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Introduction The 2030 Sustainable Development Agenda and the United Nations Convention on the Rights of Persons with Disabilities (CRPD) aspire to leave no one behind and call for the inclusion of persons with disabilities in all spheres of life. To monitor this goal of inclusion, CRPD's Article 31 requires state parties to collect data about the situation of persons with disabilities. The Disability Statistics -- Questionnaire Review Database (DS-QR Database) reports on whether population and housing censuses and household surveys include internationally recommended disability questions for adults ages 15 and older. Methods The Disability Data Initiative (DDI), an international consortium of researchers, regularly retrieves and analyses a list of surveys and censuses from international catalogs, libraries and websites of national statistics offices. Questionnaires are reviewed to identify if they include internationally recommended questions on functional difficulties (e.g. difficulty seeing), more specifically (i) the Washington Group Short Set (WG-SS) or (ii) questions that meet at least the United Nations 2017 guidelines for disability measurement in censuses (other functional difficulty questions thereafter). Results The DS-QR Database includes the review results for the questionnaires of 3027 population censuses and surveys from 199 countries and territories collected from 2009 to 2023. The review has information on whether each dataset has the WG-SS or other functional difficulty questions and overall results per country, region, type of dataset and over time. Conclusion By identifying countries that collect internationally comparable disability data, the DS-QR Database can help researchers, policymakers and advocates determine whether countries fulfill their obligations as per CRPD Article 31. It can also assist in identifying which datasets use functional difficulty questions and can be used to research and monitor disability rights over time and across countries. The DS-QR Database is in a Supplementary file and will be accessible on a website upon publication of this article.

Abstract Background High levels of maternal morbidity and mortality persist in low- and middle-income countries, despite increases in coverage of facility delivery and skilled assistance at delivery. We compared levels of facility birth to a summary delivery care measure and quantified gaps. Methods We approximated a delivery care score from type of delivery (home, lower-level facility, or hospital), skilled attendant at delivery, a stay of 24-or-more-hours after delivery, and a health check within 48-h after delivery. Data were obtained from 333,316 women aged 15–49 who had a live birth in the previous 2 years, and from 71 countries with nationally representative surveys between 2013 and 2020. We computed facility delivery and delivery care coverage estimates to assess the gap. We stratified the analysis by country characteristics, including the national maternal mortality ratio (MMR), to assess the size of coverage gaps, and we assessed missed opportunities through coverage cascades. We looked at the association between MMR and delivery care coverage. Results Delivery care coverage varied by country, ranging from 24% in Sudan to 100% in Cuba. Median coverage was 70% with an interquartile range of 30 percentage points (55% and 85%). The cascade showed that while 76% of women delivered in a facility, only 41% received all four interventions. Coverage gaps exist across all MMR levels. Gaps between highest and lowest wealth quintiles were greatest in countries with MMR levels of 100 or higher, and the gap narrowed in countries with MMR levels below 100. The delivery care indicator had a negative association with MMR. Conclusions In addition to providing high-quality evidenced-based care to women during birth and the postpartum period, there is also a need to address gaps in delivery care, which occur within and between countries, wealth quintiles, and MMR phases.

Summary: Background: Within Laos, the vaccination coverage rates with the monovalent hepatitis B birth dose vaccine and hepatitis B antigen-containing combination vaccines remain stagnant with 75% and 64%, respectively, in 2021. In this study, we used data from the Multiple Indicator Cluster Surveys to identify possible factors that represent barriers for receiving these childhood vaccinations. Methods: Data from the Multiple Indicator Cluster Surveys in 2011/12 and 2017 were analysed to examine factors associated with receiving the hepatitis B-containing vaccines using regression modelling. Data analyses were conducted in R. Findings: In 2011/12, the weight-adjusted coverage rate for receiving the hepatitis B birth dose was 48%, while the coverage with the hepatitis B antigen-containing combination vaccine was 55.1% based on both vaccination documents and recall; compared to 69.3% and 59.4% respectively in 2017. Ethno-linguistic group, maternal education, healthcare utilization and wealth were associated with receiving the vaccinations against hepatitis B. Interpretation: National estimates of vaccination coverage rates can conceal country-specific regional or socio-economic variations. Children from Hmong-Mien households, from less wealthier households and whose mothers were less educated and were not able to or did not utilize healthcare were identified as being less likely to receive the vaccinations. These findings indicate the need for improving access to healthcare, in particular for minority groups. Funding: This work was supported by the Ministry of Foreign and European Affairs, Luxembourg and the Luxembourg Institute of Health (project “Luxembourg–Laos Partnership for Research and Capacity Building in Infectious Disease Surveillance”).

Household energy is critical for sustainable development, but many rural and off-grid communities lack access. As global concerns about climate change prompt a re-evaluation of energy strategies, understanding rural household energy decisions becomes increasingly complex, particularly in remote areas without grid access. This study examines the energy decisions of households in the Upper Blinkwater community to uncover the primary drivers for their choice of energy amidst grid connections. Survey data from 53 households were analyzed using multivariate regression. The findings revealed significant economic vulnerability among the respondents, marked by high unemployment and limited resource access, with the majority of households relying on social grants. These households depend on multiple energy sources, with firewood usage significantly influenced by the availability of grants, total income, post-primary education, household size, and remittance income. The findings contradict the energy ladder hypothesis, indicating that despite economic improvements, a complete transition to modern fuels may not be possible as firewood remains a crucial energy source. These results highlight the complex interplay of economic, social, and cultural factors in household energy decisions and underscore the importance of enhancing infrastructure, providing economic incentives, and conducting educational campaigns to facilitate the transition to cleaner energy alternatives.

