Because space matters: conceptual framework to help distinguish slum from non-slum urban areas

Association Between Household Deprivation and Living in Informal Settlements and Incidence of Diarrhea in Children Under 5 in Eleven Latin American Cities

Diarrhea is a leading cause of death in children globally, mostly due to inadequate sanitary conditions and overcrowding. Poor housing quality and lack of tenure security that characterize informal settlements are key underlying contributors to these risk factors for childhood diarrhea deaths. The objective of this study is to better understand the physical attributes of informal settlement households in Latin American cities that are associated with childhood diarrhea. We used data from a household survey (Encuesta CAF) conducted by the Corporación Andina de Fomento (CAF), using responses from sampled individuals in eleven cities. We created a household deprivation score based on household water and sewage infrastructure, overcrowding, flooring and wall material, and security of tenure. We fitted a multivariable logistic regression model to estimate odds ratios (OR) and 95% confidence intervals (95% CI) to test the association between the deprivation score and its individual components and childhood diarrhea during the prior 2 weeks. We included a total of 4732 households with children, out of which 12.2% had diarrhea in the 2-week period prior to completing the survey. After adjusting for respondent age, gender, and city, we found a higher risk of diarrhea associated with higher household deprivation scores. Specifically, we found that the odds of diarrhea for children living in a mild and severe deprived household were 1.04 (95% CI 0.84-1.28) and 3.19 times (95% CI 1.80-5.63) higher, respectively, in comparison to households with no deprivation. These results highlight the connections between childhood health and deprived living conditions common in informal settlements.

Trends and Inequalities in Maternal and Newborn Health Services for Unplanned Settlements of Lusaka City, Zambia

Living conditions and other factors in urban unplanned settlements present unique challenges for improving maternal and newborn health (MNH), yet MNH inequalities associated with such challenges are not well understood. This study examined trends and inequalities in coverage of MNH services in the last 20 years in unplanned and planned settlements of Lusaka City, Zambia. Geospatial information was used to map Lusaka's settlements and health facilities. Zambia Demographic Health Surveys (ZDHS 2001, 2007, 2013/2014, and 2018) were used to compare antenatal care (ANC), institutional delivery, and Cesarean section (C-section) coverage, and neonatal mortality rates between the poorer 60% and richer 40% households. Health Management Information System (HMIS) data from 2018 to 2021 were used to compute service volumes and coverage rates for ANC1 and ANC4, and institutional delivery and C-sections by facility level and type in planned and unplanned settlements. Although the correlation is not exact, our data analysis showed close alignment; and thus, we opted to use the 60% poorer and 40% richer groups as a proxy for households in unplanned versus planned settlements. Unplanned settlements were serviced by primary centers or first-level hospitals. ZDHS findings show that by 2018, at least one ANC visit and institutional delivery became nearly universal throughout Lusaka, but early and four or more ANC visits, C-sections, and neonatal mortality rates remained worse among poorer than richer women in ZDHS. In HMIS, ANC and institutional delivery volumes were highest in public facilities, especially in unplanned settlements. The volume of C-sections was much greater within facilities in planned than unplanned settlements. Our study exposed persistent gaps in timing and use of ANC and emergency obstetric care between unplanned and planned communities. Closing such gaps requires strengthening outreach early and consistently in pregnancy and increasing emergency obstetric care capacities and referrals to improve access to important MNH services for women and newborns in Lusaka's unplanned settlements.

Developing an intervention to improve the quality of childcare centers in resource-poor urban settings: a mixed methods study in Nairobi, Kenya

Background

Globally, 350 million under-5s do not have adequate childcare. This may damage their health and development and undermine societal and economic development. Rapid urbanization is changing patterns of work, social structures, and gender norms. Parents, mainly mothers, work long hours for insecure daily wages. To respond to increasing demand, childcare centers have sprung up in informal settlements. However, there is currently little or no support to ensure they provide safe, nurturing care accessible to low-income families. Here, we present the process of co-designing an intervention, delivered by local government community health teams to improve the quality of childcare centers and ultimately the health and development of under-5 children in informal settlements in Kenya.

Methods

This mixed methods study started with a rapid mapping of the location and basic characteristics of all childcare centers in two informal settlements in Nairobi. Qualitative interviews were conducted with parents and grandparents (n = 44), childcare providers, and community health teams (n = 44). A series of 7 co-design workshops with representatives from government and non-governmental organizations (NGOs), community health teams, and childcare providers were held to design the intervention. Questionnaires to assess the knowledge, attitudes, and practices of community health volunteers (n = 22) and childcare center providers (n = 66) were conducted.

Results

In total, 129 childcare centers were identified -55 in Korogocho and 77 in Viwandani. School-based providers dominated in Korogocho (73%) while home-based centers were prevalent in Viwandani (53%). All centers reported minimal support from any organization (19% supported) and this was particularly low among home-based (9%) and center-based (14%) providers. Home-based center providers were the least likely to be trained in early childhood development (20%), hence the co-designed intervention focused on supporting these centers. All co-design stakeholders agreed that with further training, community health volunteers were well placed to support these informal centers. Findings showed that given the context of informal settlements, support for strengthening management within the centers in addition to the core domains of WHO's Nurturing Care Framework was required as a key component of the intervention.

