Creating spatially defined databases for equitable health service planning in low-income countries: the example of Kenya

A consolidated and geolocated facility list in Senegal from triangulating secondary data

Having a geolocated list of all facilities in a country - a "master facility list" (MFL) - can provide critical inputs for health program planning and implementation. To the best of our knowledge, Senegal has never had a centralized MFL, though many data sources currently exist within the broader Senegalese data landscape that could be leveraged and consolidated into a single database - a critical first step toward building a full MFL. We collated 12,965 facility observations from 16 separate datasets and lists in Senegal, and applied matching algorithms, manual checking and revisions as needed, and verification processes to identify unique facilities and triangulate corresponding GPS coordinates. Our resulting consolidated facility list has a total of 4,685 facilities, with 2,423 having at least one set of GPS coordinates. Developing approaches to leverage existing data toward future MFL establishment can help bridge data demands and inform more targeted approaches for completing a full facility census based on areas and facility types with the lowest coverage. Going forward, it is crucial to ensure routine updates of current facility lists, and to strengthen government-led mechanisms around such data collection demands and the need for timely data for health decision-making.

Geographic accessibility to public and private health facilities in Kenya in 2021: An updated geocoded inventory and spatial analysis

Objectives

To achieve universal health coverage, adequate geographic access to quality healthcare services is vital and should be characterized periodically to support planning. However, in Kenya, previous assessments of geographic accessibility have relied on public health facility lists only, assembled several years ago. Here, for the first time we assemble a geocoded list of public and private health facilities in 2021 and make use of this updated list to interrogate geographical accessibility to all health providers.

Methods

Existing health provider lists in Kenya were accessed, merged, cleaned, harmonized, and assigned a unique geospatial location. The resultant master list was combined with road network, land use, topography, travel barriers and healthcare-seeking behavior within a geospatial framework to estimate travel time to the nearest (i) private, (ii) public, and (iii) both (public and private-PP) health facilities through a travel scenario involving walking, bicycling and motorized transport. The proportion of the population within 1 h and outside 2-h was computed at 300 × 300 spatial resolution and aggregated at subnational units used for decision-making. Areas with a high disease prevalence for common infections that were outside 1-h catchment (dual burden) were also identified to guide prioritization.

Results

The combined database contained 13,579 health facilities, both in the public (55.5%) and private-for-profit sector (44.5%) in 2021. The private health facilities' distribution was skewed toward the urban counties. Nationally, average travel time to the nearest health facility was 130, 254, and 128 min while the population within 1-h was 89.4, 80.5, and 89.6% for the public, private and PP health facility, respectively. The population outside 2-h were 6% for public and PP and 11% for the private sector. Mean travel time across counties was heterogeneous, while the population within 1-h ranged between 38 and 100% in both the public sector and PP. Counties in northwest and southeast Kenya had a dual burden.

Conclusion

Continuous updating and geocoding of health facilities will facilitate an improved understanding of healthcare gaps for planning. Heterogeneities in geographical access continue to persist, with some areas having a dual burden and should be prioritized toward reducing health inequities and attaining universal health coverage.

Geospatial Analysis of Dental Access and Workforce Distribution in Kenya

Background and Objective

One of the major factors affecting access to quality oral healthcare in low- and middle-income countries is the under-supply of the dental workforce. The aim of this study was to use Geographical Information System (GIS) to analyse the distribution and accessibility of the dental workforce and facilities across the Kenyan counties.

Methods

This was a cross-sectional study targeting dental professionals and their practices in Kenya in 2013. Using QGIS 3.16, these data were overlaid with data on population size and urbanization levels. For access measurement, buffers were drawn around each clinic at distances of 2.5, 5, 10 and 20 km, and the population within each determined.

Findings

Nine hundred six dental professionals in 337 dental clinic locations were included in the study. Dentists, community oral health officers (equivalent to dental therapists) and dental technologists comprised 72%, 15% and 12%, respectively. Nairobi county with 100% urbanization and >4000 people/km² had 43% of the workforce and a dentist to population ratio of 1:9,018. Wajir with an urbanization level of 15% and 12 people/km² had no dental facility. Overall, 11%, 19%, 35% and 58% of the Kenyan population were within 2.5, 5, 10 and 20 km radius of a dental clinic respectively.

Conclusion

Maldistribution of dental workforce in Kenya persists, particularly in less urbanized and sparsely populated areas. GIS map production give health planners a better visual picture of areas that are most in need of health care services based on population profiles.

National optimisation of accessibility to emergency obstetrical and neonatal care in Togo: a geospatial analysis

OBJECTIVES

Improving access to emergency obstetrical and neonatal care (EmONC) is a key strategy for reducing maternal and neonatal mortality. Access is shaped by several factors, including service availability and geographical accessibility. In 2013, the Ministry of Health (MoH) of Togo used service availability and other criteria to designate particular facilities as EmONC facilities, facilitating efficient allocation of limited resources. In 2018, the MoH further revised and rationalised this health facility network by applying an innovative methodology using health facility characteristics and geographical accessibility modelling to optimise timely access to EmONC services. This study compares the geographical accessibility of the network established in 2013 and the smaller network developed in 2018.

DESIGN

We used data regarding travel modes and speeds, geographical barriers and topographical and urban constraints, to estimate travel times to the nearest EmONC facilities. We compared the EmONC network of 109 facilities established in 2013 with the one composed of 73 facilities established in 2018, using three travel scenarios (walking and motorised, motorcycle-taxi and walking-only).

RESULTS

When walking and motorised travel is considered, the 2013 EmONC network covers 81% and 96.6% of the population at the 1-hour and 2-hour limit, respectively. These figures are slightly higher when motorcycle-taxis are considered (82.8% and 98%), and decreased to 34.7% and 52.3% for the walking-only scenario. The 2018 prioritised EmONC network covers 78.3% (1-hour) and 95.5% (2-hour) of the population for the walking and motorised scenario.

CONCLUSIONS

By factoring in geographical accessibility modelling to our iterative EmONC prioritisation process, the MoH was able to decrease the designated number of EmONC facilities in Togo by about 30%, while still ensuring that a high proportion of the population has timely access to these services. However, the physical access to EmONC for women unable to afford motorised transport remains inequitable.

Modelling geographical accessibility to urban centres in Kenya in 2019

BACKGROUND

Access to major services, often located in urban centres, is key to the realisation of numerous Sustainable Development Goals (SDGs). In Kenya, there are no up-to-date and localised estimates of spatial access to urban centres. We estimate the travel time to urban centres and identify marginalised populations for prioritisation and targeting.

