Impact of Urban Slum Residence on Coverage of Maternal, Neonatal, and Child Health Service Indicators in the Greater Accra Region of Ghana: an Ecological Time-Series Analysis, 2018-2021.

Among other focus areas, the global Sustainable Development Goals (SDGs) 3 and 11 seek to advance progress toward universal coverage of maternal, neonatal, and child health (MNCH) services and access to safe and affordable housing and basic services by 2030. Governments and development agencies have historically neglected the health and well-being associated with living in urban slums across major capital cities in sub-Saharan Africa since health policies and programs have tended to focus on people living in rural communities. This study assessed the trends and compared inequities in MNCH service utilization between slum and non-slum districts in the Greater Accra region of Ghana. It analyzed information from 29 districts using monthly time-series Health Management Information System (HMIS) data on MNCH service utilization between January 2018 and December 2021. Multivariable quantile regression models with robust standard errors were used to quantify the impact of urban slum residence on MNCH service utilization. We assessed the inequality of MNCH coverage indicators between slum and non-slum districts using the Gini index with bootstrapped standard errors and the generalized Lorenz curve. The results indicate that rates of vaccination coverage and antenatal care (ANC) attendance have declined significantly in slum districts compared to those in non-slum districts. However, skilled birth delivery and postnatal care (PNC) were found to be higher in urban slum areas compared to those in non-urban slum areas. To help achieve the SDGs' targets, it is important for the government of Ghana and other relevant stakeholders to prioritize the implementation of effective policies, programs, and interventions that will improve access to and utilization of ANC and immunization services among urban slum dwellers.

Quality of maternal healthcare and travel time influence birthing service utilisation in Ghanaian health facilities: a geographical analysis of routine health data.

OBJECTIVES: To investigate how the quality of maternal health services and travel times to health facilities affect birthing service utilisation in Eastern Region, Ghana. DESIGN: The study is a cross-sectional spatial interaction analysis of birth service utilisation patterns. Routine birth data were spatially linked to quality care, service demand and travel time data. SETTING: 131 Health facilities (public, private and faith-based) in 33 districts in Eastern Region, Ghana. PARTICIPANTS: Women who gave birth in health facilities in the Eastern Region, Ghana in 2017. OUTCOME MEASURES: The count of women giving birth, the quality of birthing care services and the geographic coverage of birthing care services. RESULTS: As travel time from women's place of residence to the health facility increased up to two2 hours, the utilisation rate markedly decreased. Higher quality of maternal health services haves a larger, positive effect on utilisation rates than service proximity. The quality of maternal health services was higher in hospitals than in primary care facilities. Most women (88.6%) travelling via mechanised transport were within two2 hours of any birthing service. The majority (56.2%) of women were beyond the two2 -hour threshold of critical comprehensive emergency obstetric and newborn care (CEmONC) services. Few CEmONC services were in urban centres, disadvantaging rural populations. CONCLUSIONS: To increase birthing service utilisation in Ghana, higher quality health facilities should be located closer to women, particularly in rural areas. Beyond Ghana, routinely collected birth records could be used to understand the interaction of service proximity and quality.

Distance is "a big problem": a geographic analysis of reported and modelled proximity to maternal health services in Ghana.

