A comparison of approaches to measuring maternal mortality in Bangladesh, Mozambique, and Bolivia

Background Many low- and middle-income countries cannot measure maternal mortality to monitor progress against global and country-specific targets. While the ultimate goal for these countries is to have complete civil registrations systems, other interim strategies are needed to provide timely estimates of maternal mortality. Objective The objective is to inform on potential options for measuring maternal mortality. Methods This paper uses a case study approach to compare methodologies and estimates of pregnancy-related mortality ratio (PRMR)/maternal mortality ratio (MMR) obtained from four different data sources from similar time periods in Bangladesh, Mozambique, and Bolivia—national population census; post-census mortality survey; household sample survey; and sample vital registration system (SVRS). Results For Bangladesh, PRMR from the 2011 census falls closely in line with the 2010 household survey and SVRS estimates, while SVRS’ MMR estimates are closer to the PRMR estimates obtained from the household survey. Mozambique's PRMR from household survey method is comparable and shows an upward trend between 1994 and 2011, whereas the post-census mortality survey estimated a higher MMR for 2007. Bolivia's DHS and post-census mortality survey also estimated comparable MMR during 1998–2003. Conclusions Overall all these data sources presented in this paper have provided valuable information on maternal mortality in Bangladesh, Mozambique, and Bolivia. It also outlines recommendations to estimate maternal mortality based on the advantages and disadvantages of several approaches. Contribution Recommendations in this paper can help health administrators and policy planners in prioritizing investment for collecting reliable and contemporaneous estimates of maternal mortality while progressing toward a complete civil registration system.

GPS-based fine-scale mapping surveys for schistosomiasis assessment: a practical introduction and documentation of field implementation

Background Fine-scale mapping of schistosomiasis to guide micro-targeting of interventions will gain importance in elimination settings, where the heterogeneity of transmission is often pronounced. Novel mobile applications offer new opportunities for disease mapping. We provide a practical introduction and documentation of the strengths and shortcomings of GPS-based household identification and participant recruitment using tablet-based applications for fine-scale schistosomiasis mapping at sub-district level in a remote area in Pemba, Tanzania. Methods A community-based household survey for urogenital schistosomiasis assessment was conducted from November 2020 until February 2021 in 20 small administrative areas in Pemba. For the survey, 1400 housing structures were prospectively and randomly selected from shapefile data. To identify pre-selected structures and collect survey-related data, field enumerators searched for the houses’ geolocation using the mobile applications Open Data Kit (ODK) and MAPS.ME. The number of inhabited and uninhabited structures, the median distance between the pre-selected and recorded locations, and the dropout rates due to non-participation or non-submission of urine samples of sufficient volume for schistosomiasis testing was assessed. Results Among the 1400 randomly selected housing structures, 1396 (99.7%) were identified by the enumerators. The median distance between the pre-selected and recorded structures was 5.4 m. A total of 1098 (78.7%) were residential houses. Among them, 99 (9.0%) were dropped due to continuous absence of residents and 40 (3.6%) households refused to participate. In 797 (83.1%) among the 959 participating households, all eligible household members or all but one provided a urine sample of sufficient volume. Conclusions The fine-scale mapping approach using a combination of ODK and an offline navigation application installed on tablet computers allows a very precise identification of housing structures. Dropouts due to non-residential housing structures, absence, non-participation and lack of urine need to be considered in survey designs. Our findings can guide the planning and implementation of future household-based mapping or longitudinal surveys and thus support micro-targeting and follow-up of interventions for schistosomiasis control and elimination in remote areas. Trial registration ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493

Financial vulnerability and the impact of COVID-19 on American households

In May 2020, Westat, in partnership with Stanford University School of Medicine, conducted a nationally-representative household survey of American attitudes and behaviors regarding COVID-19. In this article, we examine what the Coronavirus Attitudes and Behaviors Survey tells us about the impact of COVID-19 on financial status and how this impact varies by demographic characteristics, the presence of health risk factors, and financial status (including employment factors). The survey reveals significant inequality in financial impact, as those who were most financially vulnerable prior to the pandemic found themselves under greater financial strain, while those who were more financially secure have experienced a neutral or even positive impact of the pandemic on household finances. These findings have important implications for public policy as policymakers seek to target aid to those who need it most.

