Hill and colleagues estimate that
Hill and colleagues\' estimate that, globally, about 1·5 million (95% CI 1·2–1·8) children aged 5–14 years died in 2010. This finding is somewhat higher than the total estimated by the UN of 1·3 million, although the UN estimate is within the investigators\' CI. However, their estimate is 87% higher than the total deaths estimated in the IHME Global Burden of Disease (GBD) study 2010 of 0·82 million for 2010. Hill and colleagues conclude that their analysis of the empirical evidence broadly provides support for the UN estimates, but is almost double that of the data underpinning GBD 2010. The GBD relational model life-table system, which is fitted to the probability of dying aged younger than 5 years and the probability of dying between ages 15 and 60 years, seems to underestimate older child deaths.
GDB has published updated mortality estimates for the years up to 2013 and continues to estimate substantially lower numbers of deaths in the age range 5–14 years than the UN. We have compared GBD\'s estimates for year 2013, with those from WHO life tables that are based mainly on UN life-table analyses for developing countries without adequate death registration systems ().
As shown, the largest discrepancy between GBD and WHO estimates of number of deaths is between those for ages 5–14 years. The GBD 2013 estimates for older child deaths in this TAK 165 what age range are similar to those of their earlier 2010 estimates, and are 600 000 deaths lower than those estimated by WHO for the same year.
At their meeting in May, 2015, the technical advisory group of the UN Interagency Group on Mortality Estimates (UN-IGME) discussed possible approaches to the estimation of death rates for older children aged 5–14 and adolescents aged 15–19 years. The UN-IGME prepares annual updates of estimates and trends in mortality for neonates, infants, and children for more than 195 countries, based on data from full and summary birth histories in surveys and censuses, and from analyses of available data for death registrations. The group agreed to explore the extension of the birth-history analysis to the 5–14 year age group, and to investigate the feasibility of expanding the scope of UN-IGME to also address this age group. They also discussed data availability to assess mortality rates in the 15–19 years age group, but this assessment will involve use of data for sibling histories and deaths in households from surveys and censuses, for which a substantial amount of research is needed to identify their usefulness. Hill and colleagues are to be commended for their pioneering efforts in undertaking this systematic empirical analysis of the available evidence on levels of older child mortality in developing countries. We hope that their analysis leads to improved estimates for levels and trends of older child mortality in both UN and GBD mortality assessments. Additionally, we share their recommendations that global policy emphasis on reduction of mortality should be broadened to include older children and adolescents.
The development of resistance to sulfadoxine-pyrimethamine is a threat to the effectiveness of intermittent preventive treatment for malaria during pregnancy (IPTp), especially in areas of east Africa where the A581G molecular marker denoting super-resistance is prevalent. As a result, alternative strategies for protection from malaria during pregnancy are being explored. One idea, intermittent screening and treatment during pregnancy (ISTp), involves a rapid diagnostic test (RDT) for the screening of women who present to antenatal clinics and use of highly effective artemisinin-based drugs to treat those with malaria parisitaemia. As Anna Maria van Eijk and colleagues highlight in , the inclusion of rapid diagnostic tests for malaria in to routine care at antenatal clinics could provide a valuable and extremely convenient source of information about local patterns in malaria transmission. Further, such a strategy has become feasible since the price of RDT has decreased sharply. However, for these data to be useful as a surveillance tool we must understand the relation between prevalence in pregnant women and the endemicity of infection in the general population, especially in children who are the most commonly sampled sentinels of infection and who bear most of the malaria burden.