Child Mortality Estimation 2013: An Overview of Updates in Estimation Methods by the United Nations Inter-Agency Group for Child Mortality Estimation

Background

In September 2013, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) published an update of the estimates of the under-five mortality rate (U5MR) and under-five deaths for all countries. Compared to the UN IGME estimates published in 2012, updated data inputs and a new method for estimating the U5MR were used.

Methods

We summarize the new U5MR estimation method, which is a Bayesian B-spline Bias-reduction model, and highlight differences with the previously used method. Differences in UN IGME U5MR estimates as published in 2012 and those published in 2013 are presented and decomposed into differences due to the updated database and differences due to the new estimation method to explain and motivate changes in estimates.

Findings

Compared to the previously used method, the new UN IGME estimation method is based on a different trend fitting method that can track (recent) changes in U5MR more closely. The new method provides U5MR estimates that account for data quality issues. Resulting differences in U5MR point estimates between the UN IGME 2012 and 2013 publications are small for the majority of countries but greater than 10 deaths per 1,000 live births for 33 countries in 2011 and 19 countries in 1990. These differences can be explained by the updated database used, the curve fitting method as well as accounting for data quality issues. Changes in the number of deaths were less than 10% on the global level and for the majority of MDG regions.

Conclusions

The 2013 UN IGME estimates provide the most recent assessment of levels and trends in U5MR based on all available data and an improved estimation method that allows for closer-to-real-time monitoring of changes in the U5MR and takes account of data quality issues.     

Child Mortality Estimation: A Global Overview of Infant and Child Mortality Age Patterns in Light of New Empirical Data

Background

The under-five mortality rate (the probability of dying between birth and age 5 y, also denoted in the literature as U5MR and ₅ q ₀) is a key indicator of child health, but it conceals important information about how this mortality is distributed by age. One important distinction is what amount of the under-five mortality occurs below age 1 y (₁ q ₀) versus at age 1 y and above (₄ q ₁). However, in many country settings, this distinction is often difficult to establish because of various types of data errors. As a result, it is common practice to resort to model age patterns to estimate ₁ q ₀ and ₄ q ₁ on the basis of an observed value of ₅ q ₀. The most commonly used model age patterns for this purpose are the Coale and Demeny and the United Nations systems. Since the development of these models, many additional sources of data for under-five mortality have become available, making possible a general evaluation of age patterns of infant and child mortality. In this paper, we do a systematic comparison of empirical values of ₁ q ₀ and ₄ q ₁ against model age patterns, and discuss whether observed deviations are due to data errors, or whether they reflect true epidemiological patterns not addressed in existing model life tables.

Methods and Findings

We used vital registration data from the Human Mortality Database, sample survey data from the World Fertility Survey and Demographic and Health Surveys programs, and data from Demographic Surveillance Systems. For each of these data sources, we compared empirical combinations of ₁ q ₀ and ₄ q ₁ against combinations provided by Coale and Demeny and United Nations model age patterns. We found that, on the whole, empirical values fall relatively well within the range provided by these models, but we also found important exceptions. Sub-Saharan African countries have a tendency to exhibit high values of ₄ q ₁ relative to ₁ q ₀, a pattern that appears to arise for the most part from true epidemiological causes. While this pattern is well known in the case of western Africa, we observed that it is more widespread than commonly thought. We also found that the emergence of HIV/AIDS, while perhaps contributing to high relative values of ₄ q ₁, does not appear to have substantially modified preexisting patterns. We also identified a small number of countries scattered in different parts of the world that exhibit unusually low values of ₄ q ₁ relative to ₁ q ₀, a pattern that is not likely to arise merely from data errors. Finally, we illustrate that it is relatively common for populations to experience changes in age patterns of infant and child mortality as they experience a decline in mortality.

Conclusions

Existing models do not appear to cover the entire range of epidemiological situations and trajectories. Therefore, model life tables should be used with caution for estimating ₁ q ₀ and ₄ q ₁ on the basis of ₅ q ₀. Moreover, this model-based estimation procedure assumes that the input value of ₅ q ₀ is correct, which may not always be warranted, especially in the case of survey data. A systematic evaluation of data errors in sample surveys and their impact on age patterns of ₁ q ₀ and ₄ q ₁ is urgently needed, along with the development of model age patterns of under-five mortality that would cover a wider range of epidemiological situations and trajectories. Please see later in the article for the Editors'' Summary.     

Child Mortality Estimation: Appropriate Time Periods for Child Mortality Estimates from Full Birth Histories

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.     

