This statistic presents the estimated number of cats owned by households in Europe in 2010, 2012, 2014, 2016, 2017, 2018, 2019, 2020, 2021, 2022, and 2023. The cat population in Europe was measured at approximately ****** million in 2023.

Cats are a popular choice in Europe when it comes to pet ownership, although we don’t see them outside as often as their canine friends. As shown in this statistic, Germany and France are the two countries leading the list of cat owners in the EU, with the former’s narrow win. While Germany also ranks as the top EU country with the highest number of pet dogs, cats still win in European households.

EU loves cats

Compared with the cat population in Germany and France, countries such as Latvia, Ireland and Estonia had a low number of household felines. Yet across Europe in general, the number of cats has gone up significantly since 2010. In 2022, the EU alone was home to a large population of cats, making them the most preferred pets.

Cat food in pet care industry

The population of household cats in the European Union also corresponds to the volume of the pet care industry in this region. Between 2010 and 2022, pet food industry achieved steady growth.

This dataset is a modelled dataset, describing the predicted population of cats per postcode district (e.g. YO41). This dataset gives the upper estimate for population for each district, and was generated as part of the delivery of commissioned research. The data contained within this dataset are modelled figures, based on upper 95th percentile national estimates for pet population, and available information on Veterinary activity across GB. The data are accurate as of 01/01/2015. The data provided are summarised to the postcode district level. Further information on this research is available in a research publication by James Aegerter, David Fouracre & Graham C. Smith, discussing the structure and density of pet cat and dog populations across Great Britain. Attribution statement:

The population of pet cats in India amounted to nearly 3.6 million in the year 2023 and the population was forecast to reach approximately 5.76 million by the end of year 2028. The growth in the number of pets in India had led to the increase in of pet food sales, from approximately 172 million U.S. dollars in 2016 to approximately 629 million dollars in 2023.

This dataset is a modelled dataset, describing an upper estimate of cats per square kilometre across GB. The figures are aligned to the British national grid, with a population estimate provided for each 1km square. These data were generated as part of the delivery of commissioned research. The data contained within this dataset are modelled figures, based on upper 95th percentile national estimates for pet population, and available information on Veterinary activity across GB. The data are accurate as of 01/01/2015. The data provided are summarised to the 1km level. Further information on this research is available in a research publication by James Aegerter, David Fouracre & Graham C. Smith, discussing the structure and density of pet cat and dog populations across Great Britain. Attribution statement: ©Crown Copyright, APHA 2016

Presented are survival (s), sterilization rate (n), and fecundity (f) for owned cats, free-roaming cats, feral cats, and cats moving between these states via the shelter system. Survival and sterilization are annual probabilities whereas fecundity is the number of female kittens produced per female per year. Some vital rates are density dependent. Listed are the state and stage of the cat, the variable in the population model, the value or equation for the vital rate, and references that inform parameterization. Note that values may differ slightly from those presented in the original source and that if left blank the variable was assumed for this model. The number of litters per female per year was where 149 is the number of days required to produce 1 litter (pregnancy lasts 65 days, weaning young requires 84 days) and b is the length of the breeding season in days.

The estimated number of cats owned by households in Sweden increased in selected years from 2010 to 2023. The cat population in Sweden was measured at approximately 1.72 million in 2023, an increase form the previous year.

1. Estimating feral cat population densities in urban environments can be difficult due to lack of public space and human interference. The purpose of this study was to use distance sampling in a citywide landscape to determine population size and areas of high abundance to inform trap-neuter-release management programs.
2. Line transect distance sampling was used to estimate density of the feral cat population in Windsor, Ontario from June to July 2014. Windsor has a human population of 217,188 and is about 146 km2 in size. Most transects were placed along local roads.
3. Density was estimated at about 13.3 (95% CI 9.7 – 18.1) cats per km2, and an estimated population size of 1858 cats (95% CI 1361 – 2537) with the highest relative density occurring in West and Central Windsor.
4. Urban wildlife managers could utilize these methods to monitor feral cat populations and evaluate the effectiveness of trap-neuter-release programs.

In 2020, the number of pet cats in the Philippines amounted to approximately 2.06 million. The number of pet cats was forecast to reach nearly 3.15 million in 2029.

