Differences in COVID-19 cyclicity and predictability among U.S. counties and states reflect the effectiveness of protective measures.

During the COVID-19 pandemic, many quantitative approaches were employed to predict the course of disease spread. However, forecasting faces the challenge of inherently unpredictable spread dynamics, setting a limit to the accuracy of all models. Here, we analyze COVID-19 data from the USA to explain variation among jurisdictions in disease spread predictability (that is, the extent to which predictions are possible), using a combination of statistical and simulation models. We show that for half the counties and states the spread rate of COVID-19, r(t), was predictable at most 9 weeks and 8 weeks ahead, respectively, corresponding to at most 40% and 35% of an average cycle length of 23 weeks and 26 weeks. High predictability was associated with high cyclicity of r(t) and negatively associated with R0 values from the pandemic's onset. Our statistical evidence suggests the following explanation: jurisdictions with a severe initial outbreak, and where individuals and authorities took strong and sustained protective measures against COVID-19, successfully curbed subsequent waves of disease spread, but at the same time unintentionally decreased its predictability. Decreased predictability of disease spread should be viewed as a by-product of positive and sustained steps that people take to protect themselves and others.

Exploring artificial habitat fragmentation to control invasion by infectious wildlife diseases.

One way to reduce the impacts of invading wildlife diseases is setting up fences that would reduce the spread of pathogens by limiting connectivity, similarly to exclusion fences that are commonly used to conserve threatened species against invasive predators. One of the problems with fences is that, while they may have the short-term benefit of impeding the spread of disease, this benefit may be offset by potential long-term ecological costs of fragmentation by fencing. However, managers facing situations where a pathogen has been detected near the habitat of a (highly) vulnerable species may be willing to explore such a trade-off. To aid such exploration quantitatively, we present a series of models trading off the benefits of fragmentation (potential reduction of disease impacts on susceptible individuals) against its costs (both financial and ecological, i.e. reduced viability in the patches created by fragmentation), and exploring the effects of fragmentation on non-target species richness. For all model variants we derive the optimal number of artificial patches. We show that pre-emptive disease fences may have benefits when the risk of disease exceeds the impacts of fragmentation, when fence failure rates are lower than a specific threshold, and when sufficient resources are available to implement optimal solutions. A useful step to initiate planning is to obtain information about the expected number of initial infection events and on the host's extinction threshold with respect to the focal habitat and management duration. Our approach can assist managers to identify whether the trade-offs support the decision to fence and how intensive fragmentation should be.

Estimating and explaining the spread of COVID-19 at the county level in the USA.

The basic reproduction number, R0, determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA at the start of the epidemic. We show that most of the high among-county variance is explained by four factors (R2 = 0.70): the timing of outbreak, population size, population density, and spatial location. For predictions of future spread, population density and spatial location are important, and for the latter we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread. Finally, the high predictability of R0 allows extending estimates to all 3109 counties in the conterminous 48 states. The high variation of R0 argues for public health policies enacted at the county level for controlling COVID-19.

Active responses to outbreaks of infectious wildlife diseases: objectives, strategies and constraints determine feasibility and success.

Emerging wildlife diseases are taking a heavy toll on animal and plant species worldwide. Mitigation, particularly in the initial epidemic phase, is hindered by uncertainty about the epidemiology and management of emerging diseases, but also by vague or poorly defined objectives. Here, we use a quantitative analysis to assess how the decision context of mitigation objectives, available strategies and practical constraints influences the decision of whether and how to respond to epidemics in wildlife. To illustrate our approach, we parametrized the model for European fire salamanders affected by Batrachochytrium salamandrivorans, and explored different combinations of conservation, containment and budgetary objectives. We found that in approximately half of those scenarios, host removal strategies perform equal to or worse than no management at all during a local outbreak, particularly where removal cannot exclusively target infected individuals. Moreover, the window for intervention shrinks rapidly if an outbreak is detected late or if a response is delayed. Clearly defining the decision context is, therefore, vital to plan meaningful responses to novel outbreaks. Explicitly stating objectives, strategies and constraints, if possible before an outbreak occurs, avoids wasting precious resources and creating false expectations about what can and cannot be achieved during the epidemic phase.

Inbreeding reduces long-term growth of Alpine ibex populations.

Many studies document negative inbreeding effects on individuals, and conservation efforts to preserve rare species routinely employ strategies to reduce inbreeding. Despite this, there are few clear examples in nature of inbreeding decreasing the growth rates of populations, and the extent of population-level effects of inbreeding in the wild remains controversial. Here, we take advantage of a long-term dataset of 26 reintroduced Alpine ibex (Capra ibex ibex) populations spanning nearly 100 years to show that inbreeding substantially reduced per capita population growth rates, particularly for populations in harsher environments. Populations with high average inbreeding (F ≈ 0.2) had population growth rates reduced by 71% compared with populations with no inbreeding. Our results show that inbreeding can have long-term demographic consequences even when environmental variation is large and deleterious alleles may have been purged during bottlenecks. Thus, efforts to guard against inbreeding effects in populations of endangered species have not been misplaced.