Abstract Background The timely and accurate identification of food insecurity situations represents a challenging issue. Household surveys are routinely used in low-income countries and are an essential tool for obtaining key food security indicators that are used by decision makers to determine the targets of food security interventions. Methodology This paper investigates the spatial and temporal quality of the food security indicators obtained through household surveys. The empirical case of Burkina Faso is used in this paper, where a large-scale rural household survey has been conducted yearly since 2009. From this data set, three food security indicators (the Food Consumption Score, the Household Dietary Diversity Score and the Coping Strategies Index) are calculated at the regional level for each year during the 2009–2017 period. Results Results highlight that observed spatiotemporal variations in these indicators are consistent with the major regional food shocks reported in food warning system reports and are significantly correlated with variations computed from other sources of data, such as satellite images, rainfall and food prices. Conclusion These results raise new research questions on food security monitoring systems and on the use of heterogeneous data and multiple food security indicators.

ABSTRACTData availability plays a crucial role in the fight against poverty. Yet, it lags behind the data available on most other economic phenomena. This paper catalogs and reviews existing data availability for low- and middle-income countries with a view to break the cycle of outdated poverty data and strengthen statistical systems – while drawing readers’ attention to existing information and experiences. Countries that generate and analyze frequent and accurate poverty data are identified to show what is possible and to better document what is already available. Results show that data for both monetary and multidimensional poverty dramatically increased since 1980. Sixty countries already produce annual updates to key statistics, and some have continuous household surveys with cost-cutting synergies. International agencies have explored short surveys for comparable data but the success and uptake of these have not followed expected patterns. Certain regions have agreed on harmonized variable definitions across countries, and new technologies reduce lags between data collection and analysis. These existing resources and experiences can inform much-needed efforts to expand data availability.

IntroductionImproving maternal health and survival remains a public health priority for Sudan. Significant investments were made to expand access to maternal health services, such as through the training and deployment of providers with varying skills and competencies to work across the country. This study investigates trends in the coverage of different birth attendants and their relationship with the maternal mortality ratio (MMR).MethodsTrend analyses were conducted using data from the 2006, 2010, and 2014 Sudan Household surveys. Three categories of birth attendants were identified: (1) skilled birth attendants (SBA) such as doctors, nurse-midwives, and health visitors, (2) locally certified midwives, and (3) traditional birth attendants (TBA). Multivariable logistic regression models were used to examine trends in SBAs (vs. locally certified midwives and TBAs), locally certified midwives (vs SBAs and TBAs), and SBAs and locally certified midwives by place of birth (health facility and home). The analyses were adjusted for potential confounders. An ecological analysis was conducted to assess the relationship between birth attendants by place of birth and MMR at the state level.ResultsBirths by 15,848 women were analysed. Locally certified midwives attended most births in each survey year, with their contribution increasing from 36.3% in 2006 to 55.5% in 2014. The contributions of SBAs and TBAs decreased over the same period. In 2014 compared with 2006, births were more likely to be attended by a locally certified midwife (aOR: 2.19; 95%CI: 1.82–2.63) but less likely to be attended by a SBA (aOR: 0.46; 95%CI: 0.37–0.56). The decrease in SBA was more substantial for births taking place at home (aOR: 0.17; 95%CI: 0.12–0.23) than for health facility births (aOR: 0.45; 95%CI: 0.31–0.65). In the ecological analysis 2014–2016, the proportion of births attended by SBA in health facilities correlated negatively with MMR at state level (rho −0.55; p: 0.02).ConclusionThis analysis suggests that although an improved coverage of maternal health with locally certified midwives has been observed, it has not provided the skill level reached by SBA. SBAs working in facility settings were a key correlating factor to reduced maternal mortality. Urgent action is needed to improve access to SBAs in health facilities, thereby accelerating progress in reducing maternal mortality.

Abstract Background Much applied research on the consequences of conflicts for health suffers from data limitations, particularly the absence of longitudinal data spanning pre-, during- and post-conflict periods for affected individuals. Such limitations often hinder reliable measurement of the causal effects of conflict and their pathways, hampering also the design of effective post-conflict health policies. Researchers have sought to overcome these data limitations by conducting ex-post surveys, asking participants to recall their health and living standards before (or during) conflict. These questions may introduce important analytical biases due to recall error and misreporting. Methods We investigate how to implement ex-post health surveys that collect recall data, for conflict-affected populations, which is reliable for empirical analysis via standard quantitative methods. We propose two complementary strategies based on methods developed in the psychology and psychometric literatures—the Flashbulb and test-retest approaches—to identify and address recall bias in ex-post health survey data. We apply these strategies to the case study of a large-scale health survey which we implemented in Colombia in the post-peace agreement period, but that included recall questions referring to the conflict period. Results We demonstrate how adapted versions of the Flashbulb and test-retest strategies can be used to test for recall bias in (post-)conflict survey responses. We also show how these test strategies can be incorporated into post-conflict health surveys in their design phase, accompanied by further ex-ante mitigation strategies for recall bias, to increase the reliability of survey data analysis—including by identifying the survey modules, and sub-populations, for which empirical analysis is likely to yield more reliable causal inference about the health consequences of conflict. Conclusions Our study makes a novel contribution to the field of applied health research in humanitarian settings, by providing practical methodological guidance for the implementation of data collection efforts in humanitarian contexts where recall information, collected from primary surveys, is required to allow assessments of changes in health and wellbeing. Key lessons include the importance of embedding appropriate strategies to test and address recall bias into the design of any relevant data collection tools in post-conflict or humanitarian contexts.

