scholarly journals Geographic Variation in Access to Pathology and Laboratory Services in Tanzania: A Cross-Sectional Geospatial Analysis

2020 ◽  
Vol 6 (Supplement_1) ◽  
pp. 45-45
Author(s):  
Hari S. Iyer ◽  
Nicholas G. Wolf ◽  
Edda Vuhahula ◽  
Charles Massambu ◽  
Devanshi Shah ◽  
...  
Keyword(s):  
Population Density ◽  
Spatial Autocorrelation ◽  
Travel Time ◽  
Geographic Variation ◽  
District Level ◽  
Health Centers ◽  
Travel Times ◽  
Spatial Correlations ◽  
District Hospitals ◽  
Referral Hospitals

PURPOSE Increasing noncommunicable disease burden in sub-Saharan Africa requires the urgent scale-up of pathology and laboratory medicine (PALM) services. To identify service gaps at the district level, we studied geographic variation in the correlation between travel time to health facilities and population density. METHODS We linked geospatial data for Tanzania from multiple sources. Facility locations were extracted from a comprehensive facility list in Africa. Data on geographic factors, demographics, and roads were collected from government and nonprofit databases. We classified facilities assuming increasing PALM service readiness by level: dispensaries, health centers, district hospitals, and regional/referral hospitals. We input these data into the AccessMod 5 algorithm to estimate travel time across Tanzania with 1-km resolution for each PALM classification. We then calculated district-level averages of population and travel time for each PALM category. Associations between these variables were estimated using a bivariable local indicator of spatial autocorrelation, specifying immediate contiguity neighborhood definition. Spatial analysis was restricted to 172 contiguous districts (islands not included). Significance tests were two sided, with an α of .05. RESULTS Analysis included 5,342 dispensaries, 667 health centers, 185 district hospitals, and 34 regional/referral hospitals. Maps revealed clusters of estimated travel time in excess of 6 hours in less populated western and southern districts. More districts reported an average travel time of less than 1 hour to the nearest dispensary (69%) than to regional/referral hospitals (16%). Bivariable local indicators of spatial autocorrelation revealed few significant clusters of spatial correlations; however, significant correlations between low population density and longer travel times in neighboring districts were obtained for 13%, 16%, 15%, and 13% of districts for dispensaries, health centers, district hospitals, and regional/referral hospitals, respectively. CONCLUSION Limited variability of district-level spatial correlations suggests somewhat equitable geographic allocation of PALM services in Tanzania, with small areas of low population density and long travel times that demand additional intervention. Limitations include a lack of ascertainment of specific PALM services.

scholarly journals Geospatial evaluation of trade-offs between equity in physical access to healthcare and health systems efficiency

2020 ◽  
Vol 5 (10) ◽  
pp. e003493
Author(s):  
Hari S Iyer ◽  
John Flanigan ◽  
Nicholas G Wolf ◽  
Lee Frederick Schroeder ◽  
Susan Horton ◽  
...  
Keyword(s):  
Population Density ◽  
Spatial Autocorrelation ◽  
Travel Time ◽  
Geographical Distribution ◽  
Pearson’S Correlation ◽  
Trade Offs ◽  
Health Centres ◽  
Pearson's Correlation ◽  
Physical Access ◽  
Geographical Clusters