Conclusion

Implementing a co-design process embedded within existing community health systems and drawing on the lived experiences of childcare providers and parents in informal settlements facilitated the development of an intervention with the potential for scalability and sustainability. Such interventions are urgently needed as the number of home-based and small center-based informal childcare centers is growing rapidly to meet the demand; yet, they receive little support to improve quality and are largely unregulated. Childcare providers, and government and community health teams were able to co-design an intervention delivered within current public community health structures to support centers in improving nurturing care. Further research on the effectiveness and sustainability of support to private and informal childcare centers in the context of low-income urban neighborhoods is needed.

Identifying deprived "slum" neighbourhoods in the Greater Accra Metropolitan Area of Ghana using census and remote sensing data

Background

Identifying urban deprived areas, including slums, can facilitate more targeted planning and development policies in cities to reduce socio-economic and health inequities, but methods to identify them are often ad-hoc, resource intensive, and cannot keep pace with rapidly urbanizing communities.

Objectives

We apply a spatial modelling approach to identify census enumeration areas (EAs) in the Greater Accra Metropolitan Area (GAMA) of Ghana with a high probability of being a deprived area using publicly available census and remote sensing data.

Methods

We obtained United Nations (UN) supported field mapping data that identified deprived "slum" areas in Accra's urban core, data on housing and population conditions from the most recent census, and remotely sensed data on environmental conditions in the GAMA. We first fitted a Bayesian logistic regression model on the data in Accra's urban core (n=2,414 EAs) that estimated the relationship between housing, population, and environmental predictors and being a deprived area according to the UN's deprived area assessment. Using these relationships, we predicted the probability of being a deprived area for each of the 4,615 urban EAs in GAMA.

Results

899 (19%) of the 4,615 urban EAs in GAMA, with an estimated 745,714 residents (22% of its urban population), had a high predicted probability (≥80%) of being a deprived area. These deprived EAs were dispersed across GAMA and relatively heterogeneous in their housing and environmental conditions, but shared some common features including a higher population density, lower elevation and vegetation abundance, and less access to indoor piped water and sanitation.

Conclusion

Our approach using ubiquitously available administrative and satellite data can be used to identify deprived neighbourhoods where interventions are warranted to improve living conditions, and track progress in achieving the Sustainable Development Goals aiming to reduce the population living in unsafe or vulnerable human settlements.

Intimate partner violence among young women in Ibadan, Nigeria: are there slum and non-slum differences?

This study determined the past-year prevalence of physical, sexual and psychological intimate partner violence (IPV) and associated factors among young women in urban slums and non-slums of Ibadan, Nigeria.A cross-sectional study, using a multistage cluster sampling method was used to select 1050 ever-partnered young women aged between 18 and 24 years from the five Local Government Areas (LGAs) in Ibadan municipal. All localities were classified into slums and non-slums using the UN-Habitat 2003 criterion. Independent variables were respondents' and partners' characteristics. Dependent variables were physical, sexual and psychological IPV. Data were analysed using descriptive statistics and binary logistic regression model (α0.05).Prevalence of physical (31.4%, 13.4%), sexual (37.1%, 18.3%), and psychological IPV (58.6%, 31.5%) were significantly higher in the slum than non-slum communities. Multivariate analysis showed that secondary education (aOR:0.45, 95%CI: 0.21 - 0.92) reduced IPV experience while being unmarried (aOR:2.83, 95%CI: 1.28 - 6.26), partner's alcohol use (aOR:1.97, 95%CI: 1.22 - 3.18), and partner's relationship with other women (aOR:1.79, 95%CI: 1.10 -2.91) increased IPV experience in slum communities. In non-slum communities, having children (aOR:2.99, 95%CI: 1.05-8.51), non-consensual sexual debut (aOR: 1.88, 95%CI: 1.07-3.31) and witness of abuse in childhood (aOR:1.82: 95%CI: 1.01 - 3.28) increased experience of IPV. Acceptance of IPV and partner's witness of abuse in childhood increased experience of IPV in both settings.This study confirms that IPV is common among young women in Ibadan, Nigeria, but higher among women in slum communities. Findings also showed different factors associated with IPV in slum and non-slum communities. Therefore, targeted interventions for each urban stratum are recommended.

A review of spatial characteristics influencing circular economy in the built environment

Industrialization, population growth, and urbanization are all trends driving the explosive growth of the construction industry. Creating buildings to house people and operate industry, together with building infrastructure to provide public services, requires prodigious quantities of energy and materials. Most of these virgin materials are non-renewable, and resource shortages caused by the development of the built environment are becoming increasingly inevitable. The gradually evolved circular economy (CE) is considered a way to ease the depletion of resources by extending service life, increasing efficiency, and converting waste into resources. However, the circularity of construction materials shows heavy regional distinctness due to the difference in spatial contexts in the geographical sense, resulting in the same CE business models (CEBMs) not being adapted to all regions. To optimize resource loops and formulate effective CEBMs, it is essential to understand the relationship between space and CE in the built environment. This paper reviews existing publications to summarize the research trends, examine how spatial features are reflected in the circularity of materials, and identify connections between spatial and CE clues. We found that the majority of contributors in this interdisciplinary field are from countries with middle to high levels of urbanization. Further, the case analysis details the material dynamics in different spatial contexts and links space and material cycles. The results indicate that the spatial characteristics can indeed influence the circularity of materials through varying resource cycling patterns. By utilizing spatial information wisely can help design locally adapted CEBMs and maximize the value chain of construction materials.

