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Prestige Tatenda Makanga - One of the best experts on this subject based on the ideXlab platform.

  • Is the closest health facility the one used in pregnancy care-seeking? A cross-sectional comparative analysis of self-reported and modelled Geographical Access to maternal care in Mozambique, India and Pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Background Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. Objectives This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Methods Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Results Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H_0: Mean difference = 0)] 

  • is the closest health facility the one used in pregnancy care seeking a cross sectional comparative analysis of self reported and modelled Geographical Access to maternal care in mozambique india and pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H0: Mean difference = 0)] < .001, limits of agreement: [− 273.81; 56.40] and [− 264.10; 94.25] respectively. In Mozambique, mean differences between the two measures of Access were significantly different from 0 [P (H0: Mean difference = 0) = 0.31, limits of agreement: [− 187.26; 199.96]]. Modelling Access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling Access should not be viewed through a Geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of Access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494

  • Seasonal variation in Geographical Access to maternal health services in regions of southern Mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura Magee, Peter Dadelszen, Esperança Sevene, Khátia Munguambe
    Abstract:

    Background Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. Methods A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Results Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Conclusions Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

  • seasonal variation in Geographical Access to maternal health services in regions of southern mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura A Magee, Peter Von Dadelszen, Esperança Sevene
    Abstract:

    Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

Esperança Sevene - One of the best experts on this subject based on the ideXlab platform.

  • Is the closest health facility the one used in pregnancy care-seeking? A cross-sectional comparative analysis of self-reported and modelled Geographical Access to maternal care in Mozambique, India and Pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Background Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. Objectives This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Methods Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Results Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H_0: Mean difference = 0)] 

  • is the closest health facility the one used in pregnancy care seeking a cross sectional comparative analysis of self reported and modelled Geographical Access to maternal care in mozambique india and pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H0: Mean difference = 0)] < .001, limits of agreement: [− 273.81; 56.40] and [− 264.10; 94.25] respectively. In Mozambique, mean differences between the two measures of Access were significantly different from 0 [P (H0: Mean difference = 0) = 0.31, limits of agreement: [− 187.26; 199.96]]. Modelling Access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling Access should not be viewed through a Geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of Access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494

  • Seasonal variation in Geographical Access to maternal health services in regions of southern Mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura Magee, Peter Dadelszen, Esperança Sevene, Khátia Munguambe
    Abstract:

    Background Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. Methods A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Results Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Conclusions Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

  • seasonal variation in Geographical Access to maternal health services in regions of southern mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura A Magee, Peter Von Dadelszen, Esperança Sevene
    Abstract:

    Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

Nadine Schuurman - One of the best experts on this subject based on the ideXlab platform.

  • cancer resection rates socioeconomic deprivation and Geographical Access to surgery among urban suburban and rural populations across canada
    PLOS ONE, 2020
    Co-Authors: Blake Byron Walker, Nadine Schuurman, Chuck K Wen, Saad Shakeel, Laura Schneider, Christian Finley
    Abstract:

    High-risk cancer resection surgeries are increasingly being performed at fewer, more specialised, and higher-volume institutions across Canada. The resulting increase in travel time for patients to obtain treatment may be exacerbated by socioeconomic barriers to Access. Focussing on five high-risk surgery types (oesophageal, ovarian/fallopian, liver, lung, and pancreatic cancers), this study examines socioeconomic trends in age-adjusted resection rates and travel time to surgery location for urban, suburban, and rural populations across Canada, excluding Quebec, from 2004 to 2012. Significant differences in age-adjusted resection rates were observed between urban (14.9 per 100 000 person-years [95% CI: 12.2, 17.6]), suburban (40.7 [40.1, 41.2]), and rural (32.7 [29.6, 35.9]) populations, with higher rates in suburban and rural areas throughout the study period for all cancer types. Resection rates did not differ between the highest (Q1) and lowest (Q5) socioeconomic strata (Q1: 13.3 [12.2, 14.4]; Q5: 12.0 [10.7, 13.4]), with significantly higher rates among middle-SES patients (Q2: 27.3 [25.6, 29.0]; Q3: 39.6 [37.4, 41.8]; Q4: 37.5 [35.3, 39.7]). Travel times to treatment were consistently higher among the most socioeconomically deprived patients, most notably in suburban and rural areas. The results suggest that the conventional inclusion of suburbs with urban areas in health research may obfuscate important trends for public health policy and programmes.