Abstract Background Coverage with the third dose of diphtheria-pertussis-tetanus-containing vaccine (DPT3) is a widely used measure of the performance of routine immunization systems. Since 2015, data reported by Ethiopia’s health facilities have suggested DPT3 coverage to be greater than 95%. Yet, Demographic and Health Surveys in 2016 and 2019 found DPT3 coverage to be 53 and 61% respectively for years during this period. This case study reviews the last 20 years of administrative (based on facility data), survey and United Nations (UN) estimates of Ethiopia’s nationwide immunization coverage to document long-standing discrepancies in these statistics. Methods Published estimates were compiled of Ethiopia’s nationwide DPT3 coverage from 1999 to 2018. These estimates come from the Joint Reporting Form submitted annually to WHO and UNICEF, a series of 8 population-based surveys and the annual reports of the WHO/UNICEF Estimates of National Immunization Coverage (WUENIC). Possible reasons for variation in survey findings were explored through secondary analysis of data from the 2012 immunization coverage survey. In addition, selected health officials involved with management of the immunization program were interviewed to obtain their perspectives on the reliability of various methods for estimation of immunization coverage. Findings Comparison of Ethiopia’s estimates for the same year from different sources shows major and persistent discrepancies between administrative, survey and WUENIC estimates. Moreover, the estimates from each of these sources have repeatedly shown erratic year-to-year fluctuations. Those who were interviewed expressed scepticism of Demographic and Health Survey (DHS) statistics. Officials of the national immunization programme have repeatedly shown a tendency to overlook all survey statistics when reporting on programme performance. Conclusions The present case study raises important questions, not only about the estimation methods of national and UN agencies, but about the reliability and comparability of widely trusted coverage surveys. Ethiopia provides an important example of a country where no data source provides a truly robust “gold standard” for estimation of immunization coverage. It is essential to identify and address the reasons for these discrepancies and arrive at a consensus on how to improve the reliability and acceptability of each data source and how best to “triangulate” between them.

Though societal acceptance of same-sex unions has grown, resulting in more inclusive government programs and policies and expanded legal protections, analysts remain uncertain about how to identify and enumerate same-sex households. Presently, the counts available of same-sex households in the United States oftentimes disagree. We show that the origins of these conflicting counts can be traced back to definitional and measurement issues in household surveys. In this study, we demonstrate how counts of same-sex households conflict, mislead, and undermine the goal of accurately representing the population of households with same-sex couples. By providing alternative approaches to counting household with same-sex couples we highlight the challenges in enumerating these households. We draw upon three federal household surveys to demonstrate the inconsistencies in the counts of same-sex households and to illustrate our methods. We argue that our proposed methods lead to more comprehensive and credible counts of households containing same-sex couples.

Abstract Background Electronic data collection is increasingly used for household surveys, but factors influencing design and implementation have not been widely studied. The Every Newborn-INDEPTH (EN-INDEPTH) study was a multi-site survey using electronic data collection in five INDEPTH health and demographic surveillance system sites. Methods We described experiences and learning involved in the design and implementation of the EN-INDEPTH survey, and undertook six focus group discussions with field and research team to explore their experiences. Thematic analyses were conducted in NVivo12 using an iterative process guided by a priori themes. Results Five steps of the process of selecting, adapting and implementing electronic data collection in the EN-INDEPTH study are described. Firstly, we reviewed possible electronic data collection platforms, and selected the World Bank’s Survey Solutions® as the most suited for the EN-INDEPTH study. Secondly, the survey questionnaire was coded and translated into local languages, and further context-specific adaptations were made. Thirdly, data collectors were selected and trained using standardised manual. Training varied between 4.5 and 10 days. Fourthly, instruments were piloted in the field and the questionnaires finalised. During data collection, data collectors appreciated the built-in skip patterns and error messages. Internet connection unreliability was a challenge, especially for data synchronisation. For the fifth and final step, data management and analyses, it was considered that data quality was higher and less time was spent on data cleaning. The possibility to use paradata to analyse survey timing and corrections was valued. Synchronisation and data transfer should be given special consideration. Conclusion We synthesised experiences using electronic data collection in a multi-site household survey, including perceived advantages and challenges. Our recommendations for others considering electronic data collection include ensuring adaptations of tools to local context, piloting/refining the questionnaire in one site first, buying power banks to mitigate against power interruption and paying attention to issues such as GPS tracking and synchronisation, particularly in settings with poor internet connectivity.

Abstract Background Data collection is the most critical stage in any population health study and correctly implementing fieldwork enhances the quality of collected information. However, even the most carefully planned large-scale household surveys can encounter many context-specific issues. This paper reflected on our research team’s recent experience conducting surveys for a quasi-experimental evaluation of a reproductive health program in urban areas of Karachi, Pakistan. We aim to describe the issues encountered and lessons learned from this process, and present some potential solutions for conducting future household surveys in similar urban environments. Methods The study followed a three-stage random sampling design. Initially, a Geographical Information System (GIS) was used to construct the sampling frame with union council (UC) area mapping and cluster demarcation followed by random selection of clusters in the selected UCs within the intervention and control sites. The second stage involved a complete household listing in selected clusters and the final stage was a random sampling of households with eligible women. Result This paper describes the issues that were encountered including technical problems related to GIS demarcation of cluster boundaries and hand-held devices for computer assisted personal interviews (CAPI), household listing, interviewing respondents on sensitive topics and their expectations, and ensuring privacy during the survey. Conclusion This study identifies a number of unique barriers to conducting household surveys in Karachi and highlights some key lessons for survey research in urban settlements. GIS mapping technology is a cost-effective method for developing sampling frames in resource-constrained settings. Secondly, the strategy of interviewing women immediately after the cluster is listed may be applied to make it easier to re-locate selected respondents and to reduce loss-to-follow up. Understanding local norms and developing culturally appropriate strategies to build trust with communities may significantly improve survey participation. Researchers should hire experienced female enumerators and provide continuous training on best practices for interviewing women on sensitive reproductive health topics in urban communities.

Conservation translocations have traditionally focused on ecological aspects while overlooking or underestimating the importance of human dimensions. Here, we present a feasibility analysis for a conservation translocation that up front took a holistic approach by investigating both ecological and socio-economic suitability of reinforcing mountain bongo in Eburu National Forest, Kenya. From 2018 to 2019, we set up 50 cameras to detect mountain bongo and searched for secondary signs in a grid overlaying Eburu. We also conducted surveys with 200 households surrounding the forest and interviewed 300 students to understand local perceptions of and interactions with Eburu Forest and their desire for a mountain bongo translocation. We used data from camera trapping and secondary signs in a MaxEnt model to determine the amount and location of available habitat for a bongo conservation translocation. Camera traps recorded only five bongo events in the 2-year study, and MaxEnt models revealed that these antelopes were relegated to less than 2.5 km of available habitat. Socio-economic surveys indicated local support for the conservation of bongo and their habitat, and yet our camera traps uncovered threatening illicit activities that could jeopardize both bongo survival and any attempt at boosting the remnant population with captive-bred individuals. We report how we built on long-term community and stakeholder engagement to mitigate these threats and provide concrete recommendations for how to proceed with a conservation translocation in terms of both the biological aspects and continued efforts to integrate socio-economic needs and community engagement.

