Location Of Health Facilities Research Articles

Geospatial analysis and impact of targeted development of breast cancer care in The Gambia: a cross-sectional study

BackgroundThe Gambia has one of the lowest survival rates for breast cancer in Africa. Contributing factors are late presentation, delays within the healthcare system, and decreased availability of resources. We aimed to characterize the capacity and geographic location of healthcare facilities in the country and calculate the proportion of the population with access to breast cancer care.MethodsA facility-based assessment tool was administered to secondary and tertiary healthcare facilities and private medical centers and clinics in The Gambia. GPS coordinates were obtained, and proximity of service availability and population analysis were performed. Distance thresholds of 10, 20, and 45 km were chosen to determine access to screening, pathologic diagnosis, and surgical management. An additional population analysis was performed to observe the potential impact of targeted development of resources for breast cancer care.ResultsAll 102 secondary and tertiary healthcare facilities and private medical centers and clinics in The Gambia were included. Breast cancer screening is mainly performed through clinical breast examination and is available in 52 facilities. Seven facilities provide pathologic diagnosis and surgical management of breast cancer. The proportion of the Gambian population with access to screening, pathologic diagnosis, and surgical management is 72, 53, and 62%, respectively. A hypothetical targeted expansion of resources would increase the covered population to 95, 62, and 84%.ConclusionsAlmost half of the Gambian population does not have access to pathologic diagnosis and surgical management of breast cancer within the distance threshold utilized in the study. Mapping and population analysis can identify areas for targeted development of resources to increase access to breast cancer care.

Penentuan Lokasi Fasilitas Kesehatan Strategis Menggunakan Metode Naive Bayes pada RSU Bintang

At present the selection of strategic health facility locations is not easy, to determine the right location and in accordance with the needs of patients must use the right calculation. Bintang General Hospital (RSU Bintang) has difficulties in determining the strategic location of new health facilities. The difficulty is due to the absence of data processing from the current system so that in determining the location of strategic health facilities is not based on data that has been analyzed. Based on the problems experienced by RSU Bintang and to assist in making a decision in establishing a strategic health facility location, a study was made to design a decision support system that can perform calculations to determine the location of the most strategic health facility with the title "Decision Support System. Determining the Location of Strategic Health Facilities Using the Naive Bayes Method at RSU Bintang”. Decision support system that is built will have several functions, such as processing patient register data, user data processing, alternative location data processing, criteria data processing, data processing rules, Naive Bayes calculations and managing several reports that can be used as decision support for the RSU Bintang. in determining the location of the most strategic health facilities. In this system, testing has been done by using blackbox testing which gets the test results in accordance with the system design.

Situational analysis of diabetic retinopathy treatment Services in Ghana

BackgroundAlthough the equitable distribution of diabetic retinopathy (DR) services across Ghana remains paramount, there is currently a poor understanding of nationwide DR treatment services. This study aims to conduct a situation analysis of DR treatment services in Ghana and provide evidence on the breadth, coverage, workload, and gaps in service delivery for DR treatment.MethodsA cross-sectional study was designed to identify health facilities which treat DR in Ghana from June 2018 to August 2018. Data were obtained from the facilities using a semi-structured questionnaire which included questions identifying human resources involved in DR treatment, location of health facilities with laser, vitreoretinal surgery and Anti–vascular endothelial growth factor therapy (Anti-VEGF) for DR treatment, service utilisation and workload at these facilities, and the average price of DR treatment in these facilities.ResultsFourteen facilities offer DR treatment in Ghana; four in the public sector, seven in the private sector and three in the Christian Health Association of Ghana (CHAG) centres. There was a huge disparity in the distribution of facilities offering DR services, the eye care cadre, workload, and DR treatment service (retinal laser, Anti-VEGF, and vitreoretinal surgery). The retinal laser treatment price was independent of all variables (facility type, settings, regions, and National Health Insurance Scheme coverage). However, settings (p = 0.028) and geographical regions (p = 0.010) were significantly associated with anti-VEGF treatment price per eye.ConclusionOur results suggest a disproportionate distribution of DR services in Ghana. Hence, there should be a strategic development and implementation of an eye care plan to ensure the widespread provision of DR services to the disadvantaged population as we aim towards a disadvantaged population as we aim towards a universal health coverage.