BACKGROUND: Geographic barriers to healthcare are associated with adverse maternal health outcomes. Modelling travel times using georeferenced data is becoming common in quantifying physical access. Multiple Demographic and Health Surveys ask women about distance-related problems accessing healthcare, but responses have not been evaluated against modelled travel times. This cross-sectional study aims to compare reported and modelled distance by socio-demographic characteristics and evaluate their relationship with skilled birth attendance. Also, we assess the socio-demographic factors associated with self-reported distance problems in accessing healthcare. METHODS: Distance problems and socio-demographic characteristics reported by 2210 women via the 2017 Ghana Maternal Health Survey were included in analysis. Geospatial methods were used to model travel time to the nearest health facility using roads, rivers, land cover, travel speeds, cluster locations and health facility locations. Logistic regressions were used to predict skilled birth attendance and self-reported distance problems. RESULTS: Women reporting distance challenges accessing healthcare had significantly longer travel times to the nearest health facility. Poverty significantly increased the odds of reporting challenges with distance. In contrast, living in urban areas and being registered with health insurance reduced the odds of reporting distance challenges. Women with a skilled attendant at birth, four or more skilled antenatal appointments and timely skilled postnatal care had shorter travel times to the nearest health facility. Generally, less educated, poor, rural women registered with health insurance had longer travel times to their nearest health facility. After adjusting for socio-demographic characteristics, the following factors increased the odds of skilled birth attendance: wealth, health insurance, higher education, living in urban areas, and completing four or more antenatal care appointments. CONCLUSION: Studies relying on modelled travel times to nearest facility should recognise the differential impact of geographic access to healthcare on poor rural women. Physical access to maternal health care should be scaled up in rural areas and utilisation increased by improving livelihoods.

Patient and family financial burden associated with cancer treatment in Canada: a national study.

GOAL: To determine patient-reported financial and family burden associated with treatment of cancer in the previous 28 days across Canada. METHODS: A self-administered questionnaire (P-SAFE v7.2.4) was completed by 901 patients with cancer from twenty cancer centres nationally (344 breast, 183 colorectal, 158 lung, 216 prostate) measuring direct and indirect costs related to cancer treatment and foregone care. Monthly self-reported out-of-pocket-costs (OOPCs) included drugs, homecare, homemaking, complementary/ alternative medicines, vitamins/supplements, family care, accommodations, devices, and "other" costs. Travel and parking costs were captured separately. Patients indicated if OOPC, travel, parking, and lost income were a financial burden. RESULTS: Mean 28-day OOPCs were CA$518 (US Purchase Price Parity [PPP] $416), plus CA$179 (US PPP $144) for travel and CA$84 (US PPP $67) for parking. Patients self-reporting high financial burden had total OOPCs (33%), of CA$961 (US PPP $772), while low-burden participants (66%) had OOPCs of CA$300 (US PPP $241). "Worst burden" respondents spent a mean of 50.7% of their monthly income on OOPCs (median 20.8%). Among the 29.4% who took time off work, patients averaged 18.0 days off. Among the 26.0% of patients whose caregivers took time off work, caregivers averaged 11.5 days off. Lastly, 41% of all patients had to reduce spending. Fifty-two per cent of those who reduced spending were families earning < CA$50,000/year. CONCLUSIONS: In our Canadian sample, high levels of financial burden exist for 33% of patients, and the severity of burden is higher for those with lower household incomes.

An Assessment of Inter-Observer Agreement in Water Source Classification and Sanitary Risk Observations.

Sanitary risk inspection, an observation protocol for identifying contamination hazards around water sources, is promoted for managing rural water supply safety. However, it is unclear how far different observers consistently identify contamination hazards and consistently classify water source types using standard typologies. This study aimed to quantify inter-observer agreement in hazard identification and classification of rural water sources. Six observers separately visited 146 domestic water sources in Siaya County, Kenya, in wet and dry seasons. Each observer independently classified the source type and conducted a sanitary risk inspection using a standard protocol. Water source types assigned by an experienced observer were cross-tabulated against those of his colleagues, as were contamination hazards identified, and inter-observer agreement measures calculated. Agreement between hazards observed by the most experienced observer versus his colleagues was significant but low (intra-class correlation = 0.49), with inexperienced observers detecting fewer hazards. Inter-observer agreement in classifying water sources was strong (Cohen's kappa = 0.84). However, some source types were frequently misclassified, such as sources adapted to cope with water insecurity (e.g. tanks drawing on both piped and rainwater). Observers with limited training and experience thus struggle to consistently identify hazards using existing protocols, suggesting observation protocols require revision and their implementation should be supported by comprehensive training. Findings also indicate that field survey teams struggle to differentiate some water source types based on a standard water source classification, particularly sources adapted to cope with water insecurity. These findings demonstrate uncertainties underpinning international monitoring and analyses of safe water access via household surveys.