The Impact of the Pandemic on Poor Urban Neighborhoods: A Participatory Action Research Study of a "Favela" in Rio de Janeiro

The pandemic provoked by the coronavirus disease 2019 (COVID-19) devastated poor urban neighborhoods across the world, particularly in the Global South, although empirical data on this remain limited. In this article, the authors present data collected through a mixed-methods, participatory action research approach on the impacts of the pandemic in Cidade de Deus, a "favela," or poor informal settlement, in Rio de Janeiro. The authors find that the indirect consequences of COVID-19, in particular economic and mental health problems, were experienced as more severe than the direct effects of the virus itself, despite high rates of infection and mortality. The study also revealed that residents relied heavily on one another through local systems of mutual aid to address immediate crises. These findings suggest that the pandemic provoked a complex and diverse set of challenges and actions in the economic, social, physical, and mental spheres of poor urban neighborhoods.

A Qualitative Assessment of Place and Mental Health: Perspectives of Young Women Ages 18-24 Living in the Urban Slums of Kampala, Uganda

This paper examines the link between place and mental health using a qualitative assessment and focus group discussion with young women, ages 18 to 24 years of age, residing in three slums in Kampala, Uganda. The assessment, conducted in August of 2022, engaged 15 women who participated in Uganda Youth Development Drop-in center activities. The objective was to assess mental health and the link between place and mental health. Facilitated group discussions and photograph review yielded the following results. In terms of understanding their views of mental health and wellbeing, participants clearly focused on feelings. However, they also assessed resilience, the environment and a person's choice as relating to their mental health. Participants also found the physical spaces related to sports, education, worship, workplaces and green space to be linked to happiness. In terms of the attributes that were linked to sadness, participants listed the physical locations where drugs are sold, clubs for dancing and partying and also sanitation issues in the community. Participants frequently reported on the social environment and reflected on harassment, discrimination, alcohol use and criminal behavior that did not reflect a specific physical space, but rather the embedded social interactions they may face or observe by living in close proximity to hotspots for criminal activity. Given the dire shortages of mental health services and care that are available in this setting, a better understanding of young women's perceptions of place and mental health will be key for low-cost interventions and strategies to mitigate the contextual factors that may exacerbate mental illness.

Improving early childhood development in the context of the nurturing care framework in Kenya: A policy review and qualitative exploration of emerging issues with policy makers

Introduction

The Nurturing Care Framework (NCF) describes "nurturing care" as the ability of nations and communities to support caregivers and provide an environment that ensures children's good health and nutrition, protects them from threats, and provides opportunities for early learning through responsive and emotionally supportive interaction. We assessed the extent to which Kenyan government policies address the components of the NCF and explored policy/decision makers' views on policy gaps and emerging issues.

Methods

A search strategy was formulated to identify policy documents focusing on early childhood development (ECD), health and nutrition, responsive caregiving, opportunities for early learning and security and safety, which are key components of the NCF. We limited the search to policy documents published since 2010 when the Kenya constitution was promulgated and ECD functions devolved to county governments. Policy/decision-maker interviews were also conducted to clarify emerging gaps from policy data. Data was extracted, coded and analyzed based on the components of the NCF. Framework analysis was used for interview data with NCF being the main framework of analysis. The Jaccard's similarity coefficient was used to assess similarities between the themes being compared to further understand the challenges, successes and future plans of policy and implementation under each of the NCF domains.

Results

127 policy documents were retrieved from government e-repository and county websites. Of these, n = 91 were assessed against the inclusion criteria, and n = 66 were included in final analysis. The 66 documents included 47 County Integrated Development Plans (CIDPs) and 19 national policy documents. Twenty policy/decision-maker interviews were conducted. Analysis of both policy and interview data reveal that, while areas of health and nutrition have been considered in policies and county level plans (coefficients >0.5), the domains of early learning, responsive caregiving and safety and security face significant policy and implementation gaps (coefficients ≤ 0.5), particularly for the 0-3 year age group. Inconsistencies were noted between county level implementation plans and national policies in areas such as support for children with disabilities and allocation of budget to early learning and nutrition domains.

Conclusion

Findings indicate a strong focus on nutrition and health with limited coverage of responsive caregiving and opportunities for early learning domains. Therefore, if nurturing care goals are to be achieved in Kenya, policies are needed to support current gaps identified with urgent need for policies of minimum standards that provide support for improvements across all Nurturing Care Framework domains.

Uncertainty-Aware Interpretable Deep Learning for Slum Mapping and Monitoring

Over a billion people live in slums, with poor sanitation, education, property rights and working conditions having a direct impact on current residents and future generations. Slum mapping is one of the key problems concerning slums. Policymakers need to delineate slum settlements to make informed decisions about infrastructure development and allocation of aid. A wide variety of machine learning and deep learning methods have been applied to multispectral satellite images to map slums with outstanding performance. Since the physical and visual manifestation of slums significantly varies with geographical region and comprehensive slum maps are rare, it is important to quantify the uncertainty of predictions for reliable and confident application of models to downstream tasks. In this study, we train a U-Net model with Monte Carlo Dropout (MCD) on 13-band Sentinel-2 images, allowing us to calculate pixelwise uncertainty in the predictions. The obtained outcomes show that the proposed model outperforms the previous state-of-the-art model, having both higher AUPRC and lower uncertainty when tested on unseen geographical regions of Mumbai using the regional testing framework introduced in this study. We also use SHapley Additive exPlanations (SHAP) values to investigate how the different features contribute to our model’s predictions which indicate a certain shortwave infrared image band is a powerful feature for determining the locations of slums within images. With our results, we demonstrate the usefulness of including an uncertainty quantification approach in detecting slum area changes over time.

