The present prospective study is reliable because these three source diseases were determined based on predefined criteria using examples from published studies of nursing homes 8 12–16 (table 1).
For this, we used MalaCards' capacity to relate a search string to a large diversity of diseases, based on its multi-source disease-centric textual information.
After being collected, the data are aggregated by source, disease, and geographic location and then overlaid on an interactive map for user-friendly access to the original report.
Furthermore, utilizing the genome-scale metabolic models (GSMMs), Yizhak et al. [ 39] proposed a metabolic transformation algorithm (MTA) to search for targets that could restore the metabolism within the cell from the source (disease) state to the target (healthy) state.
We performed independent and duplicate screening and abstraction of study administrative data, prevalence, determinants, type of antimicrobial agent, source, disease conditions, inappropriate use, drug adverse events and clinical outcomes of antibiotic self-medication where possible.
A summary table including author, title, journal, published year, study period, objectives, data source, disease definition, country in which the study was conducted, and main findings of each study was created (Table 1).
This approach is endorsed by NICE [ 14] and there is a growing body of literature related to the development of mapping functions linking source disease specific HRQL measures onto target preference-based measured using regression models [ 15].
David Quammen's Spillover is a collection of stories about the sources of diseases called zoonoses.
Clark provided me with numerous links, some with assertions and unnamed sources saying diseases (new polio strains, tuberculosis, measles) are being brought to America by undocumented immigrants.
First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics.