METHODS

Urban centres were mapped from the 2019 Kenya population census and combined with spatial databases of road networks, elevation, land use and travel barriers within a cost-friction algorithm to compute travel time. Seven travel scenarios were considered: i) walking only (least optimistic), ii) bicycle only, iii) motorcycle only, iv) vehicle only (most optimistic), v) walking followed by motorcycle transport, vi) walking followed by vehicle transport, and vii) walking followed by motorcycle and then vehicle transport (most pragmatic). Mean travel time, and proportion of the population within 1-hour and 2-hours of the urban centres were summarized at sub-national units (counties) used for devolved planning. Inequities were explored and correlations between the proportion of the population within 1-hour of an urban centre and ten SDG indicators were computed.

RESULTS

A total of 307 urban centres were digitised. Nationally, the mean travel time was 4.5-hours for the walking-only scenario, 1.0-hours for the vehicle only (most optimistic) scenario and 1.5-hours for the walking-motorcycle-vehicle (most pragmatic) scenario. Forty-five per cent (21.3 million people) and 87% (41.6 million people) of Kenya's population resided within 1-hour of the nearest urban centre for the least optimistic and most pragmatic scenarios respectively. Over 3.2 million people were considered marginalised or living outside the 2-hour threshold in the pragmatic scenario, 16.0 million Kenyans for walking only, and 2.2 million for the most optimistic scenario. County-level spatial access was highly heterogeneous ranging between 8%-100% and 32%-100% of people within the 1-hour threshold for the least and most optimistic scenarios, respectively. Counties in northern and eastern parts of Kenya were generally most marginalised. The correlation coefficients for nine SDG indicators ranged between 0.45 to 0.78 and were statistically significant.

CONCLUSION

Travel time to urban centres in Kenya is heterogeneous. Therefore, marginalised populations should be prioritised during resource allocation and policies should be formulated to enhance equitable access to public services and opportunities in urban areas.

Methods of Measuring Spatial Accessibility to Health Care in Uganda

Ensuring everyone has access to health care regardless of demographic, geographic and social economic status is a key component of universal health coverage. In sub-Saharan Africa, where populations are often sparsely distributed and services scarcely available, reducing distances or travel time to facilities is key in ensuring access to health care. This chapter traces the key concepts in measuring spatial accessibility by reviewing six methods—Provider-to-population ratio, Euclidean distance, gravity models, kernel density, network analysis and cost distance analysis—that can be used to model spatial accessibility. The advantages and disadvantages of using each of these models are also laid out, with the aim of choosing a model that can be used to capture spatial access. Using an example from Uganda, a cost distance analysis is used to model travel time to the nearest primary health care facility. The model adjusts for differences in land use, weather patterns and elevation while also excluding barriers such as water bodies and protected areas in the analysis. Results show that the proportion of population within 1-h travel times for the 13 regions in the country varies from 64.6% to 96.7% in the dry period and from 61.1% to 96.3% in the wet period. The model proposed can thus be used to highlight disparities in spatial accessibility, but as we demonstrate, care needs to be taken in accurate assembly of data and interpreting results in the context of the limitations.

Activity-specific mobility of adults in a rural region of western Kenya

Improving rural household access to resources such as markets, schools and healthcare can help alleviate poverty in low-income settings. Current models of geographic accessibility to various resources rarely take individual variation into account due to a lack of appropriate data, yet understanding mobility at an individual level is key to knowing how people access their local resources. Our study used both an activity-specific survey and GPS trackers to evaluate how adults in a rural area of western Kenya accessed local resources. We calculated the travel time and time spent at six different types of resource and compared the GPS and survey data to see how well they matched. We found links between several demographic characteristics and the time spent at different resources, and that the GPS data reflected the survey data well for time spent at some types of resource, but poorly for others. We conclude that demography and activity are important drivers of mobility, and a better understanding of individual variation in mobility could be obtained through the use of GPS trackers on a wider scale.

A Qualitative Study to Examine Approaches used to Manage Data about Health Facilities and their Challenges: A Case of Uganda

Availability of an accurate and complete health facility list is fundamental in producing quality and timely data that is sufficient to aid evidence-based decision, resource allocation and planning within the healthcare ecosystem. This study aimed at examining the approaches used in Uganda to manage data about health facilities and the challenges they are facing. We conducted a qualitative study involving 32 interviews with participants from Ministry of Health, government regulatory organizations, district local government, general public, academia, implementing partners and healthcare providers. Our analysis identified four divergent approaches that had five common challenges, namely; lack of a health facility unique identifier, non-standardized, incomplete, inaccurate data, difficulty accessing and using data. Establishing a national central health facility registry to manage the national health facility list would improve patient referrals, facility look-ups, health information exchange, data curation and access and health information system integration.

Quantifying Seasonal Variation in Insecticide-Treated Net Use among Those with Access

Seasonal variation in the proportion of the population using an insecticide-treated net (ITN) is well documented and is widely believed to be dependent on mosquito abundance and heat, driven by rainfall and temperature. However, seasonal variation in ITN use has not been quantified controlling for ITN access. Demographic and Health Survey and Malaria Indicator Survey datasets, their georeferenced data, and public rainfall and climate layers were pooled for 21 countries. Nine rainfall typologies were developed from rainfall patterns in Köppen climate zones. For each typology, the odds of ITN use among individuals with access to an ITN within their households (“ITN use given access”) were estimated for each month of the year, controlling for region, wealth quintile, residence, year, temperature, and malaria parasitemia level. Seasonality of ITN use given access was observed over all nine rainfall typologies and was most pronounced in arid climates and less pronounced where rainfall was relatively constant throughout the year. Peak ITN use occurred 1–3 months after peak rainfall and corresponded with peak malaria incidence and average malaria transmission season. The observed lags between peak rainfall and peak ITN use given access suggest that net use is triggered by mosquito density. In equatorial areas, ITN use is likely to be high year-round, given the presence of mosquitoes and an associated year-round perceived malaria risk. These results can be used to inform behavior change interventions to improve ITN use in specific times of the year and to inform geospatial models of the impact of ITNs on transmission.

A spatial database of health facilities managed by the public health sector in sub Saharan Africa

Health facilities form a central component of health systems, providing curative and preventative services and structured to allow referral through a pyramid of increasingly complex service provision. Access to health care is a complex and multidimensional concept, however, in its most narrow sense, it refers to geographic availability. Linking health facilities to populations has been a traditional per capita index of heath care coverage, however, with locations of health facilities and higher resolution population data, Geographic Information Systems allow for a more refined metric of health access, define geographic inequalities in service provision and inform planning. Maximizing the value of spatial heath access requires a complete census of providers and their locations. To-date there has not been a single, geo-referenced and comprehensive public health facility database for sub-Saharan Africa. We have assembled national master health facility lists from a variety of government and non-government sources from 50 countries and islands in sub Saharan Africa and used multiple geocoding methods to provide a comprehensive spatial inventory of 98,745 public health facilities.

