Allocating limited surveillance effort for outbreak detection of endemic foot and mouth disease.

Foot and Mouth Disease (FMD) affects cloven-hoofed animals globally and has become a major economic burden for many countries around the world. Countries that have had recent FMD outbreaks are prohibited from exporting most meat products; this has major economic consequences for farmers in those countries, particularly farmers that experience outbreaks or are near outbreaks. Reducing the number of FMD outbreaks in countries where the disease is endemic is an important challenge that could drastically improve the livelihoods of millions of people.

Differences in adult survival drive divergent demographic responses to warming on the Tibetan Plateau.

A central question in biodiversity conservation is whether species will maintain viable populations under climate warming. Assessing species viability under climate warming requires demographic studies integrating vital rate responses to long-term warming throughout species' life cycles. However, studies of this nature are rare.

Seedling size affects the strategy of dune seedlings responding to rainfall variation.

Background And Aims: Climate change poses a growing threat to population maintenance in harsh desert habitats with high precipitation variability. Desert seeds may germinate at different times as a bet-hedging strategy to cope with increased rainfall fluctuation. As a result, a population may consist of seedlings of various sizes.

Vivifying Outbreaks: Investigating the Influence of a Forecast Visual on Risk Perceptions, Time-Urgency, and Behavioral Intentions.

Although visual depictions of epidemiological data are not new in public health, the US public saw more of them during the COVID-19 pandemic than ever before. In this study, we considered visualizations of forecasts (i.e.

Scenario design for infectious disease projections: Integrating concepts from decision analysis and experimental design.

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication.

When do we need multiple infectious disease models? Agreement between projection rank and magnitude in a multi-model setting.

Mathematical models are useful for public health planning and response to infectious disease threats. However, different models can provide differing results, which can hamper decision making if not synthesized appropriately. To address this challenge, multi-model hubs convene independent modeling groups to generate ensembles, known to provide more accurate predictions of future outcomes.

Ensemble: Scenarios ensembling for communication and performance analysis.

Throughout the COVID-19 pandemic, scenario modeling played a crucial role in shaping the decision-making process of public health policies. Unlike forecasts, scenario projections rely on specific assumptions about the future that consider different plausible states-of-the-world that may or may not be realized and that depend on policy interventions, unpredictable changes in the epidemic outlook, etc. As a consequence, long-term scenario projections require different evaluation criteria than the ones used for traditional short-term epidemic forecasts.

The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy.

Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt to coordinate, synthesize and effectively use the unprecedented amount of predictive modeling that emerged throughout the COVID-19 pandemic. Here we describe the history of this massive collective research effort, the process of convening and maintaining an open modeling hub active over multiple years, and attempt to provide a blueprint for future efforts.

Climate warming increases insect-driven seed removal of two elaiosome-bearing invasive thistle species.

Ants and other insects are often a source of localized secondary dispersal for wind-dispersed plants and thus play an important ecological role in their spatial dynamics, but there is limited information on how climate change will affect such dispersal processes. Here, we use field experiments to investigate how climate warming affects seed removal, as this initiation of movement represents the first step in insect-driven secondary dispersal. Our results indicate that for the invasive thistles Carduus nutans and Carduus acanthoides, increased growing temperature influences seed attractiveness to insect dispersers, with seeds from maternal plants grown at temperatures 0.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.

Elevated temperatures shift flower head height distributions and seed dispersal patterns in two invasive thistle species.

Climate change may significantly alter how organisms disperse, with implications for population spread and species management. Wind-dispersed plants have emerged as a useful study system for investigating how climate change affects dispersal, although studies modeling wind dispersal often assume propagules are released from a single point on an individual. This simplifying assumption, while useful, may misestimate dispersal.

Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design.

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication.

Diversity loss from multiple interacting disturbances is regime-dependent.

Anthropogenic activities expose many ecosystems to multiple novel disturbances simultaneously. Despite this, how biodiversity responds to simultaneous disturbances remains unclear, with conflicting empirical results on their interactive effects. Here, we experimentally test how one disturbance (an invasive species) affects the diversity of a community over multiple levels of another disturbance regime (pulse mortality).

Informing pandemic response in the face of uncertainty. .

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.

Optimal spatial evaluation of a pro rata vaccine distribution rule for COVID-19.

The COVID-19 Vaccines Global Access (COVAX) is a World Health Organization (WHO) initiative that aims for an equitable access of COVID-19 vaccines. Despite potential heterogeneous infection levels across a country, countries receiving allotments of vaccines may follow WHO's allocation guidelines and distribute vaccines based on a jurisdictions' relative population size. Utilizing economic-epidemiological modeling, we benchmark the performance of this pro rata allocation rule by comparing it to an optimal one that minimizes the economic damages and expenditures over time, including a penalty representing the social costs of deviating from the pro rata strategy.

Context-dependent representation of within- and between-model uncertainty: aggregating probabilistic predictions in infectious disease epidemiology.

Probabilistic predictions support public health planning and decision making, especially in infectious disease emergencies. Aggregating outputs from multiple models yields more robust predictions of outcomes and associated uncertainty. While the selection of an aggregation method can be guided by retrospective performance evaluations, this is not always possible.

Pulse and Press Disturbances Have Different Effects on Transient Community Dynamics.

AbstractDisturbances are important determinants of diversity, and the combination of their aspects (e.g., disturbance intensity, frequency) can result in complex diversity patterns.

Cattle transport network predicts endemic and epidemic foot-and-mouth disease risk on farms in Turkey.

The structure of contact networks affects the likelihood of disease spread at the population scale and the risk of infection at any given node. Though this has been well characterized for both theoretical and empirical networks for the spread of epidemics on completely susceptible networks, the long-term impact of network structure on risk of infection with an endemic pathogen, where nodes can be infected more than once, has been less well characterized. Here, we analyze detailed records of the transportation of cattle among farms in Turkey to characterize the global and local attributes of the directed-weighted shipments network between 2007-2012.

Vote-processing rules for combining control recommendations from multiple models.

Mathematical modelling is used during disease outbreaks to compare control interventions. Using multiple models, the best method to combine model recommendations is unclear. Existing methods weight model projections, then rank control interventions using the combined projections, presuming model outputs are directly comparable.

Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination.

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July-December 2021 for the United States.