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1.  Evidence for localised HIV related micro–epidemics associated with the decentralised provision of antiretroviral treatment in rural South Africa: a spatio–temporal analysis of changing mortality patterns (2007–2010) 
Journal of Global Health  2014;4(1):010403.
Background
In this study we analysed the spatial and temporal changes in patterns of mortality over a period when antiretroviral therapy (ART) was rolled out in a rural region of north–eastern South Africa. Previous studies have identified localised concentrated HIV related sub–epidemics and recommended that micro–level analyses be carried out in order to direct focused interventions.
Methods
Data from an ongoing health and socio–demographic surveillance study was used in the analysis. The follow–up was divided into two periods, 2007–2008 and 2009–2010, representing the times immediately before and after the effects on mortality of the decentralised ART provision from a newly established local health centre would be expected to be evident. The study population at the start of the analysis was approximately 73 000 individuals. Data were aggregated by village and also using a 2 × 2 km grid. We identified villages, grid squares and regions in the site where mortality rates within each time period or rate ratios between the periods differed significantly from the overall trends. We used clustering techniques to identify cause–specific mortality hotspots.
Findings
Comparing the two periods, there was a 30% decrease in age and gender standardised adult HIV–related and TB (HIV/TB) mortality with no change in mortality due to other causes. There was considerable spatial heterogeneity in the mortality patterns. Areas separated by 2 to 4 km with very different epidemic trajectories were identified. There was evidence that the impact of ART in reducing HIV/TB mortality was greatest in communities with higher mortality rates in the earlier period.
Conclusions
This study shows the value of conducting high resolution spatial analyses in order to understand how local micro–epidemics contribute to changes seen over a wider area. Such analyses can support targeted interventions.
doi:10.7189/jogh.04.010403
PMCID: PMC4073250  PMID: 24976962
2.  The development and experience of epidemiological transition theory over four decades: a systematic review 
Global Health Action  2014;7:10.3402/gha.v7.23574.
Background
Epidemiological transition (ET) theory, first postulated in 1971, has developed alongside changes in population structures over time. However, understandings of mortality transitions and associated epidemiological changes remain poorly defined for public health practitioners. Here, we review the concept and development of ET theory, contextualising this in empirical evidence, which variously supports and contradicts the original theoretical propositions.
Design
A Medline literature search covering publications over four decades, from 1971 to 2013, was conducted. Studies were included if they assessed human populations, were original articles, focused on mortality and health or demographic or ET and were in English. The reference lists of the selected articles were checked for additional sources.
Results
We found that there were changes in emphasis in the research field over the four decades. There was an increasing tendency to study wide-ranging aspects of the determinants of mortality, including risk factors, lifestyle changes, socio-economics, and macro factors such as climate change. Research on ET has focused increasingly on low- and middle-income countries rather than industrialised countries, despite its origins in industrialised countries. Countries have experienced different levels of progress in ET in terms of time, pace, and underlying mechanisms. Elements of ET are described for many countries, but observed transitions have not always followed pathways described in the original theory.
Conclusions
The classic ET theory largely neglected the critical role of social determinants, being largely a theoretical generalisation of mortality experience in some countries. This review shows increasing interest in ET all over the world but only partial concordance between established theory and empirical evidence. Empirical evidence suggests that some unconsidered aspects of social determinants contributed to deviations from classic theoretical pathways. A better-constructed, revised ET theory, with a stronger basis in evidence, is needed.
doi:10.3402/gha.v7.23574
PMCID: PMC4038769  PMID: 24848657
epidemiological transition; demographic transition; mortality; social determinants
3.  Verbal autopsy as a tool for identifying children dying of sickle cell disease: a validation study conducted in Kilifi district, Kenya 
BMC Medicine  2014;12:65.
Background
Sickle cell disease (SCD) is common in many parts of sub-Saharan Africa (SSA), where it is associated with high early mortality. In the absence of newborn screening, most deaths among children with SCD go unrecognized and unrecorded. As a result, SCD does not receive the attention it deserves as a leading cause of death among children in SSA. In the current study, we explored the potential utility of verbal autopsy (VA) as a tool for attributing underlying cause of death (COD) in children to SCD.
Methods
We used the 2007 WHO Sample Vital Registration with Verbal Autopsy (SAVVY) VA tool to determine COD among child residents of the Kilifi Health and Demographic Surveillance System (KHDSS), Kenya, who died between January 2008 and April 2011. VAs were coded both by physician review (physician coded verbal autopsy, PCVA) using COD categories based on the WHO International Classification of Diseases 10th Edition (ICD-10) and by using the InterVA-4 probabilistic model after extracting data according to the 2012 WHO VA standard. Both of these methods were validated against one of two gold standards: hospital ICD-10 physician-assigned COD for children who died in Kilifi District Hospital (KDH) and, where available, laboratory confirmed SCD status for those who died in the community.
Results
Overall, 6% and 5% of deaths were attributed to SCD on the basis of PCVA and the InterVA-4 model, respectively. Of the total deaths, 22% occurred in hospital, where the agreement coefficient (AC1) for SCD between PCVA and hospital physician diagnosis was 95.5%, and agreement between InterVA-4 and hospital physician diagnosis was 96.9%. Confirmatory laboratory evidence of SCD status was available for 15% of deaths, in which the AC1 against PCVA was 87.5%.
Conclusions
Other recent studies and provisional data from this study, outlining the importance of SCD as a cause of death in children in many parts of the developing world, contributed to the inclusion of specific SCD questions in the 2012 version of the WHO VA instruments, and a specific code for SCD has now been included in the WHO and InterVA-4 COD listings. With these modifications, VA may provide a useful approach to quantifying the contribution of SCD to childhood mortality in rural African communities. Further studies will be needed to evaluate the generalizability of our findings beyond our local context.
doi:10.1186/1741-7015-12-65
PMCID: PMC4022330  PMID: 24755265
Sickle cell disease; Verbal autopsy; Agreement coefficient; Child mortality; Kenya
4.  A probabilistic method to estimate the burden of maternal morbidity in resource-poor settings: preliminary development and evaluation 
Background
Maternal morbidity is more common than maternal death, and population-based estimates of the burden of maternal morbidity could provide important indicators for monitoring trends, priority setting and evaluating the health impact of interventions. Methods based on lay reporting of obstetric events have been shown to lack specificity and there is a need for new approaches to measure the population burden of maternal morbidity. A computer-based probabilistic tool was developed to estimate the likelihood of maternal morbidity and its causes based on self-reported symptoms and pregnancy/delivery experiences. Development involved the use of training datasets of signs, symptoms and causes of morbidity from 1734 facility-based deliveries in Benin and Burkina Faso, as well as expert review. Preliminary evaluation of the method compared the burden of maternal morbidity and specific causes from the probabilistic tool with clinical classifications of 489 recently-delivered women from Benin, Bangladesh and India.
