Search

Timely, accurate, and comprehensive estimates of SARS-CoV-2 daily infection rates, cumulative infections, the proportion of the population that has been infected at least once, and the effective reproductive number (Reffective) are essential for understanding the determinants of past infection, current transmission patterns, and a population's susceptibility to future infection with the same variant. Although several studies have estimated cumulative SARS-CoV-2 infections in select locations at specific points in time, all of these analyses have relied on biased data inputs that were not adequately corrected for. In this study, we aimed to provide a novel approach to estimating past SARS-CoV-2 daily infections, cumulative infections, and the proportion of the population infected, for 190 countries and territories from the start of the pandemic to Nov 14, 2021. This approach combines data from reported cases, reported deaths, excess deaths attributable to COVID-19, hospitalisations, and seroprevalence surveys to produce more robust estimates that minimise constituent biases.

National rates of COVID-19 infection and fatality have varied dramatically since the onset of the pandemic. Understanding the conditions associated with this cross-country variation is essential to guiding investment in more effective preparedness and response for future pandemics.

Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021.

Before 2020, mental disorders were leading causes of the global health-related burden, with depressive and anxiety disorders being leading contributors to this burden. The emergence of the COVID-19 pandemic has created an environment where many determinants of poor mental health are exacerbated. The need for up-to-date information on the mental health impacts of COVID-19 in a way that informs health system responses is imperative. In this study, we aimed to quantify the impact of the COVID-19 pandemic on the prevalence and burden of major depressive disorder and anxiety disorders globally in 2020.

Goose management in Europe is faced by multiple challenges, as some species are declining and in need of conservation actions, while other populations have become very abundant, resulting in calls for increased harvest. Sweden has long-term series of harvest data and counts of breeding and autumn-staging geese. We used national data (indices) for greylag goose, bean goose and Canada goose to study shifts in temporal trends and correlative patterns, and to infer possible causal links between harvest and population trends. Our study provides an opportunity to guide management given the data collected within the present monitoring, as well as to suggest improvements for future data collection. The populations of greylag and Canada geese increased in Sweden 1979–2018, but this long-term trend included a recent decrease in the latter species. Bean goose breeding index decreased, whilst staging numbers and harvest varied with no clear long-term trend. For Canada goose, our analysis suggests that harvest may affect population growth negatively. For bean goose and greylag goose we could not detect any effect of harvest on autumn counts the following year. We find that the present data and analysis of coherence may suffice as basis for decisions for the current management situation in Sweden with its rather unspecific goals for greylag (very abundant) and Canada goose (invasive species) populations. However, for management of bean geese, with international concerns of over harvest, data lack crucial information. For future management challenges, with more explicit goals, for all goose species we advocate information that is more precise. Data such as hunting effort, age-structure of goose populations and mark–recapture data to estimate survival and population size, is needed to feed predictive population models guiding future Swedish and European goose management.

In western Europe, the majority of wild goose populations have increased exponentially over the last decades. Such increase is the source of many socio–ecological conflicts. The need for coordinated management actions to handle the goose-related conflicts at the European scale has led to the establishment of a specific European Goose Management Platform (EGMP) under the auspices of the Agreement on the Conservation of African–Eurasian Migratory Waterbirds (AEWA). The northwest/south-west (NW/SW) European population of greylag goose Anser anserhas been considered as a priority concern, and an AEWA international single species management plan has been recently adopted. Because of the complex structure of the greylag goose population (e.g. spatial differences in migration strategies), and management (e.g. different hunting schemes among the range states), delineation of management units (MUs) based on goose movement characteristics was deemed necessary to further implement effective management actions. Based on neckband marking in various breeding regions and subsequent resighting locations, we conducted spatio–temporal analysis based on kernel methods to infer spatio–temporal and migratory movements of greylag geese in the NW/SW European flyway. The results highlight the existence of contrasted migratory behaviour, dispersal patterns and phenology within the flyway. From these results three international management units could be delineated. The first MU would include migratory birds from Norway. Birds from breeding grounds in Sweden and Denmark would represent the second MU. Finally, a third central MU was delineated, including primarily breeding birds from the Netherlands and northwestern Germany, which do not show migratory behaviour at the flyway scale. The delineation of these MUs has to be considered within an adaptive process, and future studies will enable a refinement of the definition of such units in order to continuously improve the efficiency of management plans.

