^Adjusted for age group, sex, highest education level completed, ethnicity/race and number of children living in household. Reference group: other pet owner.*P < 0.05** P < 0.001Odds ratios (95% CI) for getting to know people, friendship formation and social support by dog compared with other pet ownership.

With the DDMM (Data-Based Management Model) in Istanbul research, it is aimed to determine the general sociodemographic and socioeconomic profile, needs and tendencies of the people of Istanbul and to produce data that will form the basis for strategies to be formed on investment and services. For this purpose, interviews were conducted with 50,000 households throughout the city using face-to-face survey method. The number of surveys was distributed in proportion to the number of neighborhood households, with at least 12 surveys per neighborhood. In order for the results of the study to represent Istanbul, the households to be interviewed were selected at the neighborhood level by stratified random sampling method. The fieldwork, in which the final form of the questionnaire was applied through workshops and meetings, was carried out between 29.11.2021 and 07.03.2022. In this data set; District-based analysis data of Data-Driven Management Model research shared as raw data are included takes.

Abstract

The financing of the public health sector in Madagascar has gone through significant changes over the last years. Before the new government came to power in the middle of 2002, it adhered strictly to a patient fee policy. After the new government took office, the user fee policy was abolished in an effort to mitigate the effect of the large poverty increase after the political crisis in 2002 on formal health care.

The objectives of this study were to evaluate health facilities' efficiency, measure patients' satisfaction and determine the impact of the suspension of user fees in the health sector.

Madagascar PETS-QSDS in Health also known as Etude sur l'Efficience et Equité des Formations Sanitaires à Madagascar (EEEFS) was fielded in May - June 2003. The sampling frame was the same as used for the nationwide household survey, the Enquête Permanente auprès des Ménages (EPM) in 2002.

Geographic coverage

Antananarivo, Fianarantsoa, Toamasina, Mahajanga, Toliara and Antsiranana provinces.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame for PETS-QSDS in Health 2003 was the same as used for the nationwide household survey, the Enquête Permanente auprès des Ménages (EPM) in 2002. The primary sampling units of the EPM were "zones de denombrement" (ZDs) or groups of ZDs; each ZD corresponds generally to the fokontany administrative level which in turn is equivalent to a village. Eighty out of 303 of the ZDs from the original EPM survey were randomly chosen to be re-surveyed for the PETS-QSDS in Health. This was done to allow the study to build on the earlier EPM data collection. Twenty seven (34%) of the 80 ZDs were rural, reflecting the oversampling of urban areas in the EPM (the population of the country as a whole is about 80% rural).

For the household survey, the objective was to re-interview all the households in selected ZDs. This effort was quite successful (1010 of the original 1066 households were re-interviewed), reflecting the fact that the EPM survey had been carried out just several months earlier. Households lost to attrition were replaced by other households in the cluster. Since the usual range of information on household characteristics and activities was collected for the EPM for the re-interviewed households, the new survey was an abbreviated one that focused in detail on health-related behavior.

Mode of data collection

Face-to-face [f2f]

Research instrument

The data were collected using the following survey instruments: - the health district questionnaire, - the facility questionnaire, - the community questionnaire, - the user exit questionnaire, - the household questionnaire.

For the user exit survey, patients were randomly selected to be interviewed upon exiting each facility. They were asked questions about their impressions of the quality of care and the condition of the health care facility, the welcome provided by the facility, the actions taken and information provided to them by the health practitioner during their consultation, and the cost of the consultation and of drugs provided. The user survey also collected information about the characteristics of respondents and their families.