Results
Using training datasets, it was possible to create a probabilistic tool that handled uncertainty of women’s self reports of pregnancy and delivery experiences in a unique way to estimate population-level burdens of maternal morbidity and specific causes that compared well with clinical classifications of the same data. When applied to test datasets, the method overestimated the burden of morbidity compared with clinical review, although possible conceptual and methodological reasons for this were identified.
Conclusion
The probabilistic method shows promise and may offer opportunities for standardised measurement of maternal morbidity that allows for the uncertainty of women’s self-reported symptoms in retrospective interviews. However, important discrepancies with clinical classifications were observed and the method requires further development, refinement and evaluation in a range of settings.
doi:10.1186/1742-7622-11-3
PMCID: PMC3975153  PMID: 24620784
Maternal health; Morbidity; Developing countries; Pregnancy; Childbirth; Bayesian analysis; Africa; Asia
5.  Performance of four computer-coded verbal autopsy methods for cause of death assignment compared with physician coding on 24,000 deaths in low- and middle-income countries 
BMC Medicine  2014;12:20.
Background
Physician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (CODs) in countries where medical certification of death is uncommon. Computer-coded verbal autopsy (CCVA) methods have been proposed as a faster and cheaper alternative to PCVA, though they have not been widely compared to PCVA or to each other.
Methods
We compared the performance of open-source random forest, open-source tariff method, InterVA-4, and the King-Lu method to PCVA on five datasets comprising over 24,000 verbal autopsies from low- and middle-income countries. Metrics to assess performance were positive predictive value and partial chance-corrected concordance at the individual level, and cause-specific mortality fraction accuracy and cause-specific mortality fraction error at the population level.
Results
The positive predictive value for the most probable COD predicted by the four CCVA methods averaged about 43% to 44% across the datasets. The average positive predictive value improved for the top three most probable CODs, with greater improvements for open-source random forest (69%) and open-source tariff method (68%) than for InterVA-4 (62%). The average partial chance-corrected concordance for the most probable COD predicted by the open-source random forest, open-source tariff method and InterVA-4 were 41%, 40% and 41%, respectively, with better results for the top three most probable CODs. Performance generally improved with larger datasets. At the population level, the King-Lu method had the highest average cause-specific mortality fraction accuracy across all five datasets (91%), followed by InterVA-4 (72% across three datasets), open-source random forest (71%) and open-source tariff method (54%).
Conclusions
On an individual level, no single method was able to replicate the physician assignment of COD more than about half the time. At the population level, the King-Lu method was the best method to estimate cause-specific mortality fractions, though it does not assign individual CODs. Future testing should focus on combining different computer-coded verbal autopsy tools, paired with PCVA strengths. This includes using open-source tools applied to larger and varied datasets (especially those including a random sample of deaths drawn from the population), so as to establish the performance for age- and sex-specific CODs.
doi:10.1186/1741-7015-12-20
PMCID: PMC3912488  PMID: 24495855
Causes of death; Computer-coded verbal autopsy (CCVA); InterVA-4; King-Lu; Physician-certified verbal autopsy (PCVA); Random forest; Tariff method; Validation; Verbal autopsy
6.  Usefulness of the Population Health Metrics Research Consortium gold standard verbal autopsy data for general verbal autopsy methods 
BMC Medicine  2014;12:23.
Background
Verbal Autopsy (VA) is widely viewed as the only immediate strategy for registering cause of death in much of Africa and Asia, where routine physician certification of deaths is not widely practiced. VA involves a lay interview with family or friends after a death, to record essential details of the circumstances. These data can then be processed automatically to arrive at standardized cause of death information.
Methods
The Population Health Metrics Research Consortium (PHMRC) undertook a study at six tertiary hospitals in low- and middle-income countries which documented over 12,000 deaths clinically and subsequently undertook VA interviews. This dataset, now in the public domain, was compared with the WHO 2012 VA standard and the InterVA-4 interpretative model.
Results
The PHMRC data covered 70% of the WHO 2012 VA input indicators, and categorized cause of death according to PHMRC definitions. After eliminating some problematic or incomplete records, 11,984 VAs were compared. Some of the PHMRC cause definitions, such as ‘preterm delivery’, differed substantially from the International Classification of Diseases, version 10 equivalent. There were some appreciable inconsistencies between the hospital and VA data, including 20% of the hospital maternal deaths being described as non-pregnant in the VA data. A high proportion of VA cases (66%) reported respiratory symptoms, but only 18% of assigned hospital causes were respiratory-related. Despite these issues, the concordance correlation coefficient between hospital and InterVA-4 cause of death categories was 0.61.
Conclusions
The PHMRC dataset is a valuable reference source for VA methods, but has to be interpreted with care. Inherently inconsistent cases should not be included when using these data to build other VA models. Conversely, models built from these data should be independently evaluated. It is important to distinguish between the internal and external validity of VA models. The effects of using tertiary hospital data, rather than the more usual application of VA to all-community deaths, are hard to evaluate. However, it would still be of value for VA method development to have further studies of population-based post-mortem examinations.
doi:10.1186/1741-7015-12-23
PMCID: PMC3912496  PMID: 24495341
Verbal autopsy; Cause of death; Death registration; Low- and middle-income countries; InterVA
7.  Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries: systematic review 
BMC Medicine  2014;12:22.