Factors associated with accessing and utilisation of healthcare and provision of health services for residents of slums in low and middle-income countries: a scoping review of recent literature

OBJECTIVE

To identify factors associated with accessing and utilisation of healthcare and provision of health services in slums.

DESIGN

A scoping review incorporating a conceptual framework for configuring reported factors.

DATA SOURCES

MEDLINE, Embase, CINAHL, Web of Science and the Cochrane Library were searched from their inception to December 2021 using slum-related terms.

ELIGIBILITY CRITERIA

Empirical studies of all designs reporting relevant factors in slums in low and middle-income countries.

DATA EXTRACTION AND SYNTHESIS

Studies were categorised and data were charted according to a preliminary conceptual framework refined by emerging findings. Results were tabulated and narratively summarised.

RESULTS

Of the 15 469 records retrieved from all years, 4368 records dated between 2016 and 2021 were screened by two independent reviewers and 111 studies were included. The majority (63 studies, 57%) were conducted in Asia, predominantly in India. In total, 104 studies examined healthcare access and utilisation from slum residents' perspective while only 10 studies explored provision of health services from providers/planners' perspective (three studies included both). A multitude of factors are associated with accessing, using and providing healthcare in slums, including recent migration to slums; knowledge, perception and past experience of illness, healthcare needs and health services; financial constraint and competing priorities between health and making a living; lacking social support; unfavourable physical environment and locality; sociocultural expectations and stigma; lack of official recognition; and existing problems in the health system.

CONCLUSION

The scoping review identified a significant body of recent literature reporting factors associated with accessing, utilisation and provision of healthcare services in slums. We classified the diverse factors under seven broad categories. The findings can inform a holistic approach to improving health services in slums by tackling barriers at different levels, taking into account local context and geospatial features of individual slums. SYSTEMATIC REVIEW REGISTRATION NUMBER: https://osf.io/694t2.

A community engagement approach for an integrated early childhood development intervention: a case study of an urban informal settlement with Kenyans and embedded refugees

BACKGROUND

Community engagement is crucial for the design and implementation of community-based early childhood development (ECD) programmes. This paper aims to share key components and learnings of a community engagement process for an integrated ECD intervention. The lessons shared are drawn from a case study of urban informal settlement with embedded refugees in Nairobi, Kenya.

METHODS

We conducted three stakeholder meetings with representatives from the Ministry of Health at County and Sub-County, actors in the ECD sector, and United Nations agency in refugee management, a transect walk across five villages (Ngando, Muslim, Congo, Riruta and Kivumbini); and, six debrief meetings by staff from the implementing organization. The specific steps and key activities undertaken, the challenges faced and benefits accrued from the community engagement process are highlighted drawing from the implementation team's perspective.

RESULTS

Context relevant, well-planned community engagement approaches can be integrated into the five broad components of stakeholder engagement, formative research, identification of local resources, integration into local lives, and shared control/leadership with the local community. These can yield meaningful stakeholder buy-in, community support and trust, which are crucial for enabling ECD programme sustainability.

CONCLUSION

Our experiences underscore that intervention research on ECD programmes in urban informal settlements requires a well-planned and custom-tailored community engagement model that is sensitive to the needs of each sub-group within the community to avoid unintentionally leaving anyone out.

Global prevalence and trends in hypertension and type 2 diabetes mellitus among slum residents: a systematic review and meta-analysis

OBJECTIVE

First, to obtain regional estimates of prevalence of hypertension and type 2 diabetes in urban slums; and second, to compare these with those in urban and rural areas.

DESIGN

Systematic review and meta-analysis.

ELIGIBILITY CRITERIA

Studies that reported hypertension prevalence using the definition of blood pressure ≥140/90 mm Hg and/or prevalence of type 2 diabetes.

INFORMATION SOURCES

Ovid MEDLINE, Cochrane CENTRAL and EMBASE from inception to December 2020.

RISK OF BIAS

Two authors extracted relevant data and assessed risk of bias independently using the Strengthening the Reporting of Observational Studies in Epidemiology guideline.

SYNTHESIS OF RESULTS

We used random-effects meta-analyses to pool prevalence estimates. We examined time trends in the prevalence estimates using meta-regression regression models with the prevalence estimates as the outcome variable and the calendar year of the publication as the predictor.

RESULTS

A total of 62 studies involving 108 110 participants met the inclusion criteria. Prevalence of hypertension and type 2 diabetes in slum populations ranged from 4.2% to 52.5% and 0.9% to 25.0%, respectively. In six studies presenting comparator data, all from the Indian subcontinent, slum residents were 35% more likely to be hypertensive than those living in comparator rural areas and 30% less likely to be hypertensive than those from comparator non-slum urban areas.

