ESBL-producing Enterobacteriaceae in a rural Rwandan community: Carriage among community members, livestock, farm products and environment.

OBJECTIVES: Extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE) are spreading globally. However, respective data from African communities including livestock and environmental specimens are rare. In a rural community of southern Rwanda, we assessed intestinal carriage of ESBL-PE among residents and livestock as well as presence in household specimens and examined associated factors. METHODS: Samples of humans and livestock (both rectal swabs), soil, water, vegetables and animal products were collected within 312 community households in Sovu, Southern Rwanda. Specimens were screened for ESBL-PE on chromogenic agar, and susceptibility to common antibiotics was determined by disc diffusion assays. Socio-demographic information was collected with questionnaires focusing on the socio-economic background, alimentation, living conditions, hygiene measures and medical history of the participants. RESULTS: Data and specimens from 312 randomly selected households including 617 human beings, 620 livestock and of approximately each 300 kitchen vegetables, animal products, soil and drinking water were analysed. Overall, 14.8% of 2508 collected samples were positive for ESBL-PE; figures were highest for humans (37.9%) and livestock (15.6%), lower for vegetables (3.8%) and animal products (3.3%), and lowest for soil (1.6%) and water (0.6%). Most detected ESBL-PE were Escherichia coli (93.5%) in addition to Klebsiella pneumoniae (6.5%). Cross-resistance to ampicillin-sulbactam, ciprofloxacin and co-trimoxazole was common. Logistic regression identified increasing age, another ESBL-PE positive household member, prolonged time for fetching water, current diarrhoea and the ability to pay school fees as independent predictors of intestinal ESBL-PE carriage among community members. CONCLUSIONS: ESBL-PE carriage is common in a rural Rwandan farming community. Carriage in livestock is not associated with human carriage. Associated factors suggest few addressable risk factors. The data indicate that in southern Rwanda, ESBL-PE are no longer primarily hospital-based but circulate in the community.

Predictors for achieving adequate antenatal care visits during pregnancy: a cross-sectional study in rural Northwest Rwanda.

BACKGROUND: Inadequate antenatal care (ANC) in low-income countries has been identified as a risk factor for poor pregnancy outcome. While many countries, including Rwanda, have near universal ANC coverage, a significant proportion of pregnant women do not achieve the recommended regimen of four ANC visits. The present study aimed to explore the factors associated with achieving the recommendation, with an emphasis on the distance from household to health facilities. METHODS: A geo-referenced cross-sectional study was conducted in Rutsiro district, Western province of Rwanda with 360 randomly selected women. Multiple logistic regression analysis including adjusted odd ratio (aOR) were performed to identify factors associated with achieving the recommended four ANC visits. RESULTS: The majority (65.3%) of women had less than four ANC visits during pregnancy. We found a significant and negative association between distance from household to health facility and achieving the recommended four ANC visits. As the distance increased by 1 km, the odds of achieving the four ANC visits decreased by 19% (aOR = 0.81, P = 0.024). The odds of achieving the recommended four ANC visits were nearly two times higher among mothers with secondary education compared with mothers with primary education or less (aOR = 1.90, P = 0.038). In addition, mothers who responded that their household members always seek health care when necessary had 1.7 times higher odds of achieving four ANC visits compared with those who responded as unable to seek health care (aOR = 1.7, P = 0.041). Furthermore, mothers from poor households had 2.1 times lower odds of achieving four ANC visits than mothers from slightly better-off households (aOR = 2.1, P = 0.028). CONCLUSIONS: Findings from the present study suggest that, in Rutsiro district, travel distance to health facility, coupled with socio-economic constraints, including low education and poverty can make it difficult for pregnant women to achieve the recommended ANC regimen. Innovative strategies are needed to decrease distance by bringing ANC services closer to pregnant women and to enhance ANC seeking behaviour. Interventions should also focus on supporting women to attain at least secondary education level as well as to improve the household socioeconomic status of pregnant women, with a particular focus on women from poor households.

Even low levels of tree cover improve dietary quality in West Africa.