Coenurosis, a fatal parasitic disease, is widespread in the highlands of Ethiopia, where 75% of the country’s sheep population is found. There is a significant prevalence of the disease in the current study area. Therefore, the current study was conducted to reduce the impact of cerebral coenurosis on sheep production in the study area by integrating different prevention and control options and raising community awareness of the disease. Questionnaire surveys, coproscopic examination of dog feces, and household-level surveillance were used to collect data on reported coenurosis cases and taeniid infections. Awareness creation training and regular dog deworming were used as an intervention to reduce the prevalence of the disease. A total of 107, 134, 153, and 124 dogs were dewormed during the first, second, third, and fourth rounds during the study period, respectively. Eggs were detected in 58.53% (95% CI 47.4- 68.86) of pre-deworming fecal samples of dogs. Eggs were detected in 24.18% (95% CI: 40.0–49.7) of the fecal samples after the intervention, 34.35% less than before the intervention. At the beginning of the intervention, the level of awareness of farmers in the intervention sites about the cause of the disease was 12.2%, which increased to 51.03% at the end of the intervention. The community-based integrated animal health management approach for coenurosis control has the potential to be expanded throughout the country, thus reducing economic losses in communities where the disease is endemic. Methods A representative number of animals were randomly selected from each intervention village for physical examination and fecal sampling before and after deworming. The pre- and posttreatment samples were not paired, with independent cross-sectional sampling at both pre- and post-treatment. The sampling was performed at the time of treatment and 14 days later. Deworming and sampling were performed four times per year, every three months. Fecal samples were taken from dogs for fecal egg count and parasite identification and speciation. The fecal samples were collected directly from the rectum. From each animal, 5–10 g of fecal material was collected in a clean polythene bag containing 10% formalin as a preservative. A semi-structured questionnaire was administered to those small ruminant owners to reveal information on the prevalence, morbidity, and mortality of the disease in the last 1 / 2 years, perception and awareness about the cause, risk factors, and transmission of the disease, the level of animal-dog interaction, the existence of wildlife (foxes and rabbits) and their interaction with the domestic and socioeconomic impact of the disease. The households were selected by random sampling from the households list at the Kebele administration office. Thirty households were randomly selected from each Kebele study Kebele. A local ethics committee ruled that formal ethics approval was not required for this research. Before conducting the investigation, informed consent was obtained from the animal owners in this study.

Campylobacteriosis disproportionately affects children under five in low-income countries. However, epidemiological and antimicrobial resistance (AMR) information at the children-animal interface is lacking. We hypothesized that Campylobacter is a major cause of enteritis in children in Ethiopia, and contact with animals is a potential source of transmission. The objective of the study was to determine Campylobacter occurrence and its AMR in children under five with diarrhea, backyard farm animals, and companion pets. Stool from 303 children and feces from 711 animals were sampled. Campylobacter was isolated through membrane filtration on modified charcoal cefoperazone deoxycholate agar plates under microaerobic incubation, and the technique showed to be feasible for use in regions lacking organized laboratories. Typical isolates were characterized with MALDI-TOF MS and multiplex PCR. Of 303 children, 20% (n = 59) were infected, with a higher proportion in the 6 to 11-month age group. Campylobacter occurred in 64% (n = 14) of dogs and 44% (n = 112) of poultry. Campylobacter jejuni was present in both a child and animal species in 15% (n = 23) of 149 households positive for Campylobacter. MICs using the gradient strip diffusion test of 128 isolates displayed resistance rates of 20% to ciprofloxacin and 11% to doxycycline. MICs of ciprofloxacin and doxycycline varied between C. coli and C. jejuni, with higher resistance in C. coli and poultry isolates. Campylobacter infection in children and its prevalent excretion from backyard poultry and dogs is a understudied concern. The co-occurrence of C. jejuni in animals and children suggest household-level transmission As resistance to ciprofloxacin and doxycycline was observed, therapy of severe campylobacteriosis should consider susceptibility testing. Findings from this study can support evidence-based diagnosis, antimicrobial treatment, and further investigations on the spread of AMR mechanisms for informed One Health intervention.

Kenward-et-al_RADA_Buzzard_radio-tracking_dataData used to infer the resource needs of common buzzards (Buteo buteo) Dorset, southern UK. Inference was made by applying Resource-Area-Dependence Analysis (RADA) to a sample of 114 buzzard home ranges and a thematic map depicting resource distribution. The compressed archive contains the radio-tracking dataset, which consists of standardized 30 locations per home range obtained via VHF telemetry between 1990 and 1995. The thematic map, formed by using knowledge about buzzards to group 25 land-cover types of the Land Cover Map of Great Britain into 16 map classes, is available against permission at public site http://www.ceh.ac.uk/services/land-cover-map-1990. All coordinates are in UK National Grid format (EPSG 27700). The radio-tracking dataset is provided as: (i) .txt and (ii) .loc. The format in (ii) is native to the Ranges suite of software (http://www.anatrack.com/home.php) for the analysis of animal home ranging and habitat use. Sinc...

Companion Animal Postoperative Pain Management Therapeutics Market Outlook 2032

The global companion animal postoperative pain management therapeutics market size was USD 319.7 Million in 2023 and is projected to reach USD 582.8 Million by 2032, expanding at a CAGR of 6.9% during 2024–2032. The market growth is attributed to the rising awareness regarding animal health and welfare among consumers.



The companion animal postoperative pain management therapeutics market is experiencing a significant surge, driven by an increasing awareness of animal welfare and the growing demand for advanced veterinary care. As pet ownership continues to rise, so does the need for effective pain management solutions post-surgery. This trend is further propelled by the escalating advancements in veterinary medicine, which have led to the development of innovative therapeutics that ensure a faster and more comfortable recovery for companion animals.