Background
Computer-coded verbal autopsy (CCVA) methods to assign causes of death (CODs) for medically unattended deaths have been proposed as an alternative to physician-certified verbal autopsy (PCVA). We conducted a systematic review of 19 published comparison studies (from 684 evaluated), most of which used hospital-based deaths as the reference standard. We assessed the performance of PCVA and five CCVA methods: Random Forest, Tariff, InterVA, King-Lu, and Simplified Symptom Pattern.
Methods
The reviewed studies assessed methods’ performance through various metrics: sensitivity, specificity, and chance-corrected concordance for coding individual deaths, and cause-specific mortality fraction (CSMF) error and CSMF accuracy at the population level. These results were summarized into means, medians, and ranges.
Results
The 19 studies ranged from 200 to 50,000 deaths per study (total over 116,000 deaths). Sensitivity of PCVA versus hospital-assigned COD varied widely by cause, but showed consistently high specificity. PCVA and CCVA methods had an overall chance-corrected concordance of about 50% or lower, across all ages and CODs. At the population level, the relative CSMF error between PCVA and hospital-based deaths indicated good performance for most CODs. Random Forest had the best CSMF accuracy performance, followed closely by PCVA and the other CCVA methods, but with lower values for InterVA-3.
Conclusions
There is no single best-performing coding method for verbal autopsies across various studies and metrics. There is little current justification for CCVA to replace PCVA, particularly as physician diagnosis remains the worldwide standard for clinical diagnosis on live patients. Further assessments and large accessible datasets on which to train and test combinations of methods are required, particularly for rural deaths without medical attention.
doi:10.1186/1741-7015-12-22
PMCID: PMC3912516  PMID: 24495312
Causes of death; Computer-coded verbal autopsy; InterVA; King and Lu; Physician-certified verbal autopsy; Random forest; Simplified symptom pattern; Tariff; Validity; Verbal autopsy
8.  “No one says ‘No’ to money” – a mixed methods approach for evaluating conditional cash transfer schemes to improve girl children’s status in Haryana, India 
Introduction
Haryana was the first state in India to launch a conditional cash transfer (CCT) scheme in 1994. Initially it targeted all disadvantaged girls but was revised in 2005 to restrict it to second girl children of all groups. The benefit which accrued at girl attaining 18 years and subject to conditionalities of being fully immunized, studying till class 10 and remaining unmarried, was increased from about US$ 500 to US$ 2000. Using a mixed methods approach, we evaluated the implementation and possible impact of these two schemes.
Methods
A survey was conducted among 200 randomly selected respondents of Ballabgarh Block in Haryana to assess their perceptions of girl children and related schemes. A cohort of births during this period was assembled from population database of 28 villages in this block and changes in sex ratio at birth and in immunization coverage at one year of age among boys and girls was measured. Education levels and mean age at marriage of daughters were compared with daughters-in-law from outside Haryana. In-depth interviews were conducted among district level implementers of these schemes to assess their perceptions of programs’ implementation and impact. These were analyzed using a thematic approach.
Results
The perceptions of girls as a liability and poor (9% to 15%) awareness of the schemes was noted. The cohort analysis showed that while there has been an improvement in the indicators studied, these were similar to those seen among the control groups. Qualitative analysis identified a “conspiracy of silence” - an underplaying of the pervasiveness of the problem coupled with a passive implementation of the program and a clash between political culture of giving subsidies and a bureaucratic approach that imposed many conditionalities and documentary needs for availing of benefits.
Conclusion
The apparent lack of impact on the societal mindset calls for a revision in the current approach of addressing a social issue by a purely conditional cash transfer program.
doi:10.1186/1475-9276-13-11
PMCID: PMC3922091  PMID: 24484583
9.  Evaluating the InterVA model for determining AIDS mortality from verbal autopsies in the adult population of Addis Ababa 
Summary
OBJECTIVE
To evaluate the performance of a Verbal Autopsy (VA) expert algorithm (the InterVA model) for diagnosing AIDS mortality against a reference standard from hospital records that include HIV serostatus information in Addis Ababa, Ethiopia.
METHODS
Verbal autopsies were conducted for 193 individuals who visited a hospital under surveillance during terminal illness. Decedent admission diagnosis and HIV serostatus information is used to construct two reference standards (AIDS versus other causes of death and TB/AIDS versus other causes). The InterVA model is used to interpret the VA interviews, and the sensitivity, specificity, and cause-specific mortality fractions are calculated as indicators of the diagnostic accuracy of the InterVA model.
RESULTS
The sensitivity and specificity of the InterVA model for diagnosing AIDS are 0.82 (95%-CI: 0.74-0.89) and 0.76 (95%-CI: 0.64-0.86), respectively. The sensitivity and specificity for TB/AIDS are 0.91 (95%-CI: 0.85-0.96) and 0.78 (95%-CI: 0.63-0.89), respectively. The AIDS specific mortality fraction estimated by the model is 61.7% (95%-CI: 54%-69%), which is close to 64.7% (95%-CI: 57%-72%) in the reference standard. The TB/AIDS mortality fraction estimated by the model is 73.6% (95%-CI: 67%-80%), compared to 74.1% (95%-CI: 68%-81%) in the reference standard.
CONCLUSION
The InterVA model is an easy to use and cheap alternative to physician review for assessing AIDS mortality in countries without vital registration and medical certification of causes of death. The model seems to perform better when TB and AIDS are combined, but the sample is too small to statistically confirm that.
doi:10.1111/j.1365-3156.2010.02484.x
PMCID: PMC3901008  PMID: 20214760
mortality; surveillance; verbal autopsy; InterVA; cause of death; HIV/AIDS; Ethiopia
10.  InterVA-4 as a public health tool for measuring HIV/AIDS mortality: a validation study from five African countries 
Global Health Action  2013;6:10.3402/gha.v6i0.22448.
Background
Reliable population-based data on HIV infection and AIDS mortality in sub-Saharan Africa are scanty, even though that is the region where most of the world’s AIDS deaths occur. There is therefore a great need for reliable and valid public health tools for assessing AIDS mortality.
Objective
The aim of this article is to validate the InterVA-4 verbal autopsy (VA) interpretative model within African populations where HIV sero-status is recorded on a prospective basis, and examine the distribution of cause-specific mortality among HIV-positive and HIV-negative people.