Access to safe, effective, affordable, and acceptable contraceptive methods of choice is a basic right for displaced people. Yet displaced people are typically invisible in national sample surveys on population health, and quantitative evidence on their reproductive health outcomes is limited. This study focuses on the case of Iraq, a country with widespread displacement and where contraceptive use is a government policy priority. Using displacement screening questions in the Iraq 2018 Multiple Indicator Cluster Survey questionnaires, I construct two displacement-related indicators based on reason for last move and previous household residence. Descriptive statistics and binary logistic regression are used to test associations between modern contraceptive use and displacement, demographic, and socioeconomic factors. Controlling for the variables in the models, factors significantly associated with modern contraceptive use among married women aged 15–49 in Iraq are Federal Iraq region (reference Kurdish Region of Iraq, OR 1.78), upper secondary and primary education (reference pre-primary or no education, OR 1.50 and 1.20, respectively), parity, age, and exposure to television. The association between displacement (reason for last move) and modern contraceptive use significantly depends on a woman's level of education and whether they live in an urban or rural area. Women who previously lived in a camp are almost half as likely to use modern contraception compared to other previous residence types. This paper highlights the methodological potential and substantive value of using national household surveys to analyse reproductive health outcomes through a displacement lens. It also critically examines the limitations of these data and measures, drawing on total survey error and feminist theory.

It is often claimed that cocoa producers are poor, but the extent of their poverty is rarely defined. We analyzed six data sets derived from household questionnaires of 385–88,896 cocoa producers in Côte d'Ivoire and Ghana. Across all data sets, many households (30–58%) earn a gross income below the World Bank extreme poverty line and the majority (73–90%) do not earn a Living Income. Households with less income per person per day generally achieve lower cocoa yields, consist of more household members, have a smaller land size available, and rely more on cocoa income than households with higher incomes. When comparing the effects of increasing prices and yields on gross income, yield increases lead to larger benefits especially for the poorest households. Doubling the cocoa price would leave 15–25% of households with a gross income below the extreme poverty line and 53–65% below the Living Income benchmark. At yields of 600 kg/ha, against current yields around 300 kg/ha, these percentages are reduced to 7–11 and 48–62%, respectively, while at yields of 1,500 kg/ha only 1–2% of households remain below the extreme poverty line and 13–20% below the Living Income benchmark. If we assume that the production costs of achieving a yield of 1,500 kg/ha are 30% of revenue, still only 2–4% of households earn a net income below the extreme poverty line and 25–32% below the Living Income benchmark. Whilst sustainable intensification of cocoa production is undoubtedly a strong approach to increase cocoa yields and farmer incomes, achieving this does not come without pitfalls. The poorer households face multiple barriers to invest in cocoa production. A better understanding of cocoa producing households and the resources available to them, as well as the opportunity for alternative income generation, is required to tailor options to increase their income. The utility and interpretability of future household surveys would be drastically improved if definitions and variables addressed were approached in a standardized way.

Abstract Background Demographic and Health Survey (DHS) data are an important source of maternal, newborn, and child health as well as nutrition information for low- and middle-income countries. However, DHSs are often unavailable at the administrative unit that is most interesting or useful for program planning. In addition, the location of DHS survey clusters are geomasked within 10 km, and prior to 2009, may have crossed district boundaries. We aim to use DHS surveyed information with these geomasked coordinates to estimate district assignments for use in health program planning and evaluation. Methods We developed three methods to assign a district to a geomasked survey cluster in two DHS surveys from Malawi: 2000 and 2004. Method A assigns districts of origin in proportion to the likelihood that results from repeated simulated geomasking, allowing more than one possible district of origin. Method B assigns a single district of origin which contains the greatest proportion of simulated geomasked survey clusters. Method C maps the geomasked survey cluster’s location to a district polygon. We used these method assignments to estimate a selection of commonly used coverage indicators for each district. We compared the district coverage estimates, confidence intervals, and concordance correlation coefficients, by each of the methods, to those which used validated district assignments in 2004, and we looked at coverage change from 2000 to 2004. Results The methods we tested each approximated the validated estimates in 2004 by confidence interval comparison and concordance correlation coefficient. Estimated agreement for method A was between .14 and .98, for method B the estimated agreement was between .97 and .99, and for method C the agreement ranged from .93 to .99 when compared with the validated district assignments. Therefore, we recommend the protocol which is the simplest to implement—method C—overlaying geomasked survey cluster within district polygon. Conclusions Using geomasked survey clusters from DHSs to assign districts provided district level coverage rates similar to those using the validated surveyed locations. This method may be applied to data sources where survey cluster centroids are available and where district level estimates are needed for program implementation and evaluation in low- and middle-income settings. This method is of special interest to those using DHSs to study spatiotemporal trends as it allows for the utilization of historic DHS data where geomasking hinders the generation of reliable subnational estimates of health in areas smaller than the first-order administrative unit (ADM1).

Missing-data is a problem that occurs frequently in survey data. Missing-data can result in bias and reduced efficiency for regression estimates. The objective of the current study is to analyze the impact of missing-data imputation, using multiple imputation methods, on regression estimates for survey data. The results of the current study show that multiple imputation methods result in lower standard errors for regression estimates than the regression using only complete observations. Multiple imputation methods also resulted in chances in magnitude, sign, and statistical significance for some the regression coefficient estimates. Hence, ignoring the missing-data problem might lead to significant differences in the results for regression analysis and the policy recommendations based on these results.