Accessibility to primary health care in low-density regions. A case study: NUTS III - Baixo Alentejo - Portugal.

This study diagnosed the situation regarding the physical accessibility of the resident population to primary health care, based on the characteristics of the population served, their spatial distribution in the territory, based on space-time analysis. Thus, bearing the different means of transport available and the specific features of a low-density territory, we considered several mobility profiles under analysis, and selected the Baixo Alentejo as the study area. In methodological terms, besides using the location of primary health facilities and their areas of influence, the use of the road network and its restrictions, we selected the use the new 1x1 km grid, recently implemented throughout the EU (European Union), instead of using the statistical units or administrative boundaries. Its advantages allow overcoming some of the issues of the usual base cartography. The final results can be divided into two groups: conclusions related to the methodologies used and conclusions related to the accessibility of primary health care equipment in the study area.

Intellectual structure and trends in the humanitarian operations field.

Humanitarian Operations (HO) have attracted the interest of professionals and academics, mainly due to their potential to reduce human suffering in disaster situations, leading to consolidation as a research field. With the evolution of the HO research field, synthesis of the knowledge and previous discoveries has become an important task for its advancement. In this study, a literature review based on bibliometric mapping techniques was carried out in order to identify the HO intellectual structure. As main results, we visually present the general emerging structure of the HO field using the VOS viewer software to devise the networks of the principal articles. The seminal research in this field is organized into two clusters: Humanitarian Supply Chain Management, and Distribution Optimization in Humanitarian Logistics. Regarding the emerging intellectual structure, three clusters were identified: Relationship Management and Big Data, Healthcare facility location, and Network flow restoration optimization. Finally, some gaps and questions for future research are presented.

An Open Source GIS Application for Spatial Assessment of Health Care Quality Indicators

Prevention quality indicators (PQIs) constitute a set of measures that can be combined with hospital inpatient data to identify the quality of care for ambulatory care sensitive conditions (ACSC). Geographical information system (GIS) web mapping and applications contribute to a better representation of PQI spatial distribution. Unlike many countries in the world, in Portugal, this type of application remains underdeveloped. The main objective of this work was to facilitate the assessment of geographical patterns and trends of health data in Portugal. Therefore, two innovative open source applications were developed. Leaflet Javascript Library, PostGIS, and GeoServer were used to create a web map application prototype. Python language was used to develop the GIS application. The geospatial assessment of geographical patterns of health data in Portugal can be obtained through a GIS application and a web map application. Both tools proposed allowed for an easy and intuitive assessment of geographical patterns and time trends of PQI values in Portugal, alongside other relevant health data, i.e., the location of health care facilities, which, in turn, showed some association between the location of facilities and quality of health care. However, in the future, more research is still required to map other relevant data, for more in-depth analyses.

Incremental planning of the location of public health facilities in a rural region

Some people in rural areas are often excluded from using health facilities in developing nations due to political interference in facility location decision-making. Limited attention has been paid in the literature to promoting inclusiveness in public facilities usage in developing nations. Therefore, this study was designed to examine the access to Primary Health Centres (PHCs) in the Yewa region, Nigeria. Data on the 509 settlements and 91 PHCs in the Yewa region were obtained from government directories. The p-median Location-Allocation model was used for data analyses. The study showed that the number of PHCs increased and access to them improved in the Yewa region between 1991 and 2019. It was also shown that inclusiveness in facilities could be promoted by optimally adding new PHCs. The study assessed the effectiveness of past locational decisions, similar to other studies in Bangladesh and India, and revealed that the military administration performed better than the civilian administration in facility location decision-making between 1991 and 2019. The study showed how new facilities could be optimally located to improve access and inclusiveness in public usage.

Hierarchical Healthcare Facility Location at the Subdistrict Level in Western Uttar Pradesh: A Heuristic Approach

The Governments across the world are making continuous efforts to attain health for all. The efforts can gain more efficiency if the new healthcare facilities are created at optimal locations. There are various constraints on healthcare facilities, like cost of setup, coverage distance, service distance, population load, manpower and services offered. These constraints operate in a complex setting giving rise to alternate scenarios. The study proposes replicable heuristics to obtain the optimal locations under alternate scenarios for the Sub Centers (SC), Primary healthcare centers (PHC) and Community healthcare centers (CHC). The study takes the case of a block of villages in most populous state of India using the publicly available data, data from census, government portals and Bing Maps services. The study generates several alternatives scenarios for maximize demand, minimize service distance and minimize total costs for different population covered and service distance. The methodology suggested here might be helpful for the location decision making at the block level by the district administration.