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.

OBJECTIF: Cette étude visait à utiliser les données d'enquête pour prédire l'assistance qualifiée à l'accouchement (AQA) à travers le Ghana à partir de la qualité des soins de santé et de l'accessibilité des établissements de santé. MÉTHODES: Grâce à une étude observationnelle transversale, nous avons utilisé une approche de modélisation logistique à multiniveau à effets mixtes d'interception aléatoire pour estimer les chances d'avoir une AQA, puis avons appliqué des estimations de modèle aux couches spatiales pour évaluer la probabilité d'AQA avec une résolution spatiale élevée à travers le Ghana. Nous avons combiné les données de l'Enquête démographique et de santé (EDS), les registres de naissance de routine, une évaluation de la prestation des services de soins obstétricaux d'urgence, des estimations démographiques quadrillées et un temps de trajet modélisé vers les établissements de santé. RÉSULTATS: En moins d'une heure de trajet, 97,1% des femmes échantillonnées dans l'EDS pouvaient accéder à un établissement de santé, 96,6% pouvaient atteindre un établissement fournissant des services d'accouchement et 86,2% pouvaient atteindre un hôpital secondaire. Après avoir ajusté pour les caractéristiques de chaque femme, le fait de vivre dans une zone urbaine et à proximité d'un établissement de santé offrant des services de haute qualité étaient des déterminants positifs significatifs de l'adoption de l'AQA. La variance estimée suggère des effets significatifs de regroupement et de la région sur l'AQA, car 7,1% de la variation résiduelle de la propension à utiliser l'AQA est attribuée à des caractéristiques régionales non observées et 16,5% entre les regroupements au sein des régions. CONCLUSION: Compte tenu de l'expansion des établissements de soins primaires au Ghana, cette étude suggère que des services de santé de meilleure qualité, par opposition à une plus grande proximité des établissements aux femmes, sont nécessaires pour élargir le recours à l'AQA et améliorer la santé maternelle.

Mapping access to domestic water supplies from incomplete data in developing countries: An illustrative assessment for Kenya.

Water point mapping databases, generated through surveys of water sources such as wells and boreholes, are now available in many low and middle income countries, but often suffer from incomplete coverage. To address the partial coverage in such databases and gain insights into spatial patterns of water resource use, this study investigated the use of a maximum entropy (MaxEnt) approach to predict the geospatial distribution of drinking-water sources, using two types of unimproved sources in Kenya as illustration. Geographic locations of unprotected dug wells and surface water sources derived from the Water Point Data Exchange (WPDx) database were used as inputs to the MaxEnt model alongside geological/hydrogeological and socio-economic covariates. Predictive performance of the MaxEnt models was high (all > 0.9) based on Area Under the Receiver Operator Curve (AUC), and the predicted spatial distribution of water point was broadly consistent with household use of these unimproved drinking-water sources reported in household survey and census data. In developing countries where geospatial datasets concerning drinking-water sources often have necessarily limited resolution or incomplete spatial coverage, the modelled surface can provide an initial indication of the geography of unimproved drinking-water sources to target unserved populations and assess water source vulnerability to contamination and hazards.

A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability.