A key challenge for wildlife management is to handle competing goals. High ungulate densities may be desirable from hunting and recreational perspectives, but may come in conflict with needs to limit or reduce browsing damage. Since browsing intensity is negatively related to forage availability it may be possible to mitigate damage on forest by increasing forage availability within the landscape. A commonly used method to increase the attractiveness of a localized part of the landscape is to establish food plots. In a multiyear setup using enclosures, wildlife observations, field surveys, and controlled biomass removal, we studied food plots to document forage production, utilization by ungulates, and browsing on adjacent forests in southern Sweden. The fenced parts of the food plots produced on average 2230 to 5810 kg ha-1marrow-stem kale, second-year clover mix or early-sown rapeseed. The biomass of target crops was generally higher within ungrazed (exclosures) compared to grazed (controls) quadrats on the food plots, which demonstrates that the crops were used as forage by ungulates. Browsing on deciduous trees in the adjacent forest was higher within 70–135 m from the food plots compared to areas further away. For wildlife management, our study shows that establishment of food plots provides substantial amounts of forage both during growing season and at the onset of the dormant season, and that a large share of this food is consumed. Finally, our study documents that forage availability for ungulates at the onset of the often-limiting dormant season can be increased by fencing food plots throughout the growing season.

We need to monitor wildlife populations to determine whether management goals are achieved and to improve future decisions. Therefore, it is important to evaluate the cost and accuracy of monitoring strategies in the context of management. Using a computer simulation of a harvested population, we tested the relative performance of three survey methods: aerial survey, pellet-group counts and hunters' observations, to inform about the management of Swedish moose Alces alces populations. Where more than one survey method was used in a single year, we used Bayes' theorem to combine information and estimate population size. We used two measures of performance: the fraction of time in which the population had an ‘undesirable’ size and inter-annual variation in harvest. Furthermore, we traded these performance measures against their cost. An annual aerial survey was the most costly monitoring method (27,000€) and maintained the population within the desired range 72% of the time. The least expensive monitoring strategy (hunters' observations; 1,600€) maintained the population within a desired range of 66% of the time. A combination of two relatively inexpensive survey methods (i.e. pellet-group counts and hunters' observations; at an expense of 10,000€) maintained the population within the desired range in 76% of the simulated years. Thus, a combination of annual pellet-group counts and hunters' observations performed better than annual aerial surveys, but was considerably less expensive. Furthermore, the annual combination of pellet-group counts and hunters' observations also performed best regarding the inter-annual harvest variation. Management actions only maintained the population within the desired range 81% of the time, even when population size was observed without error, mainly due to variable net growth rates. In wildlife management systems, where a variety of monitoring methods are used, the overall performance generally improves with monitoring expenditure, but very few studies explicitly account for expenditure. However, our study shows that combinations of inexpensive methods can reduce monitoring costs substantially while yielding an equal or an increased performance.

Foraging patterns, behaviour and the distribution of animals are affected by the availability and distribution of food in the landscape. Increasing numbers of ungulates may also be in conflict with agriculture, timber, infrastructure and conservation interests. Understanding foraging habits of ungulates and how these are affected by a change in forage availability or composition are, therefore, issues of major importance both from ecological and management perspectives. Supplementary feeding (i.e. artificial supply of food) is being used to improve local habitat, and thereby affecting ungulate movements, habitat choice and migration patterns. We experimentally tested the predictions that supplementary feeding redistributes moose Alces alces during two different migration phases (early, i.e. during the onset of migration and late, i.e. in the wintering areas). We used individually marked moose and pellet group counts to investigate the effect of supplementary feeding both at the individual and population level. We monitored 30 moose with GPS-collars before, during and after the supplementary feeding experiment, corresponding to 8-10% of the moose population in two different valleys in Northern Scandinavia. During early migration, moose ignored supplementary feeding sites even though migration routes were close to the sites. At the end of the migration route, supplementary feeding affected moose movement, distribution and behaviour. In conclusion, we suggest that there is a clear difference in response to supplementary feeding by moose due to the phase of migration. We conclude that supplementary feeding can be used under certain conditions to redistribute moose in relation to browsing, or to traffic, preferably at the end-point of migration.

Various survey methods are used to monitor and manage ungulate populations. The choice of optimal method depends on estimation accuracy, management objective and financial constraints. Here we compare estimates produced by four different methods for estimating population size, i.e. aerial counts, hunter observations, pellet group counts and cohort analysis. A Swedish moose Alces alces population was studied during 1973–2005 in the Grimsö Wildlife Research Area (135?km2). The highest correlation was found between cohort analysis and aerial counts (r=0.69, P<0.05), and the hunter observations and the aerial counts (r=0.76, P<0.10). The different methods produced relatively consistent trends in population estimates over years. Pellet group counts prior to 1997 were not significantly correlated with the other methods, probably due to unrepresentative spatial sampling. A comparison of the aerial and pellet group counts in 2002 and 2006, showed that the average defecation rate was estimated at approximately 14 pellet groups per day per moose. Our results show the importance of having representative spatial sampling in pellet group surveys and indicate that hunter observations can be a useful tool for estimating long-term population trends even in moderately sized areas.