LIMITATIONS OF EVIDENCE

Of the included studies, only few studies from India compared the slum prevalence estimates with those living in non-slum urban and rural areas; this limits the generalisability of the finding.

INTERPRETATION

The burden of hypertension and type 2 diabetes varied widely between countries and regions and, to some degree, also within countries.

PROSPERO REGISTRATION NUMBER

CRD42017077381.

Inequity of healthcare access and use and catastrophic health spending in slum communities: a retrospective, cross-sectional survey in four countries

Introduction

Tracking the progress of universal health coverage (UHC) is typically at a country level. However, country-averages may mask significant small-scale variation in indicators of access and use, which would have important implications for policy choice to achieve UHC.

Methods

We conducted a retrospective cross-sectional household and individual-level survey in seven slum sites across Nigeria, Kenya, Bangladesh and Pakistan. We estimated the adjusted association between household capacity to pay and report healthcare need, use and spending. Catastrophic health expenditure was estimated by five different methods.

Results

We surveyed 7002 households and 6856 adults. Gini coefficients were wide, ranging from 0.32 to 0.48 across the seven sites. The total spend of the top 10% of households was 4–47 times more per month than the bottom 10%. Households with the highest budgets were: more likely to report needing care (highest vs lowest third of distribution of budgets: +1 to +31 percentage points (pp) across sites), to spend more on healthcare (2.0 to 6.4 times higher), have more inpatient and outpatient visits per year in five sites (1.0 to 3.0 times more frequently), spend more on drugs per visit (1.1 to 2.2 times higher) and were more likely to consult with a doctor (1.0 to 2.4 times higher odds). Better-off households were generally more likely to experience catastrophic health expenditure when calculated according to four methods (−1 to +12 pp), but much less likely using a normative method (−60 to −80 pp).

Conclusions

Slums have a very high degree of inequality of household budget that translates into inequities in the access to and use of healthcare. Evaluation of UHC and healthcare access interventions targeting these areas should consider distributional effects, although the standard measures may be unreliable.

Earth Observations and Statistics: Unlocking Sociodemographic Knowledge through the Power of Satellite Images

The continuous urbanisation in most Low-to-Middle-Income-Country (LMIC) cities is accompanied by rapid socio-economic changes in urban and peri-urban areas. Urban transformation processes, such as gentrification as well as the increase in poor urban neighbourhoods (e.g., slums) produce new urban patterns. The intersection of very rapid socio-economic and demographic dynamics are often insufficiently understood, and relevant data for understanding them are commonly unavailable, dated, or too coarse (resolution). Traditional survey-based methods (e.g., census) are carried out at low temporal granularity and do not allow for frequent updates of large urban areas. Researchers and policymakers typically work with very dated data, which do not reflect on-the-ground realities and data aggregation hide socio-economic disparities. Therefore, the potential of Earth Observations (EO) needs to be unlocked. EO data have the ability to provide information at detailed spatial and temporal scales so as to support monitoring transformations. In this paper, we showcase how recent innovations in EO and Artificial Intelligence (AI) can provide relevant, rapid information about socio-economic conditions, and in particular on poor urban neighbourhoods, when large scale and/or multi-temporal data are required, e.g., to support Sustainable Development Goals (SDG) monitoring. We provide solutions to key challenges, including the provision of multi-scale data, the reduction in data costs, and the mapping of socio-economic conditions. These innovations fill data gaps for the production of statistical information, addressing the problems of access to field-based data under COVID-19.

Inequalities in the prevalence of major depressive disorder in Brazilian slum populations: a cross-sectional analysis

AIMS

The mental health of slum residents is under-researched globally, and depression is a significant source of worldwide morbidity. Brazil's large slum-dwelling population is often considered part of a general urban-poor demographic. This study aims to identify the prevalence and distribution of depression in Brazil and compare mental health inequalities between slum and non-slum populations.

METHODS

Data were obtained from Brazil's 2019 National Health Survey. Slum residence was defined based on the UN-Habitat definition for slums and estimated from survey responses. Doctor-diagnosed depression, Patient Health Questionnaire (PHQ-9)-screened depression and presence of undiagnosed depression (PHQ-9-screened depression in the absence of a doctor's diagnosis) were analysed as primary outcomes, alongside depressive symptom severity as a secondary outcome. Prevalence estimates for all outcomes were calculated. Multivariable logistic regression models were used to investigate the association of socioeconomic characteristics, including slum residence, with primary outcomes. Depressive symptom severity was analysed using generalised ordinal logistic regression.

RESULTS

Nationally, the prevalence of doctor diagnosed, PHQ-9 screened and undiagnosed depression were 9.9% (95% confidence interval (CI): 9.5-10.3), 10.8% (95% CI: 10.4-11.2) and 6.9% (95% CI: 6.6-7.2), respectively. Slum residents exhibited lower levels of doctor-diagnosed depression than non-slum urban residents (8.6%; 95% CI: 7.9-9.3 v. 10.7%; 95% CI: 10.2-11.2), while reporting similar levels of PHQ-9-screened depression (11.3%; 95% CI: 10.4-12.1 v. 11.3%; 95% CI: 10.8-11.8). In adjusted regression models, slum residence was associated with a lower likelihood of doctor diagnosed (adjusted odds ratio (adjusted OR): 0.87; 95% CI: 0.77-0.97) and PHQ-9-screened depression (adjusted OR: 0.87; 95% CI: 0.78-0.97). Slum residents showed a greater likelihood of reporting less severe depressive symptoms. There were significant ethnic/racial disparities in the likelihood of reporting doctor-diagnosed depression. Black individuals were less likely to report doctor-diagnosed depression (adjusted OR: 0.66; 95% CI: 0.57-0.75) than white individuals. A similar pattern was observed in Mixed Black (adjusted OR: 0.72; 95% CI: 0.66-0.79) and other (adjusted OR: 0.63; 95% CI: 0.45-0.88) ethnic/racial groups. Slum residents self-reporting a diagnosis of one or more chronic non-communicable diseases had greater odds of exhibiting all three primary depression outcomes.