Design
Data from six sites of the Alpha Network, including HIV sero-status and VA interviews, were pooled. VA data according to the 2012 WHO format were extracted, and processed using the InterVA-4 model into likely causes of death. The model was blinded to the sero-status data. Cases with known pre-mortem HIV infection status were used to determine the specificity with which InterVA-4 could attribute HIV/AIDS as a cause of death. Cause-specific mortality fractions by HIV infection status were calculated, and a person-time model was built to analyse adjusted cause-specific mortality rate ratios.
Results
The InterVA-4 model identified HIV/AIDS-related deaths with a specificity of 90.1% (95% CI 88.7–91.4%). Overall sensitivity could not be calculated, because HIV-positive people die from a range of causes. In a person-time model including 1,739 deaths in 1,161,688 HIV-negative person-years observed and 2,890 deaths in 75,110 HIV-positive person-years observed, the mortality ratio HIV-positive:negative was 29.0 (95% CI 27.1–31.0), after adjustment for age, sex, and study site. Cause-specific HIV-positive:negative mortality ratios for acute respiratory infections, HIV/AIDS-related deaths, meningitis, tuberculosis, and malnutrition were higher than the all-cause ratio; all causes had HIV-positive:negative mortality ratios significantly higher than unity.
Conclusions
These results were generally consistent with relatively small post-mortem and hospital-based diagnosis studies in the literature. The high specificity in cause of death attribution achieved in relation to HIV status, and large differences between specific causes by HIV status, show that InterVA-4 is an effective and valid tool for assessing HIV-related mortality.
doi:10.3402/gha.v6i0.22448
PMCID: PMC3800746  PMID: 24138838
HIV/AIDS; mortality; Africa; verbal autopsy; InterVA; Alpha Network
11.  Global Health Action: surviving infancy and taking first steps 
Global Health Action  2013;6:10.3402/gha.v6i0.22815.
doi:10.3402/gha.v6i0.22815
PMCID: PMC3779786  PMID: 24054160
12.  Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring 
Global Health Action  2013;6:10.3402/gha.v6i0.21518.
Objective
Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems.
Methods
A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification.
Findings
A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach.
Conclusions
The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians.
doi:10.3402/gha.v6i0.21518
PMCID: PMC3774013  PMID: 24041439
verbal autopsy; cause of death; vital registration; civil registration; vital statistics; World Health Organization; InterVA
13.  Reflections on the Global Burden of Disease 2010 Estimates 
PLoS Medicine  2013;10(7):e1001477.
Peter Byass and colleagues raise questions about the recent, high-profile Global Burden of Disease estimates.
Please see later in the article for the Editors' Summary
doi:10.1371/journal.pmed.1001477
PMCID: PMC3699446  PMID: 23843748
14.  Beyond 2015: time to reposition Scandinavia in global health? 
Global Health Action  2013;6:10.3402/gha.v6i0.20903.
doi:10.3402/gha.v6i0.20903
PMCID: PMC3617876  PMID: 23653919
15.  Only an integrated approach across academia, enterprise, governments, and global agencies can tackle the public health impact of climate change 
Global Health Action  2013;6:10.3402/gha.v6i0.20513.
Background
Despite considerable global attention to the issues of climate change, relatively little priority has been given to the likely effects on human health of current and future changes in the global climate. We identify three major societal determinants that influence the impact of climate change on human health, namely the application of scholarship and knowledge; economic and commercial considerations; and actions of governments and global agencies.
Discussion
The three major areas are each discussed in terms of the ways in which they facilitate and frustrate attempts to protect human health from the effects of climate change. Academia still pays very little attention to the effects of climate on health in poorer countries. Enterprise is starting to recognise that healthy commerce depends on healthy people, and so climate change presents long-term threats if it compromises health. Governments and international agencies are very active, but often face immovable vested interests in other sectors. Overall, there tends to be too little interaction between the three areas, and this means that potential synergies and co-benefits are not always realised.
Conclusion
More attention from academia, enterprise, and international agencies needs to be given to the potential threats the climate change presents to human health. However, there needs to also be much closer collaboration between all three areas in order to capitalise on possible synergies that can be achieved between them.
doi:10.3402/gha.v6i0.20513
PMCID: PMC3617642  PMID: 23653920
climate change; public health; academia; research; enterprise; government; international agencies; human health
16.  Is global health really global? 
Global Health Action  2013;6:10.3402/gha.v6i0.20671.
doi:10.3402/gha.v6i0.20671
PMCID: PMC3610432  PMID: 23537563
17.  Towards elimination of maternal deaths: maternal deaths surveillance and response 
Reproductive Health  2013;10:1.
Current methods for estimating maternal mortality lack precision, and are not suitable for monitoring progress in the short run. In addition, national maternal mortality ratios (MMRs) alone do not provide useful information on where the greatest burden of mortality is located, who is concerned, what are the causes, and more importantly what sub-national variations occur. This paper discusses a maternal death surveillance and response (MDSR) system. MDSR systems are not yet established in most countries and have potential added value for policy making and accountability and can build on existing efforts to conduct maternal death reviews, verbal autopsies and confidential enquiries. Accountability at national and sub-national levels cannot rely on global, regional and national retrospective estimates periodically generated from academia or United Nations organizations but on routine counting, investigation, sub national data analysis, long term investments in vital registration and national health information systems. Establishing effective maternal death surveillance and response will help achieve MDG 5, improve quality of maternity care and eliminate maternal mortality (MMR ≤ 30 per 100,000 by 2030).
doi:10.1186/1742-4755-10-1
PMCID: PMC3562216  PMID: 23279882
18.  Progress toward Global Reduction in Under-Five Mortality: A Bootstrap Analysis of Uncertainty in Millennium Development Goal 4 Estimates 
PLoS Medicine  2012;9(12):e1001355.
Leontine Alkema and colleagues use a bootstrap procedure to assess the uncertainty around the estimates of the under-five mortality rate produced by the United Nations Inter-Agency Group for Child Mortality Estimation.
Background
Millennium Development Goal 4 calls for an annual rate of reduction (ARR) of the under-five mortality rate (U5MR) of 4.4% between 1990 and 2015. Progress is measured through the point estimates of the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). To facilitate evidence-based conclusions about progress toward the goal, we assessed the uncertainty in the estimates arising from sampling errors and biases in data series and the inferior quality of specific data series.
