This article presents the core methodological ideas and empirical assessments of an extended cohort-component approach (known as the "ProFamy model"), and applications to simultaneously project household composition, living arrangements, and population sizes-gender structures at the subnational level in the United States. Comparisons of projections from 1990 to 2000 using this approach with census counts in 2000 for each of the 50 states and Washington, DC show that 68.0 %, 17.0 %, 11.2 %, and 3.8 % of the absolute percentage errors are <3.0 %, 3.0 % to 4.99 %, 5.0 % to 9.99 %, and ≥10.0 %, respectively. Another analysis compares average forecast errors between the extended cohort-component approach and the still widely used classic headship-rate method, by projecting number-of-bedrooms-specific housing demands from 1990 to 2000 and then comparing those projections with census counts in 2000 for each of the 50 states and Washington, DC. The results demonstrate that, compared with the extended cohort-component approach, the headship-rate method produces substantially more serious forecast errors because it cannot project households by size while the extended cohort-component approach projects detailed household sizes. We also present illustrative household and living arrangement projections for the five decades from 2000 to 2050, with medium-, small-, and large-family scenarios for each of the 50 states; Washington, DC; six counties of southern California; and the Minneapolis-St. Paul metropolitan area. Among many interesting numerical outcomes of household and living arrangement projections with medium, low, and high bounds, the aging of American households over the next few decades across all states/areas is particularly striking. Finally, the limitations of the present study and potential future lines of research are discussed.
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http://dx.doi.org/10.1007/s13524-012-0171-3 | DOI Listing |
BMJ Open
January 2025
International Center for Equity in Health, Universidade Federal de Pelotas, Pelotas, Brazil.
Objective: Despite the Global Vaccine Action Plan's goal of at least 90% vaccine coverage for all children, Uganda has made limited progress in vaccination over the past decade. The objective of this study was to examine the subnational trends in the prevalence and inequalities in under-immunisation and zero-dose among children aged 12-23 months in Uganda.
Study Design: A retrospective national cross-sectional study.
J Prev Alzheimers Dis
January 2025
National Center for Disease Prevention and Health Promotion, Italian National Institute of Health Rome, Italy.
Background: Dementia is a major global public health challenge, with over 50 million cases in 2020, projected to reach 152 million by 2050. Effective prevention strategies are needed to reduce the impact of modifiable risk factors associated with dementia, particularly in countries with ageing populations like Italy. The Population Attributable Fraction (PAF) and Potential Impact Fraction (PIF) are key metrics for understanding and reducing dementia cases through targeted interventions.
View Article and Find Full Text PDFEur J Public Health
January 2025
Federal Ministry of Health, Directorate Health Emergencies and Epidemics Control (HEEC), Khartoum, Sudan.
Rift Valley Fever is endemic in Sudan, with a notable outbreak declared in 2019, affecting multiple states. In this study, we examine the Red Sea State, Sudan's experience in applying the One Health approach, to contain Red-Sea RVF outbreak. A retrospective analysis of national and sub-national data and a review of literature were conducted to assess the application of One Health response and to derive lessons learned.
View Article and Find Full Text PDFInt J Infect Dis
January 2025
School of Population Health, Faculty of Health Sciences, Curtin University, Australia; Geospatial and Tuberculosis Research Team, Telethon Kids Institute, Australia. Electronic address:
Objective: To map subnational and local prevalence of drug-resistant tuberculosis (DR-TB) across Africa.
Methods: We assembled a geolocated dataset from 173 sources across 31 African countries, comprising drug susceptibility test results and covariate data from publicly available databases. We used Bayesian model-based geostatistical framework with multivariate Bayesian logistic regression model to estimate DR-TB prevalence at lower administrative levels.
PLoS Negl Trop Dis
January 2025
The Centre for Health Informatics, Computing, and Statistics (CHICAS), Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Background: The Expanded Special Project for the Elimination of Neglected Tropical Diseases (ESPEN) was launched in 2019 by the World Health Organization and African nations to combat Neglected Tropical Diseases (NTDs), including Soil-transmitted helminths (STH), which still affect over 1.5 billion people globally. In this study, we present a comprehensive geostatistical analysis of publicly available STH survey data from ESPEN to delineate inter-country disparities in STH prevalence and its environmental drivers while highlighting the strengths and limitations that arise from the use of the ESPEN data.
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