BACKGROUND: Commercial geospatial data resources are frequently used to understand healthcare utilisation. Although there is widespread evidence of a digital divide for other digital resources and infra-structure, it is unclear how commercial geospatial data resources are distributed relative to health need. METHODS: To examine the distribution of commercial geospatial data resources relative to health needs, we assembled coverage and quality metrics for commercial geocoding, neighbourhood characterisation, and travel time calculation resources for 183 countries. We developed a country-level, composite index of commercial geospatial data quality/availability and examined its distribution relative to age-standardised all-cause and cause specific (for three main causes of death) mortality using two inequality metrics, the slope index of inequality and relative concentration index. In two sub-national case studies, we also examined geocoding success rates versus area deprivation by district in Eastern Region, Ghana and Lagos State, Nigeria. RESULTS: Internationally, commercial geospatial data resources were inversely related to all-cause mortality. This relationship was more pronounced when examining mortality due to communicable diseases. Commercial geospatial data resources for calculating patient travel times were more equitably distributed relative to health need than resources for characterising neighbourhoods or geocoding patient addresses. Countries such as South Africa have comparatively high commercial geospatial data availability despite high mortality, whilst countries such as South Korea have comparatively low data availability and low mortality. Sub-nationally, evidence was mixed as to whether geocoding success was lowest in more deprived districts. CONCLUSIONS: To our knowledge, this is the first global analysis of commercial geospatial data resources in relation to health outcomes. In countries such as South Africa where there is high mortality but also comparatively rich commercial geospatial data, these data resources are a potential resource for examining healthcare utilisation that requires further evaluation. In countries such as Sierra Leone where there is high mortality but minimal commercial geospatial data, alternative approaches such as open data use are needed in quantifying patient travel times, geocoding patient addresses, and characterising patients' neighbourhoods.

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys.

BACKGROUND: One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted. METHODS: Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty. FINDINGS: Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7-79.4) for the 2015 Kenya MIS (estimated sample size of children 0-4 years 7218 [7099-7288]), and 54.1% [50.1-56.5] for the 2014-2015 Rwanda DHS (12,220 [11,950-12,410]). CONCLUSION: This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

Treatment-seeking behaviour in low- and middle-income countries estimated using a Bayesian model.

BACKGROUND: Seeking treatment in formal healthcare for uncomplicated infections is vital to combating disease in low- and middle-income countries (LMICs). Healthcare treatment-seeking behaviour varies within and between communities and is modified by socio-economic, demographic, and physical factors. As a result, it remains a challenge to quantify healthcare treatment-seeking behaviour using a metric that is comparable across communities. Here, we present an application for transforming individual categorical responses (actions related to fever) to a continuous probabilistic estimate of fever treatment for one country in Sub-Saharan Africa (SSA). METHODS: Using nationally representative household survey data from the 2013 Demographic and Health Survey (DHS) in Namibia, individual-level responses (n = 1138) were linked to theoretical estimates of travel time to the nearest public or private health facility. Bayesian Item Response Theory (IRT) models were fitted via Markov Chain Monte Carlo (MCMC) simulation to estimate parameters related to fever treatment and estimate probability of treatment for children under five years. Different models were implemented to evaluate computational needs and the effect of including predictor variables such as rurality. The mean treatment rates were then estimated at regional level. RESULTS: Modelling results suggested probability of fever treatment was highest in regions with relatively high incidence of malaria historically. The minimum predicted threshold probability of seeking treatment was 0.3 (model 1: 0.340; 95% CI 0.155-0.597), suggesting that even in populations at large distances from facilities, there was still a 30% chance of an individual seeking treatment for fever. The agreement between correctly predicted probability of treatment at individual level based on a subset of data (n = 247) was high (AUC = 0.978), with a sensitivity of 96.7% and a specificity of 75.3%. CONCLUSION: We have shown how individual responses in national surveys can be transformed to probabilistic measures comparable at population level. Our analysis of household survey data on fever suggested a 30% baseline threshold for fever treatment in Namibia. However, this threshold level is likely to vary by country or endemicity. Although our focus was on fever treatment, the methodology outlined can be extended to multiple health seeking behaviours captured in routine national survey data and to other infectious diseases.

A cross-sectional ecological study of spatial scale and geographic inequality in access to drinking-water and sanitation.