Methods and Findings
We implemented a bootstrap procedure to construct 90% uncertainty intervals (UIs) for the U5MR and ARR to complement the UN IGME estimates. We constructed the bounds for all countries without a generalized HIV epidemic, where a standard estimation approach is carried out (174 countries). In the bootstrap procedure, potential biases in levels and trends of data series of different source types were accounted for. There is considerable uncertainty about the U5MR, particularly for high mortality countries and in recent years. Among 86 countries with a U5MR of at least 40 deaths per 1,000 live births in 1990, the median width of the UI, relative to the U5MR level, was 19% for 1990 and 48% for 2011, with the increase in uncertainty due to more limited data availability. The median absolute width of the 90% UI for the ARR from 1990 to 2011 was 2.2%. Although the ARR point estimate for all high mortality countries was greater than zero, for eight of them uncertainty included the possibility of no improvement between 1990 and 2011. For 13 countries, it is deemed likely that the ARR from 1990 to 2011 exceeded 4.4%.
Conclusions
In light of the upcoming evaluation of Millennium Development Goal 4 in 2015, uncertainty assessments need to be taken into account to avoid unwarranted conclusions about countries' progress based on limited data.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In September 2000, world leaders adopted the United Nations Millennium Declaration, committing member states (countries) to a new global partnership to reduce extreme poverty and improve global health by setting out a series of time-bound targets with a deadline of 2015—the Millennium Development Goals (MDGs). There are eight MDGs and the fourth, MDG 4, focuses on reducing the number of deaths in children aged under five years by two-thirds from the 1990 level. Monitoring progress towards meeting all of the MDG targets is of vital importance to measure the effectiveness of interventions and to prioritize slow progress areas. MDG 4 has three specific indicators, and every year, the United Nations Inter-agency Group for Child Mortality Estimation (the UN IGME, which includes the key agencies the United Nations Children's Fund, the World Health Organization, the World Bank, and the United Nations Population Division) produces and publishes estimates of child death rates for all countries.
Why Was This Study Done?
Many poorer countries do not have the infrastructure and the functioning vital registration systems in place to record the number of child deaths. Therefore, it is difficult to accurately assess levels and trends in the rate of child deaths because there is limited information (data) or because the data that exists may be inaccurate or of poor quality. In order to deal with this situation, analyzing trends in under-five child death rates (to show progress towards MDG 4) currently focuses on the “best” estimates from countries, a process that relies on “point” estimates. But this practice can lead to inaccurate results and comparisons. It is therefore important to identify a framework for calculating the uncertainty surrounding these estimates. In this study, the researchers use a statistical method to calculate plausible uncertainty intervals for the estimates of death rates in children aged under five years and the yearly reduction in those rates.
What Did the Researchers Do and Find?
The researchers used the publicly available information from the UN IGME 2012 database, which collates data from a variety of sources, and a statistical method called bootstrapping to construct uncertainty levels for 174 countries out of 195 countries for which the UN IGME published estimates in 2012. This new method improves current practice for estimating the extent of data errors, as it takes into account the structure and (potentially poor) quality of the data. The researchers used 90% as the uncertainty level and categorized countries according to the likelihood of meeting the MDG 4 target.
Using these methods, the researchers found that in countries with high child mortality rates (40 or more deaths per 1,000 children in 1990), there was a lot of uncertainty (wide uncertainty intervals) about the levels and trends of death rates in children aged under five years, especially more recently, because of the limited availability of data. Overall, in 2011 the median width of the uncertainty interval for the child death rate was 48% among the 86 countries with high death rates, compared to 19% in 1990. Using their new method, the researchers found that for eight countries, it is not clear whether any progress had been made in reducing child mortality, but for 13 countries, it is deemed likely that progress exceeded the MDG 4 target.
What Do These Findings Mean?
These findings suggest that new uncertainty assessments constructed by a statistical method called bootstrapping can provide more insights into countries' progress in reducing child mortality and meeting the MDG 4 target. As demonstrated in this study, when data are limited, uncertainty intervals should to be taken into account when estimating progress towards MDG 4 in order to give more accurate assessments on a country' progress, thus allowing for more realistic comparisons and conclusions.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001355.
The UN website has more information about the Millennium Development Goals, including country-specific data
More information is available from UNICEF's ChildInfo website about the UN IGME and child mortality
All UN IGME child mortality estimates and data are available via CME Info
Countdown to 2015 tracks coverage levels for health interventions proven to reduce child mortality and proposes new actions to reach MDG 4
doi:10.1371/journal.pmed.1001355
PMCID: PMC3519895  PMID: 23239945
19.  The impact of insecticide-treated school uniforms on dengue infections in school-aged children: study protocol for a randomised controlled trial in Thailand 
Trials  2012;13:212.
Background
There is an urgent need to protect children against dengue since this age group is particularly sensitive to the disease. Since dengue vectors are active mainly during the day, a potential target for control should be schools where children spend a considerable amount of their day. School uniforms are the cultural norm in most developing countries, worn throughout the day. We hypothesise that insecticide-treated school uniforms will reduce the incidence of dengue infection in school-aged children. Our objective is to determine the impact of impregnated school uniforms on dengue incidence.
Methods
A randomised controlled trial will be conducted in eastern Thailand in a group of schools with approximately 2,000 students aged 7–18 years. Pre-fabricated school uniforms will be commercially treated to ensure consistent, high-quality insecticide impregnation with permethrin. A double-blind, randomised, crossover trial at the school level will cover two dengue transmission seasons.
Discussion
Practical issues and plans concerning intervention implementation, evaluation, analysing and interpreting the data, and possible policy implications arising from the trial are discussed.
Trial registration
clinicaltrial.gov. Registration number: NCT01563640
doi:10.1186/1745-6215-13-212
PMCID: PMC3519696  PMID: 23153360
Dengue; Insecticide-treated clothes; School children; School uniforms; Randomised control trial; Cost effectiveness
20.  Assessing effectiveness of a community based health insurance in rural Burkina Faso 
Background
Financial barriers are a recognized major bottleneck of access and use of health services. The aim of this study was to assess effectiveness of a community based health insurance (CBHI) scheme on utilization of health services as well as on mortality and morbidity.
