Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs

An Evaluation of Projection Methods for Detailed Small Area Projections: An Application and Validation to King County, Washington

Population projections are used by a number of local agencies to better prepare for the future resource needs of counties, ensuring that educational, health, housing, and economic demands of individuals are met. Meeting the specific needs of a county's population, such as what resources to provide, where to target resources, and ensure an equitable distribution of those resources, requires population projections which are both demographically detailed, such as by age, race, and ethnicity, and geographically precise, such as at the census tract level. Despite this need, an evaluation of which methods are best suited to produce population projections at this level are lacking. In this study, we evaluate the accuracy of several cohort-based methods for small area population projections by race and ethnicity. We apply these methods to population projections of King County, Washington and assess the validity of projections using past population estimates. We find a clear pattern that demonstrates while simplified methods perform well in near term forecasts, methods which employ smoothing strategies perform better in long-term forecasting scenarios. Furthermore, we demonstrate that model's incorporating multiple stages of smoothing can provide detailed insights into the projected population size of King county and the places and groups which will most contribute to this growth. Detailed projections, such as those provided by multi-stage smoothing methods, enable city planners and policy makers a detailed view of the future structure of their county's population and provide for them a resource to better meet the needs of future populations.

Estimating quality-adjusted life expectancy (QALE) for local authorities in Great Britain and its association with indicators of the inclusive economy: a cross-sectional study

OBJECTIVES

Quantifying area-level inequalities in population health can help to inform policy responses. We describe an approach for estimating quality-adjusted life expectancy (QALE), a comprehensive health expectancy measure, for local authorities (LAs) in Great Britain (GB). To identify potential factors accounting for LA-level QALE inequalities, we examined the association between inclusive economy indicators and QALE.

SETTING

361/363 LAs in GB (lower tier/district level) within the period 2018-2020.

DATA AND METHODS

We estimated life tables for LAs using official statistics and utility scores from an area-level linkage of the Understanding Society survey. Using the Sullivan method, we estimated QALE at birth in years with corresponding 80% CIs. To examine the association between inclusive economy indicators and QALE, we used an open access data set operationalising the inclusive economy, created by the System Science in Public Health and Health Economics Research consortium.

RESULTS

Population-weighted QALE estimates across LAs in GB were lowest in Scotland (females/males: 65.1 years/64.9 years) and Wales (65.0 years/65.2 years), while they were highest in England (67.5 years/67.6 years). The range across LAs for females was from 56.3 years (80% CI 45.6 to 67.1) in Mansfield to 77.7 years (80% CI 65.11 to 90.2) in Runnymede. QALE for males ranged from 57.5 years (80% CI 40.2 to 74.7) in Merthyr Tydfil to 77.2 years (80% CI 65.4 to 89.1) in Runnymede. Indicators of the inclusive economy accounted for more than half of the variation in QALE at the LA level (adjusted R2 females/males: 50%/57%). Although more inclusivity was generally associated with higher levels of QALE at the LA level, this association was not consistent across all 13 inclusive economy indicators.

CONCLUSIONS

QALE can be estimated for LAs in GB, enabling further research into area-level health inequalities. The associations we identified between inclusive economy indicators and QALE highlight potential policy priorities for improving population health and reducing health inequalities.

Biology of Nicotiana glutinosa L., a newly recorded species from an archaeological excavation site in Egypt

BACKGROUND

During a field survey of urban flora in Alexandria city in 2019-2022, an interesting species belonging to the Solanaceae was collected from a newly archaeological excavation site and identified as Nicotiana glutinosa L. Many visits were made to the herbaria of Egypt to confirm the species records, but no single record was found. Reviewing the available literature revealed that this tropical American taxon was never recorded in the flora of Egypt.

AIMS

The present study was focused on N. glutinosa growth structure and plant macro- and micromorphology.

METHODS

Ten sampling sites were covered for N. glutinosa size structure. Plant samples were examined for stem anatomy, leaf, seed, and pollen morphology.

RESULTS

The species size structure reveals that the individual size index ranges from 1.33 to 150 cm, while its density ranges from 4 to 273 individuals /100 m-2. N. glutinosa has successfully established itself in one of the archaeological sites in Egypt, showing a "healthy" population with a high degree of size inequality, characterized by a relative majority of the juvenile individuals. Voucher specimens were deposited in the Herbarium of Alexandria University (ALEX) Faculty of Science, another specimen is processed to make herbarium specimens at the Herbarium of the Botanic Garden (Heneidy et al. collection, deposition number. 5502).

CONCLUSIONS

From our observations, N. glutinosa seems to have invasive potential, as it shows characteristics shared by most invasive species that are thought to help in their successful establishment in new habitats. This article emphasizes the importance of monitoring and regularly reporting the threats of alien invasive species to avoid any possible negative impacts on indigenous biodiversity in the future.

Probabilistic County-Level Population Projections

Population projections provide predictions of future population sizes for an area. Historically, most population projections have been produced using deterministic or scenario-based approaches and have not assessed uncertainty about future population change. Starting in 2015, however, the United Nations (UN) has produced probabilistic population projections for all countries using a Bayesian approach. There is also considerable interest in subnational probabilistic population projections, but the UN's national approach cannot be used directly for this purpose, because within-country correlations in fertility and mortality are generally larger than between-country ones, migration is not constrained in the same way, and there is a need to account for college and other special populations, particularly at the county level. We propose a Bayesian method for producing subnational population projections, including migration and accounting for college populations, by building on but modifying the UN approach. We illustrate our approach by applying it to the counties of Washington State and comparing the results with extant deterministic projections produced by Washington State demographers. Out-of-sample experiments show that our method gives accurate and well-calibrated forecasts and forecast intervals. In most cases, our intervals were narrower than the growth-based intervals issued by the state, particularly for shorter time horizons.