IntroductionDecisions regarding the geographical placement of healthcare services require consideration of trade-offs between equity and efficiency, but few empirical assessments are available. We applied a novel geospatial framework to study these trade-offs in four African countries.MethodsGeolocation data on population density (a surrogate for efficiency), health centres and cancer referral centres in Kenya, Malawi, Tanzania and Rwanda were obtained from online databases. Travel time to the closest facility (a surrogate for equity) was estimated with 1 km resolution using the Access Mod 5 least cost distance algorithm. We studied associations between district-level average population density and travel time to closest facility for each country using Pearson’s correlation, and spatial autocorrelation using the Global Moran’s I statistic. Geographical clusters of districts with inefficient resource allocation were identified using the bivariate local indicator of spatial autocorrelation.ResultsPopulation density was inversely associated with travel time for all countries and levels of the health system (Pearson’s correlation range, health centres: −0.89 to −0.71; cancer referral centres: −0.92 to −0.43), favouring efficiency. For health centres, negative spatial autocorrelation (geographical clustering of dissimilar values of population density and travel time) was weaker in Rwanda (−0.310) and Tanzania (−0.292), countries with explicit policies supporting equitable access to rural healthcare, relative to Kenya (−0.579) and Malawi (−0.543). Stronger spatial autocorrelation was observed for cancer referral centres (Rwanda: −0.341; Tanzania: −0.259; Kenya: −0.595; Malawi: −0.666). Significant geographical clusters of sparsely populated districts with long travel times to care were identified across countries.ConclusionNegative spatial correlations suggested that the geographical distribution of health services favoured efficiency over equity, but spatial autocorrelation measures revealed more equitable geographical distribution of facilities in certain countries. These findings suggest that even when prioritising efficiency, thoughtful decisions regarding geographical allocation could increase equitable physical access to services.

scholarly journals Sistem Rujukan Maternal dan Neonatal di Daerah Kepulauan (Studi Kasus di Provinsi Papua dan Maluku)

2018 ◽  
Vol 28 (2) ◽  
pp. 83-94
Author(s):  
Heny Lestary ◽  
Sugiharti Sugiharti ◽  
Mujiati Mujiati
Keyword(s):  
Health Workers ◽  
District Hospital ◽  
Health Centers ◽  
Referral System ◽  
Cross Sectional ◽  
Neonatal Deaths ◽  
District Hospitals ◽  
Referral Hospitals ◽  
Maternal And Neonatal Health ◽  
Document Review

Maternal and neonatal health services are aimed to produce a healthy and quality generation and reduce maternal mortality rate (MMR) and infant mortality (IMR). MMR and IMR in Indonesia tend not to improve. Targeted reduction of MMR and IMR will be difficult to achieve if not given appropriate intervention, both socially, economically and culturally, as well as stabilization of referral system. In 2015, research on maternal and neonatal referral system in Papua and Maluku provinces was conducted. Data were collected at selected health centers, District hospitals, provincial hospitals, and regional referral hospitals. Study design is cross sectional. Data collection was done by interview, document review, verbal autopsy, and survey to health facilities and infrastructure. The results show that both provinces already have Governor Decree related to health care system and regionalization policy, but have not translated into Mayor Decree in each selected district. Referral flow indicates that there are still many health workers / families who choose directly to the district hospital or provincial hospital or health worker who refers to other closer regency hospitals. The number of maternal and neonatal deaths is still high, the unavailability of OBGY and Pediatricians, low compliance of the BEONC and CEONC standards. Consumables and drugs are often depleted because of the lack of coordination, uncontrolled stock, and the late of drug requests. Event though maternal and neonatal referrals have been financed through National Health Insurance, however still many shortcomings, both in terms of funding flows and problems in administrative completeness, as well as unavailability of accommodation and transportation costs for families and midwives who will accompany mother. Abstrak Pelayanan kesehatan maternal dan neonatal ditujukan untuk menjaga kesehatan ibu sehingga mampu melahirkan generasi yang sehat dan berkualitas serta mengurangi Angka Kematian Ibu (AKI) dan Angka Kematian Bayi (AKB). AKI dan AKB di Indonesia cenderung tidak mengalami perbaikan. Target penurunan AKI dan AKB akan sulit dicapai jika tidak diberikan intervensi yang tepat, baik secara sosial, ekonomi dan budaya, serta pemantapan sistem rujukan. Pada tahun 2015 dilakukan penelitian sistem rujukan maternal dan neonatal di Provinsi Papua dan Maluku. Pengumpulan data dilakukan di puskesmas terpilih, RSUD Kabupaten, RSUP Provinsi, dan RSUP Rujukan Regional. Disain penelitian studi potong lintang. Pengumpulan data dilakukan dengan wawancara, penelusuran dokumen, autopsi verbal, dan check list kelengkapan sarana dan prasarana. Hasil penelitian menunjukkan kedua provinsi sudah memiliki PerGub terkait dengan sistem pelayanan kesehatan dan kebijakan regionalisasi, namun belum diterjemahkan ke dalam PerBup di masing – masing kabupaten terpilih. Alur rujukan menunjukkan masih banyak tenaga kesehatan/keluarga yang memilih langsung ke RS kabupaten/RS provinsi atau tenaga kesehatan yang merujuk ke RS kabupaten lain yang lebih dekat. Jumlah kematian maternal dan neonatal masih tinggi, tidak tersedianya DSOG dan DSA, sarana prasarana masih belum sesuai standar PONED dan PONEK, ketersediaan dan kecukupan alat di Provinsi Papua masih di bawah 50 persen. Bahan habis pakai dan obat sering habis karena tingkat koordinasi, pengontrolan stok, dan daftar permintaan obat kurang terkontrol. Pembiayaan rujukan maternal dan neonatal melalui sistem JKN dan Jamkesda, namun banyak mengalami kekurangan, baik dalam hal alur pembiayaan maupun permasalahan di kelengkapan administrasi, serta tidak tersedianya biaya akomodasi dan transportasi bagi keluarga dan bidan pendamping pasien.