This work introduces a relatively new procedure for integrating social survey data through combined use of machine learning techniques and well-known statistical matching methods. The integration is performed with the scope of studying the relationship between variables not jointly observed in the same survey. The results of the new matching procedure seem promising since they are better than those provided by traditional matching methods.

Background: The spread of SARS-CoV-2 in Sub-Saharan Africa is poorly understood and to date has generally been characterised by a lower number of declared cases and deaths as compared to other regions of the world. Paucity of reliable information, with insights largely derived from limited RT-PCR testing in high-risk and urban populations, has been one of the biggest barriers to understanding the course of the pandemic and informed policy-making. Here we estimate seroprevalence of anti-SARS-CoV-2 antibodies in Ethiopia during the first wave of the pandemic. Methods: We undertook a population-based household seroprevalence serosurvey based on 1856 participants in Ethiopia, in the capital city Addis Ababa, and in Jimma, a middle-sized town in the Oromia region, and its rural surroundings (districts of Seka and Mana), between 22 July and 02 September 2020. We tested one random participant per household for anti-SARS-CoV-2 antibodies using a high specificity rapid diagnostic tests (RDTs) and evaluated population seroprevalence using a Bayesian logistic regression model taking into account test performance as well as age and sex of the participants. Findings: In total, 2304 random households were visited, with 1856 individuals consenting to participate. This produced a sample of 956 participants in Addis Ababa and 900 participants in Jimma. IgG prevalence was estimated at 1.9% (95% CI 0.4–3.7%), and combined IgM/IgG prevalence at 3.5% (95% CI 1.7–5.4%) for Addis Ababa in early August 2020, with higher prevalence in central sub-cities. Prevalence in Jimma town was lower at 0.5% (95% CI 0–1.8%) for IgG and 1.6% (95%CI 0–4.1%) for IgM/IgG, while in rural Jimma IgG prevalence was 0.2% and IgM/IgG 0.4% in early September. Interpretation: More than four months after the first cases were detected in Ethiopia, Addis Ababa displayed a prevalence under 5% and likely as low as 2%, while rural Jimma displayed a prevalence of 0.2%. A 2% seroprevalence figure for the capital translated to a number of cases at least five times larger than those reported for the country as a whole. At the same time, it contrasts with significantly higher seroprevalence figures in large cities in Europe and America only two to three months after the first cases. This population-based seroepidemiological study thus provides evidence of a slower spread of SARS-CoV-2 in the Ethiopian population during the first wave of the pandemic and does not appear to support the notion that lower case numbers were simply a reflection of limited testing and surveillance. Funding: Schmidt Family Foundation, Joachim Hertz Foundation, Nespresso, Peet's and Smuckers.

AimThis study aimed to investigate the household medication-taking behavior and affordability of patients with chronic diseases in Gansu Province. As well as to propose suggestions to assist improvement of related policies.MethodsA multistage stratified cluster sampling technique was used to select the research sites and households according to the WHO manual for the “Household Survey to Measure Access and Use of Medicines”. The impact factors of medication-taking behavior were estimated using binary logistic regression models. Medication treatment affordability of hypertension patients was evaluated.ResultsA total of 1,080 completed questionnaires were collected, in which 690 families reported to have chronic patients in their home. The total number of chronic disease patients were 915. About 93% of the patient reported scheduled medicine intake. Approximately 86.60% of patients with chronic medical conditions were able to adhere to the physicians’ prescriptions. Age, gender, and the number of household chronic disease patients were the main factors influencing whether the patients take medication. Respondents’ self-reported monthly expenditure on household medicine accounted for 16.95% of their total monthly expenditure. The total cost of irbesartan and valsartan for hypertension treatment was two-fold higher than the minimum daily wage of the families.ConclusionThis study found that patients with chronic diseases have a high proportion of medication and medication compliance. However, family drug burden, especially for those living with hypertension are among the key challenges. Related policy needs to be revised to promote the affordability of medication under chronic conditions.

The spread of the novel coronavirus, SARS-CoV-2, poses major challenges for individuals and societies at large. The question now is how individuals and society are dealing with these challenges, and what health, psychological, social, and economic effects they will have to bear. Meaningful answers can only be provided using a generalizable database that contains contextual information such as family characteristics and offers a life-course perspective. We argue that these criteria are best met by household panel survey data. In this paper, we illustrate the importance of such data and show how they can aid in explaining the current and future effects of the pandemic on individuals, households, and society. Furthermore, we describe the survey design of SOEP-CoV, a supplementary telephone survey to the German Socio-Economic Panel (SOEP) study.

Abstract Background Antenatal care (ANC) is a means to identify high-risk pregnancies and educate women so that they might experience a healthier delivery and outcome. There is a lack of evidence about whether receipt of ANC is an effective strategy for keeping women in the system so they partake in other maternal and child interventions, particularly for poor women. The present analysis examines whether ANC uptake is associated with other maternal and child health behaviors in poor mothers in Guatemala, Honduras, Nicaragua, and Mexico (Chiapas). Methods We conducted a cross-sectional survey of women regarding their uptake of ANC for their most recent delivery in the last two years and their uptake of selected services and healthy behaviors along a continuity of maternal and child healthcare. We conducted logistic regressions on a sample of 4844 births, controlling for demographic, household, and maternal characteristics to understand the relationship between uptake of ANC and later participation in the continuum of care. Results Uptake of four ANC visits varied by country from 17.0% uptake in Guatemala to 81.4% in Nicaragua. In all countries but Nicaragua, ANC was significantly associated with in-facility delivery (IFD) (Guatemala odds ratio [OR] = 5.28 [95% confidence interval [CI] 3.62–7.69]; Mexico OR = 5.00 [95% CI: 3.41–7.32]; Honduras OR = 2.60 [95% CI: 1.42–4.78]) and postnatal care (Guatemala OR = 4.82 [95% CI: 3.21–7.23]; Mexico OR = 4.02 [95% CI: 2.77–5.82]; Honduras OR = 2.14 [95% CI: 1.26–3.64]), but did not appear to have any positive relationship with exclusive breastfeeding habits or family planning methods, which may be more strongly determined by cultural influences. Conclusions Our results demonstrate that uptake of the WHO-recommended four ANC visits has limited effectiveness on uptake of services in some poor populations in Mesoamérica. Our study highlights the need for continued and varied efforts in these populations to increase both the uptake and the effectiveness of ANC in encouraging positive and lasting effects on women’s uptake of health care services.