How prepared is Mozambique to treat COVID-19 patients? A new approach for estimating oxygen service availability, oxygen treatment capacity, and population access to oxygen-ready treatment facilities

BackgroundThis study aims to assess the COVID-19 response preparedness of the Mozambican health system by 1) determining the location of oxygen-ready public health facilities, 2) estimating the oxygen treatment capacity, and 3) determining the population coverage of oxygen-ready health facilities in Mozambique.MethodsThis analysis utilizes information on the availability of oxygen sources and delivery apparatuses to determine if a health facility is ready to deliver oxygen therapy to patients in need, and estimates how many patients can be treated with continuous oxygen flow for a 7-day period based on the available oxygen equipment at health facilities. Using GIS mapping software, the study team modeled varying travel times to oxygen-ready facilities to estimate the proportion of the population with access to care.Results0.4% of all health facilities in Mozambique are prepared to deliver oxygen therapy to patients, for a cumulative total of 283.9 to 406.0 patients-weeks given the existing national capacity, under varying assumptions including ability to divert oxygen from a single source to multiple patients. 35% of the population in Mozambique has adequate access within one-hour driving time of an oxygen-ready health facility. This varies widely by region; 89.1% of the population of Maputo City was captured by the one-hour driving time network, as compared ot 4.4% of the population of Niassa province.ConclusionsThe Mozambican health system faces the dual challenges of under-resourced health facilities and low geographic accessibility to healthcare as it prepares to confront the COVID-19 pandemic. This analysis also illustrates the disparity between provinces in preparedness to deliver oxygen therapy to patient, with Cabo Delgado and Nampula being particularly under-resourced.

Network constrained and classified spatial pattern analysis of healthcare facilities and their relationship with the road structure: a case study of Thiruvananthapuram city

Equity of the utilization of medical facilities is extremely dependant on the spatial distribution of healthcare amenities. In this study, an attempt is made to study the geographic distribution of the various categories of healthcare facilities in the city of Thiruvananthapuram, South India using the centrographic analysis that includes the Mean Center, Standard Deviational Ellipse and Average Nearest Neighbour and it was found that there is an uneven distribution. Network-based point pattern analysis is also performed and cross k-function is used to determine the distribution of medical shops relative to the healthcare services. A weighted node approach is used to calculate the indices of centrality by weighing all nodes based on their degree using Geographical Information System (GIS). Multi centrality assessment model consisting of betweenness, closeness and straightness centrality is used to compute the weighted road centrality on a local and global scale. Kernel Density Estimation technique is applied to modify the centrality values and the vector points to a basic raster framework. Correlation analysis was performed to find the role of the network centrality on the location of healthcare facilities in the study area. Correlation values are greatest among category 2 hospitals; straightness centrality and betweenness centrality favours the location of category 1 hospitals and homeopathy hospitals respectively. The results confirm that network topology influences the location of medical facilities in the study area.

A reproducible picture of open access health facility data in Africa andR tools to support improvement.

Background: Open data on the locations and services provided by health facilities have, in some countries, allowed the development of software tools contributing to COVID-19 response. The UN and WHO encourage countries to make health facility location data open, to encourage use and improvement. We provide a summary of open access health facility location data in Africa using re-useable R code. We aim to support data analysts developing software tools to address COVID-19 response in individual countries. In Africa there are currently three main sources of such open data; 1) direct from national ministries of health, 2) a database for sub-Saharan Africa collated and published by a team from KEMRI-Wellcome Trust Research Programme and now hosted by WHO, and 3) The Global Healthsites Mapping Project in collaboration with OpenStreetMap. Methods: We searched for and documented official national facility location data that were openly available. We developed re-useable open-source R code to summarise and visualise facility location data by country from the three sources. This re-useable code is used to provide a web user interface allowing data exploration through maps and plots of facility type. Results: Out of 52 African countries, seven currently provide an official open facility list that can be downloaded and analysed reproducibly. Considering all three sources, there are over 185,000 health facility locations available for Africa. However, there are differences and overlaps between sources and a lack of data on capacities and service provision. Conclusions: These summaries and software tools can be used to encourage greater use of existing health facility location data, incentivise further improvements in the provision of those data by national suppliers, and encourage collaboration within wider data communities. The tools are a part of the afrimapr project, actively developing R building blocks to facilitate the use of health data in Africa.