Vehicle Travel Time Prediction in Spatio-Temporal Space

2012 ◽  
Vol 253-255 ◽  
pp. 1662-1665
Author(s):  
Qing Li ◽  
William H. K. Lam ◽  
Mei Lam Tam
Keyword(s):  
Travel Time ◽  
Travel Times ◽  
Spatial Correlations ◽  
Travel Time Prediction ◽  
Time Data ◽  
Time Prediction ◽  
Temporal Space ◽  
Temporal And Spatial ◽  
Spatio Temporal ◽  
Link Travel Time

It is recognized that travel times on a link are temporally correlated with its travel times of previous time periods. Also, the link travel time are spatially correlated by travel times on its neighboring links. Based on such temporal and spatial correlations, a new method is proposed for travel time prediction in urban roads. The proposed method is capable of rapidly predicting the link travel time in the near future. For validation of the proposed method, the temporal and spatial variance-covariance of travel times on related links are employed together with historical travel time data. It is found that the proposed method is able to provide more accurate travel time prediction.

scholarly journals Increased travel times to United States SARS-CoV-2 testing sites: a spatial modeling study

2020 ◽  
Author(s):  
Benjamin Rader ◽  
Christina M. Astley ◽  
Karla Therese L. Sy ◽  
Kara Sewalk ◽  
Yulin Hswen ◽  
...  
Keyword(s):  
United States ◽  
Population Density ◽  
Travel Time ◽  
Demographic Data ◽  
The United States ◽  
List Type ◽  
Median Income ◽  
Travel Times ◽  
Cross Sectional ◽  
Geographic Accessibility

AbstractImportanceAccess to testing is key to a successful response to the COVID-19 pandemic.ObjectiveTo determine the geographic accessibility to SARS-CoV-2 testing sites in the United States, as quantified by travel time.DesignCross-sectional analysis of SARS-CoV-2 testing sites as of April 7, 2020 in relation to travel time.SettingUnited States COVID-19 pandemic.ParticipantsThe United States, including the 48 contiguous states and the District of Columbia.ExposuresPopulation density, percent minority, percent uninsured, and median income by county from the 2018 American Community Survey demographic data.Main OutcomeSARS-CoV-2 testing sites identified in two national databases (Carbon Health and CodersAgainstCovid), geocoded by address. Median county 1 km2 gridded friction surface of travel times, as a measure of geographic accessibility to SARS-CoV-2 testing sites.Results6,236 unique SARS-CoV-2 testing sites in 3,108 United States counties were identified. Thirty percent of the U.S. population live in a county (N = 1,920) with a median travel time over 20 minutes. This was geographically heterogeneous; 86% of the Mountain division population versus 5% of the Middle Atlantic population lived in counties with median travel times over 20 min. Generalized Linear Models showed population density, percent minority, percent uninsured and median income were predictors of median travel time to testing sites. For example, higher percent uninsured was associated with longer travel time (β = 0.41 min/percent, 95% confidence interval 0.3-0.53, p = 1.2×10−12), adjusting for population density.Conclusions and RelevanceGeographic accessibility to SARS-Cov-2 testing sites is reduced in counties with lower population density and higher percent of minority and uninsured, which are also risk factors for worse healthcare access and outcomes. Geographic barriers to SARS-Cov-2 testing may exacerbate health inequalities and bias county-specific transmission estimates. Geographic accessibility should be considered when planning the location of future testing sites and interpreting epidemiological data.Key PointsSARS-CoV-2 testing sites are distributed unevenly in the US geography and population.Median county-level travel time to SARS-CoV-2 testing sites is longer in less densely populated areas, and in areas with a higher percentage of minority or uninsured populations.Improved geographic accessibility to testing sites is imperative to manage the COVID-19 pandemic in the United States.