Methods
Data were collected from April to December 2007 from the Nouna’s Demographic Surveillance System on overall mortality, utilization of health services, household characteristics, distance to health facilities, membership in the Nouna CBHI. We analyzed differentials in overall mortality and selected maternal health process measures between members and non-members of the insurance scheme.
Results
After adjusting for covariates there was no significant difference in overall mortality between households who could not have been members (because their area was yet to be covered by the stepped-wedged scheme), non-members but whose households could have been members (areas covered but not enrolled), and members of the insurance scheme. The risk of overall mortality increased significantly with distance to health facility (35% more outside Nouna town) and with education level (37% lower when at least primary school education achieved in households).
Conclusion
There was no statistically significant difference in overall mortality between members and non-members. The enrolment rates remain low, with selection bias. It is important that community based health insurances, exemptions fees policy and national health insurances be evaluated on prevention of deaths and severe morbidities instead of on drop-out rates, selection bias, adverse selection and catastrophic payments for health care only. Effective social protection will require national health insurance.
doi:10.1186/1472-6963-12-363
PMCID: PMC3508949  PMID: 23082967
Effectiveness; Community based health insurance; Universal health coverage
21.  Strengthening standardised interpretation of verbal autopsy data: the new InterVA-4 tool 
Global Health Action  2012;5:10.3402/gha.v5i0.19281.
Background
Verbal autopsy (VA) is the only available approach for determining the cause of many deaths, where routine certification is not in place. Therefore, it is important to use standards and methods for VA that maximise efficiency, consistency and comparability. The World Health Organization (WHO) has led the development of the 2012 WHO VA instrument as a new standard, intended both as a research tool and for routine registration of deaths.
Objective
A new public-domain probabilistic model for interpreting VA data, InterVA-4, is described, which builds on previous versions and is aligned with the 2012 WHO VA instrument.
Design
The new model has been designed to use the VA input indicators defined in the 2012 WHO VA instrument and to deliver causes of death compatible with the International Classification of Diseases version 10 (ICD-10) categorised into 62 groups as defined in the 2012 WHO VA instrument. In addition, known shortcomings of previous InterVA models have been addressed in this revision, as well as integrating other work on maternal and perinatal deaths.
Results
The InterVA-4 model is presented here to facilitate its widespread use and to enable further field evaluation to take place. Results from a demonstration dataset from Agincourt, South Africa, show continuity of interpretation between InterVA-3 and InterVA-4, as well as differences reflecting specific issues addressed in the design and development of InterVA-4.
Conclusions
InterVA-4 is made freely available as a new standard model for interpreting VA data into causes of death. It can be used for determining cause of death both in research settings and for routine registration. Further validation opportunities will be explored. These developments in cause of death registration are likely to substantially increase the global coverage of cause-specific mortality data.
doi:10.3402/gha.v5i0.19281
PMCID: PMC3433652  PMID: 22944365
verbal autopsy; cause of death; vital registration; InterVA; World Health Organization
22.  Child Mortality Estimation: Methods Used to Adjust for Bias due to AIDS in Estimating Trends in Under-Five Mortality 
PLoS Medicine  2012;9(8):e1001298.
Neff Walker and colleagues show how the United Nations Inter-agency Group for Child Mortality Estimation use a model to correct for AIDS-related biases in the data used to estimate trends in under-five mortality.
In most low- and middle-income countries, child mortality is estimated from data provided by mothers concerning the survival of their children using methods that assume no correlation between the mortality risks of the mothers and those of their children. This assumption is not valid for populations with generalized HIV epidemics, however, and in this review, we show how the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) uses a cohort component projection model to correct for AIDS-related biases in the data used to estimate trends in under-five mortality. In this model, births in a given year are identified as occurring to HIV-positive or HIV-negative mothers, the lives of the infants and mothers are projected forward using survivorship probabilities to estimate survivors at the time of a given survey, and the extent to which excess mortality of children goes unreported because of the deaths of HIV-infected mothers prior to the survey is calculated. Estimates from the survey for past periods can then be adjusted for the estimated bias. The extent of the AIDS-related bias depends crucially on the dynamics of the HIV epidemic, on the length of time before the survey that the estimates are made for, and on the underlying non-AIDS child mortality. This simple methodology (which does not take into account the use of effective antiretroviral interventions) gives results qualitatively similar to those of other studies.
doi:10.1371/journal.pmed.1001298
PMCID: PMC3429377  PMID: 22952437
23.  Child Mortality Estimation: Accelerated Progress in Reducing Global Child Mortality, 1990–2010 
PLoS Medicine  2012;9(8):e1001303.
Kenneth Hill and colleagues provide an introductory overview of how the latest United Nations Inter-agency Group for Child Mortality Estimation estimates were produced, summarizes the key findings of these estimates and describe current methodology and recent methodological innovations.
Monitoring development indicators has become a central interest of international agencies and countries for tracking progress towards the Millennium Development Goals. In this review, which also provides an introduction to a collection of articles, we describe the methodology used by the United Nations Inter-agency Group for Child Mortality Estimation to track country-specific changes in the key indicator for Millennium Development Goal 4 (MDG 4), the decline of the under-five mortality rate (the probability of dying between birth and age five, also denoted in the literature as U5MR and 5q0). We review how relevant data from civil registration, sample registration, population censuses, and household surveys are compiled and assessed for United Nations member states, and how time series regression models are fitted to all points of acceptable quality to establish the trends in U5MR from which infant and neonatal mortality rates are generally derived. The application of this methodology indicates that, between 1990 and 2010, the global U5MR fell from 88 to 57 deaths per 1,000 live births, and the annual number of under-five deaths fell from 12.0 to 7.6 million. Although the annual rate of reduction in the U5MR accelerated from 1.9% for the period 1990–2000 to 2.5% for the period 2000–2010, it remains well below the 4.4% annual rate of reduction required to achieve the MDG 4 goal of a two-thirds reduction in U5MR from its 1990 value by 2015. Thus, despite progress in reducing child mortality worldwide, and an encouraging increase in the pace of decline over the last two decades, MDG 4 will not be met without greatly increasing efforts to reduce child deaths.
doi:10.1371/journal.pmed.1001303
PMCID: PMC3429379  PMID: 22952441
24.  Child Mortality Estimation: A Comparison of UN IGME and IHME Estimates of Levels and Trends in Under-Five Mortality Rates and Deaths 
PLoS Medicine  2012;9(8):e1001288.