Examining healthcare systems: a market analysis for Kenya

Purpose

This paper aims to present a literature review of the health workforce, hospital and clinic systems, infrastructure, primary care, regulatory climate, the pharmaceutical industry and community health behavior of the Kenyan health-care system with the purpose of providing a thorough background on the health-care environment in Kenya.

Design/methodology/approach

A systematic literature review was conducted using Pub Med, searching for “Kenya” in the title of articles published from January 1, 2015 to February 24, 2016; this provided a broad overview of the type of research being conducted in Kenya. Other data provided by governmental agencies and non-governmental agencies was also reviewed to describe the current state of population health in Kenya.

Findings

An initial review of 615 Pubmed articles included 455 relevant articles. A complete review of these studies was conducted, resulting in a final sample of 389 articles. These articles were categorized into three main subject areas with 14 secondary subject areas (Figure 1).

Research limitations/implications

The narrow scope of the search parameters set for the systematic review was a necessary limitation to focus on the most relevant literature. The findings of this study provide a thorough background on health care in Kenya to researchers and practitioners.

Originality/value

This compilation of data specific to Kenya provides a detailed summary of both the country’s health-care services and health status, focusing on potential means of realizing increased quality and length of life.

Coverage of routine reporting on malaria parasitological testing in Kenya, 2015-2016

BACKGROUND

Following the launch of District Health Information System 2 across facilities in Kenya, more health facilities are now capable of carrying out malaria parasitological testing and reporting data as part of routine health information systems, improving the potential value of routine data for accurate and timely tracking of rapidly changing disease epidemiology at fine spatial resolutions.

OBJECTIVES

This study evaluates the current coverage and completeness of reported malaria parasitological testing data in DHIS2 specifically looking at patterns in geographic coverage of public health facilities in Kenya.

METHODS

Monthly facility level data on malaria parasitological testing were extracted from Kenya DHIS2 between November 2015 and October 2016. DHIS2 public facilities were matched to a geo-coded master facility list to obtain coordinates. Coverage was defined as the geographic distribution of facilities reporting any data by region. Completeness of reporting was defined as the percentage of facilities reporting any data for the whole 12-month period or for 3, 6 and 9 months.

RESULTS

Public health facilities were 5,933 (59%) of 10,090 extracted. Fifty-nine per Cent of the public facilities did not report any data while 36, 29 and 22% facilities had data reported at least 3, 6 and 9 months, respectively. Only 8% of public facilities had data reported for every month. There were proportionately more hospitals (86%) than health centres (76%) and dispensaries/clinics (30%) reporting. There were significant geographic variations in reporting rates. Counties along the malaria endemic coast had the lowest reporting rate with only 1% of facilities reporting consistently for 12 months.

CONCLUSION

Current coverage and completeness of reporting of malaria parasitological diagnosis across Kenya's public health system remains poor. The usefulness of routine data to improve our understanding of sub-national heterogeneity across Kenya would require significant improvements to the consistency and coverage of data captured by DHIS2.

The role of community engagement in building sustainable health-care delivery interventions for Kenya

Purpose

The purpose of this article is to provide a general review of the health-care needs in Kenya which focuses on the role of community engagement in facilitating access and diminishing barriers to quality care services. Health-care concerns throughout Kenya and the culture of Kenyan’s health-care practices care are considered.

Design/methodology/approach

A comprehensive review covered studies of community engagement from 2000 till present. Studies are collected using Google Scholar, PubMed, EBSCOhost and JSTOR and from government and nongovernment agency websites. The approach focuses on why various populations seek health care and how they seek health care, and on some current health-care delivery models.

Findings

Suggestions for community engagement, including defining the community, are proposed. A model for improved health-care delivery introduces community health workers (CHWs), mHealth technologies and the use of mobile clinics to engage the community and improve health and quality of care in low-income settings.

Practical implications

The results emphasize the importance of community engagement in building a sustainable health-care delivery model. This model highlights the importance of defining the community, setting goals for the community and integrating CHWs and mobile clinics to improve health status and decrease long-term health-care costs. The implementation of these strategies contributes to an environment that promotes health and wellness for all.

Originality/value

This paper evaluates health-care quality and access issues in Kenya and provides sustainable solutions that are linked to effective community engagement. In addition, this paper adds to the limited number of studies that explore health-care quality and access alongside community engagement in low-income settings.

A retrospective cohort study to quantify the contribution of health systems to child survival in Kenya: 1996-2014

Globally, the majority of childhood deaths in the post-neonatal period are caused by infections that can be effectively treated or prevented with inexpensive interventions delivered through even very basic health facilities. To understand the role of inadequate health systems on childhood mortality in Kenya, we assemble a large, retrospective cohort of children (born 1996–2013) and describe the health systems context of each child using health facility survey data representative of the province at the time of a child’s birth. We examine the relationship between survival beyond 59 months of age and geographic distribution of health facilities, quality of services, and cost of services. We find significant geographic heterogeneity in survival that can be partially explained by differences in distribution of health facilities and user fees. Higher per capita density of health facilities resulted in a 25% reduction in the risk of death (HRR = 0.73, 95% CI:0.58 to 0.91) and accounted for 30% of the between-province heterogeneity in survival. User fees for sick-child visits increased risk by 30% (HRR = 1.30, 95% CI:1.11 to 1.53). These results implicate health systems constraints in child mortality, quantify the contribution of specific domains of health services, and suggest priority areas for improvement to accelerate reductions in child mortality.

Defining Remoteness from Health Care: Integrated Research on Accessing Emergency Maternal Care in Indonesia

The causes of maternal death are well known, and are largely preventable if skilled health care is received promptly. Complex interactions between geographic and socio-cultural factors affect access to, and remoteness from, health care but research on this topic rarely integrates spatial and social sciences. In this study, modeling of travel time was integrated with social science research to refine our understanding of remoteness from health care. Travel time to health facilities offering emergency obstetric care (EmOC) and population distribution were modelled for a district in eastern Indonesia. As an index of remoteness, the proportion of the population more than two hours estimated travel time from EmOC was calculated. For the best case scenario (transport by ambulance in the dry season), modelling estimated more than 10,000 fertile aged women were more than two hours from EmOC. Maternal mortality ratios were positively correlated with the remoteness index, however there was considerable variation around this relationship. In a companion study, ethnographic research in a subdistrict with relatively good access to health care and high maternal mortality identified factors influencing access to EmOC, including some that had not been incorporated into the travel time model. Ethnographic research provided information about actual travel involved in requesting and reaching EmOC. Modeled travel time could be improved by incorporating time to deliver request for care. Further integration of social and spatial methods and the development of more dynamic travel time models are needed to develop programs and policies to address these multiple factors to improve maternal health outcomes.