An artificial neural network based mathematical model for a stochastic health care facility location problem.

This research is conducted to investigate the problem of locating the trauma centers and helicopters' station in order to optimize the trauma care system. The stochastic characteristics of the system, such as stochastic transferring time of the patients, stochastic demand and stochastic servicing time of the patients in trauma centers are taken into account. The problem is first modeled as a stochastic mixed-integer linear mathematical model. In the proposed model, minimizing the total cost, minimizing the transferring time, and minimizing the waiting time inside the trauma center are considered as the three separate objectives. The third objective cannot be expressed by an analytical expression because of the complexity inside a trauma center. Therefore, an artificial neural network (ANN) is first trained by a simulation model and then is utilized to estimate the third objective function. A hybrid multi-objective algorithm is developed based on a non-dominated sorting water flow algorithm in order to search the solution space. Different numerical examples are applied to study the performance of the proposed method. The computational results show that the combination of simulation, ANN, and optimization technique provides an effective means for the highly complex optimization problems.

English

BACKGROUND Dengue Fever is a major contributor to morbidity and mortality among all communicable diseases in Kerala. Delay in seeking care is significantly associated with complications. Understanding health seeking behaviour of persons with risk of infection, helps in improving health care delivery. METHODS A cross sectional study was done among 100 dengue fever patients listed under Integrated Disease Surveillance Programme (IDSP) of Thiruvananthapuram district, Kerala state. Data regarding their health seeking behaviour during the course of the disease was collected using a structured questionnaire. RESULTS Inappropriate health seeking behaviour indicated by delay in seeking care and self medication was found in 22 % (95 % CI; 13.9 - 30.1) of subjects. Mean (SD) of delay in seeking health care was 3.01 (1.3) days. Treatment was initiated from government health facility by 63 % of patients. Primary level health care facility was sought by 61 % patients whereas 30 % opted for a secondary level facility. Proximity of the location of health facility to the patient’s dwelling was the factor influencing choice of treatment facility in 70 % of patients, followed by perceived quality of facility (15 %) and patient perceived competency of the physician (9 %). Male gender (p = 0.03) and educational status less than secondary level (p = 0.008) were significant risk factors for self-medication and delay in seeking health care. CONCLUSIONS Inappropriate health seeking behaviour in patients with suspected Dengue Fever is comparatively less in Kerala. Majority are seeking care from Government facilities and access to health care is influencing health seeking behaviour. Awareness generation in general and specific interventions targeting those with lower education status can further improve health seeking behaviour and reduce complications of dengue. KEYWORDS Health Seeking Behaviour, Dengue Fever, Self-Medication, Delay in Seeking Care, Healthcare Access, Kerala

A positive attitude among primary healthcare providers predicts better hepatitis B prevention practices: evidence from a cross-sectional survey in Wakiso district, Central Uganda

ABSTRACT Background: Hepatitis B Virus (HBV) infection is an important occupational health risk among primary healthcare providers (PHCPs). However, there is limited evidence on whether PHCPs’ level of knowledge and attitude can predict better HBV infection prevention practices. This study established the relationship between knowledge, attitude, and HBV infection prevention practices among PHCPs in Wakiso district, Central Uganda. Methods: A cross-sectional study design was used. Data were collected from 306 PHCPs, using a structured questionnaire. PHCPs were randomly selected from 55 healthcare facilities. STATA version 14.0 was used to analyse data. A ‘modified Poisson’ regression model was used for inferential statistics. Results: About 42.2% of PHCPs exhibited poor knowledge of HBV infection transmission and prevention, 41.8% had a negative attitude, and 41.5% exhibited poor prevention practices. Age (PR 1.82, 95% CI: 1.24–2.66) was positively associated with the level of knowledge. Healthcare facility level (PR 0.53, 95% CI: 0.34–0.84), main department of work (PR 0.69, 95% CI: 0.51–0.95), years in service (PR 0.66, 95% CI: 0.44–0.99), working in private not-for-profit healthcare facilities (PR 0.59, 95% CI: 0.34–0.99), and public healthcare facilities (PR 0.58, 95% CI: 0.42–0.80) were negatively associated with the level of knowledge. There was a negative association between the location of healthcare facility (PR 0.76, 95% CI: 0.62–0.93) and attitude, and a positive association between level of knowledge (PR 1.36, 95% 1.12–1.65) and attitude. Working in a public healthcare facility (PR 0.80, 95% CI: 0.64–0.99) was negatively associated with practices while having a positive attitude (PR 1.60, 95% CI: 1.28–1.99) predicted better HBV infection prevention practices. Conclusion: PHCPs who were more knowledgeable about HBV infection were more likely to have a positive attitude. In turn, having a positive attitude was associated with better HBV infection prevention practices. There is a need to sensitise PHCPs on HBV infection, and provision of screening and vaccination services in order to address the KAP gaps.