CONCLUSIONS

Substantial inequalities characterise the distribution of depression in Brazil including in slum settings. People living in slums may have lower diagnosed rates of depression than non-slum urban residents. Understanding the mechanisms behind the discrepancy in depression diagnosis between slum and non-slum populations is important to inform health policy in Brazil, including in addressing potential gaps in access to mental healthcare.

Pharmacies in informal settlements: a retrospective, cross-sectional household and health facility survey in four countries

BACKGROUND

Slums or informal settlements characterize most large cities in LMIC. Previous evidence suggests pharmacies may be the most frequently used source of primary care in LMICs but that pharmacy services are of variable quality. However, evidence on pharmacy use and availability is very limited for slum populations.

METHODS

We conducted household, individual, and healthcare provider surveys and qualitative observations on pharmacies and pharmacy use in seven slum sites in four countries (Nigeria, Kenya, Pakistan, and Bangladesh). All pharmacies and up to 1200 households in each site were sampled. Adults and children were surveyed about their use of healthcare services and pharmacies were observed and their services, equipment, and stock documented.

RESULTS

We completed 7692 household and 7451 individual adults, 2633 individual child surveys, and 157 surveys of pharmacies located within the seven sites. Visit rates to pharmacies and drug sellers varied from 0.1 (Nigeria) to 3.0 (Bangladesh) visits per person-year, almost all of which were for new conditions. We found highly variable conditions in what constituted a "pharmacy" across the sites and most pharmacies did not employ a qualified pharmacist. Analgesics and antibiotics were widely available but other categories of medications, particularly those for chronic illness were often not available anywhere. The majority of pharmacies lacked basic equipment such as a thermometer and weighing scales.

CONCLUSIONS

Pharmacies are locally and widely available to residents of slums. However, the conditions of the facilities and availability of medicines were poor and prices relatively high. Pharmacies may represent a large untapped resource to improving access to primary care for the urban poor.

Earth Observation for Sustainable Infrastructure: A Review

Infrastructure is a fundamental sector for sustainable development and Earth observation has great potentials for sustainable infrastructure development (SID). However, implementations of the timely, large–scale and multi–source Earth observation are still limited in satisfying the huge global requirements of SID. This study presents a systematical literature review to identify trends of Earth observation for sustainable infrastructure (EOSI), investigate the relationship between EOSI and Sustainable Development Goals (SDGs), and explore challenges and future directions of EOSI. Results reveal the close associations of infrastructure, urban development, ecosystems, climate, Earth observation and GIS in EOSI, and indicate their relationships. In addition, from the perspective of EOSI–SDGs relationship, the huge potentials of EOSI are demonstrated from the 70% of the infrastructure influenced targets that can be directly or indirectly derived from Earth observation data, but have not been included in current SDG indicators. Finally, typical EOSI cases are presented to indicate challenges and future research directions. This review emphasizes the contributions and potentials of Earth observation to SID and EOSI is a powerful pathway to deliver on SDGs.

Analysis of OpenStreetMap Data Quality at Different Stages of a Participatory Mapping Process: Evidence from Slums in Africa and Asia

This paper examines OpenStreetMap data quality at different stages of a participatory mapping process in seven slums in Africa and Asia. Data were drawn from an OpenStreetMap-based participatory mapping process developed as part of a research project focusing on understanding inequalities in healthcare access of slum residents in the Global South. Descriptive statistics and qualitative analysis were employed to examine the following research question: What is the spatial data quality of collaborative remote mapping achieved by volunteer mappers in morphologically complex urban areas? Findings show that the completeness achieved by remote mapping largely depends on the morphology and characteristics of slums such as building density and rooftop architecture, varying from 84% in the best case, to zero in the most difficult site. The major scientific contribution of this study is to provide evidence on the spatial data quality of remotely mapped data through volunteer mapping efforts in morphologically complex urban areas such as slums; the results could provide insights into how much fieldwork would be needed in what level of complexity and to what extent the involvement of local volunteers in these efforts is required.