Lessons from a geospatial analysis of depot medroxyprogesterone acetate sales by licensed chemical sellers in Ghana

OBJECTIVES

To map access to depot medroxyprogesterone acetate (DMPA) from licensed chemical sellers (LCS); to estimate the proportion of women of reproductive age in areas with access; and to examine affordability and variability of costs.

METHODS

A geospatial analysis was conducted using data collected from 298 women who purchased DMPA from 49 geocoded LCS shops in the Amansie West and Ejisu-Juabeng districts of Ghana from June 4 to August 31, 2012. The women reported on cost and average distance traveled to purchase DMPA.

RESULTS

In Amansie West, 21.1% of all women of reproductive age lived within average walking distance and 80.4% lived within average driving distance of an LCS. In Ejisu-Juabeng, 41.9% and 60.1% of women lived within average walking and driving distance, respectively. Distribution of affordability varied across each district.

CONCLUSIONS

Access to LCS shops is high, and training LCS to administer DMPA would increase access to family planning in Ghana, with associated time and cost savings.

Spatiotemporal approaches to analyzing pedestrian fatalities: the case of Cali, Colombia

OBJECTIVE

Injuries among pedestrians are a major public health concern in Colombian cities such as Cali. This is one of the first studies in Latin America to apply Bayesian maximum entropy (BME) methods to visualize and produce fine-scale, highly accurate estimates of citywide pedestrian fatalities. The purpose of this study is to determine the BME method that best estimates pedestrian mortality rates and reduces statistical noise. We further utilized BME methods to identify and differentiate spatial patterns and persistent versus transient pedestrian mortality hotspots.

METHODS

In this multiyear study, geocoded pedestrian mortality data from the Cali Injury Surveillance System (2008 to 2010) and census data were utilized to accurately visualize and estimate pedestrian fatalities. We investigated the effects of temporal and spatial scales, addressing issues arising from the rarity of pedestrian fatality events using 3 BME methods (simple kriging, Poisson kriging, and uniform model Bayesian maximum entropy). To reduce statistical noise while retaining a fine spatial and temporal scale, data were aggregated over 9-month incidence periods and censal sectors. Based on a cross-validation of BME methods, Poisson kriging was selected as the best BME method. Finally, the spatiotemporal and urban built environment characteristics of Cali pedestrian mortality hotspots were linked to intervention measures provided in Mead et al.'s (2014) pedestrian mortality review.

RESULTS

The BME space-time analysis in Cali resulted in maps displaying hotspots of high pedestrian fatalities extending over small areas with radii of 0.25 to 1.1 km and temporal durations of 1 month to 3 years. Mapping the spatiotemporal distribution of pedestrian mortality rates identified high-priority areas for prevention strategies. The BME results allow us to identify possible intervention strategies according to the persistence and built environment of the hotspot; for example, through enforcement or long-term environmental modifications.

CONCLUSIONS

BME methods provide useful information on the time and place of injuries and can inform policy strategies by isolating priority areas for interventions, contributing to intervention evaluation, and helping to generate hypotheses and identify the preventative strategies that may be suitable to those areas (e.g., street-level methods: pedestrian crossings, enforcement interventions; or citywide approaches: limiting vehicle speeds). This specific information is highly relevant for public health interventions because it provides the ability to target precise locations.

Monitoring the ability to deliver care in low- and middle-income countries: a systematic review of health facility assessment tools

Introduction Health facilities assessments are an essential instrument for health system strengthening in low- and middle-income countries. These assessments are used to conduct health facility censuses to assess the capacity of the health system to deliver health care and to identify gaps in the coverage of health services. Despite the valuable role of these assessments, there are currently no minimum standards or frameworks for these tools.

Methods We used a structured keyword search of the MEDLINE, EMBASE and HealthStar databases and searched the websites of the World Health Organization, the World Bank and the International Health Facilities Assessment Network to locate all available health facilities assessment tools intended for use in low- and middle-income countries. We parsed the various assessment tools to identify similarities between them, which we catalogued into a framework comprising 41 assessment domains.

Results We identified 10 health facility assessment tools meeting our inclusion criteria, all of which were included in our analysis. We found substantial variation in the comprehensiveness of the included tools, with the assessments containing indicators in 13 to 33 (median: 25.5) of the 41 assessment domains included in our framework. None of the tools collected data on all 41 of the assessment domains we identified.

Conclusions Not only do a large number of health facility assessment tools exist, but the data they collect and methods they employ are very different. This certainly limits the comparability of the data between different countries’ health systems and probably creates blind spots that impede efforts to strengthen those systems. Agreement is needed on the essential elements of health facility assessments to guide the development of specific indicators and for refining existing instruments.

Access and Barriers to Healthcare Vary among Three Neighboring Communities in Northern Honduras

Objective. The aim of this study is to describe and compare access and barriers to health services in three proximal yet topographically distinct communities in northern Honduras served by the nonprofit organization the Honduras Outreach Medical Brigada Relief Effort (HOMBRE). Methods. Study personnel employed a 25-item questionnaire in Spanish at the point of care during HOMBRE clinics in Coyoles, Lomitas, and La Hicaca (N = 220). We describe and compare the responses between sites, using Chi-squared and Fisher Exact tests. Results. Respondents in Lomitas demonstrated the greatest limitations in access and greatest barriers to care of all sites. Major limitations in access included "never" being able to obtain a blood test, obtain radiology services, and see a specialist. Major barriers were cost, distance, facility overcrowding, transportation, being too ill to go, inability to take time off work, and lack of alternate childcare. Conclusions. Despite being under the same local health authority, geographically remote Honduran communities experience greater burdens in healthcare access and barriers than neighboring communities of the same region.

Vaccination coverage in Haiti: results from the 2009 national survey

INTRODUCTION

Since 1977, vaccinations to protect against tuberculosis, diphtheria, tetanus, pertussis, polio, and measles (and rubella since 2009) have been offered to children in Haiti through the routine immunization program. From April to July 2009, a national vaccination coverage survey was conducted to assess the success of the routine immunization program at reaching children in Haiti.

METHODS

A multi-stage cluster survey was conducted using a modified WHO method for household sampling. A standardized questionnaire was administered to collect vaccination histories, demographic information, and reasons for under-vaccination of children aged 12-23 months. A child who received the eight recommended routine vaccinations was considered fully vaccinated. The routine vaccination schedule was used to define valid doses and estimate the percentage of children vaccinated on time.

RESULTS

Among 1345 children surveyed, 40.4% (95% CI: 36.6-44.2) of the 840 children with vaccination cards had received all eight recommended vaccinations. Coverage was highest for the Bacille Calmette-Guérin vaccine (87.3%), the first doses of the diphtheria-tetanus-pertussis vaccine (92.0%), and oral poliovirus vaccine (93.4%) and lowest for measles vaccine (46.9%). Timely vaccination rates were lower. Assuming similar coverage for the 505 children without cards, coverage with the complete vaccination series among all surveyed children 31.9%. Reasons for under-vaccination included not having enough time to reach the vaccination location (24.8%), having a child who was ill (13.8%), and not knowing when, or forgetting, to go for vaccination (12.8%).