Perception-based Assessment of Ecosystem Services of Abijata-Shalla National Park Wetlands in the Central Rift Valley of Ethiopia

Abijata-Shalla Park was established as one of Ethiopia's national parks to safeguard wetlands and ecosystem services (ESs). Some of the ESs that are offered by the wetlands are currently depleting and disappearing rather than being protected. Understanding the drivers behind these changes can help individuals and policymakers design mitigation measures. The objective of this case was to assess ESs and the drivers of change with highlighting on the Abijata wetland. In addition to a household survey and group discussion, personal interviews and field observation were employed to collect data. Using these data, the various ESs were assessed and ranked from 1-10 according to local perception. Grading scales such as very high (−2), high (−1), neutral (0), low (+1), and very low (+2) were employed to analyse the drivers of ESs change. Analyses of the study revealed that some of the ESs, including fish, papyrus, water reeds, hunting and spiritual services, existed before 1991, but have since disappeared from the site. Twenty ESs are available; 11 services pertain to provisioning, followed by 4 regulating, 3 cultural and 2 supporting services. Wetland for cultivation ranked highest, followed by domestic water supply and pasture. All services, with the exception of arable land and pasture, are on the decline. Water abstraction is the primary driver of ESs change, followed by population growth and deforestation. The park existed as a "paper park." Water withdrawals from the Ziway-Shalla sub-basin should be restricted. Instead, focus on water conservation strategies to make better use of abstracted water.

Microestimates of wealth for all low- and middle-income countries

Many critical policy decisions, from strategic investments to the allocation of humanitarian aid, rely on data about the geographic distribution of wealth and poverty. Yet many poverty maps are out of date or exist only at very coarse levels of granularity. Here we develop microestimates of the relative wealth and poverty of the populated surface of all 135 low- and middle-income countries (LMICs) at 2.4 km resolution. The estimates are built by applying machine-learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, and topographic maps, as well as aggregated and deidentified connectivity data from Facebook. We train and calibrate the estimates using nationally representative household survey data from 56 LMICs and then validate their accuracy using four independent sources of household survey data from 18 countries. We also provide confidence intervals for each microestimate to facilitate responsible downstream use. These estimates are provided free for public use in the hope that they enable targeted policy response to the COVID-19 pandemic, provide the foundation for insights into the causes and consequences of economic development and growth, and promote responsible policymaking in support of sustainable development.

Impact of food price increases on poverty in Indonesia: empirical evidence from cross-sectional data

PurposeUsing cross-sectional household survey data, this paper aims to determine the impact of food price increases on poverty in Indonesia.Design/methodology/approachThis paper uses the quadratic almost ideal demand system applied to the 2013 Indonesian household survey data. The impact of food price increase on household welfare is calculated using a welfare measure, compensating variation.FindingsThree food groups with the most outstanding price impact on poverty are rice, vegetables and fish were studied. The 20% increase in the price of each food group causes an increase in the headcount ratio by 1.360 points (rice), 0.737 points (vegetables) and 0.636 points (fish). Maintaining food price stability for these food groups is very important because the more price increases, the more impact on poverty. Food price policies in rural areas are also more critical than in urban areas because the impact of food price increases in rural areas is higher.Research limitations/implicationsThis paper does not consider the positive impact of rising food prices on food-producing households.Practical implicationsImplementing appropriate poverty alleviation policies through food policies for main food groups and social protection.Social implicationsPromoting rural development policies and agricultural growth.Originality/valueThis paper contributes to the existing literature by providing empirical results regarding the impact of domestic food prices increase on poverty in Indonesia.