scholarly journals “In cities, it’s not far, but it takes long”: comparing estimated and replicated travel times to reach life-saving obstetric care in Lagos, Nigeria

2021 ◽  
Vol 6 (1) ◽  
pp. e004318
Author(s):  
Aduragbemi Banke-Thomas ◽  
Kerry L M Wong ◽  
Francis Ifeanyi Ayomoh ◽  
Rokibat Olabisi Giwa-Ayedun ◽  
Lenka Benova
Keyword(s):  
Travel Time ◽  
Friction Surface ◽  
Obstetric Care ◽  
Travel Times ◽  
Night Time ◽  
Google Maps ◽  
Surface Approach ◽  
Low Resource ◽  
Life Saving ◽  
The Cost

BackgroundTravel time to comprehensive emergency obstetric care (CEmOC) facilities in low-resource settings is commonly estimated using modelling approaches. Our objective was to derive and compare estimates of travel time to reach CEmOC in an African megacity using models and web-based platforms against actual replication of travel.MethodsWe extracted data from patient files of all 732 pregnant women who presented in emergency in the four publicly owned tertiary CEmOC facilities in Lagos, Nigeria, between August 2018 and August 2019. For a systematically selected subsample of 385, we estimated travel time from their homes to the facility using the cost-friction surface approach, Open Source Routing Machine (OSRM) and Google Maps, and compared them to travel time by two independent drivers replicating women’s journeys. We estimated the percentage of women who reached the facilities within 60 and 120 min.ResultsThe median travel time for 385 women from the cost-friction surface approach, OSRM and Google Maps was 5, 11 and 40 min, respectively. The median actual drive time was 50–52 min. The mean errors were >45 min for the cost-friction surface approach and OSRM, and 14 min for Google Maps. The smallest differences between replicated and estimated travel times were seen for night-time journeys at weekends; largest errors were found for night-time journeys at weekdays and journeys above 120 min. Modelled estimates indicated that all participants were within 60 min of the destination CEmOC facility, yet journey replication showed that only 57% were, and 92% were within 120 min.ConclusionsExisting modelling methods underestimate actual travel time in low-resource megacities. Significant gaps in geographical access to life-saving health services like CEmOC must be urgently addressed, including in urban areas. Leveraging tools that generate ‘closer-to-reality’ estimates will be vital for service planning if universal health coverage targets are to be realised by 2030.

scholarly journals Exploring country-wide equitable government health care facility access in Uganda

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Nicholas Dowhaniuk
Keyword(s):  
Health Care ◽  
Random Forest ◽  
Health Center ◽  
Travel Time ◽  
Health Centers ◽  
Sub Saharan Africa ◽  
Walking Distance ◽  
Laboratory System ◽  
Government Health ◽  
Sub Saharan