The market is witnessing a growing emphasis on research and development activities, aimed at introducing more effective and safer therapeutic options. This is largely due to the rising incidence of chronic diseases among companion animals, necessitating surgical interventions and subsequent postoperative care. The increasing investment in these R&D initiatives is creating lucrative opportunities for market players, fostering competition and innovation in the sector.

Impact of Artificial Intelligence (AI) on Companion Animal Postoperative Pain Management Therapeutics Market

Artificial Intelligence has a positive impact on the companion animal postoperative pain management therapeutics market. AI algorithms analyze vast amounts of data to identify patterns and trends, accelerating the discovery and development of new therapeutics. These advancements result in more effective and safer pain management drugs for companion animals post-surgery.



AI-powered devices monitor patients in real-time, providing veterinarians with valuable insights into an animal's pain levels and recovery progress. This technology allows for immediate adjustments to treatment plans, ensuring optimal pain management. AI also enables the creation of personalized treatment plans based on an animal's specific needs and responses to medication, significantly improving postoperative outcomes.

Abstract

The general objectives for the Post-Harvest Survey (PHS) which is undertaken annually include: - Provision of annual agricultural data that helps to facilitate comprehensive analysis of the agricultural sector's contribution to the national economy, on annual basis; - Development of the Agricultural Statistics Management Information System (ASMIS) to a level such that it accommodates advances in information technology; and, - Provision of annual agricultural data that is useful for generation of performance indicators to facilitate interventions by Government, donors and NGOs.

The report specifically contains information on: Provision of actual figures pertaining to: - Area planted to individual crops; - Production quantities; - Sales of produce and income realized; - Purchase and use of agricultural inputs; - Capital formation and other operational expenses; - Demographic characteristics of heads of rural households; - Farming practices and soil conservation methods used; - Access to agricultural loans; and, - Access to market prices information and agricultural extension services in general.

Geographic coverage

National coverage

Analysis unit

Agricultural holding household

Universe

The survey covered households for small and medium scale farmers

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame of Standard Enumeration Areas (SEAs) was constructed using the results from the 2000 Census of Population and Housing. Within each district, the SEAs were stratified by predominant crop in order to ensure a representative sample for each crop. The SEAs were then sorted by geographic codes to ensure that geographical distribution of the sample SEAs is also representative. The sampling frame included all rural SEAs. In addition, urban SEAs, which had 70% or more agricultural households according to the Census, were included in the frame.

A two-stage sample scheme was adopted. At the first stage, an allocated proportional number in each province and district was selected using Probability Proportional to Size (PPS) selection procedure. The measure of size was the number of agricultural households (as listed in the Census) in each SEA. A sample of 410 SEAs was selected from a total of 12,789 SEAs. 20 households were selected from each of the 410 SEAs.

The household was the second stage-sampling unit. First all households in each Sample SEA were listed and agricultural households were identified. To improve the precision of the survey estimates, the agricultural households were stratified into three (3) categories- A, B and C, based on total area under crops, presence of some specified crops and on numbers of cattle, goats and chickens raised. A number of households were selected from each category using systematic random sampling method, coming up with a total of twenty (20) sample households in each Sample SEA

Sampling deviation

There was no deviation from sample design.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2003/2004 PHS questionnaires were used to collect information on the following: - Name of the village/locality; - Household serial number (assigned by the Enumerator during listing); - Name of the head of household; - Sex and age of head of household; - Household population, i.e., number of members of households by sex and age; - Type of agricultural activity the household is involved in; - Fertilizer acquisition and use; - Crop production and sales; - Vegetable and fruit production and sales; - Livestock and poultry production and marketing; - Household Production Assets/implements; - Food purchases and food aid/relief for home consumption; - Health and deaths: past 3 months and past five years; - Crop Management - input application and tillage methods; - Crop rotation and irrigation.

Cleaning operations

Supervisors and some enumerators based at provincial headquarters edited the questionnaires. The edited questionnaires were entered on microcomputers using a software package known as CSpro. Data capturing was accomplished at each provincial centre. Initial computer data processing was done at the provincial headquarters using CSpro software. Staff in Agriculture and Environment Division based at CSO headquarters did further data computer processing.

Consistency checks on the output of the raw data, with reference to the source documents, were applied before final weighted tables at district and provincial levels were produced. The software used for analysis was Statistical Package for Social Sciences (SPSS), while Microsoft Excel was used for data tabulation.

Response rate

The response rate was 100 percent.