Ticks are haematophagous arthropods that exert direct and indirect effects on their hosts. Their global importance as reservoirs and vectors of diseases of veterinary and public health importance is well recognized. However, the level of understanding of their role in disease epidemiology varies from one country to the other based on available data. Information on ticks infesting dogs across Nigeria and the public health significance is scarce. Therefore, this study aimed to provide information on ixodid ticks infesting dogs in Nigeria. Ticks were collected from 608 owned dogs presented to veterinary clinics and hospitals in 10 out of 36 states of Nigeria over a 14-month period and identified using taxonomic descriptions and morphological keys. In all, 1196 ticks belonging to three genera were identified. Rhipicephalus (including the subgenus Boophilus) ticks were collected from dogs from all the states surveyed and accounted for 95.2% of the ticks collected, followed by Haemaphysalis (3.7%) and Amblyomma species (1.2%). The brown dog tick, Rhipicephalus sanguineus sensu lato was the only tick identified in all the climatic zones of Nigeria. There is a statistically significant association between tick infection rate and rainy season, female animals, local and cross breed against exotic animals, total lack of control practice by dog owners, frequency of the control and with traditional methods of tick control but not the age of the dogs. The epidemiological and public health implications of these findings were discussed.
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http://dx.doi.org/10.1007/s10493-019-00384-2 | DOI Listing |
J Med Internet Res
January 2025
Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, United States.
Background: Clinical decision support systems leveraging artificial intelligence (AI) are increasingly integrated into health care practices, including pharmacy medication verification. Communicating uncertainty in an AI prediction is viewed as an important mechanism for boosting human collaboration and trust. Yet, little is known about the effects on human cognition as a result of interacting with such types of AI advice.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.
Background: Black adults in the United States experience disproportionately high rates of tobacco- and obesity-related diseases, driven in part by disparities in smoking cessation and physical activity. Smartphone-based interventions with financial incentives offer a scalable solution to address these health disparities.
Objective: This study aims to assess the feasibility and preliminary efficacy of a mobile health intervention that provides financial incentives for smoking cessation and physical activity among Black adults.
J Med Internet Res
January 2025
NORC at the University of Chicago, Chicago, IL, United States.
Background: Poor health outcomes are well documented among patients with a non-English language preference (NELP). The use of interpreters can improve the quality of care for patients with NELP. Despite a growing and unmet need for interpretation services in the US health care system, rates of interpreter use in the care setting are consistently low.
View Article and Find Full Text PDFStress Health
February 2025
Collaborative Innovation Center of Assessment Toward Basic Education Quality, Beijing Normal University, Beijing, China.
This study explored the structure and temporal evolution of the relationship among depression, maladaptive cognition, and internet addiction (DMI) among university students by focusing on topological and dynamic properties in a network analysis. A 3-year longitudinal survey was conducted with 873 university students (M = 18.32, SD = 0.
View Article and Find Full Text PDFJAMA Health Forum
January 2025
Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Importance: Skilled nursing facilities (SNFs) experienced high mortality during the COVID-19 pandemic, leading them to adopt preventive measures to counteract viral spread. A critical appraisal of these measures is essential to support SNFs in managing future infectious disease outbreaks.
Objective: To perform a scoping review of data and evidence on the use and effectiveness of preventive measures implemented from 2020 to 2024 to prevent COVID-19 infection in SNFs in the US.
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