Shelter metrics can be used by shelters for self-assessment to optimize the health of their animal population and to identify risk factors for disease outbreaks. However, there is a need for a wider scope of these shelter metrics, as evidenced by the interest from shelters in the benchmarking of shelter progress and the development of national best practices. For the first time Dutch shelter data were used to retrospectively signal trends using potential reliable metrics for the analysis of shelter data. The aims of this study were to apply relevant metrics describing the different phases of shelter management for shelter cats (i.e., intake, stay and outcome) and a retrospective analysis of Dutch shelter data between 2006 and 2021. Seven of the approximately 120 Dutch animal shelters participated in this study. Quantitative data on the intake of more than 74,000 shelter cats (e.g., stray cats, cats surrendered by their owners and cats obtained from other sources) and their outcomes (i.e., cats rehomed, returned to their owners, deceased, or otherwise lost) have been analysed. Metrics as rehoming rate, return to owner rate, rates for mortality and euthanasia, length of stay and risk-based live release rate, were determined. The main findings of the study during this 16 years period were that over time the number of cats per 1000 residents admitted to Dutch shelters was reduced by 39%, the numbers of feline euthanasia decreased with approximately 50%, the length of stay showed a reducing trend, while the return to owner and the risk-based live release rate increased. The shelter metrics examined in this study could be helpful in monitoring and evaluating the management and consequent health and well-being of cats in shelters and eventually be a benchmark for shelters both in the Netherlands and at European level.

In the table, the symbols represent: H—number of households in urban area, Hc—proportion of households with one or more cats, Ch—average number of cats per household with one or more cats. C is shelter capacity and S is average length of stay. Df is log-transformed density of free-roaming cats (cats/ha), Dferal is the transformed density of feral cats (cats/ha), city area is the area in hectares of the urban area of interest.

Listed are the variable, transition between states, the equation for the vital rate, the value, and references that inform parameterization. Note that some values may differ slightly from those presented in the original source and that if left blank the variable was designated specifically for this model.

Policy development, implementation, and effective contingency response rely on a strong evidence base to ensure success and cost-effectiveness. Where this includes preventing the establishment or spread of zoonotic or veterinary diseases infecting companion cats and dogs, descriptions of the structure and density of the populations of these pets are useful. Similarly, such descriptions may help in supporting diverse fields of study such as; evidence-based veterinary practice, veterinary epidemiology, public health and ecology. As well as maps of where pets are, estimates of how many may rarely, or never, be seen by veterinarians and might not be appropriately managed in the event of a disease outbreak are also important. Unfortunately both sources of evidence are absent from the scientific and regulatory literatures. We make this first estimate of the structure and density of pet populations by using the most recent national population estimates of cats and dogs across Great Britain and subdividing these spatially, and categorically across ownership classes. For the spatial model we used the location and size of veterinary practises across GB to predict the local density of pets, using client travel time to define catchments around practises, and combined this with residential address data to estimate the rate of ownership. For the estimates of pets which may provoke problems in managing a veterinary or zoonotic disease we reviewed the literature and defined a comprehensive suite of ownership classes for cats and dogs, collated estimates of the sub-populations for each ownership class as well as their rates of interaction and produced a coherent scaled description of the structure of the national population. The predicted density of pets varied substantially, with the lowest densities in rural areas, and the highest in the centres of large cities where each species could exceed 2500 animals.km-2. Conversely, the number of pets per household showed the opposite relationship. Both qualitative and quantitative validation support key assumptions in the model structure and suggest the model is useful at predicting the populations of cats at geographical scales important for decision-making, although it also indicates where further research may improve model performance. In the event of an animal health crisis, it appears that almost all dogs could be brought under control rapidly. For cats, a substantial and unknown number might never be bought under control and would be less likely to receive veterinary support to facilitate surveillance and disease management; we estimate this to be at least 1.5 million cats. In addition, the lack of spare capacity to care for unowned cats in welfare organisations suggests that any increase in their rate of acquisition of cats, or any decrease in the rate of re-homing might provoke problems during a period of crisis.

The estimated number of cats owned by households in Denmark fluctuated in selected years from 2010 to 2023. The cat population in Denmark was measured at approximately ******* in 2023.

This dataset is a modelled dataset, describing the lower estimate of cat ownership characteristics per household at a postcode district level(e.g. YO41). This dataset gives the mean household owership rate for each district, and was generated as part of the delivery of commissioned research. The data contained within this dataset are modelled figures, based on lower 95th percentile national estimates for pet population, and available information on Veterinary activity across GB. The data are accurate as of 01/01/2015. The data provided are summarised to the postcode district level. Further information on this research is available in a research publication by James Aegerter, David Fouracre & Graham C. Smith, discussing the structure and density of pet cat and dog populations across Great Britain. Attribution statement: ©Crown Copyright, APHA 2016

The historical literature suggests that in Australia, the domestic cat (Felis catus) had a European origin [~200 years before present (ybp)], but it is unclear if cats arrived from across the Asian land bridge contemporaneously with the dingo (4000 ybp), or perhaps immigrated ~40000 ybp in association with Aboriginal settlement from Asia. The origin of cats in Australia is important because the continent has a complex and ancient faunal assemblage that is dominated by endemic rodents and marsupials and lacks the large placental carnivores found on other large continents. Cats are now ubiquitous across the entire Australian continent and have been implicit in the range contraction or extinction of its small to medium sized (<3.5kg) mammals. We analyzed the population structure of 830 cats using 15 short tandem repeat (STR) genomic markers. Their origin appears to come exclusively from European founders. Feral cats in continental Australia exhibit high genetic diversity in comparison with the low diversity found in populations of feral cats living on islands. The genetic structure is consistent with a rapid westerly expansion from eastern Australia and a limited expansion in coastal Western Australia. Australian cats show modest if any population structure and a close genetic alignment with European feral cats as compared to cats from Asia, the Christmas and Cocos (Keeling) Islands (Indian Ocean), and European wildcats (F. silvestris silvestris).

