Gridded birth and pregnancy datasets for Africa, Latin America and the Caribbean

Future malaria environmental suitability in Africa is sensitive to hydrology

Changes in climate shift the geographic locations that are suitable for malaria transmission because of the thermal constraints on vector Anopheles mosquitos and Plasmodium spp. malaria parasites and the lack of availability of surface water for vector breeding. Previous Africa-wide assessments have tended to solely represent surface water using precipitation, ignoring many important hydrological processes. Here, we applied a validated and weighted ensemble of global hydrological and climate models to estimate present and future areas of hydroclimatic suitability for malaria transmission. With explicit surface water representation, we predict a net decrease in areas suitable for malaria transmission from 2025 onward, greater sensitivity to future greenhouse gas emissions, and different, more complex, malaria transmission patterns. Areas of malaria transmission that are projected to change are smaller than those estimated by precipitation-based estimates but are associated with greater changes in transmission season lengths.

Flood exposure and pregnancy loss in 33 developing countries

Floods have affected billions worldwide. Yet, the indirect health impacts of floods on vulnerable groups, particularly women in the developing world, remain underexplored. Here, we evaluated the risk of pregnancy loss for women exposed to floods. We analyzed 90,465 individual pregnancy loss records from 33 developing countries, cross-referencing each with spatial-temporal flood databases. We found that gestational flood exposure is associated with increased pregnancy loss with an odds ratio of 1.08 (95% confidence interval: 1.04 - 1.11). This risk is pronounced for women outside the peak reproductive age range (<21 or >35) or during the mid and late-stage of pregnancy. The risk escalated for women dependent on surface water, with lower income or education levels. We estimated that, over the 2010s, gestational flood events might be responsible for approximately 107,888 (CIs: 53,944 - 148,345) excess pregnancy losses annually across 33 developing countries. Notably, there is a consistent upward trend in annual excess pregnancy losses from 2010 to 2020, and was more prominent over Central America, the Caribbean, South America, and South Asia. Our findings underscore the disparities in maternal and child health aggravated by flood events in an evolving climate.

Surrounding greenness is associated with lower risk and burden of low birth weight in Iran

The nexus between prenatal greenspace exposure and low birth weight (LBW) remains largely unstudied in low- and middle-income countries (LMICs). We investigated a nationwide retrospective cohort of 4,021,741 live births (263,728 LBW births) across 31 provinces in Iran during 2013-2018. Greenness exposure during pregnancy was assessed using satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). We estimated greenness-LBW associations using multiple logistic models, and quantified avoidable LBW cases under scenarios of improved greenspace through counterfactual analyses. Association analyses provide consistent evidence for approximately L-shaped exposure-response functions, linking 7.0-11.5% declines in the odds of LBW to each 0.1-unit rise in NDVI/EVI with multiple buffers. Assuming causality, 3931-5099 LBW births can be avoided by achieving greenness targets of mean NDVI/EVI, amounting to 4.4-5.6% of total LBW births in 2015. Our findings suggest potential health benefits of improved greenspace in lowering LBW risk and burden in LMICs.

World's human migration patterns in 2000-2019 unveiled by high-resolution data

Despite being a topical issue in public debate and on the political agenda for many countries, a global-scale, high-resolution quantification of migration and its major drivers for the recent decades remained missing. We created a global dataset of annual net migration between 2000 and 2019 (~10 km grid, covering the areas of 216 countries or sovereign states), based on reported and downscaled subnational birth (2,555 administrative units) and death (2,067 administrative units) rates. We show that, globally, around 50% of the world's urban population lived in areas where migration accelerated urban population growth, while a third of the global population lived in provinces where rural areas experienced positive net migration. Finally, we show that, globally, socioeconomic factors are more strongly associated with migration patterns than climatic factors. While our method is dependent on census data, incurring notable uncertainties in regions where census data coverage or quality is low, we were able to capture migration patterns not only between but also within countries, as well as by socioeconomic and geophysical zonings. Our results highlight the importance of subnational analysis of migration-a necessity for policy design, international cooperation and shared responsibility for managing internal and international migration.