Child Mortality Estimation: Methods Used to Adjust for Bias due to AIDS in Estimating 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.     

Child Mortality Estimation: Estimating Sex Differences in Childhood Mortality since the 1970s

Introduction

Producing estimates of infant (under age 1 y), child (age 1–4 y), and under-five (under age 5 y) mortality rates disaggregated by sex is complicated by problems with data quality and availability. Interpretation of sex differences requires nuanced analysis: girls have a biological advantage against many causes of death that may be eroded if they are disadvantaged in access to resources. Earlier studies found that girls in some regions were not experiencing the survival advantage expected at given levels of mortality. In this paper I generate new estimates of sex differences for the 1970s to the 2000s.

Methods and Findings

Simple fitting methods were applied to male-to-female ratios of infant and under-five mortality rates from vital registration, surveys, and censuses. The sex ratio estimates were used to disaggregate published series of both-sexes mortality rates that were based on a larger number of sources. In many developing countries, I found that sex ratios of mortality have changed in the same direction as historically occurred in developed countries, but typically had a lower degree of female advantage for a given level of mortality. Regional average sex ratios weighted by numbers of births were found to be highly influenced by China and India, the only countries where both infant mortality and overall under-five mortality were estimated to be higher for girls than for boys in the 2000s. For the less developed regions (comprising Africa, Asia excluding Japan, Latin America/Caribbean, and Oceania excluding Australia and New Zealand), on average, boys'' under-five mortality in the 2000s was about 2% higher than girls''. A number of countries were found to still experience higher mortality for girls than boys in the 1–4-y age group, with concentrations in southern Asia, northern Africa/western Asia, and western Africa. In the more developed regions (comprising Europe, northern America, Japan, Australia, and New Zealand), I found that the sex ratio of infant mortality peaked in the 1970s or 1980s and declined thereafter.

Conclusions

The methods developed here pinpoint regions and countries where sex differences in mortality merit closer examination to ensure that both sexes are sharing equally in access to health resources. Further study of the distribution of causes of death in different settings will aid the interpretation of differences in survival for boys and girls. Please see later in the article for the Editors'' Summary.     

Identifying and Targeting Mortality Disparities: A Framework for Sub-Saharan Africa Using Adult Mortality Data from South Africa

Background

Health inequities in developing countries are difficult to eradicate because of limited resources. The neglect of adult mortality in Sub-Saharan Africa (SSA) is a particular concern. Advances in data availability, software and analytic methods have created opportunities to address this challenge and tailor interventions to small areas. This study demonstrates how a generic framework can be applied to guide policy interventions to reduce adult mortality in high risk areas. The framework, therefore, incorporates the spatial clustering of adult mortality, estimates the impact of a range of determinants and quantifies the impact of their removal to ensure optimal returns on scarce resources.

Methods

Data from a national cross-sectional survey in 2007 were used to illustrate the use of the generic framework for SSA and elsewhere. Adult mortality proportions were analyzed at four administrative levels and spatial analyses were used to identify areas with significant excess mortality. An ecological approach was then used to assess the relationship between mortality “hotspots” and various determinants. Population attributable fractions were calculated to quantify the reduction in mortality as a result of targeted removal of high-impact determinants.

Results

Overall adult mortality rate was 145 per 10,000. Spatial disaggregation identified a highly non-random pattern and 67 significant high risk local municipalities were identified. The most prominent determinants of adult mortality included HIV antenatal sero-prevalence, low SES and lack of formal marital union status. The removal of the most attributable factors, based on local area prevalence, suggest that overall adult mortality could be potentially reduced by ∼90 deaths per 10,000.

Conclusions

The innovative use of secondary data and advanced epidemiological techniques can be combined in a generic framework to identify and map mortality to the lowest administration level. The identification of high risk mortality determinants allows health authorities to tailor interventions at local level. This approach can be replicated elsewhere.     

Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories

Background

Given the lack of complete vital registration data in most developing countries, for many countries it is not possible to accurately estimate under-five mortality rates from vital registration systems. Heavy reliance is often placed on direct and indirect methods for analyzing data collected from birth histories to estimate under-five mortality rates. Yet few systematic comparisons of these methods have been undertaken. This paper investigates whether analysts should use both direct and indirect estimates from full birth histories, and under what circumstances indirect estimates derived from summary birth histories should be used.