Climate-smart agriculture (CSA) is agriculture that increases productivity, improves resilience, and mitigates climate change. Smallholder adoption of farming technology is necessary to speed the transition to CSA. Here, we assessed the determinants of adoption of five technologies that can help achieve some of the CSA outcomes in smallholder farms in Tanzania. They included crop and livestock diversity, irrigation, application of chemical fertilizers, and agroforestry. Using data collected from 821 farming households, a multivariate probit model was employed to evaluate the determinants of adoption, allowing for examination of synergies and trade-offs between the technologies. Application of chemical fertilizers was fairly well adopted (34% of farmers), while irrigation was least adopted (26%). Some technologies, including crop diversity and irrigation as well as application of chemical fertilizer and agro-forestry, complemented each other. Trade-offs were observed between livestock diversity and irrigation. Female control of farm resources, farm location, and household resources were major determinants of adoption. We, therefore, recommend strategies that seeks to enhance building household resource as pathway for improved adoption of new technologies.

This paper provides recommendations on how large-scale household surveys should be conducted to generate the data needed to train models for satellite-based crop type mapping in smallholder farming systems. The analysis focuses on maize cultivation in Malawi and Ethiopia, and leverages rich, georeferenced plot-level data from national household surveys that were conducted in 2018–20 and integrated with Sentinel-2 satellite imagery and complementary geospatial data. To identify the approach to survey data collection that yields optimal data for training remote sensing models, 26,250 in silico experiments are simulated within a machine learning framework. The best model is then applied to map seasonal maize cultivation from 2016 to 2019 at 10-m resolution in both countries. The analysis reveals that smallholder plots with maize cultivation can be identified with up to 75% accuracy. Collecting full plot boundaries or complete plot corner points provides the best quality of information for model training. Classification performance peaks with slightly less than 60% of the training data. Seemingly little erosion in accuracy under less preferable approaches to georeferencing plots results in the total area under maize cultivation being overestimated by 0.16–0.47 million hectares (8–24%) in Malawi.

The present study aimed to examine the nutritional deprivation of Paraguayan households (measured as households' access to diverse diets) and investigate the association between nutritional deprivation and socio-economic characteristics in a large sample. An extension of Alkire–Foster methodology, a technique widely employed in multidimensional poverty measurement, was used to calculate both the incidence and intensity of nutritional deprivation. The resulting Nutritional Deprivation Index allows us to consider minimum food group requirements that vary by food groups as well as by individual characteristics such as age, sex and activity level. Applying the methodology to a nationally representative sample of households from the 2011–2012 Income and Expenditures Household Survey, the study found that about two in every three Paraguayan households (67 %) were inadequately nourished in at least four (of the total of six) food groups. Although no significant differences were found between rural and urban households, the incidence of multi-dimensionally deprived households generally decreased as income increased. Logistic regression results showed that nutritional deprivation decreased as household income and mother's education increased and increased with household size. Our study concludes that the majority of Paraguayan households is significantly nutritionally deprived across most food groups and suggests that strategies are needed to improve their access to diverse diets, especially among its lower- and middle-income segments.

Abstract Background Diarrhea remains a high burden disease, responsible for nine percent of deaths in children under five globally. We analyzed diarrhea management practices in young children and their association with the source of care. Methods We used Demographic and Health Survey data from 12 countries in sub-Saharan Africa with high burdens of childhood diarrhea. We classified the quality of diarrhea management practices as good, fair, or poor based on mothers’ reports for children with diarrhea, using WHO/UNICEF recommendations for appropriate treatment. We described the prevalence of diarrhea management by type and assessed the association between good management and source of care, adjusting for potential confounders. Results Prevalence of good diarrhea management is low in 11 of the 12 analyzed surveys, varying from 17 % in Cote d’Ivoire to 38 % in Niger. The exception is Sierra Leone, where prevalence of good practice is 67 %. Prevalence of good management was low even among children taken to health facilities [median 52 %, range: 34–64 %]. Diarrhea careseeking from health facilities or community providers was associated with higher odds of good management than care from traditional/informal sources or no care. Careseeking from facilities did not result systematically in a higher likelihood of good diarrhea management than care from community providers. The odds of good diarrhea management were similar for community versus facility providers in six countries, higher in community than facility providers in two countries, and higher in facility than in community providers in four countries. Conclusion Many children’s lives can be saved with correct management of childhood diarrhea. Too many children are not receiving adequate care for diarrhea in high-burden sub-Saharan African countries, even among those seen in health facilities. Redoubling efforts to increase careseeking and improve quality of care for childhood diarrhea in both health facilities and at community level is an urgent priority.

The recently proposed Green Deals and ‘building back better’ plans have affirmed the importance to make green transitions inclusive. This is particularly related to the labour market, which may witness significant changes. Empirically, this issue has until now received limited attention. The links between poverty and climate change are explored mainly through the lenses of climate change adaptation, or via the effects of rising energy prices on the purchasing power of poor households. We aim to address this gap by using results from a simulation of the global energy transition required to meet the 2-degree target, and compare this to a 6-degree baseline scenario. The simulation with a multi-regional input–output model finds that, overall, this transition results in a small net job increase of 0.3% globally, with cross-country heterogeneity. We complement this macro-level analysis with cross-country household data to draw implications of the effects on poverty through labour market outcomes. The few job losses will be concentrated in specific industries, while new jobs will be created in industries that currently witness relatively high in-work poverty rates, such as construction. We show that high in-work poverty in the industries of interest, and especially in middle-income countries, is often associated with low skills and an insufficient reach of social protection mechanisms. We conclude that green transitions must ensure that the jobs created are indeed decent including fair wages, adequate working conditions, sufficient social protection measures, and accessible to the vulnerable and poorest households.