A scoping review of the landscape of health-related open datasets in Latin America

Artificial intelligence (AI) algorithms have the potential to revolutionize healthcare, but their successful translation into clinical practice has been limited. One crucial factor is the data used to train these algorithms, which must be representative of the population. However, most healthcare databases are derived from high-income countries, leading to non-representative models and potentially exacerbating health inequities. This review focuses on the landscape of health-related open datasets in Latin America, aiming to identify existing datasets, examine data-sharing frameworks, techniques, platforms, and formats, and identify best practices in Latin America. The review found 61 datasets from 23 countries, with the DATASUS dataset from Brazil contributing to the majority of articles. The analysis revealed a dearth of datasets created by the authors themselves, indicating a reliance on existing open datasets. The findings underscore the importance of promoting open data in Latin America. We provide recommendations for enhancing data sharing in the region.

Stillbirths attributable to open fires and their geographic disparities in non-Western countries

Due to global warming, an increased number of open fires is becoming a major contributor to PM2.5 pollution and thus a threat to public health. However, the burden of stillbirths attributable to fire-sourced PM2.5 is unknown. In low- and middle-income countries (LMICs), there is a co-occurrence of high baseline stillbirth rates and frequent firestorms, which may lead to a geographic disparity. Across 54 LMICs, we conducted a self-matched case-control study, making stillbirths comparable to the corresponding livebirths in terms of time-invariant characteristics (e.g., genetics) and duration of gestational exposure. We established a joint-exposure-response function (JERF) by simultaneously associating stillbirth with fire- and non-fire-sourced PM2.5 concentrations, which were estimated by fusing multi-source data, such as chemical transport model simulations and satellite observations. During 2000-2014, 35,590 pregnancies were selected from multiple Demographic and Health Surveys. In each mother, a case of stillbirth was compared to her livebirth(s) based on gestational exposure to fire-sourced PM2.5. We further applied the JERF to assess stillbirths attributable to fire-sourced PM2.5 in 136 non-Western countries. The disparity was evaluated using the Gini index. The risk of stillbirth increased by 17.4% (95% confidence interval [CI]: 1.6-35.7%) per 10 μg/m3 increase in fire-sourced PM2.5. In 2014, referring to a minimum-risk exposure level of 10 μg/m3, total and fire-sourced PM2.5 contributed to 922,860 (95% CI: 578,451-1,183,720) and 49,951 (95% CI: 3,634-92,629) stillbirths, of which 10% were clustered within the 6.4% and 0.6% highest-exposure pregnancies, respectively. The Gini index of stillbirths attributable to fire-sourced PM2.5 was 0.65, much higher than for total PM2.5 (0.28). Protecting pregnant women against PM2.5 exposure during wildfires is critical to avoid stillbirths, as the burden of fire-associated stillbirths leads to a geographic disparity in maternal health.

Estimation of stillbirths attributable to ambient fine particles in 137 countries

Gestational exposure to ambient fine particles (PM_2.5) increases the risk of stillbirth, but the related disease burden is unknown, particularly in low- and middle-income countries (LMICs). We combine state-of-the-art estimates on stillbirths, and multiple exposure-response functions obtained from previous meta-analyses or derived by a self-matched case-control study in 54 LMICs. 13,870 stillbirths and 32,449 livebirths are extracted from 113 geocoded surveys from the Demographic and Health Surveys. Each stillbirth is compared to livebirth(s) of the same mother using a conditional logit regression. We find that 10-µg/m³ increase of PM_2.5 is associated with an 11.0% (95% confidence interval [CI] 6.4, 15.7) increase in the risk of stillbirth, and the association is significantly enhanced by maternal age. Based on age-specific nonlinear PM_2.5-stillbirth curves, we evaluate the PM_2.5-related stillbirths in 137 countries. In 2015, of 2.09 (95% CI: 1.98, 2.20) million stillbirths, 0.83 (0.54, 1.08) million or 39.7% (26.1, 50.8) are attributable to PM_2.5 exposure exceeding the reference level of 10 μg/m³. In LMICs, preventing pregnant women from being exposed to PM_2.5 can improve maternal health.

