National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty.

Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred. Some conflict-affected and resource-poor countries have not conducted a census in over 10 y. We developed a hierarchical Bayesian model to estimate population numbers in small areas based on enumeration data from sample areas and nationwide information about administrative boundaries, building locations, settlement types, and other factors related to population density. We demonstrated this model by estimating population sizes in every 10- m grid cell in Nigeria with national coverage. These gridded population estimates and areal population totals derived from them are accompanied by estimates of uncertainty based on Bayesian posterior probabilities. The model had an overall error rate of 67 people per hectare (mean of absolute residuals) or 43% (using scaled residuals) for predictions in out-of-sample survey areas (approximately 3 ha each), with increased precision expected for aggregated population totals in larger areas. This statistical approach represents a significant step toward estimating populations at high resolution with national coverage in the absence of a complete and recent census, while also providing reliable estimates of uncertainty to support informed decision making.

Census-independent population mapping in northern Nigeria.

Although remote sensing has long been used to aid in the estimation of population, it has usually been in the context of spatial disaggregation of national census data, with the census counts serving both as observational data for specifying models and as constraints on model outputs. Here we present a framework for estimating populations from the bottom up, entirely independently of national census data, a critical need in areas without recent and reliable census data. To make observations of population density, we replace national census data with a microcensus, in which we enumerate population for a sample of small areas within the states of Kano and Kaduna in northern Nigeria. Using supervised texture-based classifiers with very high resolution satellite imagery, we produce a binary map of human settlement at 8-meter resolution across the two states and then a more refined classification consisting of 7 residential types and 1 non-residential type. Using the residential types and a model linking them to the population density observations, we produce population estimates across the two states in a gridded raster format, at approximately 90-meter resolution. We also demonstrate a simulation framework for capturing uncertainty and presenting estimates as prediction intervals for any region of interest of any size and composition within the study region. Used in concert with previously published demographic estimates, our population estimates allowed for predictions of the population under 5 in ten administrative wards that fit strongly with reference data collected during polio vaccination campaigns.

Resident continuity of care experience: a casualty of ambulatory surgery and current patient admission practices.

BACKGROUND: The purpose of this study was to define and assess the impact of changes in health care delivery on the current continuity of care experience of surgical residents. METHODS: This 4-week, prospective cohort study included all patients who underwent a general surgical procedure at the University of British Columbia if a resident was present at the operation. The residents' perioperative involvement in each patient's care was recorded. RESULTS: Of the 592 eligible cases, 74.8% were elective same-day admissions, 5.4% elective previously admitted patients, and 19.8% emergencies. The overall rate of assessment was 27% preoperatively, 84% postoperatively on the ward, and <1% in oupatient clinic postdischarge. Elective cases were associated with significantly lower rates of preoperative assessment compared with emergency cases (15% versus 74%, P < .001). CONCLUSIONS: Changes in health care delivery have outpaced changes in the structure of surgical education, resulting in suboptimal continuity of care experiences for trainees. Residency programs must adapt their curricula to include adequate ambulatory experience.