INTRODUCTION: Measuring inequality in access to safe drinking-water and sanitation is proposed as a component of international monitoring following the expiry of the Millennium Development Goals. This study aims to evaluate the utility of census data in measuring geographic inequality in access to drinking-water and sanitation. METHODS: Spatially referenced census data were acquired for Colombia, South Africa, Egypt, and Uganda, whilst non-spatially referenced census data were acquired for Kenya. Four variants of the dissimilarity index were used to estimate geographic inequality in access to both services using large and small area units in each country through a cross-sectional, ecological study. RESULTS: Inequality was greatest for piped water in South Africa in 2001 (based on 53 areas (N) with a median population (MP) of 657,015; D = 0.5599) and lowest for access to an improved water source in Uganda in 2008 (N = 56; MP = 419,399; D = 0.2801). For sanitation, inequality was greatest for those lacking any facility in Kenya in 2009 (N = 158; MP = 216,992; D = 0.6981), and lowest for access to an improved facility in Uganda in 2002 (N = 56; MP = 341,954; D = 0.3403). Although dissimilarity index values were greater for smaller areal units, when study countries were ranked in terms of inequality, these ranks remained unaffected by the choice of large or small areal units. International comparability was limited due to definitional and temporal differences between censuses. CONCLUSIONS: This five-country study suggests that patterns of inequality for broad regional units do often reflect inequality in service access at a more local scale. This implies household surveys designed to estimate province-level service coverage can provide valuable insights into geographic inequality at lower levels. In comparison with household surveys, censuses facilitate inequality assessment at different spatial scales, but pose challenges in harmonising water and sanitation typologies across countries.

Global assessment of exposure to faecal contamination through drinking water based on a systematic review.

OBJECTIVES: To estimate exposure to faecal contamination through drinking water as indicated by levels of Escherichia coli (E. coli) or thermotolerant coliform (TTC) in water sources. METHODS: We estimated coverage of different types of drinking water source based on household surveys and censuses using multilevel modelling. Coverage data were combined with water quality studies that assessed E. coli or TTC including those identified by a systematic review (n = 345). Predictive models for the presence and level of contamination of drinking water sources were developed using random effects logistic regression and selected covariates. We assessed sensitivity of estimated exposure to study quality, indicator bacteria and separately considered nationally randomised surveys. RESULTS: We estimate that 1.8 billion people globally use a source of drinking water which suffers from faecal contamination, of these 1.1 billion drink water that is of at least 'moderate' risk (>10 E. coli or TTC per 100 ml). Data from nationally randomised studies suggest that 10% of improved sources may be 'high' risk, containing at least 100 E. coli or TTC per 100 ml. Drinking water is found to be more often contaminated in rural areas (41%, CI: 31%-51%) than in urban areas (12%, CI: 8-18%), and contamination is most prevalent in Africa (53%, CI: 42%-63%) and South-East Asia (35%, CI: 24%-45%). Estimates were not sensitive to the exclusion of low quality studies or restriction to studies reporting E. coli. CONCLUSIONS: Microbial contamination is widespread and affects all water source types, including piped supplies. Global burden of disease estimates may have substantially understated the disease burden associated with inadequate water services.

Fecal contamination of drinking-water in low- and middle-income countries: a systematic review and meta-analysis.

BACKGROUND: Access to safe drinking-water is a fundamental requirement for good health and is also a human right. Global access to safe drinking-water is monitored by WHO and UNICEF using as an indicator "use of an improved source," which does not account for water quality measurements. Our objectives were to determine whether water from "improved" sources is less likely to contain fecal contamination than "unimproved" sources and to assess the extent to which contamination varies by source type and setting. METHODS AND FINDINGS: Studies in Chinese, English, French, Portuguese, and Spanish were identified from online databases, including PubMed and Web of Science, and grey literature. Studies in low- and middle-income countries published between 1990 and August 2013 that assessed drinking-water for the presence of Escherichia coli or thermotolerant coliforms (TTC) were included provided they associated results with a particular source type. In total 319 studies were included, reporting on 96,737 water samples. The odds of contamination within a given study were considerably lower for "improved" sources than "unimproved" sources (odds ratio [OR] = 0.15 [0.10-0.21], I2 = 80.3% [72.9-85.6]). However over a quarter of samples from improved sources contained fecal contamination in 38% of 191 studies. Water sources in low-income countries (OR = 2.37 [1.52-3.71]; p<0.001) and rural areas (OR = 2.37 [1.47-3.81] p<0.001) were more likely to be contaminated. Studies rarely reported stored water quality or sanitary risks and few achieved robust random selection. Safety may be overestimated due to infrequent water sampling and deterioration in quality prior to consumption. CONCLUSION: Access to an "improved source" provides a measure of sanitary protection but does not ensure water is free of fecal contamination nor is it consistent between source types or settings. International estimates therefore greatly overstate use of safe drinking-water and do not fully reflect disparities in access. An enhanced monitoring strategy would combine indicators of sanitary protection with measures of water quality.