Peri-urban water, sanitation and hygiene in Lusaka, Zambia: photovoice empowering local assessment via ecological theory

Water, sanitation and hygiene (WASH) factors are responsible for 11.4% of deaths in Zambia, making WASH a key public health concern. Despite annual waterborne disease outbreaks in the nation's peri-urban (slum) settlements being linked to poor WASH, few studies have proactively analysed and conceptualised peri-urban WASH and its maintaining factors. Our study aimed to (a) establish residents' definition of peri-urban WASH and their WASH priorities; and (b) use ecological theory to analyse the peri-urban WASH ecosystem, highlighting maintaining factors. Our study incorporated 16 young people (aged 17-24) residing in peri-urban Lusaka, Zambia in a photovoice exercise. Participants took photographs answering the framing question, 'What is WASH in your community?' Then, through contextualisation and basic codifying, participants told the stories of their photographs and made posters to summarise problems and WASH priorities. Participant contextualisation and codifying further underwent theoretical thematic analysis to pinpoint causal factors alongside key players, dissecting the peri-urban WASH ecosystem via the five-tier ecological theory ranging from intrapersonal to public policy levels. Via ecological theory, peri-urban WASH was defined as: (a) poor practice (intrapersonal, interpersonal); (b) a health hazard (community norm); (c) substandard and unregulated (public policy, organisational); and (d) offering hope for change (intrapersonal, interpersonal). Linked to these themes, participant findings revealed a community level gap, with public policy level standards, regulations and implementation having minimal impact on overall peri-urban WASH and public health due to shallow community engagement and poor acknowledgement of the WASH realities of high-density locations. Rather than a top-down approach, participants recommended increased government-resident collaboration, offering residents more ownership and empowerment for intervention, implementation and defending of preferred peri-urban WASH standards.

Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews

BACKGROUND

The etiologies of chronic neurological diseases, which heavily contribute to global disease burden, remain far from elucidated. Despite available umbrella reviews on single contributing factors or diseases, no study has systematically captured non-purely genetic risk and/or protective factors for chronic neurological diseases.

METHODS

We performed a systematic analysis of umbrella reviews (meta-umbrella) published until September 20th, 2018, using broad search terms in MEDLINE, SCOPUS, Web of Science, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations & Theses, JBI Database of Systematic Reviews and Implementation Reports, DARE, and PROSPERO. The PRISMA guidelines were followed for this study. Reference lists of the identified umbrella reviews were also screened, and the methodological details were assessed using the AMSTAR tool. For each non-purely genetic factor association, random effects summary effect size, 95% confidence and prediction intervals, and significance and heterogeneity levels facilitated the assessment of the credibility of the epidemiological evidence identified.

RESULTS

We identified 2797 potentially relevant reviews, and 14 umbrella reviews (203 unique meta-analyses) were eligible. The median number of primary studies per meta-analysis was 7 (interquartile range (IQR) 7) and that of participants was 8873 (IQR 36,394). The search yielded 115 distinctly named non-genetic risk and protective factors with a significant association, with various strengths of evidence. Mediterranean diet was associated with lower risk of dementia, Alzheimer disease (AD), cognitive impairment, stroke, and neurodegenerative diseases in general. In Parkinson disease (PD) and AD/dementia, coffee consumption, and physical activity were protective factors. Low serum uric acid levels were associated with increased risk of PD. Smoking was associated with elevated risk of multiple sclerosis and dementia but lower risk of PD, while hypertension was associated with lower risk of PD but higher risk of dementia. Chronic occupational exposure to lead was associated with higher risk of amyotrophic lateral sclerosis. Late-life depression was associated with higher risk of AD and any form of dementia.

CONCLUSIONS

We identified several non-genetic risk and protective factors for various neurological diseases relevant to preventive clinical neurology, health policy, and lifestyle counseling. Our findings could offer new perspectives in secondary research (meta-research).

Informal urbanism in the state of uncertainty: forms of informality and urban health emergencies

Forms of informality—ranging from informal settlements to street vending and informal transport—have become integral, yet not necessarily limited to how cities of the global South work. Our aim in this paper is to explore the dynamics of informal urbanism in the face of the COVID-19 pandemic and the extent to which forms of informality can adapt in the state of uncertainty. This paper lies in the intersections of informal urbanism and urban design in relation to public health emergencies. This is an exploratory paper in nature, structured in three main sections to focus on the implications of the Coronavirus pandemic on informal settlements, street vending, and informal transport, respectively. We point to how different forms of informality work across cities and conclude by outlining some key considerations and discussing the role of urban design in addressing the capacities and challenges of informal urbanism in the state of uncertainty facing public health emergencies such as the Coronavirus pandemic.

COVID-19 and Slums: A Pandemic Highlights Gaps in Knowledge About Urban Poverty

According to the United Nations, about 1 billion persons live in so-called slums. Numerous studies have shown that this population is particularly vulnerable to infectious diseases. The current COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, emphatically underlines this problem. The often high-density living quarters coupled with a large number of persons per dwelling and the lack of adequate sanitation are reasons why measures to contain the pandemic only work to a limited extent in slums. Furthermore, assignment to risk groups for severe courses of COVID-19 caused by noncommunicable diseases (eg, cardiovascular diseases) is not possible due to inadequate data availability. Information on people living in slums and their health status is either unavailable or only exists for specific regions (eg, Nairobi). We argue that one of the greatest problems with regard to the COVID-19 pandemic in the context of slums in the Global South is the lack of data on the number of people, their living conditions, and their health status.

Impact of the societal response to COVID-19 on access to healthcare for non-COVID-19 health issues in slum communities of Bangladesh, Kenya, Nigeria and Pakistan: results of pre-COVID and COVID-19 lockdown stakeholder engagements

INTRODUCTION

With COVID-19, there is urgency for policymakers to understand and respond to the health needs of slum communities. Lockdowns for pandemic control have health, social and economic consequences. We consider access to healthcare before and during COVID-19 with those working and living in slum communities.

