat to human health. Understanding the ecology of these pathogens is especially timely, given the continued anthropogenic impacts on biodiversity. Here, we integrate empirical scaling laws from community ecology within a theoretical reservoir-vector-pathogen framework to study the transmission consequences of host community structure and diversity within large assemblages. We show that heterogeneity in susceptibility of the reservoir species promotes transmission "dilution," while a greater vector species richness "amplifies" it. These contrasting transmission impacts of vector and reservoir communities can yield very different epidemiological patterns. We demonstrate that vector and reservoir species richness can explain per se most of the pathogen transmission observed for West Nile virus in different parts of the United States, giving empirical support for the validity of these opposing theoretically predicted effects. We conclude that, in the context of disease emergence, the integration of a community perspective can provide critical insights into the understanding of pathogen transmission in wildlife.

Ecology of zoonoses: natural and unnatural histories.

More than 60% of human infectious diseases are caused by pathogens shared with wild or domestic animals. Zoonotic disease organisms include those that are endemic in human populations or enzootic in animal populations with frequent cross-species transmission to people. Some of these diseases have only emerged recently. Together, these organisms are responsible for a substantial burden of disease, with endemic and enzootic zoonoses causing about a billion cases of illness in people and millions of deaths every year. Emerging zoonoses are a growing threat to global health and have caused hundreds of billions of US dollars of economic damage in the past 20 years. We aimed to review how zoonotic diseases result from natural pathogen ecology, and how other circumstances, such as animal production, extraction of natural resources, and antimicrobial application change the dynamics of disease exposure to human beings. In view of present anthropogenic trends, a more effective approach to zoonotic disease prevention and control will require a broad view of medicine that emphasises evidence-based decision making and integrates ecological and evolutionary principles of animal, human, and environmental factors. This broad view is essential for the successful development of policies and practices that reduce probability of future zoonotic emergence, targeted surveillance and strategic prevention, and engagement of partners outside the medical community to help improve health outcomes and reduce disease threats.

A common scaling rule for abundance, energetics, and production of parasitic and free-living species.

The metabolic theory of ecology uses the scaling of metabolism with body size and temperature to explain the causes and consequences of species abundance. However, the theory and its empirical tests have never simultaneously examined parasites alongside free-living species. This is unfortunate because parasites represent at least half of species diversity. We show that metabolic scaling theory could not account for the abundance of parasitic or free-living species in three estuarine food webs until accounting for trophic dynamics. Analyses then revealed that the abundance of all species uniformly scaled with body mass to the -¾ power. This result indicates "production equivalence," where biomass production within trophic levels is invariant of body size across all species and functional groups: invertebrate or vertebrate, ectothermic or endothermic, and free-living or parasitic.

Climate forcing and desert malaria: the effect of irrigation.

BACKGROUND: Rainfall variability and associated remote sensing indices for vegetation are central to the development of early warning systems for epidemic malaria in arid regions. The considerable change in land-use practices resulting from increasing irrigation in recent decades raises important questions on concomitant change in malaria dynamics and its coupling to climate forcing. Here, the consequences of irrigation level for malaria epidemics are addressed with extensive time series data for confirmed Plasmodium falciparum monthly cases, spanning over two decades for five districts in north-west India. The work specifically focuses on the response of malaria epidemics to rainfall forcing and how this response is affected by increasing irrigation. METHODS AND FINDINGS: Remote sensing data for the Normalized Difference Vegetation Index (NDVI) are used as an integrated measure of rainfall to examine correlation maps within the districts and at regional scales. The analyses specifically address whether irrigation has decreased the coupling between malaria incidence and climate variability, and whether this reflects (1) a breakdown of NDVI as a useful indicator of risk, (2) a weakening of rainfall forcing and a concomitant decrease in epidemic risk, or (3) an increase in the control of malaria transmission. The predictive power of NDVI is compared against that of rainfall, using simple linear models and wavelet analysis to study the association of NDVI and malaria variability in the time and in the frequency domain respectively. CONCLUSIONS: The results show that irrigation dampens the influence of climate forcing on the magnitude and frequency of malaria epidemics and, therefore, reduces their predictability. At low irrigation levels, this decoupling reflects a breakdown of local but not regional NDVI as an indicator of rainfall forcing. At higher levels of irrigation, the weakened role of climate variability may be compounded by increased levels of control; nevertheless this leads to no significant decrease in the actual risk of disease. This implies that irrigation can lead to more endemic conditions for malaria, creating the potential for unexpectedly large epidemics in response to excess rainfall if these climatic events coincide with a relaxation of control over time. The implications of our findings for control policies of epidemic malaria in arid regions are discussed.

Urban habituation, ecological connectivity and epidemic dampening: the emergence of Hendra virus from flying foxes (Pteropus spp.).

Anthropogenic environmental change is often implicated in the emergence of new zoonoses from wildlife; however, there is little mechanistic understanding of these causal links. Here, we examine the transmission dynamics of an emerging zoonotic paramyxovirus, Hendra virus (HeV), in its endemic host, Australian Pteropus bats (fruit bats or flying foxes). HeV is a biosecurity level 4 (BSL-4) pathogen, with a high case-fatality rate in humans and horses. With models parametrized from field and laboratory data, we explore a set of probable contributory mechanisms that explain the spatial and temporal pattern of HeV emergence; including urban habituation and decreased migration-two widely observed changes in flying fox ecology that result from anthropogenic transformation of bat habitat in Australia. Urban habituation increases the number of flying foxes in contact with human and domestic animal populations, and our models suggest that, in addition, decreased bat migratory behaviour could lead to a decline in population immunity, giving rise to more intense outbreaks after local viral reintroduction. Ten of the 14 known HeV outbreaks occurred near urbanized or sedentary flying fox populations, supporting these predictions. We also demonstrate that by incorporating waning maternal immunity into our models, the peak modelled prevalence coincides with the peak annual spill-over hazard for HeV. These results provide the first detailed mechanistic framework for understanding the sporadic temporal pattern of HeV emergence, and of the urban/peri-urban distribution of HeV outbreaks in horses and people.

Spatial guilds in the Serengeti food web revealed by a Bayesian group model.

Food webs, networks of feeding relationships in an ecosystem, provide fundamental insights into mechanisms that determine ecosystem stability and persistence. A standard approach in food-web analysis, and network analysis in general, has been to identify compartments, or modules, defined by many links within compartments and few links between them. This approach can identify large habitat boundaries in the network but may fail to identify other important structures. Empirical analyses of food webs have been further limited by low-resolution data for primary producers. In this paper, we present a Bayesian computational method for identifying group structure using a flexible definition that can describe both functional trophic roles and standard compartments. We apply this method to a newly compiled plant-mammal food web from the Serengeti ecosystem that includes high taxonomic resolution at the plant level, allowing a simultaneous examination of the signature of both habitat and trophic roles in network structure. We find that groups at the plant level reflect habitat structure, coupled at higher trophic levels by groups of herbivores, which are in turn coupled by carnivore groups. Thus the group structure of the Serengeti web represents a mixture of trophic guild structure and spatial pattern, in contrast to the standard compartments typically identified. The network topology supports recent ideas on spatial coupling and energy channels in ecosystems that have been proposed as important for persistence. Furthermore, our Bayesian approach provides a powerful, flexible framework for the study of network structure, and we believe it will prove instrumental in a variety of biological contexts.