Leontine Alkema and Danzhen You compare and summarize differences in underlying data and modelling approaches used by two key groups who publish data on global under-5 mortality rates
Background
Millennium Development Goal 4 calls for a reduction in the under-five mortality rate (U5MR) by two-thirds between 1990 and 2015. In 2011, estimates were published by the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) and the Institute for Health Metrics and Evaluation (IHME). The difference in the U5MR estimates produced by the two research groups was more than 10% and corresponded to more than ten deaths per 1,000 live births for 10% of all countries in 1990 and 20% of all countries in 2010, which can lead to conflicting conclusions with respect to countries' progress. To understand what caused the differences in estimates, we summarised differences in underlying data and modelling approaches used by the two groups, and analysed their effects.
Methods and Findings
UN IGME and IHME estimation approaches differ with respect to the construction of databases and the pre-processing of data, trend fitting procedures, inclusion and exclusion of data series, and additional adjustment procedures. Large differences in U5MR estimates between the UN IGME and the IHME exist in countries with conflicts or civil unrest, countries with high HIV prevalence, and countries where the underlying data used to derive the estimates were different, especially if the exclusion of data series differed between the two research groups. A decomposition of the differences showed that differences in estimates due to using different data (inclusion of data series and pre-processing of data) are on average larger than the differences due to using different trend fitting methods.
Conclusions
Substantial country-specific differences between UN IGME and IHME estimates for U5MR and the number of under-five deaths exist because of various differences in data and modelling assumptions used. Often differences are illustrative of the lack of reliable data and likely to decrease as more data become available. Improved transparency on methods and data used will help to improve understanding about the drivers of the differences.
Please see later in the article for the Editors' Summary.
Editors' Summary
Background
In 2010, more than seven million children died before they reached their fifth birthday, and the global under-five mortality rate (also denoted in the literature as U5MR and 5q0) was 57 deaths per 1,000 live births. Most deaths before the age of five years occur in developing countries (about half occur in just five countries—India, Nigeria, the Democratic Republic of the Congo, Pakistan, and China), and most are caused by preventable or treatable diseases such as pneumonia, diarrhea, and malaria. Faced with this largely avoidable loss of young lives, in 1990, the United Nations (UN) World Summit for Children pledged to improve the survival of children. Later, in 2000, world leaders set a target of reducing under-five mortality to one-third of its 1990 level (12 million) by 2015, as Millennium Development Goal 4 (MDG 4). This goal, together with seven others, is designed to improve the social, economic, and health conditions in the world's poorest countries.
Why Was This Study Done?
Although progress towards MDG 4 is accelerating, MDG 4 is unlikely to be reached. It is important, therefore, to know which countries are making poor progress towards MDG 4 so that extra resources can be concentrated in these areas. To monitor both national and global progress, accurate, up-to-date estimates of U5MR are essential. The first step in estimating U5MR is the collection of data on child deaths, usually through vital registration systems (which record all births and deaths) in developed countries and through surveys that ask women about their living and dead children in developing countries. Country-specific U5MR estimates that are comparable over time and across countries are obtained from these data using a statistical process called trend fitting. Two groups—the UN Inter-agency Group for Child Mortality Estimation (UN IGME) and the Institute for Health Metrics and Evaluation (IHME)—recently published new estimates of the levels and trends in U5MR and under-five deaths across the world. However, their estimates differ somewhat and, for some countries, disagree on the progress being made towards MDG 4. Here, the researchers examine the differences in the underlying data and the trend fitting approaches used by the UN IGME and the IHME to try to understand why their estimates are different.
What Did the Researchers Do and Find?
The researchers first compared the estimates produced by the two groups. From 1990 to 2010, the UN IGME's global estimates of U5MR and under-five deaths were consistently slightly higher than those of the IHME. For example, in 2010, the UN IGME and IMHE estimates of U5MR were 56.7 and 53.9 deaths per 1,000 births, respectively. However, although the global estimates from the two groups were broadly similar, there were important differences between the two sets of estimates at the country level, particularly in countries where there was conflict or civil unrest (for example, Somalia) or high HIV prevalence. The researchers then examined the data used by the two groups to estimate under-five deaths and U5MR, the method used for U5MR trend fitting, and additional adjustment procedures (for example, the UN IGME incorporates feedback from experts and country consultations in its estimates). The UN IGME and IHME estimation approaches included differences in all of these areas, but differences in the data used caused on average larger differences in the estimates than the use of different trend fitting methods did.
What Do These Findings Mean?
These findings show that the substantial country-specific differences between UN IGME and IHME estimates for U5MR and the number of under-five deaths are the result of several differences between the data and trend fitting methods used by the two groups. In particular, the findings indicate that the lack of reliable data in many developing countries, especially those where there is civil unrest or ongoing conflicts, is often responsible for differences in estimates. These differences should, therefore, decrease as more reliable data become available. For now, though, the differences between the UN IGME and IHME national estimates of child mortality may cause confusion about the true extent of progress towards MDG 4 and could foster policy inactivity if the reasons for the discrepancies are not made clear. The researchers call, therefore, for more transparency on the methods and data used in the estimation of U5MR and for a concerted effort by governments, UN agencies, and non-governmental organizations to improve the collection of reliable data on child deaths.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001288.
This paper is part of a collection of papers on Child Mortality Estimation Methods published in PLOS Medicine
The United Nations Childrens Fund (UNICEF) works for children's rights, survival, development, and protection around the world; it provides information on Millennium Development Goal 4, and its Childinfo website provides detailed statistics about child survival and health, including a description of the UN Inter-agency Group for Child Mortality Estimation and a link to its database; the 2011 UN IGME report on Levels and Trends in Child Mortality is available
The Institute for Health Metrics and Evaluation website includes a summary of their 2011 analysis of U5MR and under-five deaths
The World Health Organization also has information about Millennium Development Goal 4 and provides estimates of child mortality rates (some information in several languages)
Further information about the Millennium Development Goals is available
doi:10.1371/journal.pmed.1001288
PMCID: PMC3429386  PMID: 22952434
25.  Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories 
PLoS Medicine  2012;9(8):e1001289.