Quantifying the burden of managing wildlife diseases in multiple host species.

Mitigation of infectious wildlife diseases is especially challenging where pathogens affect communities of multiple host species. Although most ecological studies recognize the challenge posed by multiple-species pathogens, the implications for management are typically assessed only qualitatively. Translating the intuitive understanding that multiple host species are important into practice requires a quantitative assessment of whether and how secondary host species should also be targeted by management and the effort this will require. Using a multiple-species compartmental model, we determined analytically whether and how intensively secondary host species should be managed to prevent outbreaks in focal hosts based on the reproduction number of individual host species and between-species transmission rates. We applied the model to the invasive pathogenic fungus Batrachochytrium salamandrivorans in a 2-host system in northern Europe. Avoiding a disease outbreak in the focal host (fire salamanders [Salamandra salamandra]) was impossible unless management also heavily targeted the secondary host (alpine newts [Ichthyosaura alpestris]). Preventing an outbreak in the community required targeted removal of at least 80% of each species. This proportion increased to 90% in the presence of an environmental reservoir of B. salamandrivorans and when the proportion of individuals removed could not be adjusted for different host species (e.g., when using traps that are not species specific). We recommend the focus of disease-mitigation plans should shift from focal species to the community level and calculate explicitly the management efforts required on secondary host species to move beyond the simple intuitive understanding that multiple host species may all influence the system. Failure to do so may lead to underestimating the magnitude of the effort required and ultimately to suboptimal or futile management attempts.

Cuantificación de la Carga que Representa el Manejo de Enfermedades de Fauna Silvestre en Múltiples Especies Hospederas Resumen La mitigación de enfermedades infecciosas en fauna silvestre representa un reto especial cuando los patógenos afectan a comunidades de múltiples especies hospederas. Aunque la mayoría de los estudios ecológicos reconocen el reto que plantean los patógenos de múltiples especies, las implicaciones para el manejo comúnmente sólo se evalúan en el aspecto cualitativo. La traducción del entendimiento intuitivo hacia la práctica de que las múltiples especies hospederas son importantes requiere una valoración cuantitativa sobre si y cuán intensivamente se deberían considerar en el manejo las especies hospederas secundarias y los esfuerzos que esto requerirá. Determinamos analíticamente con un modelo compartimentado de múltiples especies si y cuán intensivamente se deberían manejar las especies hospederas secundarias para prevenir brotes en los hospederos focales con base en el número de reproducción de las especies hospederas individuales y en las tasas de transmisión entre especies. Aplicamos el modelo al hongo patógeno invasivo Batrachochytrium salamandrivorans en un sistema de dos hospederos al norte de Europa. Fue imposible evitar un brote de enfermedad en el hospedero focal (la salamandra de fuego [Salamandra salamandra]) a menos que el manejo también se enfocara considerablemente en el hospedero secundario (el tritón alpino [Ichthyosaura alpestris]). Para prevenir un brote dentro de la comunidad se requirió de la extirpación de al menos el 80% de cada especie. Esta proporción incrementó al 90% con la presencia de un reservorio ambiental de B. salamandrivorans y cuando la proporción de individuos removidos no pudo ajustarse para diferentes especies (p. ej.: el uso de trampas que nos son específicas para una especie) Recomendamos que el foco de los planes para la mitigación de enfermedades cambie de una especie focal al nivel de comunidad y que calculen explícitamente los esfuerzos de manejo requeridos sobre las especies hospederas secundarias para avanzar más allá del simple entendimiento intuitivo de que múltiples especies hospederas pueden todas influir sobre el sistema. Si se falla en esto, se podría subestimar la magnitud del esfuerzo requerido y finalmente podría resultar en intentos de manejo sub-óptimos o inútiles.

Dynamics of host populations affected by the emerging fungal pathogen Batrachochytrium salamandrivorans.

Emerging infectious diseases cause extirpation of wildlife populations. We use an epidemiological model to explore the effects of a recently emerged disease caused by the salamander-killing chytrid fungus Batrachochytrium salamandrivorans (Bsal) on host populations, and to evaluate which mitigation measures are most likely to succeed. As individuals do not recover from Bsal, we used a model with the states susceptible, latent and infectious, and parametrized the model using data on host and pathogen taken from the literature and expert opinion. The model suggested that disease outbreaks can occur at very low host densities (one female per hectare). This density is far lower than host densities in the wild. Therefore, all naturally occurring populations are at risk. Bsal can lead to the local extirpation of the host population within a few months. Disease outbreaks are likely to fade out quickly. A spatial variant of the model showed that the pathogen could potentially spread rapidly. As disease mitigation during outbreaks is unlikely to be successful, control efforts should focus on preventing disease emergence and transmission between populations. Thus, this emerging wildlife disease is best controlled through prevention rather than subsequent actions.