Abstract Background Rural access to health care remains a challenge in Sub-Saharan Africa due to urban bias, social determinants of health, and transportation-related barriers. Health systems in Sub-Saharan Africa often lack equity, leaving disproportionately less health center access for the poorest residents with the highest health care needs. Lack of health care equity in Sub-Saharan Africa has become of increasing concern as countries enter a period of simultaneous high infectious and non-communicable disease burdens, the second of which requires a robust primary care network due to a long continuum of care. Bicycle ownership has been proposed and promoted as one tool to reduce travel-related barriers to health-services among the poor. Methods An accessibility analysis was conducted to identify the proportion of Ugandans within one-hour travel time to government health centers using walking, bicycling, and driving scenarios. Statistically significant clusters of high and low travel time to health centers were calculated using spatial statistics. Random Forest analysis was used to explore the relationship between poverty, population density, health center access in minutes, and time saved in travel to health centers using a bicycle instead of walking. Linear Mixed-Effects Models were then used to validate the performance of the random forest models. Results The percentage of Ugandans within a one-hour walking distance of the nearest health center II is 71.73%, increasing to 90.57% through bicycles. Bicycles increased one-hour access to the nearest health center III from 53.05 to 80.57%, increasing access to the tiered integrated national laboratory system by 27.52 percentage points. Significant clusters of low health center access were associated with areas of high poverty and urbanicity. A strong direct relationship between travel time to health center and poverty exists at all health center levels. Strong disparities between urban and rural populations exist, with rural poor residents facing disproportionately long travel time to health center compared to wealthier urban residents. Conclusions The results of this study highlight how the most vulnerable Ugandans, who are the least likely to afford transportation, experience the highest prohibitive travel distances to health centers. Bicycles appear to be a “pro-poor” tool to increase health access equity.

Estimation of Path Travel Time Distributions in Stochastic Time-Varying Networks with Correlations

2021 ◽  
pp. 036119812110184
Author(s):  
Monika Filipovska ◽  
Hani S. Mahmassani ◽  
Archak Mittal
Keyword(s):  
Time Dependence ◽  
Travel Time ◽  
Correlation Structure ◽  
Time Varying ◽  
Travel Times ◽  
Trajectory Data ◽  
Time Varying Networks ◽  
Transportation Research ◽  
Search Approach ◽  
Stochastic Time

Transportation research has increasingly focused on the modeling of travel time uncertainty in transportation networks. From a user’s perspective, the performance of the network is experienced at the level of a path, and, as such, knowledge of variability of travel times along paths contemplated by the user is necessary. This paper focuses on developing approaches for the estimation of path travel time distributions in stochastic time-varying networks so as to capture generalized correlations between link travel times. Specifically, the goal is to develop methods to estimate path travel time distributions for any path in the networks by synthesizing available trajectory data from various portions of the path, and this paper addresses that problem in a two-fold manner. Firstly, a Monte Carlo simulation (MCS)-based approach is presented for the convolution of time-varying random variables with general correlation structures and distribution shapes. Secondly, a combinatorial data-mining approach is developed, which aims to utilize sparse trajectory data for the estimation of path travel time distributions by implicitly capturing the complex correlation structure in the network travel times. Numerical results indicate that the MCS approach allowing for time-dependence and a time-varying correlation structure outperforms other approaches, and that its performance is robust with respect to different path travel time distributions. Additionally, using the path segmentations from the segment search approach with a MCS approach with time-dependence also produces accurate and robust estimates of the path travel time distributions with the added benefit of shorter computation times.

scholarly journals Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Cong Bai ◽  
Zhong-Ren Peng ◽  
Qing-Chang Lu ◽  
Jian Sun
Keyword(s):  
Travel Time ◽  
Dynamic Model ◽  
Kalman Filtering ◽  
Prediction Models ◽  
Support Vector ◽  
Travel Times ◽  
Travel Time Prediction ◽  
Real World Data ◽  
Time Prediction ◽  
Bus Travel Time

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

Intensities and travel times of seismic rays in a sphere with a linear velocity function

1977 ◽  
Vol 67 (1) ◽  
pp. 33-42
Author(s):  
Mark E. Odegard ◽  
Gerard J. Fryer
Keyword(s):  
Velocity Profile ◽  
Travel Time ◽  
Upper Mantle ◽  
Intensity Ratio ◽  
Computation Time ◽  
Spherical Body ◽  
Travel Times ◽  
Velocity Function ◽  
Intensity Ratios ◽  
Distance Travel

Abstract Equations are presented which permit the calculation of distances, travel times and intensity ratios of seismic rays propagating through a spherical body with concentric layers having velocities which vary linearly with radius. In addition, a method is described which removes the infinite singularities in amplitude generated by second-order discontinuities in the velocity profile. Numerical calculations involving a reasonable upper mantle model show that the standard deviations of the errors for distance, travel time and intensity ratio are 0.0046°, 0.057 sec, and 0.04 dB, respectively. Computation time is short.

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