Related Experiment Video
Updated: Feb 15, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
Published on: February 3, 2015
Effective cataract surgical coverage in adults aged 50 years and older: empirical estimates from population-based
Ian McCormick1, Yamna Ouchtar2, David Macleod2
1International Centre for Eye Health, London School of Hygiene & Tropical Medicine, London, UK.
Background:
Cataract is the leading cause of blindness worldwide despite treatment being very cost-effective. To stimulate efforts to address the large unmet need for affordable, good-quality cataract services, member states at the 74th World Health Assembly endorsed a global target of a 30 percentage-point increase in effective cataract surgical coverage (eCSC) by 2030. In this Article, we report on progress towards that target.
Methods:
We did a secondary analysis of 233 participant-level population-based survey datasets (Rapid Assessment of Avoidable Blindness [RAAB] surveys and other population-based cross-sectional surveys) from 68 countries (2003-24) to estimate eCSC with a cataract surgical threshold of worse than 6/18 pinhole visual acuity and a threshold of 6/18 or better for postoperative presenting visual acuity (eCSC6/18) for each country. Eligible studies included people aged 50 years and older, without any further age restrictions. eCSC was calculated as the number of people who had received surgery and had a good visual outcome as a proportion of all people who had received or were still to receive surgery. For countries with only one survey estimate available, we reported the survey as the country estimate; for each country with two or more surveys, we used more recent and nationally representative survey to generate estimates. We included 228 of 233 datasets (excluding five datasets from the European region) in a mixed-effects logistic regression to estimate global and WHO regional temporal trends in eCSC6/18 from 2000 to 2030. For global estimates, we used eCSC in the Americas region as a proxy for the European region. We used 120 RAAB surveys that measured visual acuity at the 6/12 threshold to analyse causes of non-good outcomes (postoperative presenting visual acuity worse than 6/12) and estimated potential gains in eCSC (with a cataract surgical threshold of worse than 6/12 pinhole visual acuity and a 6/12 or better threshold for postoperative presenting visual acuity [eCSC6/12]) from correcting residual postoperative refractive errors. Potential gains were estimated by comparing eCSC6/12 calculated using postoperative presenting visual acuity with eCSC6/12 calculated using pinhole visual acuity (a proxy for visual acuity with optical correction of refractive error).
Findings:
We used 130 studies to report 68 country estimates of eCSC6/18. Country estimates for eCSC6/18 from surveys ranged from 2·1% (95% CI 0·9-3·4) in Burundi (2024) to 77·7% (72·9-82·5) in Qatar (2023). Globally, we predicted eCSC6/18 of 48·2% (39·7-57·2) in 2025, increasing by 8·4 percentage points (8·1-8·6) between 2020 and 2030 (from 43·9% [36·6-51·2] to 52·3% [41·4-62·7]). Uncorrected refractive error accounted for a median 26·4% of non-good outcomes per survey; we estimated that treating this condition could yield a median 3·7 percentage-point gain in eCSC6/12 globally.
Interpretation:
Global efforts are not on track to meet the target of a 30 percentage-point increase in eCSC between 2020 and 2030-immediate and substantial investment in cataract services is, therefore, required. Survey data indicated which elements of the cataract care pathway could be targeted for quality-improvement initiatives. A suite of cataract surgery quality indicators should be collected to better inform service providers.
Funding:
Indigo Trust, The Fred Hollows Foundation, and Wellcome Trust.
Related Concept Videos
Estimating Population Standard Deviation
Estimating Population Mean with Known Standard Deviation
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
Confidence Interval for Estimating Population Mean
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
Distributions to Estimate Population Parameter
Estimating Population Mean with Unknown Standard Deviation
William S. Gosset (1876–1937) of the...
What are Estimates?
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...