National Cultural Frames and Muslims’ Economic Incorporation: A Comparison of France and Canada

This article shows that differences in the economic incorporation of Muslims and other immigrant minorities in France and in Canada are mainly related to immigrant selectivity, labor market structures, and welfare transfers. Differences in ethno-specific penalties due to national cultural frames — related to multiculturalism in Canada and secular republicanism in France — are small, affect only the second generation, and are related both to minority household patterns and to treatment in mainstream institutions. Using data on household incomes from two large-scale surveys (Trajectories and Origins in France 2008–2009 and the Canadian National Household Survey 2011) and taking account of cross-setting differences in Muslim and other minority origins, we model cross-generational economic trajectories reflecting the impact of immigrant selectivity, labor market structures, and welfare transfers. Within this framework, we examine four ways that cultural frames may affect minority economic disadvantage: the significance of religion relative to race, citizenship access, labor market discrimination, and minority household patterns, including employment of women in couples and intergenerational cohabitation. Across all minorities, we find a striking cross-national difference in intergenerational economic trajectories: flat in France and upward in Canada, plausibly reflecting institutional differences. Net of sociodemographic controls, both religion and race matter in each setting, and net Muslim disadvantage is similar in each. Citizenship differences have little impact. Labor market earnings discrimination appears similar. A small potential effect of cultural frames appears in second-generation Muslim households: in France, lower female employment rates reduce household incomes, while in English-speaking Canada, more frequent cohabitation with more affluent parents increases household incomes. Yet even these findings do not necessarily diminish the overriding significance of immigrant selectivity, labor market structure, and welfare transfers.

Market chain analysis of goat in south omo zone of SNNPR, Ethiopia

This study was initiated to identify market chain actors and their function in the market, investigate the structure conduct and performance of goat marketing in south omo zones of SNNPR, Ethiopia during the year 2018. Primary data were collected from sampled pastoralists and agro pastoralists, traders and brokers. Before the household survey, key informant interview and focus group discussions were conducted with producers, traders and brokers. Descriptive Statistics and qualitative data analysis techniques were employed to analyze the goat market structure, conduct and performance. The results show that producers, brokers, traders and consumers were the major goat market actors. Regarding the market structure, cattle market is known to be dominated by few traders. Although the degree of competition varies, goat market structure in the study area has an oligopolistic nature. This shows that only few traders have the majority of market share and earn abnormal profit. Besides, goat market is characterized by entry barriers, distant market point, high trucking cost, seasonality of marketing, information asymmetries and unfriendly relation between actors. As the pastoralists and agro pastoralists mainly depend on goat for their livelihoods and other cultural values, traders take advantage of the asymmetric market information towards them. The larger share of the market gains remains with end traders thereby limiting the pastoralists and agro pastoralists chance to realize the economic gains in goat production. Thus, linking producers to market and its benefits, establishing cooperatives and development of infrastructure could play a significant role for optimization of the sector. Int. J. Agril. Res. Innov. Tech. 11(2): 52-60, Dec 2021

Labor market and crisis: an analysis of sectoral segmentation in Brazilian rural

The article aims to analyze which factors contributed to the inequality across income distribution of Brazilian workers in rural areas, occupied in agricultural and non-agricultural activities. Quantile regression with sample selection bias correction and counterfactual decomposition of income by quantiles were applied, using the microdata from the National Continuous Household Survey (PNAD-C) for the years 2012 and 2019. The results showed that there is income inequality favorable to workers occupied in non-agricultural activities concerning agricultural activities, which is intensive for those with lower incomes, as well as for those with high incomes. The presence of sectorial segmentation was also confirmed, of which the largest portion in 2012 corresponds to the labor market duality. However in 2019, in lower quantiles the segmentation obtained greater explanatory power for the difference in income between the groups, while in higher quantiles the theory of human capital prevailed.