  • Seasonal variation in Geographical Access to maternal health services in regions of southern Mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura Magee, Peter Dadelszen, Esperança Sevene, Khátia Munguambe
    Abstract:

    Background Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. Methods A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Results Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Conclusions Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

  • seasonal variation in Geographical Access to maternal health services in regions of southern mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura A Magee, Peter Von Dadelszen, Esperança Sevene
    Abstract:

    Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

  • measuring potential spatial Access to primary health care physicians using a modified gravity model
    Canadian Geographer, 2010
    Co-Authors: Nadine Schuurman, Myriam Berube, Valorie A Crooks
    Abstract:

    Ensuring equity of Access to primary health care (PHC) across Canada is a continuing challenge, especially in rural and remote regions. Despite considerable attention recently by the World Health Organization, Health Canada and other health policy bodies, there has been no nation-wide study of potential (versus realized) spatial Access to PHC. This knowledge gap is partly attributable to the difficulty of conducting the analysis required to accurately measure and represent spatial Access to PHC. The traditional epidemiological method uses a simple ratio of PHC physicians to the denominator population to measure Geographical Access. We argue, however, that this measure fails to capture relative Access. For instance, a person who lives 90 minutes from the nearest PHC physician is unlikely to be as well cared for as the individual who lives more proximate and potentially has a range of choice with respect to PHC providers. In this article, we discuss spatial analytical techniques to measure potential spatial Access. We consider the relative merits of kernel density estimation and a gravity model. Ultimately, a modified version of the gravity model is developed for this article and used to calculate potential spatial Access to PHC physicians in the Canadian province of Nova Scotia. This model incorporates a distance decay function that better represents relative spatial Access to PHC. The results of the modified gravity model demonstrate greater nuance with respect to potential Access scores. While variability in Access to PHC physicians across the test province of Nova Scotia is evident, the gravity model better accounts for real Access by assuming that people can travel across artificial census boundaries. We argue that this is an important innovation in measuring potential spatial Access to PHC physicians in Canada. It contributes more broadly to assessing the success of policy mandates to enhance the equitability of PHC provisioning in Canadian provinces.

Khátia Munguambe - One of the best experts on this subject based on the ideXlab platform.

  • is the closest health facility the one used in pregnancy care seeking a cross sectional comparative analysis of self reported and modelled Geographical Access to maternal care in mozambique india and pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H0: Mean difference = 0)] < .001, limits of agreement: [− 273.81; 56.40] and [− 264.10; 94.25] respectively. In Mozambique, mean differences between the two measures of Access were significantly different from 0 [P (H0: Mean difference = 0) = 0.31, limits of agreement: [− 187.26; 199.96]]. Modelling Access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling Access should not be viewed through a Geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of Access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494

  • Is the closest health facility the one used in pregnancy care-seeking? A cross-sectional comparative analysis of self-reported and modelled Geographical Access to maternal care in Mozambique, India and Pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Background Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. Objectives This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Methods Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Results Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H_0: Mean difference = 0)] 

  • Seasonal variation in Geographical Access to maternal health services in regions of southern Mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura Magee, Peter Dadelszen, Esperança Sevene, Khátia Munguambe
    Abstract:

    Background Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. Methods A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Results Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Conclusions Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

Marianne Vidler - One of the best experts on this subject based on the ideXlab platform.

  • Is the closest health facility the one used in pregnancy care-seeking? A cross-sectional comparative analysis of self-reported and modelled Geographical Access to maternal care in Mozambique, India and Pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Background Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. Objectives This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Methods Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Results Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H_0: Mean difference = 0)] 

  • is the closest health facility the one used in pregnancy care seeking a cross sectional comparative analysis of self reported and modelled Geographical Access to maternal care in mozambique india and pakistan
    International Journal of Health Geographics, 2020
    Co-Authors: Liberty Makacha, Prestige Tatenda Makanga, Marianne Vidler, Esperança Sevene, Khátia Munguambe, Yolisa Prudence Dube, Jeffrey Bone, Geetanjali Katageri, Sumedha Sharma, Umesh Ramadurg
    Abstract:

    Travel time to care is known to influence uptake of health services. Generally, pregnant women who take longer to transit to health facilities are the least likely to deliver in facilities. It is not clear if modelled Access predicts fairly the vulnerability in women seeking maternal care across different spatial settings. This cross-sectional analysis aimed to (i) compare travel times to care as modelled in a GIS environment with self-reported travel times by women seeking maternal care in Community Level Interventions for Pre-eclampsia: Mozambique, India and Pakistan; and (ii) investigate the assumption that women would seek care at the closest health facility. Women were interviewed to obtain estimated travel times to health facilities (R). Travel time to the closest facility was also modelled (P) (closest facility tool (ArcGIS)) and time to facility where care was sought estimated (A) (route network layer finder (ArcGIS)). Bland–Altman analysis compared spatial variation in differences between modelled and self-reported travel times. Variations between travel times to the nearest facility (P) with modelled travel times to the actual facilities Accessed (A) were analysed. Log-transformed data comparison graphs for medians, with box plots superimposed distributions were used. Modelled Geographical Access (P) is generally lower than self-reported Access (R), but there is a geography to this relationship. In India and Pakistan, potential Access (P) compared fairly with self-reported travel times (R) [P (H0: Mean difference = 0)] < .001, limits of agreement: [− 273.81; 56.40] and [− 264.10; 94.25] respectively. In Mozambique, mean differences between the two measures of Access were significantly different from 0 [P (H0: Mean difference = 0) = 0.31, limits of agreement: [− 187.26; 199.96]]. Modelling Access successfully predict potential vulnerability in populations. Differences between modelled (P) and self-reported travel times (R) are partially a result of women not seeking care at their closest facilities. Modelling Access should not be viewed through a Geographically static lens. Modelling assumptions are likely modified by spatio-temporal and/or socio-cultural settings. Geographical stratification of Access reveals disproportionate variations in differences emphasizing the varied nature of assumptions across spatial settings. Trial registration ClinicalTrials.gov, NCT01911494. Registered 30 July 2013, https://clinicaltrials.gov/ct2/show/NCT01911494

  • Seasonal variation in Geographical Access to maternal health services in regions of southern Mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura Magee, Peter Dadelszen, Esperança Sevene, Khátia Munguambe
    Abstract:

    Background Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. Methods A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Results Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Conclusions Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.

  • seasonal variation in Geographical Access to maternal health services in regions of southern mozambique
    International Journal of Health Geographics, 2017
    Co-Authors: Prestige Tatenda Makanga, Nadine Schuurman, Charfudin Sacoor, Helena Edith Boene, Faustino Vilanculo, Marianne Vidler, Laura A Magee, Peter Von Dadelszen, Esperança Sevene
    Abstract:

    Geographic proximity to health facilities is a known determinant of Access to maternal care. Methods of quantifying Geographical Access to care have largely ignored the impact of precipitation and flooding. Further, travel has largely been imagined as unimodal where one transport mode is used for entire journeys to seek care. This study proposes a new approach for modeling potential spatio-temporal Access by evaluating the impact of precipitation and floods on Access to maternal health services using multiple transport modes, in southern Mozambique. A facility assessment was used to classify 56 health centres. GPS coordinates of the health facilities were acquired from the Ministry of Health while roads were digitized and classified from high-resolution satellite images. Data on the geographic distribution of populations of women of reproductive age, pregnancies and births within the preceding 12 months, and transport options available to pregnant women were collected from a household census. Daily precipitation and flood data were used to model the impact of severe weather on Access for a 17-month timeline. Travel times to the nearest health facilities were calculated using the closest facility tool in ArcGIS software. Forty-six and 87 percent of pregnant women lived within a 1-h of the nearest primary care centre using walking or public transport modes respectively. The populations within these catchments dropped by 9 and 5% respectively at the peak of the wet season. For journeys that would have commenced with walking to primary facilities, 64% of women lived within 2 h of life-saving care, while for those that began journeys with public transport, the same 2-hour catchment would have contained 95% of the women population. The population of women within two hours of life-saving care dropped by 9% for secondary facilities and 18% for tertiary facilities during the wet season. Seasonal variation in Access to maternal care should not be imagined through a dichotomous and static lens of wet and dry seasons, as Access continually fluctuates in both. This new approach for modelling spatio-temporal Access allows for the GIS output to be utilized not only for health services planning, but also to aid near real time community-level delivery of maternal health services.