Public perception of drinking water safety in South Africa 2002-2009: a repeated cross-sectional study.

BACKGROUND: In low and middle income countries, public perceptions of drinking water safety are relevant to promotion of household water treatment and to household choices over drinking water sources. However, most studies of this topic have been cross-sectional and not considered temporal variation in drinking water safety perceptions. The objective of this study is to explore trends in perceived drinking water safety in South Africa and its association with disease outbreaks, water supply and household characteristics. METHODS: This repeated cross-sectional study draws on General Household Surveys from 2002-2009, a series of annual nationally representative surveys of South African households, which include a question about perceived drinking water safety. Trends in responses to this question were examined from 2002-2009 in relation to reported cholera cases. The relationship between perceived drinking water safety and organoleptic qualities of drinking water, supply characteristics, and socio-economic and demographic household characteristics was explored in 2002 and 2008 using hierarchical stepwise logistic regression. RESULTS: The results suggest that perceived drinking water safety has remained relatively stable over time in South Africa, once the expansion of improved supplies is controlled for. A large cholera outbreak in 2000-02 had no apparent effect on public perception of drinking water safety in 2002. Perceived drinking water safety is primarily related to water taste, odour, and clarity rather than socio-economic or demographic characteristics. CONCLUSION: This suggests that household perceptions of drinking water safety in South Africa follow similar patterns to those observed in studies in developed countries. The stability over time in public perception of drinking water safety is particularly surprising, given the large cholera outbreak that took place at the start of this period.

Accounting for water quality in monitoring access to safe drinking-water as part of the Millennium Development Goals: lessons from five countries.

OBJECTIVE: To determine how data on water source quality affect assessments of progress towards the 2015 Millennium Development Goal (MDG) target on access to safe drinking-water. METHODS: Data from five countries on whether drinking-water sources complied with World Health Organization water quality guidelines on contamination with thermotolerant coliform bacteria, arsenic, fluoride and nitrates in 2004 and 2005 were obtained from the Rapid Assessment of Drinking-Water Quality project. These data were used to adjust estimates of the proportion of the population with access to safe drinking-water at the MDG baseline in 1990 and in 2008 made by the Joint Monitoring Programme for Water Supply and Sanitation, which classified all improved sources as safe. FINDINGS: Taking account of data on water source quality resulted in substantially lower estimates of the percentage of the population with access to safe drinking-water in 2008 in four of the five study countries: the absolute reduction was 11% in Ethiopia, 16% in Nicaragua, 15% in Nigeria and 7% in Tajikistan. There was only a slight reduction in Jordan. Microbial contamination was more common than chemical contamination. CONCLUSION: The criterion used by the MDG indicator to determine whether a water source is safe can lead to substantial overestimates of the population with access to safe drinking-water and, consequently, also overestimates the progress made towards the 2015 MDG target. Monitoring drinking-water supplies by recording both access to water sources and their safety would be a substantial improvement.

Overall quality of outcomes framework scores lower in practices in deprived areas.

BACKGROUND: There has been much debate as to whether quality points allocated through the new general medical services contract are more difficult to achieve for practices in deprived and rural areas. We used multiple regression to assess the relationships between deprivation, rurality and the number of overall quality points achieved by each practice. Multiple deprivation was significantly inversely related to quality points achieved. Practices in villages and towns gained 2% more quality points than urban areas and hamlets.