Jon Pedersen and Jing Liu examine the feasibility and potential advantages of using one-year rather than five-year time periods along with calendar year-based estimation when deriving estimates of child mortality.
Background
Child mortality estimates from complete birth histories from Demographic and Health Surveys (DHS) surveys and similar surveys are a chief source of data used to track Millennium Development Goal 4, which aims for a reduction of under-five mortality by two-thirds between 1990 and 2015. Based on the expected sample sizes when the DHS program commenced, the estimates are usually based on 5-y time periods. Recent surveys have had larger sample sizes than early surveys, and here we aimed to explore the benefits of using shorter time periods than 5 y for estimation. We also explore the benefit of changing the estimation procedure from being based on years before the survey, i.e., measured with reference to the date of the interview for each woman, to being based on calendar years.
Methods and Findings
Jackknife variance estimation was used to calculate standard errors for 207 DHS surveys in order to explore to what extent the large samples in recent surveys can be used to produce estimates based on 1-, 2-, 3-, 4-, and 5-y periods. We also recalculated the estimates for the surveys into calendar-year-based estimates. We demonstrate that estimation for 1-y periods is indeed possible for many recent surveys.
Conclusions
The reduction in bias achieved using 1-y periods and calendar-year-based estimation is worthwhile in some cases. In particular, it allows tracking of the effects of particular events such as droughts, epidemics, or conflict on child mortality in a way not possible with previous estimation procedures. Recommendations to use estimation for short time periods when possible and to use calendar-year-based estimation were adopted in the United Nations 2011 estimates of child mortality.
Editors' Summary
Background
In 2000, world leaders set, as Millennium Development Goal 4 (MDG 4), a target of reducing global under-five mortality (the number of children who die before their fifth birthday to a third of its 1990 level (12 million deaths per year) by 2015. (The MDGs are designed to alleviate extreme poverty by 2015.) To track progress towards MDG 4, the under-five mortality rate (also shown as 5q0) needs to be estimated both “precisely” and “accurately.” A “precise” estimate has a small random error (a quality indicated by a statistical measurement called the coefficient of variance), and an “accurate” estimate is one that is close to the true value because it lacks bias (systematic errors). In an ideal world, under-five mortality estimates would be based on official records of births and deaths. However, developing countries, which are where most under-five deaths occur, rarely have such records, and under-five mortality estimation relies on “complete birth histories” provided by women via surveys. These are collected by Demographic and Health Surveys (DHS, a project that helps developing countries collect data on health and population trends) and record all the births that a surveyed woman has had and the age at death of any of her children who have died.
Why Was This Study Done?
Because the DHS originally surveyed samples of 5,000–6,000 women, estimates of under-five mortality are traditionally calculated using data from five-year time periods. Over shorter periods with this sample size, the random errors in under-five mortality estimates become unacceptably large. Nowadays, the average DHS survey sample size is more than 10,000 women, so it should be possible to estimate under-five mortality over shorter time periods. Such estimates should be able to track the effects on under-five mortality of events such as droughts and conflicts better than estimates made over five years. In this study, the researchers determine appropriate time periods for child mortality estimates based on full birth histories, given different sample sizes. Specifically, they ask whether, with the bigger sample sizes that are now available, details about trends in under-five mortality rates are being missed by using the estimation procedures that were developed for smaller samples. They also ask whether calendar-year-based estimates can be calculated; mortality is usually estimated in “years before the survey,” a process that blurs the reference period for the estimate.
What Did the Researchers Do and Find?
The researchers used a statistical method called “jackknife variance estimation” to determine coefficients of variance for child mortality estimates calculated over different time periods using complete birth histories from 207 DHS surveys. Regardless of the estimation period, half of the estimates had a coefficient of variance of less than 10%, a level of random variation that is generally considered acceptable. However, within each time period, some estimates had very high coefficients of variance. These estimates were derived from surveys where there was a small sample size, low fertility (the women surveyed had relatively few babies), or low child mortality. Other analyses show that although the five-year period estimates had lower standard errors than the one-year period estimates, the latter were affected less by bias than the five-year period estimates. Finally, estimates fixed to calendar years rather than to years before the survey were more directly comparable across surveys and brought out variations in child mortality caused by specific events such as conflicts more clearly.
What Do These Findings Mean?
These findings show that although under-five mortality rate estimates based on five-year periods of data have been the norm, the sample sizes currently employed in DHS surveys make it feasible to estimate mortality for shorter periods. The findings also show that using shorter periods of data in estimations of the under-five mortality rate, and using calendar-year-based estimation, reduces bias (makes the estimations more accurate) and allows the effects of events such as droughts, epidemics, or conflict on under-five mortality rates to be tracked in a way that is impossible when using five-year periods of data. Given these findings, the researchers recommend that time periods shorter than five years should be adopted for the estimation of under-five mortality and that estimations should be pegged to calendar years rather than to years before the survey. Both recommendations have already been adopted by the United Nations Inter-agency Group for Child Mortality Estimation (IGME) and were used in their 2011 analysis of under-five mortality.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001289.
This paper is part of a collection of papers on Child Mortality Estimation Methods published in PLOS Medicine
The United Nations Childrens Fund (UNICEF) works for children's rights, survival, development, and protection around the world; it provides information on Millennium Development Goal 4, and its Childinfo website provides detailed statistics about child survival and health, including a description of the United Nations Inter-agency Group for Child Mortality Estimation; the 2011 IGME report on Levels and Trends in Child Mortality is available
The World Health Organization also has information about Millennium Development Goal 4 and provides estimates of child mortality rates (some information in several languages)
Further information about the Millennium Development Goals is available
Information is also available about Demographic and Health Surveys of infant and child mortality
doi:10.1371/journal.pmed.1001289
PMCID: PMC3429388  PMID: 22952435

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