Methods and Findings

Usings Demographic and Health Surveys data from West Africa, East Africa, Latin America, and South/Southeast Asia, I quantify the differences between direct and indirect estimates of under-five mortality rates, analyze data quality issues, note the relative effects of these issues, and test whether these issues explain the observed differences. I find that indirect estimates are generally consistent with direct estimates, after adjustment for fertility change and birth transference, but don''t add substantial additional insight beyond direct estimates. However, choice of direct or indirect method was found to be important in terms of both the adjustment for data errors and the assumptions made about fertility.

Conclusions

Although adjusted indirect estimates are generally consistent with adjusted direct estimates, some notable inconsistencies were observed for countries that had experienced either a political or economic crisis or stalled health transition in their recent past. This result suggests that when a population has experienced a smooth mortality decline or only short periods of excess mortality, both adjusted methods perform equally well. However, the observed inconsistencies identified suggest that the indirect method is particularly prone to bias resulting from violations of its strong assumptions about recent mortality and fertility. Hence, indirect estimates of under-five mortality rates from summary birth histories should be used only for populations that have experienced either smooth mortality declines or only short periods of excess mortality in their recent past. Please see later in the article for the Editors'' Summary.     

Improving the Measurement of Maternal Mortality: The Sisterhood Method Revisited

Background

Over the past several decades the efforts to improve maternal survival and the consequent demand for accurate estimates of maternal mortality have increased. However, measuring maternal mortality remains a difficult task especially in developing countries with weak information systems. Sibling histories included in household surveys (most notably the Demographic and Health Surveys (DHS)) have emerged as an important source of maternal mortality data. Data have been mainly collected from women and have not been widely collected from men due to concerns about data quality. We assess data quality of histories obtained from men and the potential to improve the efficiency of surveys measuring maternal mortality by collecting such data.

Methods and Findings

We used data from 10 Demographic and Health Surveys (DHS) that have included a full sibling history in both their women’s and men’s questionnaires. We estimated adult and maternal mortality indicators from histories obtained from men and women. We assessed the completeness and accuracy of these histories using several indicators of data quality. Our study finds that mortality estimates based on sibling histories obtained from men do not systematically or significantly differ from those obtained from women. Quality indicators were similar when comparing data from men and women. Pooling data obtained from men and women produced narrower confidence intervals.

Conclusion

From experience across nine developing countries, sibling history data obtained from men appear to be a reliable source of information on adult and maternal mortality. Given that there are no significant differences between mortality estimates based on data obtained from men and women, data can be pooled to increase efficiency. This finding improves the feasibility for countries to generate robust empirical estimates of adult and maternal mortality from surveys. Further we recommend that male sibling histories be collected from all sample households rather than from a subsample.     

Location Matters: Trends in Inequalities in Child Mortality in Indonesia. Evidence from Repeated Cross-Sectional Surveys

Background

Considerable improvements in life expectancy and other human development indicators in Indonesia are thought to mask considerable disparities between populations in the country. We examine the existence and extent of these disparities by measuring trends and inequalities in the under-five mortality rate and neonatal mortality rate across wealth, education and geography.

Methodology

Using data from seven waves of the Indonesian Demographic and Health Surveys, direct estimates of under-five and neonatal mortality rates were generated for 1980–2011. Absolute and relative inequalities were measured by rate differences and ratios, and where possible, slope and relative indices of inequality. Disparities were assessed by levels of rural/urban location, island groups, maternal education and household wealth.

Findings

Declines in national rates of under-five and neonatal mortality have accorded with reductions of absolute inequalities in clusters stratified by wealth, maternal education and rural/urban location. Across these groups, relative inequalities have generally stabilised, with possible increases with respect to mortality across wealth subpopulations. Both relative and absolute inequalities in rates of under-five and neonatal mortality stratified by island divisions have widened.

Conclusion

Indonesia has made considerable gains in reducing under-five and neonatal mortality at a national level, with the largest reductions happening before the Asian financial crisis (1997–98) and decentralisation (2000). Hasty implementation of decentralisation reforms may have contributed to a slowdown in mortality rate reduction thereafter. Widening inequities between the most developed provinces of Java-Bali and those of other island groupings should be of particular concern for a country embarking on an ambitious plan for universal health coverage by 2019. A focus on addressing the key supply side barriers to accessing health care and on the social determinants of health in remote and disadvantaged regions will be essential for this plan to be realised.     

