Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study
Introduction Many low-income and middle-income countries lack an organised emergency transportation system, leaving people to arrange informal transport to hospital in the case of a medical emergency. Estimating the effect of implementing an emergency transport system is impractical and expensive, s...
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BMJ Publishing Group
2024-04-01
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| Series: | BMJ Public Health |
| Online Access: | https://bmjpublichealth.bmj.com/content/2/1/e000321.full |
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| author | Justine Davies Dmitri Nepogodiev Stephen Tabiri Richard Lilford Srinivasa Vittal Katikireddi Samuel I Watson Katie Scandrett |
| author_facet | Justine Davies Dmitri Nepogodiev Stephen Tabiri Richard Lilford Srinivasa Vittal Katikireddi Samuel I Watson Katie Scandrett |
| author_sort | Justine Davies |
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| description | Introduction Many low-income and middle-income countries lack an organised emergency transportation system, leaving people to arrange informal transport to hospital in the case of a medical emergency. Estimating the effect of implementing an emergency transport system is impractical and expensive, so there is a lack of evidence to support policy and investment decisions. Alternative modelling strategies may be able to fill this gap.Methods We have developed a spatial-epidemiological model of emergency transport for life-threatening conditions. The model incorporates components to both predict travel times across an area of interest under different scenarios and predict survival for emergency conditions as a function of time to receive care. We review potentially relevant data sources for different model parameters. We apply the model to the illustrative case study of providing emergency transport for postpartum haemorrhage in Northern Ghana.Results The model predicts that the effects of an ambulance service are likely to be ephemeral, varying according to local circumstances such as population density and road networks. In our applied example, the introduction of the ambulance service may save 40 lives (95% credible interval 5 to 111), or up to 107 lives (95% credible interval −293 to –13) may be lost across the region in a year, dependent on various model assumptions and parameter specifications. Maps showing the probability of reduced transfer time with the ambulance service may be particularly useful and allow for resource allocation planning.Conclusions Although there is scope for improvement in our model and in the data available to populate the model and inform parameter choices, we believe this work provides a foundation for pioneering methodology to predict the effect of introducing an ambulance system. Our spatial-epidemiological model includes much oppurtunity for flexibility and can be updated as required to best represent a chosen case study. |
| format | Article |
| id | doaj-art-76d8542497e544bd9bc6b15ebeabacae |
| institution | Kabale University |
| issn | 2753-4294 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Public Health |
| spelling | doaj-art-76d8542497e544bd9bc6b15ebeabacae2025-01-29T02:50:08ZengBMJ Publishing GroupBMJ Public Health2753-42942024-04-012110.1136/bmjph-2023-000321Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling studyJustine Davies0Dmitri Nepogodiev1Stephen Tabiri2Richard Lilford3Srinivasa Vittal Katikireddi4Samuel I Watson5Katie Scandrett610 Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit, Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South AfricaNIHR Global Health Research Unit on Global Surgery, Institute of Applied Health Research, University of Birmingham, Birmingham, UKSchool of Medicine, University for Development Studies, Tamale, GhanaInstitute of Applied Health Research, University of Birmingham, Birmingham, UKMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UKInstitute of Applied Health Research, University of Birmingham, Birmingham, UK1 Department of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UKIntroduction Many low-income and middle-income countries lack an organised emergency transportation system, leaving people to arrange informal transport to hospital in the case of a medical emergency. Estimating the effect of implementing an emergency transport system is impractical and expensive, so there is a lack of evidence to support policy and investment decisions. Alternative modelling strategies may be able to fill this gap.Methods We have developed a spatial-epidemiological model of emergency transport for life-threatening conditions. The model incorporates components to both predict travel times across an area of interest under different scenarios and predict survival for emergency conditions as a function of time to receive care. We review potentially relevant data sources for different model parameters. We apply the model to the illustrative case study of providing emergency transport for postpartum haemorrhage in Northern Ghana.Results The model predicts that the effects of an ambulance service are likely to be ephemeral, varying according to local circumstances such as population density and road networks. In our applied example, the introduction of the ambulance service may save 40 lives (95% credible interval 5 to 111), or up to 107 lives (95% credible interval −293 to –13) may be lost across the region in a year, dependent on various model assumptions and parameter specifications. Maps showing the probability of reduced transfer time with the ambulance service may be particularly useful and allow for resource allocation planning.Conclusions Although there is scope for improvement in our model and in the data available to populate the model and inform parameter choices, we believe this work provides a foundation for pioneering methodology to predict the effect of introducing an ambulance system. Our spatial-epidemiological model includes much oppurtunity for flexibility and can be updated as required to best represent a chosen case study.https://bmjpublichealth.bmj.com/content/2/1/e000321.full |
| spellingShingle | Justine Davies Dmitri Nepogodiev Stephen Tabiri Richard Lilford Srinivasa Vittal Katikireddi Samuel I Watson Katie Scandrett Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study BMJ Public Health |
| title | Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study |
| title_full | Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study |
| title_fullStr | Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study |
| title_full_unstemmed | Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study |
| title_short | Predicting the effects of introducing an emergency transport system in low-income and middle-income countries: a spatial-epidemiological modelling study |
| title_sort | predicting the effects of introducing an emergency transport system in low income and middle income countries a spatial epidemiological modelling study |
| url | https://bmjpublichealth.bmj.com/content/2/1/e000321.full |
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