Although technology and medicine have advanced rapidly in today’s globalized world, many low- and middle-income countries still lack the necessary tools and resources for measuring vital health statistics. Political leaders and public health officials are forced to seek global health estimates as a substitute for non-existent or unreliable data because civil registration systems in these areas are ineffective and underfunded. Data is imputed using statistical models based on mathematical and scientific predictions when data is missing or unavailable. In general, this type of estimation work is conducted, funded, and published by either agencies under the direction of the United Nations, such as the World Health Organization, or by private academic institutions. There has been controversy between experts regarding who is better suited to generate global health estimates, as well as the accuracy of those estimates due to incongruous estimates and competing statistics published by the dichotomous groups. Since estimates are used to allocate public resources and have a strong influence on health policy, accuracy is crucial to public health planning and prevention. Consequently, the United Nations and academic institutions alike are focusing on improving the accuracy of global health estimates while also looking for ways to improve data collection in resource-poor countries. (4)
The benefits of global health estimates
Health estimates continue to play an important role in shaping global health initiatives and prevention strategies, despite the controversy. When actual data is not available, estimates provide a framework for decision making and policy planning that would otherwise be impossible. (5) As low-income and middle-income countries strengthen their capacity to collect, archive, and access vital health statistics, the reliance on global Health Estimates should eventually decrease. Estimates at least partially compensate for resource-poor countries’ lack of data. Quantifying the magnitude of an issue is possible by using specific numbers to define the prevalence of a health issue, whether derived from an estimate or based on real measurements. Thus, estimates play a crucial role in drawing attention to global health challenges that may have otherwise gone unacknowledged or underestimated.(7) Additionally, once a health estimate has been published, by the UN or an academic institution, the publication is likely to incite public support for the issue and inspire further research on the subject.
Public health estimates could have implications in international economics as well. Global health estimates serve as an important economic benchmark that help to guide policymakers and health officials towards more fiscally-sound spending decisions.(8) Health care spending currently represents over 10% of the world’s economic output, and as it continues to assume a growing role in the global economy, it is increasingly important that the UN and other governing bodies allocate health resources judiciously.(9) Estimates of the prevalence, cost, and impact of a disease equip policymakers with the information necessary to analyze and select the most appropriate planning and prevention strategies, and ultimately these decisions have the potential to save lives and money.(10) Radboud Duintjer Tebbens, an advocate of the Global Polio Eradication Initiative (GPEI), explains: “Polo eradication is a good deal, from both a humanitarian and an economic perspective. As a result of the GPEI, developing countries and the world can realize meaningful financial benefits and prevent devastating paralysis and death for children.”(11) In the case the GPEI’s estimates are correct, eradicating wild polioviruses by 2015 could result in a global net savings of 40 to 50 billion dollars.
The challenges of estimating global health
Global health estimates are, however, dependent upon their accuracy, despite these benefits. Global health estimates are, however, dependent upon their accuracy, despite these benefits. The biggest challenge associated with global health estimates lies here: estimates are rarely considered as accurate and reliable as actual data, assuming the data has been processed correctly. Some estimates can generate dependable figures when the right tools, technology, and information are used. As researchers use increasingly complex statistical models to compensate for missing data, many estimates are highly unreliable. As a result, the data used to develop these estimates eventually become completely overworked, yielding measurements that barely resemble the original data. The probability of accuracy decreases as statistical and methodological complexity increases. “The complexity of such models often masks a stark reality: most people are born and die uncounted, the reasons for their deaths unknown.”(15) Despite this reality, estimates generated using overly intricate models are often reported as actual facts rather than estimates: “Literature is relatively scare on the extent and quality of primary sources of health data on a global scale, even though there are many reports that present aggregated global data on various health issues, sometimes giving the impression that those estimates carry a high degree of certainty.”(16) Mistaking estimates as more reliable than they actually are poses a dangerous threat to the efficacy of public health planning and policy, making the inaccuracies of global health estimates a considerable challenge.
Global health estimates are erratic due to the inappropriate use of statistical modeling. Furthermore, the lack of standards and regulations governing how specific health statistics should be measured, stored, and shared further hinders estimation accuracy. Additionally, there are no uniform standards or training procedures in place to ensure that technology designed to collect vital health statistics is being used appropriately. Lack of standards often leads to biased data collection, especially in developing countries. In low-income countries, modern medical services are likely to be used by a small minority of the population. Consequently, vital registration systems in these areas are more likely to record health information about a country’s wealthiest and most educated citizens rather than a more representative sample of the entire population. As well, in resource-poor countries, most health care facilities are reserved for the most severely ill patients, so these people are far more likely to be formally counted. (18) The development and enactment of international regulations to guide data collection is critically important for obtaining high quality information, but there has been debate over who should set these rules. Many experts believe that the World Health Organization or the United Nations is best equipped to set universal standards.(19) However, others groups worry that the United Nation’s involvement in collecting and generating global health estimates would compromise it’s ability to set unbiased standards: “It is difficult to see how the UN can be the trusted developer of norms and standards and a respected neutral broker when it is also trying to compete in the health measurement arena.”(It is particularly dicey to decide who is best suited to oversee the creation of universal standards, as well as how those standards should be implemented, a challenge that is further complicated by the fact that not all countries possess the same resources and technology for collecting vital health information, making uniform regulation especially difficult.