Targeted policy intervention for reducing red meat consumption: conflicts and trade-offs

BACKGROUND

There are a range of policies and guidelines focused on meat consumption which aim to tackle health and environmental issues. Policies are often siloed in nature and propose universal limits on consumption. Despite this, there will be a number of conflicts and trade-offs between interest groups. This study explores secondary impacts associated with guidelines issued by the World Cancer Research Fund and assesses the utility of a targeted policy intervention strategy for reducing red meat consumption.

METHODS

We used highly detailed consumption data of over 5,000 individuals from the National Diet and Nutrition Survey. We firstly compared individual consumption against the policy guidelines to identify demographic groups most likely to consume above recommended levels. We then synthetically modified the food diary data to investigate the secondary impacts of adherence to the recommendations by all individuals. We assessed changes in overall consumption, nutrient intake (iron, zinc, vitamin B12, vitamin B3, fat and saturated fat) and global warming potential. We also projected future impacts under various population projections.

RESULTS

We found that certain demographic groups are much more likely to exceed the recommendations and would therefore benefit from a targeted intervention approach. Our results provide a baseline for which the impacts of any meat substitute diets can be assessed against. Whilst secondary health benefits may be realised by reducing intake of certain nutrients (e.g. fats), negative impacts may occur due to the reduced intake of other nutrients (e.g. iron, zinc). Reduced overall consumption is likely to have implications for the wider meat industry whilst complementary impacts would occur in terms of reduced greenhouse gas emissions. Impacts will be counteracted or maybe even reversed by any substitute products, highlighting the need to carefully consider the suitability and impacts of meat-replacements.

CONCLUSION

The future structure of the meat industry will depend on how conflicts and trade-offs are addressed and how more holistic policy ideas are implemented. This research provides a framework for using demographic and consumption data to reduce negative trade-offs and improve policy effectiveness.

Global holiday datasets for understanding seasonal human mobility and population dynamics

Public and school holidays have important impacts on population mobility and dynamics across multiple spatial and temporal scales, subsequently affecting the transmission dynamics of infectious diseases and many socioeconomic activities. However, worldwide data on public and school holidays for understanding their changes across regions and years have not been assembled into a single, open-source and multitemporal dataset. To address this gap, an open access archive of data on public and school holidays in 2010-2019 across the globe at daily, weekly, and monthly timescales was constructed. Airline passenger volumes across 90 countries from 2010 to 2018 were also assembled to illustrate the usage of the holiday data for understanding the changing spatiotemporal patterns of population movements.

Global estimates of pregnancies at risk of Plasmodium falciparum and Plasmodium vivax infection in 2020 and changes in risk patterns since 2000

BACKGROUND

Women are at risk of severe adverse pregnancy outcomes attributable to Plasmodium spp. infection in malaria-endemic areas. Malaria control efforts since 2000 have aimed to reduce this burden of disease.

METHODS

We used data from the Malaria Atlas Project and WorldPop to calculate global pregnancies at-risk of Plasmodium spp. infection. We categorised pregnancies as occurring in areas of stable and unstable P. falciparum and P. vivax transmission. We further stratified stable endemicity as hypo-endemic, meso-endemic, hyper-endemic, or holo-endemic, and estimated pregnancies at risk in 2000, 2005, 2010, 2015, 2017, and 2020.

FINDINGS

In 2020, globally 120.4M pregnancies were at risk of P. falciparum, two-thirds (81.0M, 67.3%) were in areas of stable transmission; 85 2M pregnancies were at risk of P. vivax, 93.9% (80.0M) were in areas of stable transmission. An estimated 64.6M pregnancies were in areas with both P. falciparum and P. vivax transmission. The number of pregnancies at risk of each of P. falciparum and P. vivax worldwide decreased between 2000 and 2020, with the exception of sub-Saharan Africa, where the total number of pregnancies at risk of P. falciparum increased from 37 3M in 2000 to 52 4M in 2020.