CONCLUSIONS AND RECOMMENDATIONS

Coverage for early-infant vaccines was high; however, most children did not complete the full vaccination series, and many children received vaccinations later than recommended. Efforts to improve the immunization program should include increasing the frequency of outreach services, training for vaccination staff to minimize missed opportunities, and better communicating the timing of vaccinations to encourage caregivers to bring their children for vaccinations at the recommended age. Efforts to promote the benefits of vaccination and card retention are also needed.

Overview of the Most Important Open Source Software

In this chapter, the authors review software that enables the proper management of EHR. The different types of software share the feature of being open source and offer the best opportunity in health care to developing countries—an overall integrated approach. The authors analyze the main free software programs (technical features, programming languages, places for introduction, etc.). Then they focus on the description and the comparison of the three most important open source software programs EHR (OpenMRS, OpenVistA, and OpenEMR) that are installed on two operating systems (Linux Ubuntu and Windows). Finally, the authors show the results of the various parameters measured in these systems after using different Web browsers. The results show us how the three main EHR applications work depending on which operating system is installed and which web browser is used.

Uncovering the potential of private providers' involvement in health to strengthen comprehensive health systems: a discussion paper

Health systems strengthening (HSS) is being increasingly recognized as a strategic cross-cutting issue in all World Health Organization (WHO) work. Health systems comprise six building blocks: service delivery; medical products, vaccines and technologies; health workforce; health systems financing; health information system; and leadership and governance. Public-private mix (PPM) approaches or partnerships consist of initiatives aimed at increasing collaboration and improving the relationships between public-public, public-private and private-private health providers. An important component of PPM is the clear distribution of tasks between the different providers involved in the provision of health care. In practice, most PPM initiatives are disease-specific and are often related to the health service delivery block mentioned above. Although there is widespread consensus that PPM initiatives are typically of an HSS nature, efforts to make explicit the links between PPM and health systems building blocks are rather uncommon. The present paper aims to identify - in order to facilitate operationalization - potential aspects linking PPM to health systems building blocks, using a few experiences from tuberculosis control and beyond. The paper targets policymakers, donors and health systems scientists and ends with a call for more aware and innovative leadership, for increased support of PPM initiatives covering various building blocks, and for more operational research.

Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia

BACKGROUND

Despite the demonstrated utility of GIS for health applications, there are perceived problems in low resource settings: GIS software can be expensive and complex; input data are often of low quality. This study aimed to test the appropriateness of new, inexpensive and simple GIS tools in poorly resourced areas of a developing country. GIS applications were trialled in pilot studies based on mapping of health resources and health indicators at the clinic and district level in the predominantly rural province of Nusa Tenggara Timur in eastern Indonesia. The pilot applications were (i) rapid field collection of health infrastructure data using a GPS enabled PDA, (ii) mapping health indicator data using open source GIS software, and (iii) service availability mapping using a free modelling tool.

RESULTS

Through contextualised training, district and clinic staff acquired skills in spatial analysis and visualisation and, six months after the pilot studies, they were using these skills for advocacy in the planning process, to inform the allocation of some health resources, and to evaluate some public health initiatives.

CONCLUSIONS

We demonstrated that GIS can be a useful and inexpensive tool for the decentralisation of health data analysis to low resource settings through the use of free and simple software, locally relevant training materials and by providing data collection tools to ensure data reliability.

Geographic access to care is not a determinant of child mortality in a rural Kenyan setting with high health facility density

BACKGROUND

Policy-makers evaluating country progress towards the Millennium Development Goals also examine trends in health inequities. Distance to health facilities is a known determinant of health care utilization and may drive inequalities in health outcomes; we aimed to investigate its effects on childhood mortality.

METHODS

The Epidemiological and Demographic Surveillance System in Kilifi District, Kenya, collects data on vital events and migrations in a population of 220,000 people. We used Geographic Information Systems to estimate pedestrian and vehicular travel times to hospitals and vaccine clinics and developed proportional-hazards models to evaluate the effects of travel time on mortality hazard in children less than 5 years of age, accounting for sex, ethnic group, maternal education, migrant status, rainfall and calendar time.

RESULTS

In 2004-6, under-5 and under-1 mortality ratios were 65 and 46 per 1,000 live-births, respectively. Median pedestrian and vehicular travel times to hospital were 193 min (inter-quartile range: 125-267) and 49 min (32-72); analogous values for vaccine clinics were 47 (25-73) and 26 min (13-40). Infant and under-5 mortality varied two-fold across geographic locations, ranging from 34.5 to 61.9 per 1000 child-years and 8.8 to 18.1 per 1000, respectively. However, distance to health facilities was not associated with mortality. Hazard Ratios (HR) were 0.99 (95% CI 0.95-1.04) per hour and 1.01 (95% CI 0.95-1.08) per half-hour of pedestrian and vehicular travel to hospital, respectively, and 1.00 (95% CI 0.99-1.04) and 0.97 (95% CI 0.92-1.05) per quarter-hour of pedestrian and vehicular travel to vaccine clinics in children <5 years of age.

CONCLUSIONS

Significant spatial variations in mortality were observed across the area, but were not correlated with distance to health facilities. We conclude that given the present density of health facilities in Kenya, geographic access to curative services does not influence population-level mortality.

An intervention to improve paediatric and newborn care in Kenyan district hospitals: understanding the context

BACKGROUND

It is increasingly appreciated that the interpretation of health systems research studies is greatly facilitated by detailed descriptions of study context and the process of intervention. We have undertaken an 18-month hospital-based intervention study in Kenya aiming to improve care for admitted children and newborn infants. Here we describe the baseline characteristics of the eight hospitals as environments receiving the intervention, as well as the general and local health system context and its evolution over the 18 months.

METHODS

Hospital characteristics were assessed using previously developed tools assessing the broad structure, process, and outcome of health service provision for children and newborns. Major health system or policy developments over the period of the intervention at a national level were documented prospectively by monitoring government policy announcements, the media, and through informal contacts with policy makers. At the hospital level, a structured, open questionnaire was used in face-to-face meetings with senior hospital staff every six months to identify major local developments that might influence implementation. These data provide an essential background for those seeking to understand the generalisability of reports describing the intervention's effects, and whether the intervention plausibly resulted in these effects.

RESULTS

Hospitals had only modest capacity, in terms of infrastructure, equipment, supplies, and human resources available to provide high-quality care at baseline. For example, hospitals were lacking between 30 to 56% of items considered necessary for the provision of care to the seriously ill child or newborn. An increase in spending on hospital renovations, attempts to introduce performance contracts for health workers, and post-election violence were recorded as examples of national level factors that might influence implementation success generally. Examples of factors that might influence success locally included frequent and sometimes numerous staff changes, movements of senior departmental or administrative staff, and the presence of local 'donor' partners with alternative priorities.

