scholarly journals Improving estimates of district HIV prevalence and burden in South Africa using small area estimation techniques

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0212445 ◽  
Author(s):  
Steve Gutreuter ◽  
Ehimario Igumbor ◽  
Njeri Wabiri ◽  
Mitesh Desai ◽  
Lizette Durand
Keyword(s):  
South Africa ◽  
Small Area ◽  
Small Area Estimation ◽  
Hiv Prevalence ◽  
Estimation Techniques ◽  
Area Estimation

scholarly journals Enhancing the precision of broad-scale forestland removals estimates with small area estimation techniques

2021 ◽  
Author(s):  
John W Coulston ◽  
P Corey Green ◽  
Philip J Radtke ◽  
Stephen P Prisley ◽  
Evan B Brooks ◽  
...  
Keyword(s):  
Small Area ◽  
Small Area Estimation ◽  
Species Group ◽  
Tree Cover ◽  
Estimation Techniques ◽  
Spatial And Temporal Scales ◽  
Area Estimation ◽  
Forest Inventories ◽  
Southeastern Us ◽  
Increasing Demand

Abstract National Forest Inventories (NFI) are designed to produce unbiased estimates of forest parameters at a variety of scales. These parameters include means and totals of current forest area and volume, as well as components of change such as means and totals of growth and harvest removals. Over the last several decades, there has been a steadily increasing demand for estimates for smaller geographic areas and/or for finer temporal resolutions. However, the current sampling intensities of many NFI and the reliance on design-based estimators often leads to inadequate precision of estimates at these scales. This research focuses on improving the precision of forest removal estimates both in terms of spatial and temporal resolution through the use of small area estimation techniques (SAE). In this application, a Landsat-derived tree cover loss product and the information from mill surveys were used as auxiliary data for area-level SAE. Results from the southeastern US suggest improvements in precision can be realized when using NFI data to make estimates at relatively fine spatial and temporal scales. Specifically, the estimated precision of removal volume estimates by species group and size class was improved when SAE methods were employed over post-stratified, design-based estimates alone. The findings of this research have broad implications for NFI analysts or users interested in providing estimates with increased precision at finer scales than those generally supported by post-stratified estimators.

Estimating unmet need for contraception by district within Ghana: An application of small-area estimation techniques

2012 ◽  
Vol 66 (2) ◽  
pp. 105-122 ◽  
Author(s):  
Fiifi Amoako Johnson ◽  
Sabu S. Padmadas ◽  
Hukum Chandra ◽  
Zoe Matthews ◽  
Nyovani J. Madise
Keyword(s):  
Small Area ◽  
Small Area Estimation ◽  
Unmet Need ◽  
Estimation Techniques ◽  
Area Estimation ◽  
Unmet Need For Contraception

Analysis of the spatial distribution of under-5 mortality rate in local areas of South Africa

2020 ◽  
Vol 36 (4) ◽  
pp. 1161-1173
Author(s):  
Yegnanew A. Shiferaw
Keyword(s):  
South Africa ◽  
Mortality Rate ◽  
Healthcare Service ◽  
Small Area ◽  
Local Level ◽  
Small Area Estimation ◽  
National Level ◽  
Population Census ◽  
Area Estimation ◽  
Local Municipality

Policymakers and healthcare service managers demand reliable, accurate and disaggregated information about child deaths at the sub-national level to plan and monitor healthcare service delivery and health outcomes. In support of this demand, this research aimed at providing reliable local municipality estimates of the under-5 mortality rate (U5MR) in South Africa. The paper used a small area estimation approach to improve the precision of local municipality estimates of U5MR by linking data from the 2016 Community Survey (CS) and the 2011 Population Census (PC). The diagnostic measures and validation of the reliability of the results showed that the local municipality estimates of U5MR produced by small area estimation are more efficient and precise than direct estimates of U5MR based only on the CS data. Further, accurate and cost-effective local municipality estimates of U5MR were produced without the need for more resources through combining the available data sources. This was achievable since the research did not require a separate survey for this purpose. The results can be used to monitor U5MR at the local level in South Africa since they link directly with the Sustainable Development Goals (SDGs).

scholarly journals Estimating District HIV Prevalence in Zambia Using Small Area Estimation Methods (SAE)

2021 ◽  
Author(s):  
Chris Mweemba ◽  
Peter Hangoma ◽  
Isaac Fwemba ◽  
Wilbroad Mutale ◽  
Felix Masiye
Keyword(s):  
Small Area ◽  
Small Area Estimation ◽  
National Level ◽  
Population Based ◽  
Hiv Prevalence ◽  
Estimation Methods ◽  
Population Mobility ◽  
African Region ◽  
Area Estimation ◽  
Very High

Abstract BackgroundThe HIV/AIDS pandemic has had a very devastating impact at a global level, with the Eastern and Southern African region being the hardest hit. The considerable geographical variation in the pandemic means varying impact of the disease in different settings, requiring differentiated interventions. While information on the prevalence of HIV at regional and national levels is readily available, the burden of the disease at smaller area levels, where health services are organized and delivered, is not well documented. This affects the targeting of HIV resources. There is need for studies to estimate HIV prevalence at appropriate levels to improve HIV related planning and resource allocation. MethodsWe estimated the district level prevalence of HIV using Small-Area Estimation (SAE) technique by utilizing the 2016 Zambia Population-Based HIV Impact Assessment Survey (ZAMPHIA) data and auxiliary data from the 2010 Zambian Census of Population and Housing and the HIV sentinel surveillance data from selected antenatal care clinics (ANC). SAE Models were fitted in R Programming to ascertain the best HIV predicting model. We then used the Fay-Herriot (FH) model to obtain weighted, more precise and reliable HIV prevalence for all the districts.ResultsThe results revealed variations in the district HIV prevalence in Zambia, with the prevalence ranging from as low as 4.2% to as high as 23.5%. Approximately 35% of the districts (n=26) had HIV prevalence above the national average, with one district having almost twice as much prevalence as the national level. Some rural districts have very high HIV prevalence rates. ConclusionsHIV prevalence in Zambian districts is driven by population mobility Districts located near international borders, along the main transit routes and adjacent to other districts with very high prevalence, tend to have high HIV prevalence. The variations in the burden of HIV across districts in Zambia points to the need for a differentiated approaches in HIV programming in Zambia. HIV resources need to be prioritized towards districts with high population mobility.

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