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.
According to a national pet owners survey, there was a total of approximately 95.6 million cats living in households in the United States in 2017. In the same year, some 68 percent of all U.S. households owned at least one pet.
Increasing pet expenditure
Whilst the number of households owning cats, and pets in general, has remained relatively consistent over the last few years, pet industry expenditure has steadily grown. Consumers are expected to spend a record breaking 75.38 billion U.S. dollars on their pets in 2019. The majority of pet market revenue comes from food sales, followed by veterinary care costs.
Shopping location preferences
When it comes to shopping locations, most consumers still purchase their pet products in physical retail stores. However, the number of consumers buying pet products online is on the rise. Dry cat food was the number one pet product bought online by cat owners in the United States in 2018.
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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:
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
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.
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.
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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.
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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.
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.
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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 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.
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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.
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This dataset is a modelled dataset, describing the mean 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 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.
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This driver analyzes the number of domesticated pets and companion animals owned in the US. Pets, defined in this driver as either cats or dogs, provide personal company or protection but are not considered working animals or livestock. The American Pet Products Association (APPA) conducts a biennial National Pet Owners Survey, and the data used in the survey regarding cat and dog ownership is collected and discussed here.
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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).
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This study used a previously developed stochastic simulation model (1) to estimate the impact of different management actions on free-roaming kitten and cat mortality over a 10-year period. These longer-term cumulative impacts have not been systematically examined to date. We examined seven management scenarios, including: (1) taking no action, (2) low-intensity removal, (3) high-intensity removal, (4) low-intensity episodic culling, (5) high-intensity episodic culling, (6) low-intensity trap-neuter-return (TNR), and (7) high-intensity TNR. For each scenario we tracked within the model the number of kittens born, the number of kittens surviving to adulthood, and the number of adults removed using lethal control over the entire 10-year simulation. We further defined all kitten deaths and lethal removal of adults as “preventable” deaths because they could potentially be reduced by certain management actions. Our simulation results suggested that the cumulative number of preventable deaths over 10 years for an initial population of 50 cats is highest for a “no-action” scenario, estimated at 1,000 deaths. It is lowest for a high-intensity TNR scenario, estimated at 32 deaths, a 31-fold difference. For all management scenarios tested, including removal and culling, the model predicted fewer preventable deaths than for a no-action scenario. For all management scenarios, the model predicted that the higher-intensity option (defined in terms of the proportion of animals sterilized or removed within a given time period) would result in fewer preventable deaths over time than the lower-intensity option. Based on these findings, we conclude that management intensity is important not only to reduce populations more quickly, but also to minimize the number of preventable deaths that occur over time. Accordingly, the lessons for the animal welfare community are both encouraging and cautionary. With sufficient intensity, management by TNR offers significant advantages in terms of combined lifesaving and population size reduction. At lower intensity levels, these advantages are greatly reduced or eliminated. We recommend that those who seek to minimize suffering and maximize lifesaving for free-roaming cats attempt to balance prospective goals (i.e., saving lives tomorrow) with proximate goals (i.e., saving lives today), and recognize that thoughtful choice of management strategies can ensure that both of these complementary goals are achieved.
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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).
The cat population in Romania increased considerably over the last years and peaked at approximately **** million in 2023. This represented an increase of **** percent compared to the cat population registered in 2010.
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Free-ranging domestic cats are a detriment to wildlife and humans by preying on native species and transmitting disease. As a result, removing free-ranging cats from the landscape has become a conservation and public health priority. Estimating cat population size with an unbiased sampling design, however, especially in human-dominated areas, is logistically challenging and rarely done. The lack of robust cat population sampling limits our understanding of where cats pose risks, which is important for evaluating management strategies, such as trap-remove or trap-neuter-return. We hypothesized that cat abundance and activity both depend on human land use and demographics. Using a network of sites participating in a community science program, we conducted transect and camera trap surveys to test predictions of cat population abundance and activity across a gradient of residential land use intensity. Both sampling methods determined that cat abundance was greatest in areas with intermediate human population density and lower educational attainment. Transect data also provided evidence that cat abundance was greatest at intermediate levels of impervious surface cover (e.g., road and buildings), while data from camera traps also showed that cat abundance was positively associated with household income. Using counts of cats observed on cameras, we found that the timing of cat activity varied depending on the degree of urban intensity. Cats were more strictly nocturnal in medium and high intensity residential land-use areas, possibly because a greater proportion of these cats are unowned or because they avoid human activity. These results suggest that transect surveys conducted during the day may undercount cats in urban environments where unowned free-ranging cats predominate. Taken together, our results highlight the importance of incorporating human demographics, land use patterns, and urban context in estimating the abundance of free-ranging cats to better inform management decisions and improve conservation outcomes.
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.