Background: Many household surveys collect mothers' retrospective reports of reproductive, maternal, and child health. However, few empirical exercises assess survey measurement error in these data, based on comparisons with administrative records. Objective: We provide evidence on the accuracy of maternal recall regarding weeks of gestation, premature births, and the timing and number of prenatal visits. Methods: We compare the survey maternal recall and the vital statistics administrative records based on the 2013 Nutrition, Child Development and Health Survey (ENDIS) for Uruguay (2,963 children aged 0‒3). We estimate measurement error and its determinants by using a set of probit models. Results: Mothers tend to overestimate gestational weeks and the incidence of prematurity by 0.1 weeks and 2.4 percentage points, respectively. Differences are larger regarding the timeliness and sufficiency of prenatal visits (respectively, 17.0 and 14.4 pp). Discrepancies are associated with lower educational levels, the length of the recall period (child's age) and birth order. Conclusions: In general, our findings validate the use of survey data, although the identification of premature births and prenatal care sufficiency presents differences that could lead to errors in the evaluation of compliance with, for example, the United Nations' Sustainable Development Goals. Since recall accuracy is negatively associated with maternal schooling, discrepancies could be larger in relatively less developed countries. Contribution: The main contribution of this paper lies in the assessment of measurement error levels arising from maternal reports of gestational age and prenatal visits for a relatively short recall period in a Latin American country. Although previous studies estimate measurement errors using administrative records linked to maternal recall data, this is the only study that is based on a nationally representative survey.

Sub-Saharan African cities are expanding horizontally, demonstrating spatial patterns of urban sprawl and socioeconomic segregation. An important research gap around the geographies of urban populations is that city-wide analyses mask local socioeconomic inequalities. This research focuses on those inequalities by identifying the spatial settlement patterns of socioeconomic groups within the Greater Kampala Metropolitan Area (Uganda). Findings are based on a novel dataset, an extensive household survey with 541 households, conducted in Kampala in 2019. To identify different socioeconomic groups, a k-prototypes clustering method was applied to the survey data. A maximum likelihood classification method was applied on a recent Landsat-8 image of the city and compared to the socioeconomic clustering through a fuzzy error matrix. The resulting maps show how different socioeconomic clusters are located around the city. We propose a simple method to upscale household survey responses to a larger study area, to use these data as a base map for further analysis or urban planning purposes. Obtaining a better understanding of the spatial variability in socioeconomic dynamics can aid urban policy-makers to target their decision-making processes towards a more favorable and sustainable future.

Background Income is one of the most important measures of well-being, but it is notoriously difficult to measure accurately. In the United States, income data are available from surveys, tax records, and government programs, but each of these sources has important strengths and major limitations when used alone. Objectives We link multiple data sources to develop the Comprehensive Income Dataset (CID), a prototype for a restricted micro-level dataset that combines the demographic detail of survey data with the accuracy of administrative measures. Methods By incorporating information on nearly all taxable income, tax credits, and cash and in-kind government transfers, the CID surpasses previous efforts to provide an accurate and comprehensive measure of income for the population of United States individuals, families, and households. We also evaluate the accuracy of different income sources and imputation methods. Conclusions While still in development, we envision the CID enhancing Census Bureau surveys and statistics by investigating measurement error, improving imputation methods, and augmenting surveys with the best possible estimates of income. It can also be used for policy related research, such as forecasting and simulating changes in programs and taxes. Finally, the CID has substantial advantages over other sources to analyze numerous research topics, including poverty, inequality, mobility, and the distributional consequences of government transfers and taxes.

Background: This paper presents some data on cancer related mortality in Basrah governorate during the period 2010-2012 as part of a comprehensive household survey carried out during 2013 to document the extent of cancer and validate the official cancer registration. Objective: The main objective is to present data on cancer mortality in Basrah governorate Method: The study involved visiting 6999 households (families) who were interviewed on, among other aspects, incident cancer and mortality due to cancer during the three-year recall period. Results: A total of 6999 households (families) with 40688 inhabitants were successfully visited and data were collected and analyzed about their cancer experience. Eighty three persons died with cancer during 2010-2012 giving an average annual cancer specific mortality rate of 68.0 per 100000 persons. The mortality rate was higher for females (71.49 per 100000 females) as compared to males (64.61 per 100000 males) and was increasing with advancing age. The leading causes of mortality were cancers of the lung, breast, urinary bladder and colon-rectum. These four cancers accounted for almost half the deaths (49.4%) or 33.6 per 100000 of the population. Within the overall pattern of mortality in the population, cancer came in the 2nd rank after cardiovascular disease. Conclusion: Cancer is an important contributor to mortality in Basrah governorate. The current level of mortality is higher than any previously reported figures.

In rural societies of low- and middle-income countries, land is a major measure of wealth, a critical input in agricultural production, and a key variable for assessing agricultural performance and productivity. In the absence of cadastral information to refer to, measures of land plots have historically been taken with one of two approaches: traversing (accurate, but cumbersome), and farmers’ self-report (cheap, but marred by measurement error). Recently, the advent of cheap handheld GPS devices has held promise for balancing cost and precision. Guided by purposely collected primary data from Ethiopia, Nigeria, and Tanzania (Zanzibar), and with consideration for practical household survey implementation, the paper assesses the nature and magnitude of measurement error under different measurement methods and proposes a set of recommendations for plot area measurement. The results largely point to the support of GPS measurement, with simultaneous collection of farmer self-reported areas.

The aim of this study is to characterize the relationship between food consumption and socio-demographic characteristics in several groups of individuals. This is achieved by capturing the quantity of food purchased in categories on a microeconomic level. The empirical analysis is approached through the estimation of (a) expanded generalized linear models, (b) quantile regression models, (c) quadratic almost ideal demand system models and (d) Deaton’s (1988) approach. The results reveal that the composition of a household has a significant impact on the quantity of food consumed. In addition, price and income elasticities are estimated, confirming that the majority of food items are inelastic with respect to price and income except for meat. These findings can be used as a basis for considering food policy implications while evaluating the potential gains from applying specific policies.