CONCLUSION

The effectiveness of interventions delivered at hospital level over periods realistically required to achieve change may be influenced by a wide variety of factors at national and local levels. We have demonstrated how dynamic such contexts are, and therefore the need to consider context when interpreting an intervention's effectiveness.

A spatial national health facility database for public health sector planning in Kenya in 2008

BACKGROUND

Efforts to tackle the enormous burden of ill-health in low-income countries are hampered by weak health information infrastructures that do not support appropriate planning and resource allocation. For health information systems to function well, a reliable inventory of health service providers is critical. The spatial referencing of service providers to allow their representation in a geographic information system is vital if the full planning potential of such data is to be realized.

METHODS

A disparate series of contemporary lists of health service providers were used to update a public health facility database of Kenya last compiled in 2003. These new lists were derived primarily through the national distribution of antimalarial and antiretroviral commodities since 2006. A combination of methods, including global positioning systems, was used to map service providers. These spatially-referenced data were combined with high-resolution population maps to analyze disparity in geographic access to public health care.

FINDINGS

The updated 2008 database contained 5,334 public health facilities (67% ministry of health; 28% mission and nongovernmental organizations; 2% local authorities; and 3% employers and other ministries). This represented an overall increase of 1,862 facilities compared to 2003. Most of the additional facilities belonged to the ministry of health (79%) and the majority were dispensaries (91%). 93% of the health facilities were spatially referenced, 38% using global positioning systems compared to 21% in 2003. 89% of the population was within 5 km Euclidean distance to a public health facility in 2008 compared to 71% in 2003. Over 80% of the population outside 5 km of public health service providers was in the sparsely settled pastoralist areas of the country.

CONCLUSION

We have shown that, with concerted effort, a relatively complete inventory of mapped health services is possible with enormous potential for improving planning. Expansion in public health care in Kenya has resulted in significant increases in geographic access although several areas of the country need further improvements. This information is key to future planning and with this paper we have released the digital spatial database in the public domain to assist the Kenyan Government and its partners in the health sector.

USING PARTICIPATORY METHODS AND GEOGRAPHIC INFORMATION SYSTEMS (GIS) TO PREPARE FOR AN HIV COMMUNITY-BASED TRIAL IN VULINDLELA, SOUTH AFRICA (Project Accept-HPTN 043)

Recent attempts to integrate geographic information systems (GIS) and participatory techniques, have given rise to terminologies such as participatory GIS and community-integrated GIS. Although GIS was initially developed for physical geographic application, it can be used for the management and analysis of health and health care data. Geographic information systems, combined with participatory methodology, have facilitated the analysis of access to health facilities and disease risk in different populations. Little has been published about the usefulness of combining participatory methodologies and GIS technology in an effort to understand and inform community-based intervention studies, especially in the context of HIV. This article attempts to address this perceived gap in the literature. The authors describe the application of participatory research methods with GIS in the formative phase of a multisite community-based social mobilization trial, using voluntary counseling and testing and post-test support as the intervention.

Developing geostatistical space-time models to predict outpatient treatment burdens from incomplete national data

Basic health system data such as the number of patients utilising different health facilities and the types of illness for which they are being treated are critical for managing service provision. These data requirements are generally addressed with some form of national Health Management Information System (HMIS) which coordinates the routine collection and compilation of data from national health facilities. HMIS in most developing countries are characterised by widespread under-reporting. Here we present a method to adjust incomplete data to allow prediction of national outpatient treatment burdens. We demonstrate this method with the example of outpatient treatments for malaria within the Kenyan HMIS. Three alternative modelling frameworks were developed and tested in which space-time geostatistical prediction algorithms were used to predict the monthly tally of treatments for presumed malaria cases (MC) at facilities where such records were missing. Models were compared by a cross-validation exercise and the model found to most accurately predict MC incorporated available data on the total number of patients visiting each facility each month. A space-time stochastic simulation framework to accompany this model was developed and tested in order to provide estimates of both local and regional prediction uncertainty. The level of accuracy provided by the predictive model, and the accompanying estimates of uncertainty around the predictions, demonstrate how this tool can mitigate the uncertainties caused by missing data, substantially enhancing the utility of existing HMIS data to health-service decision-makers.

High resolution population maps for low income nations: combining land cover and census in East Africa

Background

Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.

Methodology/Principal Findings

We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.

Conclusions

We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km². The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available.

Information for decision making from imperfect national data: tracking major changes in health care use in Kenya using geostatistics

BACKGROUND

Most Ministries of Health across Africa invest substantial resources in some form of health management information system (HMIS) to coordinate the routine acquisition and compilation of monthly treatment and attendance records from health facilities nationwide. Despite the expense of these systems, poor data coverage means they are rarely, if ever, used to generate reliable evidence for decision makers. One critical weakness across Africa is the current lack of capacity to effectively monitor patterns of service use through time so that the impacts of changes in policy or service delivery can be evaluated. Here, we present a new approach that, for the first time, allows national changes in health service use during a time of major health policy change to be tracked reliably using imperfect data from a national HMIS.

METHODS

Monthly attendance records were obtained from the Kenyan HMIS for 1 271 government-run and 402 faith-based outpatient facilities nationwide between 1996 and 2004. A space-time geostatistical model was used to compensate for the large proportion of missing records caused by non-reporting health facilities, allowing robust estimation of monthly and annual use of services by outpatients during this period.

RESULTS

We were able to reconstruct robust time series of mean levels of outpatient utilisation of health facilities at the national level and for all six major provinces in Kenya. These plots revealed reliably for the first time a period of steady nationwide decline in the use of health facilities in Kenya between 1996 and 2002, followed by a dramatic increase from 2003. This pattern was consistent across different causes of attendance and was observed independently in each province.

CONCLUSION

The methodological approach presented can compensate for missing records in health information systems to provide robust estimates of national patterns of outpatient service use. This represents the first such use of HMIS data and contributes to the resurrection of these hugely expensive but underused systems as national monitoring tools. Applying this approach to Kenya has yielded output with immediate potential to enhance the capacity of decision makers in monitoring nationwide patterns of service use and assessing the impact of changes in health policy and service delivery.