Median 10-year population growth rate (PGR) projections (95% CI) according to proportion of owned cats neutered prior to 6 months to prevent parturition at 6 months (prepubertally) and overall levels of neutering of adult owned cats.

Predation by feral cats Felis sylvestris catus is currently one hypothesized cause for the recent dramatic small mammal declines across northern Australia. We conducted a field experiment to measure …Show full descriptionPredation by feral cats Felis sylvestris catus is currently one hypothesized cause for the recent dramatic small mammal declines across northern Australia. We conducted a field experiment to measure the effect of predation by for this areas typically low-density cat populations on the demography of a native small mammal which due to the now natural scarce abundance of small mammals in the wild had to be reintroduced. We established two 12.5-ha enclosures in tropical savanna woodland on Wongalara Sanctuary, south of Arnhem Land in the Northern Territory. Each enclosure was divided in half, with cats allowed access to one half but not the other. We introduced about 20 individuals of Rattus villosissimus, a native rodent, into each of the four compartments (two enclosures x two predator-access treatments) and monitored rat demography by mark-recapture analysis and radio-tracking, and predator incursions by camera surveillance and track and scat searches. The data can be used for the mark-recapture analysis. The radio-tracking data and predator incursions data will be uploaded separately. The Cat and Dingoes camera trap dataset was produced using a heat-in-motion cameras (Reconyx PC800 Hyperfire, Holmen, Wisconsin, USA) around the outside of the perimeter fences to detect predators. At least four (but up to six and always the same number of cameras at a time) cameras were placed as one camera installed at each side on the outside of the fences of each enclosure. Cameras were un-baited, to avoid attracting predators. This one file dataset contains the information on the presence/absence data of cats and dingoes on each day. 'Site' indicates the enclosure the camera was attached to ('Enclosure_I' or Enclosure_II'), 'Camera number' indicates which site the camera was on. Note that between October 2011 and April 2012, Enclosure II had two additional cameras (one facing the front gate and one additional monitoring the lower half of the back fence of the enclosure) which resulted in a total of six cameras for during that time. 'Date' indicates the date the photo(s) was/were taken, 'Photos_recorded' whether the camera was operational or photos were retained (e.g. one SD-cards was lost). And columns 'Dingo' and 'Cat' indicate whether these animals were present that day or not (na = no photos recorded, 0 = not present that day, 1 = present that day).

Background: The concept of sustainability can be applied to the management of free-roaming cat populations by humans in their environment. An increasing and uncontrolled free-roaming cat population can create problems for humans, the environment and the cats themselves. One of the efforts to manage the local cat population is carried out by the Universitas Indonesia Cares About Animals/Universitas Indonesia Peduli Hewan (UIPH) community in an urban campus environment. Such management is not necessarily in line with the concept of sustainability because it can be influenced by local community and environmental factors about which there is not much knowledge yet. Methods: Therefore, research is needed to find out more about the condition of free-roaming cats, the motivation and the role of UIPH in the UI Depok campus. A qualitative approach with in-depth interviews, direct observation and literature study is used. Findings: The results show that UIPH is a community of members from lecturers, staff and students who have concern for the survival of cats. UIPH activities include Feeding, Rescue, Fostering, Adoption and Education which are also assisted by volunteers, donations and co-sponsor collaborations. Activities by UIPH contribute to the condition of free-roaming cats that can roam freely on campus with relatively fat and healthy bodies. Conclusion: In its process, UIPH also faces problems and challenges related to the natural, social or man-made environment. But so far, they have been able to face them and carry out their routine activities. Membership, connections and ongoing programs have become an opportunity to develop community activities and regenerate wild animal awareness on campus. Novelty/Originality of this article: This study highlights the unique role of the UIPH community in managing free-roaming cat populations on an urban campus, contributing to the health and well-being of the animals. It also emphasizes the influence of local environmental and social factors in shaping sustainable wildlife management strategies.

From 2010 to 2023 the cat population in Germany increased each year. In 2010, the cat population was only at about *** million and had close to double by 2023, reaching **** million. The cat population decreased to **** million in 2023.