A better understanding of the epidemiology of envenoming would improve care, provided that the survey is representative, reliable and accurate. Several types of surveys could help to clarify the incidence, severity, circumstances, factors and determinants of envenomations. The relevant information may be collected and analyzed from hospital records or case report forms (for retrospective studies) or established from a protocol of longitudinal observation of cases attended at health facilities during a given period (prospective study). The household survey includes interviewing all or part of the population of a locality with a standardized questionnaire to obtain information on the circumstances of the accident. Finally, standardized questionnaires can be administered to health workers in order to ascertain the circumstances and procedures of care, the availability and use of treatment and the level of knowledge of agents. Correctly performed, these surveys should promote the organization of the management of snakebites or scorpion stings because they identify the location of envenomation and quantify the needs. However, the surveyed localities should be chosen for relevance to be representative of the territory, just as methodology and analysis should be rigorous in order to give useful results.

A importância crescente da avaliação em saúde requer a incorporação do método epidemiológico, tanto no processo de avaliação de tecnologias, como na avaliação do desempenho dos serviços de saúde. Esta avaliação necessita de informações com base populacional, que identifiquem a demanda reprimida e caracterizem o padrão de utilização de serviços, as quais podem ser obtidas através de inquéritos domiciliares. As informações geradas através destes inquéritos não só permitem uma "linha de base" para o planejamento de saúde e posterior avaliação, como também são importantes na avaliação dos serviços. Inquérito domiciliar realizado na Grande São Paulo permitiu identificar o padrão de uso dos serviços de saúde para a população residente na área. Este padrão reflete a organização dos serviços de saúde, mostrando a baixa cobertura dos serviços locais, inclusive a dos serviços públicos, os diferentes perfis dos usuários dos serviços privados e públicos e a grande procura de serviços fora da área, no Município de São Paulo, principalmente para o parto. As vantagens de incorporar inquéritos domiciliares no processo de avaliação de serviços devem ser analisadas frente ao uso potencial dos resultados e aos custos destes estudos, devendo ser discutido, em cada situação específica, o delineamento mais adequado para uma melhor relação custo-benefício.The increasing importance of health evaluation has raised the need of incorporating epidemiological methodology to assess both technologies and health services. Evaluation of health services performance requires population data to identify the unmet demand and patterns of health services utilization. Such data can be obtained through household surveys. A household survey in the Greater São Paulo Metropolitan Area identified the pattern of health services utilization by the local population. This pattern, which reflects current organization of health services, pointed to a low coverage level by local services, including public clinics, different profiles for users of private and public services, and a large demand for health services outside the area, mainly for childbirth. The information obtained through these surveys produces a "base line" for health planning and further evaluation and is central to the assessment of existing services. The advantages of household surveys in health services evaluation should be analyzed in relation to the potential use of such data and study costs, thereby designing the best cost-benefit relationship for each specific situation.

Abstract Introduction A recent health reform was implemented in Chile (the AUGE reform) with the objective of reducing the socioeconomic gaps to access healthcare. This reform did not seek to eliminate the private insurance system, which coexists with the public one, but to ensure minimum conditions of access to the entire population, at a reasonable cost and with a quality guarantee, to cover an important group of health conditions. This paper’s main objective is to enquire what has happened with the use of several healthcare services after the reform was fully implemented. Methods Concentration and Horizontal Inequity indices were estimated for the use of general practitioners, specialists, emergency room visits, laboratory and x-ray exams and hospitalization days. The change in such indices (pre and post-reform) was decomposed, following Zhong (2010). A “mean effect” (how these indices would change if the differential use in healthcare services were evenly distributed) and a “distribution effect” (how these indices would change with no change in average use) were obtained. Results Changes in concentration indices were mainly due to mean effects for all cases, except for specialists (where “distribution effect” prevailed) and hospitalization days (where none of these effects prevailed over others). This implies that by providing more services across socioeconomic groups, less inequality in the use of services was achieved. On the other hand, changes in horizontal inequity indices were due to distribution effects in the case of GP, ER visits and hospitalization days; and due to mean effect in the case of x-rays. In the first three cases indices reduced their pro-poorness implying that after the reform relatively higher socioeconomic groups used these services more (in relation to their needs). In the case of x-rays, increased use was responsible for improving its horizontal inequity index. Conclusions The increase in the average use of healthcare services after the AUGE reform has not always led to improved equity in the use of such services in most services. This indicates that there are still barriers to the equitable use of healthcare services (e.g. insufficient medical human resources, financial barriers, capacity constraints, etc.) that have remained after the reform.

A importância crescente da avaliação em saúde requer a incorporação do método epidemiológico, tanto no processo de avaliação de tecnologias, como na avaliação do desempenho dos serviços de saúde. Esta avaliação necessita de informações com base populacional, que identifiquem a demanda reprimida e caracterizem o padrão de utilização de serviços, as quais podem ser obtidas através de inquéritos domiciliares. As informações geradas através destes inquéritos não só permitem uma "linha de base" para o planejamento de saúde e posterior avaliação, como também são importantes na avaliação dos serviços. Inquérito domiciliar realizado na Grande São Paulo permitiu identificar o padrão de uso dos serviços de saúde para a população residente na área. Este padrão reflete a organização dos serviços de saúde, mostrando a baixa cobertura dos serviços locais, inclusive a dos serviços públicos, os diferentes perfis dos usuários dos serviços privados e públicos e a grande procura de serviços fora da área, no Município de São Paulo, principalmente para o parto. As vantagens de incorporar inquéritos domiciliares no processo de avaliação de serviços devem ser analisadas frente ao uso potencial dos resultados e aos custos destes estudos, devendo ser discutido, em cada situação específica, o delineamento mais adequado para uma melhor relação custo-benefício.