Systematic review of birth cohort studies in Africa

In sub-Saharan Africa, unacceptably high rates of mortality amongst women and children continue to persist. The emergence of research employing new genomic technologies is advancing knowledge on cause of disease. This review aims to identify birth cohort studies conducted in sub-Saharan Africa and to consider their suitability as a platform to support genetic epidemiological studies

Understanding the determinants of the complex interplay between cost-effectiveness and equitable impact in maternal and child mortality reduction

One of the most unexpected outcomes arising from the efforts towards maternal and child mortality reduction is that all too often the objective success has been coupled with increased inequity in the population. The aim of this study is to analyze the determinants of the complex interplay between cost-effectiveness and equity and suggest strategies that will promote an impact on mortality that reduce population child health inequities

Setting health research priorities using the CHNRI method: VI. Quantitative properties of human collective opinion.

INTRODUCTION: Crowdsourcing has become an increasingly important tool to address many problems - from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. METHODS: We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. RESULTS: The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14-16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank correlation coefficient = 0.95; IQR 0.94-0.96). CONCLUSIONS: Our analyses suggest that the collective opinion of an expert group on a large number of research ideas, expressed through categorical variables (Yes/No/Not Sure/Don't know), stabilises relatively quickly in terms of identifying the ideas that have most support. In the exercise we found a high degree of reproducibility of the identified research priorities was achieved with as few as 45-55 experts

Reducing mortality from childhood pneumonia and diarrhoea:The leading priority is also the greatest opportunity

Pneumonia and diarrhoea have been the leading causes of global child mortality for many decades. The work of Child Health Epidemiology Reference Group (CHERG) has been pivotal in raising awareness that the UN's Millennium Development Goal 4 cannot be achieved without increased focus on preventing and treating the two diseases in low– and middle–income countries. Global Action Plan for Pneumonia (GAPP) and Diarrhoea Global Action Plan (DGAP) groups recently concluded that addressing childhood pneumonia and diarrhoea is not only the leading priority but also the greatest opportunity in global health today: scaling up of existing highly cost–effective interventions could prevent 95% of diarrhoea deaths and 67% of pneumonia deaths in children younger than 5 years by the year 2025. The cost of such effort was estimated at about US$ 6.7 billion

Setting health research priorities using the CHNRI method: V. Quantitative properties of human collective knowledge.

INTRODUCTION: The CHNRI method for setting health research priorities has crowdsourcing as the major component. It uses the collective opinion of a group of experts to generate, assess and prioritize between many competing health research ideas. It is difficult to compare the accuracy of human individual and collective opinions in predicting uncertain future outcomes before the outcomes are known. However, this limitation does not apply to existing knowledge, which is an important component underlying opinion. In this paper, we report several experiments to explore the quantitative properties of human collective knowledge and discuss their relevance to the CHNRI method. METHODS: We conducted a series of experiments in groups of about 160 (range: 122-175) undergraduate Year 2 medical students to compare their collective knowledge to their individual knowledge. We asked them to answer 10 questions on each of the following: (i) an area in which they have a degree of expertise (undergraduate Year 1 medical curriculum); (ii) an area in which they likely have some knowledge (general knowledge); and (iii) an area in which they are not expected to have any knowledge (astronomy). We also presented them with 20 pairs of well-known celebrities and asked them to identify the older person of the pair. In all these experiments our goal was to examine how the collective answer compares to the distribution of students' individual answers. RESULTS: When answering the questions in their own area of expertise, the collective answer (the median) was in the top 20.83% of the most accurate individual responses; in general knowledge, it was in the top 11.93%; and in an area with no expertise, the group answer was in the top 7.02%. However, the collective answer based on mean values fared much worse, ranging from top 75.60% to top 95.91%. Also, when confronted with guessing the older of the two celebrities, the collective response was correct in 18/20 cases (90%), while the 8 most successful individuals among the students had 19/20 correct answers (95%). However, when the system in which the students who were not sure of the correct answer were allowed to either choose an award of half of the point in all such instances, or withdraw from responding, in order to improve the score of the collective, the collective was correct in 19/20 cases (95%), while the 3 most successful individuals were correct in 17/20 cases (85%). CONCLUSIONS: Our experiments showed that the collective knowledge of a group with expertise in the subject should always be very close to the true value. In most cases and under most assumption, the collective knowledge will be more accurate than the knowledge of an "average" individual, but there always seems to be a small group of individuals who manage to out-perform the collective. The accuracy of collective prediction may be enhanced by allowing the individuals with low confidence in their answer to withdraw from answering

From Genomic Advances to Public Health Benefits: The Unbearable Lightness of Being Stuck

Genetic determinants of common human diseases are still poorly understood. Due to large investments, many small successes have been made and the research field is rapidly expanding. However, genetic susceptibility variants showing repeatable associations with common diseases are usually of small effect. They are therefore unlikely to individually explain substantial share of disease burden in any community or provide new insights into disease pathogenesis that could lead to development of new drugs effective in considerable portion of the disease cases in a population. Genetic architecture of common diseases is beginning to reveal an incredible diversity of potential genetic causes that act through somewhat limited number of mechanisms with important contribution of environmental interactions. In light of these findings, we present current understanding of genetic architecture of a spectrum of human diseases. We address the encountered problems in susceptibility gene identification, review the success of leading gene identification strategies and discuss current prospects for translating genomic advances into measurable public health benefits