Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Background: Mapping malaria risk is an integral component of efficient resource allocation. Routine health facility data are convenient to collect, but without information on the locations at which transmission occurred, their utility for predicting variation in risk at a sub-catchment level is presently unclear.
Methods: Using routinely collected health facility level case data in Swaziland between 2011-2013, and fine scale environmental and ecological variables, this study explores the use of a hierarchical Bayesian modelling framework for downscaling risk maps from health facility catchment level to a fine scale (1 km x 1 km). Fine scale predictions were validated using known household locations of cases and a random sample of points to act as pseudo-controls.
Results: Results show that fine-scale predictions were able to discriminate between cases and pseudo-controls with an AUC value of 0.84. When scaled up to catchment level, predicted numbers of cases per health facility showed broad correspondence with observed numbers of cases with little bias, with 84 of the 101 health facilities with zero cases correctly predicted as having zero cases.
Conclusions: This method holds promise for helping countries in pre-elimination and elimination stages use health facility level data to produce accurate risk maps at finer scales. Further validation in other transmission settings and an evaluation of the operational value of the approach is necessary.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349235 | PMC |
| http://dx.doi.org/10.1186/1475-2875-13-421 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Impact of a Home-Based Remote Patient Monitoring System on Hospitalizations and Emergency Department Visits of Older Adults With Polypathology: Multicenter Retrospective Observational Study.
J Med Internet Res
September 2025
Centre Hospitalier Rives de Seine, Courbevoie, France.
Background: Every year in France, 40% of people aged ≥80 years are hospitalized, with an average length of hospital stay of 25 days and a readmission rate of 14% to 30% within the month following discharge. This situation is putting pressure on the health care system, encouraging the reinforcement of home care to reduce avoidable hospitalization. The EPOCA remote patient monitoring (RPM) system is a medical and social telehealth solution specialized in RPM, teleconsultation, tele-expertise, and care coordination in emergency medicine and geriatrics.
View Article and Find Full Text PDFQuantifying Spatial Shadow Zones and Their Association With Hospital Falls in Acute Care Unit: Real-Time Location System Observational Study.
JMIR Form Res
September 2025
Department of Emergency Medicine, College of Medicine, National Taiwan University Hospital, Taipei, Taiwan.
Background: Hospital falls represent a persistent and significant threat to safety within health care systems worldwide, impacting both patient well-being and the occupational health of health care staff. While patient falls are a primary concern, addressing fall risks for all individuals within the health care environment remains a key objective. Caregiver visibility and spatial monitoring are recognized as crucial considerations in mitigating fall-related incidents.
View Article and Find Full Text PDFMedications for Opioid Use Disorder in County Jails - Outcomes after Release.
N Engl J Med
September 2025
Department of Health Promotion and Policy, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst.
Background: In 2019, seven county correctional facilities (jails) in Massachusetts initiated pilot programs to provide all Food and Drug Administration-approved medications for opioid use disorder (MOUD).
Methods: This observational study used linked state data to examine postrelease MOUD receipt, overdose, death, and reincarceration among persons with probable opioid use disorder (OUD) in carceral settings who did or did not receive MOUD from these programs from September 1, 2019, through December 31, 2020. Log-binomial and proportional-hazards models were adjusted for propensity-score weights and baseline covariates that remained imbalanced after propensity-score weighting.
Analysis of the work of the inpatient military hospital during the Russian-Ukrainian war.
Pol Merkur Lekarski
September 2025
POLTAVA STATE MEDICAL UNIVERSITY, POLTAVA, UKRAINE.
Objective: Aim: The aim of this work is to analyze the provision of medical care to military personnel on the example of the activities of the Poltava Military Hospital (Poltava, Ukraine) for the period 2021-2023.
Patients And Methods: Materials and Methods: The design of our study was descriptive. During the research, the reporting and accounting documentation of the Poltava Military Hospital for the relevant years was used.
Palineo score: development of a score to identify the palliative care needs of neonatal patients admitted to the neonatal intensive care unit.
Crit Care Sci
September 2025
Brazilian Biosciences National Laboratory, Brazilian Center for Research on Energy and Materials - Campinas (SP), Brazil.
Objective: To develop a score (Palineo score) to identify the palliative care needs of newborn patients admitted to a Brazilian neonatal intensive care unit of a tertiary maternity hospital that serves as a reference center for high-risk pregnancies, ensuring timely follow-up by a specialist.
Methods: Patients were assessed by three specialists using a questionnaire that included the same clinical elements as those used for the Palineo score but did not assign scores to the criteria. The score was determined by the consensus reached by the specialists.