Rethinking Physical Access to Healthcare: Aligning Healthcare Facilities with Population in Mbeya City, Tanzania

Local governments, such as the Mbeya City Council (MCC), desire its citizens to have better physical access to healthcare services as stipulated in the national health policy and the World Health Organization (WHO). The challenge, however, is for the MCC to ensure that physical accessibility to healthcare facilities align with urban planning initiatives and the respective population in the wards. This study employed the Geographical Information System (GIS) and a Location-Allocation model in data analysis. Multiple spatial and aspatial datasets were analysed to establish the current distribution of healthcare facilities, spatial accessibility by the people, population distribution and how physical accessibility to healthcare facilities is reflected in physical planning of urban space. The results show that on average people in the respective wards travel over 15–25km, which is beyond the 5km distance recommended by the WHO. In addition, people spend 30–51 minutes to reach healthcare facilities that are centrally located within the city. Similarly, physical planning of urban space mismatch with actual required people’s accessibility to healthcare facilities. The locations of healthcare facilities and population distribution do not align, implying that there are still demand points that need to be served in the wards. It is concluded that physical planning for the location of healthcare facilities should reflect the population distribution and pace of urbanization of a city to improve access to healthcare facilities. The use of the central place theory in physical planning of the city, when combined with a people-centred perspective in planning for healthcare facilities, would place healthcare facilities in close proximity to the people. It is recommended that new siting of healthcare facilities should consider the distribution of the population in the city. In addition, physical planning of the urban infrastructure and the initiatives to improve accessibility to health must align at local level.

Social determinants of health in rural Zimbabwe: an econometric data analysis

This research focused on ten social determinants of health which are work type, asset ownership, personal income, age, distance to primary health centre, gender, present locality, severity of illness, education and lastly culture. The endogenous variable was health. A stratified random sampling technique was used to collect primary data from 398 observations and the data was manipulated using stata version 11. The probit model empirical results showed that, gender, distance to primary health centre, personal income, education, culture and present location statistically significant at 1% level of significance. Work type was significant at 5% level. The variables work type, gender, and education had positive influence, while distance to primary health facility, personal income and present location had a negative influence to the probability of being health. Recommendations include building more health centres, harmonisation of traditional, spiritual and conventional clinics, discouraging rural urban migration and taxing luxury products.

Geographic location of health facility and immunization program performance in Hoima district, western Uganda: a health facility level assessment

BackgroundGlobally, immunization coverage for childhood vaccines is below the immunization target of achieving at least 90% coverage with the pentavalent vaccine. In Uganda, a recent survey shows 80% of districts had poor immunization program performance. However, there is significant variation in performance within and between districts. We hypothesized that geographic location of a health facility may influence performance of its immunization programs. Therefore, the purpose of this study was to examine whether geographical location of a health facility within a district is associated with performance of the immunization program in Hoima district, western Uganda.MethodsWe conducted a cross sectional study using a mixed methods approach. The main study unit was a health center and we also interviewed health workers in-charge of the facilities and reviewed their health facility records. We reviewed the Uganda Health Management Information System (HMIS) 105 reports of six months to obtain data on immunization program performance. Performance was categorized using World Health Organization’s Reach Every District (RED) criteria and classified as poor if a facility fell in category 3 or 4 and good if 1 or 2. We also conducted key informant interviews with immunization focal persons in the district. We examined the association between dependent and independent variables using Fisher’s exact test.ResultsWe collected data at 49 health facilities. Most of these facilities (55.1%) had poor immunization program performance. Proximal location to the central district headquarters was significantly associated with poor immunization program performance (p < 0.05). Attitudes of health workers in the more urban areas, differences in strategies for outreach site selection and community mobilization in the rural and urban areas were suggested as possible explanations.ConclusionsProximal location to the urban setting near district headquarters was strongly associated with poor immunization program performance. To be able to reach larger numbers of children for vaccination, interventions to improve performance should target health facilities in urban settings.