Development and management of a geographic information system for health research in a developing-country setting: a case study from Bangladesh

In the last decade, geographic information systems (GIS) have become accessible to researchers in developing countries, yet guidance remains sparse for developing a GIS. Drawing on experience in developing a GIS for a large community trial in rural Bangladesh, six stages for constructing, maintaining, and using a GIS for health research purposes were outlined. The system contains 0.25 million landmarks, including 150,000 houses, in an area of 435 sq km with over 650,000 people. Assuming access to reasonably accurate paper boundary maps of the intended working area and the absence of pre-existing digital local-area maps, the six stages are: to (a) digitize and update existing paper maps, (b) join the digitized maps into a large-area map, (c) reference this large-area map to a geographic coordinate system, (d) insert location landmarks of interest, (e) maintain the GIS, and (f) link it to other research databases. These basic steps can produce a household-level, updated, scaleable GIS that can both enhance field efficiency and support epidemiologic analyses of demographic patterns, diseases, and health outcomes.

A local space-time kriging approach applied to a national outpatient malaria dataset

Increases in the availability of reliable health data are widely recognised as essential for efforts to strengthen health-care systems in resource-poor settings worldwide. Effective health-system planning requires comprehensive and up-to-date information on a range of health metrics and this requirement is generally addressed by a Health Management Information System (HMIS) that coordinates the routine collection of data at individual health facilities and their compilation into national databases. In many resource-poor settings, these systems are inadequate and national databases often contain only a small proportion of the expected records. In this paper we take an important health metric in Kenya (the proportion of outpatient treatments for malaria, MP) from the national HMIS database and predict the values of MP at facilities where monthly records are missing. The available MP data were densely distributed across a spatiotemporal domain and displayed second-order heterogeneity. We used three different kriging methodologies to make cross-validation predictions of MP in order to test the effect on prediction accuracy of (a) the extension of a spatial-only to a space-time prediction approach, and (b) the replacement of a globally-stationary with a locally-varying random function model. Space-time kriging was found to produce predictions with 98.4% less mean bias and 14.8% smaller mean imprecision than conventional spatial-only kriging. A modification of space-time kriging that allowed space-time variograms to be recalculated for every prediction location within a spatially-local neighbourhood resulted in a larger decrease in mean imprecision over ordinary kriging (18.3%) although mean bias was reduced less (87.5%).

Improving imperfect data from health management information systems in Africa using space-time geostatistics

BACKGROUND

Reliable and timely information on disease-specific treatment burdens within a health system is critical for the planning and monitoring of service provision. Health management information systems (HMIS) exist to address this need at national scales across Africa but are failing to deliver adequate data because of widespread underreporting by health facilities. Faced with this inadequacy, vital public health decisions often rely on crudely adjusted regional and national estimates of treatment burdens.

METHODS AND FINDINGS

This study has taken the example of presumed malaria in outpatients within the largely incomplete Kenyan HMIS database and has defined a geostatistical modelling framework that can predict values for all data that are missing through space and time. The resulting complete set can then be used to define treatment burdens for presumed malaria at any level of spatial and temporal aggregation. Validation of the model has shown that these burdens are quantified to an acceptable level of accuracy at the district, provincial, and national scale.

CONCLUSIONS

The modelling framework presented here provides, to our knowledge for the first time, reliable information from imperfect HMIS data to support evidence-based decision-making at national and sub-national levels.

The quality of sulphadoxine-pyrimethamine and amodiaquine products in the Kenyan retail sector

BACKGROUND AND OBJECTIVE

Malaria is a disease of major public health importance in Kenya killing 26,000 children under 5 years of age annually. This paper seeks to assess the quality of sulphadoxine-pyrimethamine (SP) and amodiaquine (AQ) products available over-the-counter to communities in Kenya as most malaria fevers are self-medicated using drugs from the informal retail sector.

METHODS

A retail audit of 880 retail outlets was carried in 2002 in four districts in Kenya, in which antimalarial drug stocks and their primary wholesale sources were noted. In addition, the expiry dates on audited products and the basic storage conditions were recorded on a proforma. The most commonly stocked SP and AQ products were then sampled from the top 10 wholesalers in each district and samples subjected to standard United States Pharmacopoeia (USP) tests of content and dissolution.

RESULTS AND DISCUSSION

SP and AQ were the most frequently stocked antimalarial drugs, accounting for approximately 75% of all the antimalarial drugs stocked in the four districts. Of 116 SP and AQ samples analysed, 47 (40.5%) did not meet the USP specifications for content and/or dissolution. Overall, approximately 45.3% of SP and 33.0% of AQ samples were found to be sub-standard. Of the sub-standard SP products, 55.2% were suspensions while 61.1% of the substandard AQ products were tablets. Most SP failures were because of the pyrimethamine component.

CONCLUSION

There is a need to strengthen post-marketing surveillance systems to protect patients from being treated with sub-standard and counterfeit antimalarial drugs in Kenya.

The accuracy of human population maps for public health application

OBJECTIVES

Human population totals are used for generating burden of disease estimates at global, continental and national scales to help guide priority setting in international health financing. These exercises should be aware of the accuracy of the demographic information used.

METHODS

The analysis presented in this paper tests the accuracy of five large-area, public-domain human population distribution data maps against high spatial resolution population census data enumerated in Kenya in 1999. We illustrate the epidemiological significance, by assessing the impact of using these different human population surfaces in determining populations at risk of various levels of climate suitability for malaria transmission. We also describe how areal weighting, pycnophylactic interpolation and accessibility potential interpolation techniques can be used to generate novel human population distribution surfaces from local census information and evaluate to what accuracy this can be achieved.

RESULTS

We demonstrate which human population distribution surface performed best and which population interpolation techniques generated the most accurate bespoke distributions. Despite various levels of modelling complexity, the accuracy achieved by the different surfaces was primarily determined by the spatial resolution of the input population data. The simplest technique of areal weighting performed best.

CONCLUSIONS

Differences in estimates of populations at risk of malaria in Kenya of over 1 million persons can be generated by the choice of surface, highlighting the importance of these considerations in deriving per capita health metrics in public health. Despite focussing on Kenya the results of these analyses have general application and are discussed in this wider context.

Brands, costs and registration status of antimalarial drugs in the Kenyan retail sector

Background

Although an important source of treatment for fevers, little is known about the structure of the retail sector in Africa with regard to antimalarial drugs. This study aimed to assess the range, costs, sources and registration of antimalarial drugs in the Kenyan retail sector.

Methods

In 2002, antimalarial drug registration and trade prices were established by triangulating national registration lists, government gazettes and trade price indices. Data on registration status and trade prices were compared with similar data generated through a retail audit undertaken among 880 randomly sampled retailers in four districts of Kenya.