INTERPRETATION

Historic investments in malaria control have reduced the number of women at risk of malaria in pregnancy in all endemic regions except sub-Saharan Africa. Population growth in Africa has outpaced reductions in malaria prevalence. Interventions that reduce the risk of malaria in pregnancy are needed as much today as ever.

A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators

Background

Household survey data are frequently used to measure reproductive, maternal, newborn, child and adolescent health (RMNCAH) service utilisation in low and middle income countries. However, these surveys are typically only undertaken every 5 years and tend to be representative of larger geographical administrative units. Investments in district health management information systems (DHMIS) have increased the capability of countries to collect continuous information on the provision of RMNCAH services at health facilities. However, reliable and recent data on population distributions and demographics at subnational levels necessary to construct RMNCAH coverage indicators are often missing. One solution is to use spatially disaggregated gridded datasets containing modelled estimates of population counts. Here, we provide an overview of various approaches to the production of gridded demographic datasets and outline their potential and their limitations. Further, we show how gridded population estimates can be used as alternative denominators to produce RMNCAH coverage metrics in combination with data from DHMIS, using childhood vaccination as examples.

Methods

We constructed indicators on the percentage of children one year old for diphtheria, pertussis and tetanus vaccine dose 3 (DTP3) and measles vaccine dose (MCV1) in Zambia and Nigeria at district levels. For the numerators, information on vaccines doses was obtained from each country’s respective DHMIS. For the denominators, the number of children was obtained from 3 different sources including national population projections and aggregated gridded estimates derived using top-down and bottom-up geospatial methods.

Results

In Zambia, vaccination estimates utilising the bottom-up approach to population estimation substantially reduced the number of districts with > 100% coverage of DTP3 and MCV1 compared to estimates using population projection and the top-down method. In Nigeria, results were mixed with bottom-up estimates having a higher number of districts > 100% and estimates using population projections performing better particularly in the South.

Conclusions

Gridded demographic data utilising traditional and novel data sources obtained from remote sensing offer new potential in the absence of up to date census information in the estimation of RMNCAH indicators. However, the usefulness of gridded demographic data is dependent on several factors including the availability and detail of input data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06370-y.

Geographical distribution of fertility rates in 70 low-income, lower-middle-income, and upper-middle-income countries, 2010-16: a subnational analysis of cross-sectional surveys

BACKGROUND

Understanding subnational variation in age-specific fertility rates (ASFRs) and total fertility rates (TFRs), and geographical clustering of high fertility and its determinants in low-income and middle-income countries, is increasingly needed for geographical targeting and prioritising of policy. We aimed to identify variation in fertility rates, to describe patterns of key selected fertility determinants in areas of high fertility.

METHODS

We did a subnational analysis of ASFRs and TFRs from the most recent publicly available and nationally representative cross-sectional Demographic and Health Surveys and Multiple Indicator Cluster Surveys collected between 2010 and 2016 for 70 low-income, lower-middle-income, and upper-middle-income countries, across 932 administrative units. We assessed the degree of global spatial autocorrelation by using Moran's I statistic and did a spatial cluster analysis using the Getis-Ord Gi* local statistic to examine the geographical clustering of fertility and key selected fertility determinants. Descriptive analysis was used to investigate the distribution of ASFRs and of selected determinants in each cluster.

FINDINGS

TFR varied from below replacement (2·1 children per women) in 36 of the 932 subnational regions (mainly located in India, Myanmar, Colombia, and Armenia), to rates of 8 and higher in 14 subnational regions, located in sub-Saharan Africa and Afghanistan. Areas with high-fertility clusters were mostly associated with areas of low prevalence of women with secondary or higher education, low use of contraception, and high unmet needs for family planning, although exceptions existed.

INTERPRETATION

Substantial within-country variation in the distribution of fertility rates highlights the need for tailored programmes and strategies in high-fertility cluster areas to increase the use of contraception and access to secondary education, and to reduce unmet need for family planning.