METHODS

In seven slums in Bangladesh, Kenya, Nigeria and Pakistan, we explored stakeholder perspectives and experiences of healthcare access for non-COVID-19 conditions in two periods: pre-COVID-19 and during COVID-19 lockdowns.

RESULTS

Between March 2018 and May 2020, we engaged with 860 community leaders, residents, health workers and local authority representatives. Perceived common illnesses in all sites included respiratory, gastric, waterborne and mosquitoborne illnesses and hypertension. Pre-COVID, stakeholders described various preventive, diagnostic and treatment services, including well-used antenatal and immunisation programmes and some screening for hypertension, tuberculosis, HIV and vectorborne disease. In all sites, pharmacists and patent medicine vendors were key providers of treatment and advice for minor illnesses. Mental health services and those addressing gender-based violence were perceived to be limited or unavailable. With COVID-19, a reduction in access to healthcare services was reported in all sites, including preventive services. Cost of healthcare increased while household income reduced. Residents had difficulty reaching healthcare facilities. Fear of being diagnosed with COVID-19 discouraged healthcare seeking. Alleviators included provision of healthcare by phone, pharmacists/drug vendors extending credit and residents receiving philanthropic or government support; these were inconsistent and inadequate.

CONCLUSION

Slum residents' ability to seek healthcare for non-COVID-19 conditions has been reduced during lockdowns. To encourage healthcare seeking, clear communication is needed about what is available and whether infection control is in place. Policymakers need to ensure that costs do not escalate and unfairly disadvantage slum communities. Remote consulting to reduce face-to-face contact and provision of mental health and gender-based violence services should be considered.

Need for an Integrated Deprived Area “Slum” Mapping System (IDEAMAPS) in Low- and Middle-Income Countries (LMICs)

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The first approach, classifying “slum households” in census and survey data, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human (visual) interpretation and machine classification of air or spaceborne imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of public services. We summarize common areas of understanding, and present a set of requirements and a framework to produce routine, accurate maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making across Low- and Middle-Income Countries (LMICs). We suggest that machine learning models be extended to incorporate social area-level covariates and regular contributions of up-to-date and context-relevant field-based classification of deprived urban areas.

Slums, Space, and State of Health-A Link between Settlement Morphology and Health Data

Approximately 1 billion slum dwellers worldwide are exposed to increased health risks due to their spatial environment. Recent studies have therefore called for the spatial environment to be introduced as a separate dimension in medical studies. Hence, this study investigates how and on which spatial scale relationships between the settlement morphology and the health status of the inhabitants can be identified. To this end, we summarize the current literature on the identification of slums from a geographical perspective and review the current literature on slums and health of the last five years (376 studies) focusing on the considered scales in the studies. We show that the majority of medical studies are restricted to certain geographical regions. It is desirable that the number of studies be adapted to the number of the respective population. On the basis of these studies, we develop a framework to investigate the relationship between space and health. Finally, we apply our methodology to investigate the relationship between the prevalence of slums and different health metrics using data of the global burden of diseases for different prefectures in Brazil on a subnational level.

The Role of Earth Observation in an Integrated Deprived Area Mapping “System” for Low-to-Middle Income Countries

Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups.

Extending Data for Urban Health Decision-Making: a Menu of New and Potential Neighborhood-Level Health Determinants Datasets in LMICs

Area-level indicators of the determinants of health are vital to plan and monitor progress toward targets such as the Sustainable Development Goals (SDGs). Tools such as the Urban Health Equity Assessment and Response Tool (Urban HEART) and UN-Habitat Urban Inequities Surveys identify dozens of area-level health determinant indicators that decision-makers can use to track and attempt to address population health burdens and inequalities. However, questions remain as to how such indicators can be measured in a cost-effective way. Area-level health determinants reflect the physical, ecological, and social environments that influence health outcomes at community and societal levels, and include, among others, access to quality health facilities, safe parks, and other urban services, traffic density, level of informality, level of air pollution, degree of social exclusion, and extent of social networks. The identification and disaggregation of indicators is necessarily constrained by which datasets are available. Typically, these include household- and individual-level survey, census, administrative, and health system data. However, continued advancements in earth observation (EO), geographical information system (GIS), and mobile technologies mean that new sources of area-level health determinant indicators derived from satellite imagery, aggregated anonymized mobile phone data, and other sources are also becoming available at granular geographic scale. Not only can these data be used to directly calculate neighborhood- and city-level indicators, they can be combined with survey, census, administrative and health system data to model household- and individual-level outcomes (e.g., population density, household wealth) with tremendous detail and accuracy. WorldPop and the Demographic and Health Surveys (DHS) have already modeled dozens of household survey indicators at country or continental scales at resolutions of 1 × 1 km or even smaller. This paper aims to broaden perceptions about which types of datasets are available for health and development decision-making. For data scientists, we flag area-level indicators at city and sub-city scales identified by health decision-makers in the SDGs, Urban HEART, and other initiatives. For local health decision-makers, we summarize a menu of new datasets that can be feasibly generated from EO, mobile phone, and other spatial data-ideally to be made free and publicly available-and offer lay descriptions of some of the difficulties in generating such data products.