A reproducible picture of open access health facility data in Africa and R tools to support improvement

Background: Open data on the locations and services provided by health facilities have, in some countries, allowed the development of software tools contributing to COVID-19 response. The UN and WHO encourage countries to make health facility location data open, to encourage use and improvement. We provide a summary of open access health facility location data in Africa using re-useable R code. We aim to support data analysts developing software tools to address COVID-19 response in individual countries. In Africa there are currently three main sources of such open data; 1) direct from national ministries of health, 2) a database for sub-Saharan Africa collated and published by a team from KEMRI-Wellcome Trust Research Programme and now hosted by WHO, and 3) The Global Healthsites Mapping Project in collaboration with OpenStreetMap. Methods: We searched for and documented official national facility location data that were openly available. We developed re-useable open-source R code to summarise and visualise facility location data by country from the three sources. This re-useable code is used to provide a web user interface allowing data exploration through maps and plots of facility type. Results: Out of 52 African countries, seven currently provide an official open facility list that can be downloaded and analysed reproducibly. Considering all three sources, there are over 185,000 health facility locations available for Africa. However, there are differences and overlaps between sources and a lack of data on capacities and service provision. Conclusions: These summaries and software tools can be used to encourage greater use of existing health facility location data, incentivise further improvements in the provision of those data by national suppliers, and encourage collaboration within wider data communities. The tools are a part of the afrimapr project, actively developing R building blocks to facilitate the use of health data in Africa.

Preventive healthcare facility location planning with quality-conscious clients

Pursuing the overarching goal of saving both lives and healthcare costs, we introduce an approach to increase the expected participation in a preventive healthcare program, e.g., breast cancer screening. In contrast to sick people who need urgent medical attention, the clients in preventive healthcare decide whether to go to a specific facility (if this maximizes their utility) or not to take part in the program. We consider clients’ utility functions to include decision variables denoting the waiting time for an appointment and the quality of care. Both variables are defined as functions of a facility’s utilization. We employ a segmentation approach to formulate a mixed-integer linear program. Applying GAMS/CPLEX, we optimally solved instances with up to 400 demand nodes and 15 candidate locations based on both artificial data as well as in the context of a case study based on empirical data within one hour. We found that using a Benders decomposition of our problem decreases computational effort by more than 50%. We observe a nonlinear relationship between participation and the number of established facilities. The sensitivity analysis of the utility weights provides evidence on the optimal participation given a specific application (data set, empirical findings).

A rapid and reproducible picture of open access health facility data in Africa to support the COVID-19 response.

Background: Open data on the locations and services provided by health facilities in some countries have allowed the development of software tools contributing to COVID-19 response. The UN and WHO encourage countries to make health facility location data open, to encourage use and improvement. We provide a summary of open access health facility location data in Africa using re-useable code. We aim to support data analysts developing software tools to address COVID-19 response in individual countries. In Africa there are currently three main sources of such data; 1) direct from national ministries of health, 2) a database for sub-Saharan Africa collated and published by a team from KEMRI-Wellcome Trust Research Programme and now hosted by WHO, and 3) The Global Healthsites Mapping Project in collaboration with OpenStreetMap. Methods: We searched for and documented official national facility location data that were openly available. We developed re-useable open-source R code to summarise and visualise facility location data by country from the three sources. This re-useable code is used to provide a web user interface allowing data exploration through maps and plots of facility type. Results: Out of 53 African countries, seven provide an official open facility list that can be downloaded and analysed reproducibly. Considering all three sources, there are over 185,000 health facility locations available for Africa. However, there are differences and overlaps between sources and a lack of data on capacities and service provision. Conclusions: We suggest that these summaries and tools will encourage greater use of existing health facility location data, incentivise further improvements in the provision of those data by national suppliers, and encourage collaboration within wider data communities. The tools are a part of the afrimapr project, actively developing R building blocks to facilitate the use of health data in Africa.