FUNDING

Wellcome Trust, the UK Foreign, Commonwealth and Development Office, and the Bill & Melinda Gates Foundation.

Measuring the availability and geographical accessibility of maternal health services across sub-Saharan Africa

BACKGROUND

With universal health coverage a key component of the 2030 Sustainable Development Goals, targeted monitoring is crucial for reducing inequalities in the provision of services. However, monitoring largely occurs at the national level, masking sub-national variation. Here, we estimate indicators for measuring the availability and geographical accessibility of services, at national and sub-national levels across sub-Saharan Africa, to show how data at varying spatial scales and input data can considerably impact monitoring outcomes.

METHODS

Availability was estimated using the World Health Organization guidelines for monitoring emergency obstetric care, defined as the number of hospitals per 500,000 population. Geographical accessibility was estimated using the Lancet Commission on Global Surgery, defined as the proportion of pregnancies within 2 h of the nearest hospital. These were calculated using geo-located hospital data for sub-Saharan Africa, with their associated travel times, along with small area estimates of population and pregnancies. The results of the availability analysis were then compared to the results of the accessibility analysis, to highlight differences between the availability and geographical accessibility of services.

RESULTS

Despite most countries meeting the targets at the national level, we identified substantial sub-national variation, with 58% of the countries having at least one administrative unit not meeting the availability target at province level and 95% at district level. Similarly, 56% of the countries were found to have at least one province not meeting the accessibility target, increasing to 74% at the district level. When comparing both availability and accessibility within countries, most countries were found to meet both targets; however sub-nationally, many countries fail to meet one or the other.

CONCLUSION

While many of the countries met the targets at the national level, we found large within-country variation. Monitoring under the current guidelines, using national averages, can mask these areas of need, with potential consequences for vulnerable women and children. It is imperative therefore that indicators for monitoring the availability and geographical accessibility of health care reflect this need, if targets for universal health coverage are to be met by 2030.

Incorporating hydrology into climate suitability models changes projections of malaria transmission in Africa

Continental-scale models of malaria climate suitability typically couple well-established temperature-response models with basic estimates of vector habitat availability using rainfall as a proxy. Here we show that across continental Africa, the estimated geographic range of climatic suitability for malaria transmission is more sensitive to the precipitation threshold than the thermal response curve applied. To address this problem we use downscaled daily climate predictions from seven GCMs to run a continental-scale hydrological model for a process-based representation of mosquito breeding habitat availability. A more complex pattern of malaria suitability emerges as water is routed through drainage networks and river corridors serve as year-round transmission foci. The estimated hydro-climatically suitable area for stable malaria transmission is smaller than previous models suggest and shows only a very small increase in state-of-the-art future climate scenarios. However, bigger geographical shifts are observed than with most rainfall threshold models and the pattern of that shift is very different when using a hydrological model to estimate surface water availability for vector breeding.

Prior studies mapping climatologically suitable areas for malaria transmission have used relatively simple thresholds for precipitation. Here the authors show that when models incorporate hydrological processes a more complex pattern of malaria suitability emerges in Africa and future shifts in suitability are more pronounced.

Spatial inequalities in skilled attendance at birth in Ghana: a multilevel analysis integrating health facility databases with household survey data

Objective

This study aimed at using survey data to predict skilled attendance at birth (SBA) across Ghana from healthcare quality and health facility accessibility.

Methods

Through a cross-sectional, observational study, we used a random intercept mixed effects multilevel logistic modelling approach to estimate the odds of having SBA and then applied model estimates to spatial layers to assess the probability of SBA at high-spatial resolution across Ghana. We combined data from the Demographic and Health Survey (DHS), routine birth registers, a service provision assessment of emergency obstetric care services, gridded population estimates and modelled travel time to health facilities.

Results

Within an hour’s travel, 97.1% of women sampled in the DHS could access any health facility, 96.6% could reach a facility providing birthing services, and 86.2% could reach a secondary hospital. After controlling for characteristics of individual women, living in an urban area and close proximity to a health facility with high-quality services were significant positive determinants of SBA uptake. The estimated variance suggests significant effects of cluster and region on SBA as 7.1% of the residual variation in the propensity to use SBA is attributed to unobserved regional characteristics and 16.5% between clusters within regions.

