Practical application of a measure of service delivery for childhood cataract has been useful in identifying gaps in utilisation of existing services by region as well as by gender. Testing in other settings would be helpful. An apparent inequity in use of services by girls requires attention.

Prevalence and incidence are two important measures of the impact of a disease. For many diseases, incidence is the most useful measure for response planning. However, the longitudinal studies needed to calculate incidence are resource-intensive, so prevalence estimates are often more readily available. In 1986, Podgor and Leske (Statistics in Medicine, 5:573-578, 1986) developed a model to estimate incidence of a single disease from one survey of age-specific prevalence, even where the presence of the disease increases the mortality rate of patients. Here, we extend their model to the case of progressive diseases, where the incidence of all disease stages is desired. As an example, we consider the case of cataract disease in Africa, where ophthalmologists wish to distinguish between unilateral and bilateral cataract incidence in order to plan the number of cataract surgeries needed to prevent the occurrence of blindness as a result of the disease. Our method has successfully provided cataract incidence estimates on the basis of prevalence data from new Rapid Assessment of Avoidable Blindness surveys in Africa (Lewallen et al., Archives of Ophthalmology, 128(12):1584-1589, 2010). In this paper, we provide a more general form of the model in order to promote its applicability to other diseases.

To estimate the incidence of vision-reducing cataract in sub-Saharan Africa and use these data to calculate cataract surgical rates (CSR) needed to eliminate blindness and visual impairment due to cataract. Methods: Using data from recent population-based, standardized, rapid-assessment surveys, we calculated the agespecific prevalence of cataract (including operated and unoperated eyes) from surveys in 7 "districts" across Africa. This was done at 3 levels of visual acuity. Then we used the age-specific prevalence data to develop a model to estimate age-specific incidence at different visual acuities, taking into account differences in mortality rates between those with cataract compared with those without. The model included development of opacity in the first eye and second eye of people older than 50 years. The incidence data were used to calculate target cataract surgical rates. Results: Incidence and CSR needs varied significantly in different sites and were lower in some than expected. Cataract surgical rates may depend on genetic, environmental, or cultural variations and will vary with population structure, which is not uniform across Africa. Conclusion: Africa should not be viewed as homogeneous in terms of cataract incidence or CSR needed. These CSR calculations should be useful for more appropriate planning of human resources and service delivery on the continent. The methodology can be applied to other population-based data as they become available to determine appropriate CSR targets.

This is important evidence of significant variation in the incidence of cataract within Sub-Saharan Africa. The variation may be related to genetic or cultural variations on the continent and has important implications for planning services.

In this article, we highlight the advantages of incorporating a statistical capstone experience in the undergraduate curriculum, where students perform an in-depth analysis of real-world data. Capstone experiences develop statistical thinking by allowing students to engage in a consulting-like experience that requires skills outside the scope of traditional courses: defining a complex problem, analyzing data, building a strong team, and communicating effectively. We describe the pedagogical benefits as they relate to improved student outcomes and prospective job and graduate school placement, and we classify statistical capstones into four groups: standalone capstone projects, statistical consultancies, capstone projects embedded in an advanced statistics methodology course, and instruction-focused capstone courses. This article serves as a guide for educators seeking to implement an enriching capstone experience in their undergraduate mathematics or statistics curriculum to better prepare students for industrial and academic careers in data science.