Strengths and Limitations of Period Estimation Methods for Circadian Data

A key step in the analysis of circadian data is to make an accurate estimate of the underlying period. There are many different techniques and algorithms for determining period, all with different assumptions and with differing levels of complexity. Choosing which algorithm, which implementation and which measures of accuracy to use can offer many pitfalls, especially for the non-expert. We have developed the BioDare system, an online service allowing data-sharing (including public dissemination), data-processing and analysis. Circadian experiments are the main focus of BioDare hence performing period analysis is a major feature of the system. Six methods have been incorporated into BioDare: Enright and Lomb-Scargle periodograms, FFT-NLLS, mFourfit, MESA and Spectrum Resampling. Here we review those six techniques, explain the principles behind each algorithm and evaluate their performance. In order to quantify the methods'' accuracy, we examine the algorithms against artificial mathematical test signals and model-generated mRNA data. Our re-implementation of each method in Java allows meaningful comparisons of the computational complexity and computing time associated with each algorithm. Finally, we provide guidelines on which algorithms are most appropriate for which data types, and recommendations on experimental design to extract optimal data for analysis.     

Child Mortality Estimation: A Comparison of UN IGME and IHME Estimates of Levels and Trends in Under-Five Mortality Rates and Deaths

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.     

Estimation in Semiparametric Transition Measurement Error Models for Longitudinal Data

Summary .  We consider semiparametric transition measurement error models for longitudinal data, where one of the covariates is measured with error in transition models, and no distributional assumption is made for the underlying unobserved covariate. An estimating equation approach based on the pseudo conditional score method is proposed. We show the resulting estimators of the regression coefficients are consistent and asymptotically normal. We also discuss the issue of efficiency loss. Simulation studies are conducted to examine the finite-sample performance of our estimators. The longitudinal AIDS Costs and Services Utilization Survey data are analyzed for illustration.     

A Framework for the Economic Analysis of Data Collection Methods for Vital Statistics

Background

Over recent years there has been a strong movement towards the improvement of vital statistics and other types of health data that inform evidence-based policies. Collecting such data is not cost free. To date there is no systematic framework to guide investment decisions on methods of data collection for vital statistics or health information in general. We developed a framework to systematically assess the comparative costs and outcomes/benefits of the various data methods for collecting vital statistics.

Methodology

The proposed framework is four-pronged and utilises two major economic approaches to systematically assess the available data collection methods: cost-effectiveness analysis and efficiency analysis. We built a stylised example of a hypothetical low-income country to perform a simulation exercise in order to illustrate an application of the framework.

Findings

Using simulated data, the results from the stylised example show that the rankings of the data collection methods are not affected by the use of either cost-effectiveness or efficiency analysis. However, the rankings are affected by how quantities are measured.

Conclusion

There have been several calls for global improvements in collecting useable data, including vital statistics, from health information systems to inform public health policies. Ours is the first study that proposes a systematic framework to assist countries undertake an economic evaluation of DCMs. Despite numerous challenges, we demonstrate that a systematic assessment of outputs and costs of DCMs is not only necessary, but also feasible. The proposed framework is general enough to be easily extended to other areas of health information.     

Improving the Quality of Adult Mortality Data Collected in Demographic Surveys: Validation Study of a New Siblings' Survival Questionnaire in Niakhar,Senegal

Background

In countries with limited vital registration, adult mortality is frequently estimated using siblings'' survival histories (SSHs) collected during Demographic and Health Surveys (DHS). These data are affected by reporting errors. We developed a new SSH questionnaire, the siblings'' survival calendar (SSC). It incorporates supplementary interviewing techniques to limit omissions of siblings and uses an event history calendar to improve reports of dates and ages. We hypothesized that the SSC would improve the quality of adult mortality data.

Methods and Findings

We conducted a retrospective validation study among the population of the Niakhar Health and Demographic Surveillance System in Senegal. We randomly assigned men and women aged 15–59 y to an interview with either the DHS questionnaire or the SSC. We compared SSHs collected in each group to prospective data on adult mortality collected in Niakhar. The SSC reduced respondents'' tendency to round reports of dates and ages to the nearest multiple of five or ten (“heaping”). The SSC also had higher sensitivity in recording adult female deaths: among respondents whose sister(s) had died at an adult age in the past 15 y, 89.6% reported an adult female death during SSC interviews versus 75.6% in DHS interviews (p = 0.027). The specificity of the SSC was similar to that of the DHS questionnaire, i.e., it did not increase the number of false reports of deaths. However, the SSC did not improve the reporting of adult deaths among the brothers of respondents. Study limitations include sample selectivity, limited external validity, and multiple testing.

Conclusions

The SSC has the potential to collect more accurate SSHs than the questionnaire used in DHS. Further research is needed to assess the effects of the SSC on estimates of adult mortality rates. Additional validation studies should be conducted in different social and epidemiological settings.