Population health trends and disease profile in Somalia 1990-2019, and projection to 2030: will the country achieve sustainable development goals 2 and 3?

OBJECTIVES

This study aims to evaluate whether Somalia will reach Sustainable Development Goals 2 and 3 by 2030 and what the country requires to advance closer to these objectives.

SETTING

Somalia.

PARTICIPANTS

We carried out analyses of secondary data obtained from the following open-access databases: Global Burden of Disease 2019 study; United Nations (UN) Department of Economic and Social Affairs Population Division; World Bank World Development Indicators; United Nations Children's Fund (UNICEF); UNICEF/World Health Organisation (WHO)/World Bank Joint Child Malnutrition Estimates; and UN Interagency Group for Child Mortality Estimation (UN IGME), disaggregated by sex.

PRIMARY OUTCOME MEASURES

stillbirth, neonatal, infant, under-five, maternal and child mortality; under-five malnutrition; life expectancy; health-adjusted life expectancy; age-standardised all-cause mortality; age-standardised cause-specific mortality for the leading causes of death; disability-adjusted life years.

SECONDARY OUTCOME MEASURES

vitamin A coverage; stunting, overweight in children under 5; top risk factors contributing to cause-specific mortality.

RESULTS

life expectancy in Somalia will increase to 65.42 years (95% UI 62.30-68.54) for females and 58.54 years (95% UI 54.89-62.19) for males in 2030. Stunting will continue to decline to 25.2% (90% UI 13.9-39.5%), and the under-five mortality rate will drop to 85.9 per 1000 live births (90% UI 22.0-228.1 per 1000 live births) for females and 96.4 per 1000 live births (90% UI 24.8-255.3 per 1000 live births) for males in 2030. This study's analyses predict that the maternal mortality ratio in Somalia will decline to 696.42 deaths per 100,000 live births in 2030.

CONCLUSIONS

there has been progress towards SDG targets in Somalia since 1990. To achieve these, Somalia requires greater health improvements than observed between 1990 and 2019.

Small area population denominators for improved disease surveillance and response

The Covid-19 pandemic has highlighted the value of strong surveillance systems in supporting our abilities to respond rapidly and effectively in mitigating the impacts of infectious diseases. A cornerstone of such systems is basic subnational scale data on populations and their demographics, which enable the scale of outbreaks to be assessed, risk to specific groups to be determined and appropriate interventions to be designed. Ongoing weaknesses and gaps in such data have however been highlighted by the pandemic. These can include outdated or inaccurate census data and a lack of administrative and registry systems to update numbers, particularly in low and middle income settings. Efforts to design and implement globally consistent geospatial modelling methods for the production of small area demographic data that can be flexibly integrated into health-focussed surveillance and information systems have been made, but these often remain based on outdated population data or uncertain projections. In recent years, efforts have been made to capitalise on advances in computing power, satellite imagery and new forms of digital data to construct methods for estimating small area population distributions across national and regional scales in the absence of full enumeration. These are starting to be used to complement more traditional data collection approaches, especially in the delivery of health interventions, but barriers remain to their widespread adoption and use in disease surveillance and response. Here an overview of these approaches is presented, together with discussion of future directions and needs.

Depopulation, super aging, and extreme heat events in South Korea

South Korea's population is declining and its composition changing, associated with lowest-low fertility rates and rapid aging (super aging). When estimating changes in future exposure to extreme heat events (EHE), events that are predicted to be intensified due to climate change, it is important to incorporate demographic dynamics. We analyze business-as-usual (BAU) population and climate scenarios-where BAU refers to no significant change in current processes and trends in either domain-from 2010 to 2060 for South Korea. Data for both BAU scenarios are spatially linked and used to measure and identify national and sub-national and age-group specific EHE exposure. The results reveal an increasing exposure to EHE over time at the national level, but this varies widely within the country, measured at the municipal level. The most intensive exposure levels will be in the decade ending in 2040 driven by high estimated severe EHE. Sub-nationally, Seoul will be the most vulnerable municipality associated with super aging, while severe EHE not demographic factors will be relevant in Daegu, the second-most vulnerable metropolitan area. By 2060, national estimates suggest the older population will be up to four times more exposed to EHE than today. While the population of South Korea will decline, the rapid aging of the population ensures that specific regions of the country will become exceedingly vulnerable to EHE.

Long-Term Impact of Interregional Migrants on Population Prediction

Japan is becoming depopulated, with declining fertility rates and massive urban agglomeration due to emigrations from rural areas, which results in rural–urban disparities. As demographic and social divisions between rural and urban areas increase, maintenance of infrastructure and social facilities becomes much more difficult. For social and demographic sustainability, accurate predictions of long-term population distributions are needed. This study improves the Cohort Component Analysis (CCA) into two aspects of “dependent structure” in the model system. The migration sub-model is expanded to include related structures between available job opportunities and the available workforce in each region, which are specified using the spatial autoregressive model. The advantage of the improved CCA to provides rational future projections by considering the longitudinal changes in the spatial distribution of the workforce. The simulation of the proposed model gives an alternative long-term impact of population distribution in Japan, which is compared with the conventional CCA. The results show that the future Japanese populations will become more concentrated in urban areas, with a lower fertility rate. Furthermore, the manufacturing employees will be attracted to metropolitan areas or to regions with industrial zones, and that the number of retailers will undergo changes over time, even in urbanized areas.