Conclusion

Given the expansion of primary care facilities in Ghana, this study suggests that higher quality healthcare services, as opposed to closer proximity of facilities to women, is needed to widen SBA uptake and improve maternal health.

The influence of distance and quality on utilisation of birthing services at health facilities in Eastern Region, Ghana

Objectives

Skilled birth attendance is the single most important intervention to reduce maternal mortality. However, studies have not used routinely collected health service birth data at named health facilities to understand the influence of distance and quality of care on childbirth service utilisation. Thus, this paper aims to quantify the influence of distance and quality of healthcare on utilisation of birthing services using routine health data in Eastern Region, Ghana.

Methods

We used a spatial interaction model (a model that predicts movement from one place to another) drawing on routine birth data, emergency obstetric care surveys, gridded estimates of number of pregnancies and health facility location. We compared travel distances by sociodemographic characteristics and mapped movement patterns.

Results

A kilometre increase in distance significantly reduced the prevalence rate of the number of women giving birth in health facilities by 6.7%. Although quality care increased the number of women giving birth in health facilities, its association was insignificant. Women travelled further than expected to give birth at facilities, on average journeying 4.7 km beyond the nearest facility with a recorded birth. Women in rural areas travelled 4 km more than urban women to reach a hospital. We also observed that 56% of women bypassed the nearest hospital to their community.

Conclusion

This analysis provides substantial opportunities for health planners and managers to understand further patterns of skilled birth service utilisation, and demonstrates the value of routine health data. Also, it provides evidence-based information for improving maternal health service provision by targeting specific communities and health facilities.

How accurate are modelled birth and pregnancy estimates? Comparison of four models using high resolution maternal health census data in southern Mozambique

Background

Existence of inequalities in quality and access to healthcare services at subnational levels has been identified despite a decline in maternal and perinatal mortality rates at national levels, leading to the need to investigate such conditions using geographical analysis. The need to assess the accuracy of global demographic distribution datasets at all subnational levels arises from the current emphasis on subnational monitoring of maternal and perinatal health progress, by the new targets stated in the Sustainable Development Goals.

Methods

The analysis involved comparison of four models generated using Worldpop methods, incorporating region-specific input data, as measured through the Community Level Intervention for Pre-eclampsia (CLIP) project. Normalised root mean square error was used to determine and compare the models’ prediction errors at different administrative unit levels.

Results

The models’ prediction errors are lower at higher administrative unit levels. All datasets showed the same pattern for both the live birth and pregnancy estimates. The effect of improving spatial resolution and accuracy of input data was more prominent at higher administrative unit levels.

Conclusion

The validation successfully highlighted the impact of spatial resolution and accuracy of maternal and perinatal health data in modelling estimates of pregnancies and live births. There is a need for more data collection techniques that conduct comprehensive censuses like the CLIP project. It is also imperative for such projects to take advantage of the power of mapping tools at their disposal to fill the gaps in the availability of datasets for populated areas.

Local level estimates of food, drink and tobacco expenditure for Great Britain

We present expenditure estimates for 106 product categories across Great Britain for the years 2008-2016. Estimates are at the Local Authority District level (n = 380) and the categories cover all food, drink and tobacco commodities. Reliable, local level expenditure estimates are crucial for understanding broader market trends, assessing economic stability and for projections. This is especially important for commodities such as alcohol, tobacco and unhealthy foods due to their role in the prevalence of non-communicable diseases. There has been relatively little research into local area spatial patterns of expenditure, with existing estimates often of insufficient resolution for informing planning decisions. We use spatial microsimulation to create an archive of expenditure datasets. This was achieved by linking socio-demographic foundations with detailed datasets on individual expenditure. Whilst initially developed to aid investigations into sociodemographic trends in the meat industry, the data have reuse potential in a number of disciplines, including public health, economics, retail geography and environmental management. The framework could be applied to other regions with appropriate data.