Results

Two hundred and eighteen antimalarial drugs were in circulation in Kenya in 2002. These included 65 "sulfur"-pyrimethamine (sulfadoxine-pyrimethamine and sulfalene-pyrimethamine (SP), the first-line recommended drug in 2002) and 33 amodiaquine (AQ, the second-line recommended drug) preparations. Only half of SP and AQ products were registered with the Pharmacy and Poisons Board. Of SP and AQ brands at district level, 40% and 44% were officially within legal registration requirements. 29% of retailers at district level stocked SP and 95% stocked AQ. The retail price of adult doses of SP and AQ were on average 0.38 and 0.76 US dollars, 100% and 347% higher than trade prices from manufacturers and importers. Artemether-lumefantrine, the newly announced first-line recommended antimalarial drug in 2004, was found in less than 1% of all retail outlets at a median cost of 7.6 US dollars.

Conclusion

There is a need to ensure that all antimalarial drugs are registered with the Pharmacy and Poisons Board to facilitate a more stringent post-marketing surveillance system to ensure drugs are safe and of good quality post-registration.

Climate variability and malaria epidemics in the highlands of East Africa

Malaria epidemics in the highlands of East Africa garner significant research attention, due, in part, to their proposed sensitivity to climate change. In a recent article, Zhou et al. claim that increases in climate variance, rather than simple increases in climate mean values, have had an important role in the resurgence of malaria epidemics in the East African highlands since the early 1980s. If proven, this would be an interesting result but we believe that the methods used do not test the hypothesis suggested.

Disparities in parasitic infections, perceived ill health and access to health care among poorer and less poor schoolchildren of rural Cote d'Ivoire

Differences in the state of health between rural and urban populations living in Africa have been described, yet only few studies analysed inequities within poor rural communities. We investigated disparities in parasitic infections, perceived ill health and access to formal health services among more than 4000 schoolchildren from 57 primary schools in a rural area of western Côte d'Ivoire, as measured by their socioeconomic status. In a first step, we carried out a cross-sectional parasitological survey. Stool specimens and finger prick blood samples were collected and processed with standardized, quality-controlled methods, for diagnosis of Schistosoma mansoni, soil-transmitted helminths, intestinal protozoa and Plasmodium. Then, a questionnaire survey was carried out for the appraisal of self-reported morbidity indicators, as well as housing characteristics and household assets ownership. Mean travel distance from each village to the nearest health care delivery structure was provided by the regional health authorities. Poorer schoolchildren showed a significantly higher infection prevalence of hookworm than better-off children. However, higher infection prevalences of intestinal protozoa (i.e. Blastocystis hominis, Endolimax nana and Iodamoeba butschlii) were found with increasing socioeconomic status. Significant negative associations were observed between socioeconomic status and light infection intensities with hookworm and S. mansoni, as well as with several self-reported morbidity indicators. The poorest school-attending children lived significantly further away from formal health services than their richer counterparts. Our study provides evidence for inequities among schoolchildren's parasitic infection status, perceived ill health and access to health care in a large rural part of Côte d'Ivoire. These findings call for more equity-balanced parasitic disease control interventions, which in turn might be an important strategy for poverty alleviation.

Urbanization, malaria transmission and disease burden in Africa

Many attempts have been made to quantify Africa's malaria burden but none has addressed how urbanization will affect disease transmission and outcome, and therefore mortality and morbidity estimates. In 2003, 39% of Africa's 850 million people lived in urban settings; by 2030, 54% of Africans are expected to do so. We present the results of a series of entomological, parasitological and behavioural meta-analyses of studies that have investigated the effect of urbanization on malaria in Africa. We describe the effect of urbanization on both the impact of malaria transmission and the concomitant improvements in access to preventative and curative measures. Using these data, we have recalculated estimates of populations at risk of malaria and the resulting mortality. We find there were 1,068,505 malaria deaths in Africa in 2000 - a modest 6.7% reduction over previous iterations. The public-health implications of these findings and revised estimates are discussed.

Defining approaches to settlement mapping for public health management in Kenya using medium spatial resolution satellite imagery

This paper presents an appraisal of satellite imagery types and texture measures for identifying and delineating settlements in four Districts of Kenya chosen to represent the variation in human ecology across the country. Landsat Thematic Mapper (TM) and Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) imagery of the four districts were obtained and supervised per-pixel classifications of image combinations tested for their efficacy at settlement delineation. Additional data layers including human population census data, land cover, and locations of medical facilities, villages, schools and market centres were used for training site identification and validation. For each district, the most accurate approach was determined through the best correspondence with known settlement and non-settlement pixels. The resulting settlement maps will be used in combination with census data to produce medium spatial resolution population maps for improved public health planning in Kenya.

Delivery of paediatric care at the first-referral level in Kenya

We aimed to investigate provision of paediatric care in government district hospitals in Kenya. We surveyed 14 first-referral level hospitals from seven of Kenya's eight provinces and obtained data for workload, outcome of admission, infrastructure, and resources and the views of hospital staff and caretakers of admitted children. Paediatric admission rates varied almost ten-fold. Basic anti-infective drugs, clinical supplies, and laboratory tests were available in at least 12 hospitals, although these might be charged for on discharge. In at least 11 hospitals, antistaphylococcal drugs, appropriate treatment for malnutrition, newborn feeds, and measurement of bilirubin were rarely or never available. Staff highlighted infrastructure and human and consumable resources as problems. However, a strong sense of commitment, support for the work of the hospital, and a desire for improvement were expressed. Caretakers' views were generally positive, although dissatisfaction with the physical environment in which care took place was common. The capacity of the district hospital in Kenya needs strengthening by comprehensive policies that address real needs if current or new interventions and services at this level of care are to enhance child survival.

Empirical modelling of government health service use by children with fevers in Kenya

An understanding of spatial patterns of health facility use allows a more informed approach to the modelling of catchment populations. In the absence of patient use data, an intuitive and commonly used approach to the delineation of facility catchment areas is Thiessen polygons. This study presents a series of methods by which the validity of these assumptions can be tested directly and hence the suitability of a Thiessen polygon catchment model explicitly assessed. These methods are applied to paediatric out-patient origin data from a sample of 81 government health facilities in four districts of Kenya. A geographical information system was used to predict the location of the catchment boundary along a transect between each pair of neighbouring facilities based on patient choice patterns. The mean location of boundaries between facilities of different type was found to be significantly displaced from the Thiessen boundary towards the lower-order facility. The affect of distance on within-catchment utilization rate was assessed by using exclusion buffers to remove the effect of neighbouring facilities. Utilization rate was found to exhibit a slight but steady decrease with distance up to 6 km from a facility. The accuracy of the future modelling of unsampled facility catchments can be increased by the incorporation of these trends.

Spatial analysis for epidemiology

Remote sensing, geographical information systems (GIS) and spatial analysis provide important tools that are as yet under-exploited in the fight against disease. As the use of such tools becomes more accepted and prevalent in epidemiological studies, so our understanding of the mechanisms of disease systems has the potential to increase. This paper introduces a range of techniques used in remote sensing, GIS and spatial analysis that are relevant to epidemiology. Possible future directions for the application of remote sensing, GIS and spatial analysis are also suggested.