Forests are attracting attention as a promising avenue to provide nutritious and "free" food without damaging the environment. Yet, we lack knowledge on the extent to which this holds in areas with sparse tree cover, such as in West Africa. This is largely due to the fact that existing methods are poorly designed to quantify tree cover in drylands. In this study, we estimate how various levels of tree cover across West Africa affect children's (aged 12-59 months) consumption of vitamin A-rich foods. We do so by combining detailed tree cover estimates based on PlanetScope imagery (3 m resolution) with Demographic Health Survey data from >15,000 households. We find that the probability of consuming vitamin A-rich foods increases from 0.45 to 0.53 with an increase in tree cover from the median value of 8.8 to 16.8% (which is the tree cover level at which the predicted probability of consuming vitamin A-rich foods is the highest). Moreover, we observe that the effects of tree cover vary across poverty levels and ecoregions. The poor are more likely than the non-poor to consume vitamin A-rich foods at low levels of tree cover in the lowland forest-savanna ecoregions, whereas the difference between poor and non-poor is less pronounced in the Sahel-Sudan. These results highlight the importance of trees and forests in sustainable food system transformation, even in areas with sparse tree cover.

Scattered tree death contributes to substantial forest loss in California.

In recent years, large-scale tree mortality events linked to global change have occurred around the world. Current forest monitoring methods are crucial for identifying mortality hotspots, but systematic assessments of isolated or scattered dead trees over large areas are needed to reduce uncertainty on the actual extent of tree mortality. Here, we mapped individual dead trees in California using sub-meter resolution aerial photographs from 2020 and deep learning-based dead tree detection. We identified 91.4 million dead trees over 27.8 million hectares of vegetated areas (16.7-24.7% underestimation bias when compared to field data). Among these, a total of 19.5 million dead trees appeared isolated, and 60% of all dead trees occurred in small groups ( ≤ 3 dead trees within a 30 × 30 m grid), which is largely undetected by other state-level monitoring methods. The widespread mortality of individual trees impacts the carbon budget and sequestration capacity of California forests and can be considered a threat to forest health and a fuel source for future wildfires.

Mapping every adult baobab (Adansonia digitata L.) across the Sahel and relationships to rural livelihoods.

The baobab tree (Adansonia digitata L.) is an integral part of rural livelihoods throughout the African continent. However, the combined effects of climate change and increasing global demand for baobab products are currently exerting pressure on the sustainable utilization of these resources. Here we use sub-metre-resolution satellite imagery to identify the presence of nearly 2.8 million (underestimation bias 27.1%) baobab trees in the Sahel, a dryland region of 2.4 million km2. This achievement is considered an essential step towards an improved management and monitoring system of valuable woody species. Using Senegal as a case country, we find that 94% of rural buildings have at least one baobab tree in their immediate surroundings and that the abundance of baobabs is associated with a higher likelihood of people consuming a highly nutritious food group: dark green leafy vegetables. The generated database showcases the feasibility of mapping the location of single tree species at a sub-continental scale, providing vital information in times when deforestation and climate change cause the extinction of numerous tree species.

The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe.

Trees are an integral part in European landscapes, but only forest resources are systematically assessed by national inventories. The contribution of urban and agricultural trees to national-level carbon stocks remains largely unknown. Here we produced canopy cover, height and above-ground biomass maps from 3-meter resolution nanosatellite imagery across Europe. Our biomass estimates have a systematic bias of 7.6% (overestimation; R = 0.98) compared to national inventories of 30 countries, and our dataset is sufficiently highly resolved spatially to support the inclusion of tree biomass outside forests, which we quantify to 0.8 petagrams. Although this represents only 2% of the total tree biomass, large variations between countries are found (10% for UK) and trees in urban areas contribute substantially to national carbon stocks (8% for the Netherlands). The agreement with national inventory data, the scalability, and spatial details across landscapes, including trees outside forests, make our approach attractive for operational implementation to support national carbon stock inventory schemes.

Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda.

Trees sustain livelihoods and mitigate climate change but a predominance of trees outside forests and limited resources make it difficult for many tropical countries to conduct automated nation-wide inventories. Here, we propose an approach to map the carbon stock of each individual overstory tree at the national scale of Rwanda using aerial imagery from 2008 and deep learning. We show that 72% of the mapped trees are located in farmlands and savannas and 17% in plantations, accounting for 48.6% of the national aboveground carbon stocks. Natural forests cover 11% of the total tree count and 51.4% of the national carbon stocks, with an overall carbon stock uncertainty of 16.9%. The mapping of all trees allows partitioning to any landscapes classification and is urgently needed for effective planning and monitoring of restoration activities as well as for optimization of carbon sequestration, biodiversity and economic benefits of trees.

More than one quarter of Africa's tree cover is found outside areas previously classified as forest.

The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = -6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies.