The Modell Global Database of Congenital Disorders (MGDb)

Congenital anomaly registries have two main surveillance aims: firstly to define baseline epidemiology of important congenital anomalies to facilitate programme, policy and resource planning, and secondly to identify clusters of cases and any other epidemiological changes that could give early warning of environmental or infectious hazards. However, setting up a sustainable registry and surveillance system is resource-intensive requiring national infrastructure for recording all cases and diagnostic facilities to identify those malformations that that are not externally visible. Consequently, not all countries have yet established robust surveillance systems. For these countries, methods are needed to generate estimates of prevalence of these disorders which can act as a starting point for assessing disease burden and service implications. Here, we describe how registry data from high-income settings can be used for generating reference rates that can be used as provisional estimates for countries with little or no observational data on non-syndromic congenital malformations. Electronic supplementary material The online version of this article (10.1007/s12687-018-0384-2) contains supplementary material, which is available to authorized users.

The importance of congenital disorders (also called birth defects) as a cause of early death and disability becomes increasingly apparent as countries pass through the development window and background mortality falls (Malherbe et al. 2015). Consequently, there is growing recognition of the need for their care and prevention, particularly in low- and middle-income countries. In 2010, the World Health Assembly (WHA) expressed concern that birth defects are still not recognised as a priority in public health, and called upon its member states to strengthen the prevention of congenital disorders and provision of care for those affected (World Health Assembly 2010). Nevertheless, the 2015 International Conference on Birth Defects and Disabilities in the Developing World concluded that “as the Sustainable Development Goals are adopted by United Nations member states, children with congenital disorders remain left behind in policies, programs, research, and funding” (Darmstadt et al. 2016). In fact, two WHO regional offices (those for the Eastern Mediterranean and South-East Asia) have responded to the call from World Health Assembly. In the process, both have encountered important barriers to the development of health policy in this area. Firstly, policy requires a sound epidemiological base, but in most middle- and low-income countries, the combination of (a) limited resources for the correct and accurate diagnosis of congenital disorders and (b) inadequate information systems leads to gross under-estimation of the contribution of congenital disorders to early death and disability (Christianson et al. 2006; Christianson and Modell 2004; World Health Organization 1999). Secondly, the extreme diversity of congenital disorders makes them difficult to grasp collectively at a strategic public health level. Thirdly, these problems are compounded by failure to agree and implement precise and rigorous technical terminology (World Health Organization 2006). The database described in the following articles—the Modell Global Database of Congenital Disorders (MGDb)—has been developed in order to overcome these barriers to service development.

In the absence of intervention, early-onset congenital disorders lead to pregnancy loss, early death, or disability. Currently, lack of epidemiological data from many settings limits the understanding of the burden of these conditions, thus impeding health planning, policy-making, and commensurate resource allocation. The Modell Global Database of Congenital Disorders (MGDb) seeks to meet this need by combining general biological principles with observational and demographic data, to generate estimates of the burden of congenital disorders. A range of interventions along the life course can modify adverse outcomes associated with congenital disorders. Hence, access to and quality of services available for the prevention and care of congenital disorders affects both their birth prevalence and the outcomes for affected individuals. Information on this is therefore important to enable burden estimates for settings with limited observational data, but is lacking from many settings. This paper, the third in this special issue on methods used in the MGDb for estimating the global burden of congenital disorders, describes key interventions that impact on outcomes of congenital disorders and methods used to estimate their coverage where empirical data are not available.

As child mortality rates overall are decreasing, non-communicable conditions, such as genetic disorders, constitute an increasing proportion of child mortality, morbidity and disability. To date, policy and public health programmes have focused on common genetic disorders. Rare single gene disorders are an important source of morbidity and premature mortality for affected families. When considered collectively, they account for an important public health burden, which is frequently under-recognised. To document the collective frequency and health burden of rare single gene disorders, it is necessary to aggregate them into large manageable groupings and take account of their family implications, effective interventions and service needs. Here, we present an approach to estimate the burden of these conditions up to 5 years of age in settings without empirical data. This approaches uses population-level demographic data, combined with assumptions based on empirical data from settings with data available, to provide population-level estimates which programmes and policy-makers when planning services can use.

As child mortality rates overall are decreasing, non-communicable conditions, such as genetic disorders, constitute an increasing proportion of child mortality, morbidity and disability. To date, policy and public health programmes have focused on common genetic disorders. Rare single gene disorders are an important source of morbidity and premature mortality for affected families. When considered collectively, they account for an important public health burden, which is frequently under-recognised. To document the collective frequency and health burden of rare single gene disorders, it is necessary to aggregate them into large manageable groupings and take account of their family implications, effective interventions and service needs. Here, we present an approach to estimate the burden of these conditions up to 5 years of age in settings without empirical data. This approaches uses population-level demographic data, combined with assumptions based on empirical data from settings with data available, to provide population-level estimates which programmes and policy-makers when planning services can use. Electronic supplementary material The online version of this article (10.1007/s12687-018-0376-2) contains supplementary material, which is available to authorized users.

In the absence of intervention, early-onset congenital disorders lead to pregnancy loss, early death, or disability. Currently, lack of epidemiological data from many settings limits the understanding of the burden of these conditions, thus impeding health planning, policy-making, and commensurate resource allocation. The Modell Global Database of Congenital Disorders (MGDb) seeks to meet this need by combining general biological principles with observational and demographic data, to generate estimates of the burden of congenital disorders. A range of interventions along the life course can modify adverse outcomes associated with congenital disorders. Hence, access to and quality of services available for the prevention and care of congenital disorders affects both their birth prevalence and the outcomes for affected individuals. Information on this is therefore important to enable burden estimates for settings with limited observational data, but is lacking from many settings. This paper, the third in this special issue on methods used in the MGDb for estimating the global burden of congenital disorders, describes key interventions that impact on outcomes of congenital disorders and methods used to estimate their coverage where empirical data are not available. Electronic supplementary material The online version of this article (10.1007/s12687-018-0359-3) contains supplementary material, which is available to authorized users.

The Articles and Annexes contained within this document constitute the most fine-grained description of the methods and approaches devised in the course of a large collaborative exercise since the 1980s to make estimates of the epidemiology and associated health burden of congenital disorders. The work began at a scientific meeting at WHO Headquarters in Geneva, and has continued in various forms ever since, with input from more individuals than it is possible to acknowledge via the conventional methods of shared authorship. This document is a work in progress, and so its various portions are under development, in the course of which they have been shared with members of the international collaborative group. As the component texts reach the requisite level of maturity, will be added to this document to enable wider consultation with the global community of interested parties. Earlier access to some or all of the texts may be possible – contact b.modell@ucl.ac.uk and m.darlison@ucl.ac.uk to discuss this.

Congenital disorders are an important cause of pregnancy loss, premature death and life-long disability. A range of interventions can greatly reduce their burden, but the absence of local epidemiological data on their prevalence and the impact of interventions impede policy and service development in many countries. In an attempt to overcome these deficiencies, we have developed a tool-The Modell Global Database of Congenital Disorders (MGDb) that combines general biological principles and available observational data with demographic data, to generate estimates of the birth prevalence and effects of interventions on mortality and disability due to congenital disorders. MGDb aims to support policy development by generating country, regional and global epidemiological estimates. Here we provide an overview of the concepts and methodological approach used to develop MGDb.

Chromosomal disorders, of which Down syndrome is the most common, can cause multi-domain disability. In addition, compared to the general population, there is a higher frequency of death before the age of five. In many settings, large gaps in data availability have hampered policy-making, programme priorities and resource allocation for these important conditions. We have developed methods, which overcome this lack of data and allow estimation of the burden of affected pregnancies and their outcomes in different settings worldwide. For example, the methods include a simple equation relating the percentage of mothers 35 and over to Down syndrome birth prevalence. The results obtained provide a starting point for consideration of services that can be implemented for the care and prevention of these disorders. Electronic supplementary material The online version of this article (10.1007/s12687-017-0336-2) contains supplementary material, which is available to authorized users.

Chromosomal disorders, of which Down syndrome is the most common, can cause multi-domain disability. In addition, compared to the general population, there is a higher frequency of death before the age of five. In many settings, large gaps in data availability have hampered policy-making, programme priorities and resource allocation for these important conditions. We have developed methods, which overcome this lack of data and allow estimation of the burden of affected pregnancies and their outcomes in different settings worldwide. For example, the methods include a simple equation relating the percentage of mothers 35 and over to Down syndrome birth prevalence. The results obtained provide a starting point for consideration of services that can be implemented for the care and prevention of these disorders.

Congenital disorders are an important cause of pregnancy loss, premature death and life-long disability. A range of interventions can greatly reduce their burden, but the absence of local epidemiological data on their prevalence and the impact of interventions impede policy and service development in many countries. In an attempt to overcome these deficiencies, we have developed a tool—The Modell Global Database of Congenital Disorders (MGDb) that combines general biological principles and available observational data with demographic data, to generate estimates of the birth prevalence and effects of interventions on mortality and disability due to congenital disorders. MGDb aims to support policy development by generating country, regional and global epidemiological estimates. Here we provide an overview of the concepts and methodological approach used to develop MGDb. Electronic supplementary material The online version of this article (10.1007/s12687-017-0335-3) contains supplementary material, which is available to authorized users.