Trial Registration

Controlled-Trials.com ISRCTN06849961 Please see later in the article for the Editors'' Summary     

Using Health Extension Workers for Monitoring Child Mortality in Real-Time: Validation against Household Survey Data in Rural Ethiopia

Background

Ethiopia has scaled up its community-based programs over the past decade by training and deploying health extension workers (HEWs) in rural communities throughout the country. Consequently, child mortality has declined substantially, placing Ethiopia among the few countries that have achieved the United Nations’ fourth Millennium Development Goal. As Ethiopia continues its efforts, results must be assessed regularly to provide timely feedback for improvement and to generate further support for programs. More specifically the expansion of HEWs at the community level provides a unique opportunity to build a system for real-time monitoring of births and deaths, linked to a civil registration and vital statistics system that Ethiopia is also developing. We tested the accuracy and completeness of births and deaths reported by trained HEWs for monitoring child mortality over 15 -month periods.

Methods and Findings

HEWs were trained in 93 randomly selected rural kebeles in Jimma and West Hararghe zones of the Oromia region to report births and deaths over a 15-month period from January, 2012 to March, 2013. Completeness of number of births and deaths, age distribution of deaths, and accuracy of resulting under-five, infant, and neonatal mortality rates were assessed against data from a large household survey with full birth history from women aged 15–49. Although, in general HEWs, were able to accurately report events that they identified, the completeness of number of births and deaths reported over twelve-month periods was very low and variable across the two zones. Compared to household survey estimates, HEWs reported only about 30% of births and 21% of under-five deaths occurring in their communities over a twelve-month period. The under-five mortality rate was under-estimated by around 30%, infant mortality rate by 23% and neonatal mortality by 17%. HEWs reported disproportionately higher number of deaths among the very young infants than among the older children.

Conclusion

Birth and death data reported by HEWs are not complete enough to support the monitoring of changes in childhood mortality. HEWs can significantly contribute to the success of a CRVS in Ethiopia, but cannot be relied upon as the sole source for identification of vital events. Further studies are needed to understand how to increase the level of completeness.     

Motivation Matters: Lessons for REDD+ Participatory Measurement,Reporting and Verification from Three Decades of Child Health Participatory Monitoring in Indonesia

Participatory Measurement, Reporting and Verification (PMRV), in the context of reducing emissions from deforestation and forest degradation with its co-benefits (REDD+) requires sustained monitoring and reporting by community members. This requirement appears challenging and has yet to be achieved. Other successful, long established, community self-monitoring and reporting systems may provide valuable lessons. The Indonesian integrated village healthcare program (Posyandu) was initiated in the 1980s and still provides effective and successful participatory measurement and reporting of child health status across the diverse, and often remote, communities of Indonesia. Posyandu activities focus on the growth and development of children under the age of five by recording their height and weight and reporting these monthly to the Ministry of Health. Here we focus on the local Posyandu personnel (kaders) and their motivations and incentives for contributing. While Posyandu and REDD+ measurement and reporting activities differ, there are sufficient commonalities to draw useful lessons. We find that the Posyandu kaders are motivated by their interests in health care, by their belief that it benefits the community, and by encouragement by local leaders. Recognition from the community, status within the system, training opportunities, competition among communities, and small payments provide incentives to sustain participation. We examine these lessons in the context of REDD+.     

Expert Opinions on Improving Femicide Data Collection across Europe: A Concept Mapping Study

Femicide, defined as the killings of females by males because they are females, is becoming recognized worldwide as an important ongoing manifestation of gender inequality. Despite its high prevalence or widespread prevalence, only a few countries have specific registries about this issue. This study aims to assemble expert opinion regarding the strategies which might feasibly be employed to promote, develop and implement an integrated and differentiated femicide data collection system in Europe at both the national and international levels. Concept mapping methodology was followed, involving 28 experts from 16 countries in generating strategies, sorting and rating them with respect to relevance and feasibility. The experts involved were all members of the EU-Cost-Action on femicide, which is a scientific network of experts on femicide and violence against women across Europe. As a result, a conceptual map emerged, consisting of 69 strategies organized in 10 clusters, which fit into two domains: “Political action” and “Technical steps”. There was consensus among participants regarding the high relevance of strategies to institutionalize national databases and raise public awareness through different stakeholders, while strategies to promote media involvement were identified as the most feasible. Differences in perceived priorities according to the level of human development index of the experts’ countries were also observed.