Modelling stillbirth mortality reduction with the Lives Saved Tool
Abstract Background The worldwide burden of stillbirths is large, with an estimated 2.6 million babies stillborn in 2015 including 1.3 million dying during labour. The Every Newborn Action Plan set a stillbirth target of ≤12 per 1000 in all countries by 2030. Planning tools will be essential as coun...
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| Format: | Article |
| Language: | English |
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BMC
2017-11-01
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| Series: | BMC Public Health |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12889-017-4742-5 |
| _version_ | 1811231912991129600 |
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| author | Hannah Blencowe Victoria B. Chou Joy E. Lawn Zulfiqar A. Bhutta |
| author_facet | Hannah Blencowe Victoria B. Chou Joy E. Lawn Zulfiqar A. Bhutta |
| author_sort | Hannah Blencowe |
| collection | DOAJ |
| description | Abstract Background The worldwide burden of stillbirths is large, with an estimated 2.6 million babies stillborn in 2015 including 1.3 million dying during labour. The Every Newborn Action Plan set a stillbirth target of ≤12 per 1000 in all countries by 2030. Planning tools will be essential as countries set policy and plan investment to scale up interventions to meet this target. This paper summarises the approach taken for modelling the impact of scaling-up health interventions on stillbirths in the Lives Saved tool (LiST), and potential future refinements. Methods The specific application to stillbirths of the general method for modelling the impact of interventions in LiST is described. The evidence for the effectiveness of potential interventions to reduce stillbirths are reviewed and the assumptions of the affected fraction of stillbirths who could potentially benefit from these interventions are presented. The current assumptions and their effects on stillbirth reduction are described and potential future improvements discussed. Results High quality evidence are not available for all parameters in the LiST stillbirth model. Cause-specific mortality data is not available for stillbirths, therefore stillbirths are modelled in LiST using an attributable fraction approach by timing of stillbirths (antepartum/ intrapartum). Of 35 potential interventions to reduce stillbirths identified, eight interventions are currently modelled in LiST. These include childbirth care, induction for prolonged pregnancy, multiple micronutrient and balanced energy supplementation, malaria prevention and detection and management of hypertensive disorders of pregnancy, diabetes and syphilis. For three of the interventions, childbirth care, detection and management of hypertensive disorders of pregnancy, and diabetes the estimate of effectiveness is based on expert opinion through a Delphi process. Only for malaria is coverage information available, with coverage estimated using expert opinion for all other interventions. Going forward, potential improvements identified include improving of effectiveness and coverage estimates for included interventions and addition of further interventions. Conclusions Known effective interventions have the potential to reduce stillbirths and can be modelled using the LiST tool. Data for stillbirths are improving. Going forward the LiST tool should seek, where possible, to incorporate these improving data, and to continually be refined to provide an increasingly reliable tool for policy and programming purposes. |
| first_indexed | 2024-04-12T10:54:00Z |
| format | Article |
| id | doaj.art-28a977af3dd942e19b3c0ab1c25a5333 |
| institution | Directory Open Access Journal |
| issn | 1471-2458 |
| language | English |
| last_indexed | 2024-04-12T10:54:00Z |
| publishDate | 2017-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj.art-28a977af3dd942e19b3c0ab1c25a53332022-12-22T03:36:08ZengBMCBMC Public Health1471-24582017-11-0117S4597410.1186/s12889-017-4742-5Modelling stillbirth mortality reduction with the Lives Saved ToolHannah Blencowe0Victoria B. Chou1Joy E. Lawn2Zulfiqar A. Bhutta3Maternal Adolescent Reproductive and Child Health (MARCH) Centre, London School of Hygiene & Tropical MedicineDepartment of International Health, Johns Hopkins Bloomberg School of Public HealthMaternal Adolescent Reproductive and Child Health (MARCH) Centre, London School of Hygiene & Tropical MedicineCentre for Global Child Health, Hospital for Sick ChildrenAbstract Background The worldwide burden of stillbirths is large, with an estimated 2.6 million babies stillborn in 2015 including 1.3 million dying during labour. The Every Newborn Action Plan set a stillbirth target of ≤12 per 1000 in all countries by 2030. Planning tools will be essential as countries set policy and plan investment to scale up interventions to meet this target. This paper summarises the approach taken for modelling the impact of scaling-up health interventions on stillbirths in the Lives Saved tool (LiST), and potential future refinements. Methods The specific application to stillbirths of the general method for modelling the impact of interventions in LiST is described. The evidence for the effectiveness of potential interventions to reduce stillbirths are reviewed and the assumptions of the affected fraction of stillbirths who could potentially benefit from these interventions are presented. The current assumptions and their effects on stillbirth reduction are described and potential future improvements discussed. Results High quality evidence are not available for all parameters in the LiST stillbirth model. Cause-specific mortality data is not available for stillbirths, therefore stillbirths are modelled in LiST using an attributable fraction approach by timing of stillbirths (antepartum/ intrapartum). Of 35 potential interventions to reduce stillbirths identified, eight interventions are currently modelled in LiST. These include childbirth care, induction for prolonged pregnancy, multiple micronutrient and balanced energy supplementation, malaria prevention and detection and management of hypertensive disorders of pregnancy, diabetes and syphilis. For three of the interventions, childbirth care, detection and management of hypertensive disorders of pregnancy, and diabetes the estimate of effectiveness is based on expert opinion through a Delphi process. Only for malaria is coverage information available, with coverage estimated using expert opinion for all other interventions. Going forward, potential improvements identified include improving of effectiveness and coverage estimates for included interventions and addition of further interventions. Conclusions Known effective interventions have the potential to reduce stillbirths and can be modelled using the LiST tool. Data for stillbirths are improving. Going forward the LiST tool should seek, where possible, to incorporate these improving data, and to continually be refined to provide an increasingly reliable tool for policy and programming purposes.http://link.springer.com/article/10.1186/s12889-017-4742-5StillbirthsLives saved toolMortality modelling |
| spellingShingle | Hannah Blencowe Victoria B. Chou Joy E. Lawn Zulfiqar A. Bhutta Modelling stillbirth mortality reduction with the Lives Saved Tool BMC Public Health Stillbirths Lives saved tool Mortality modelling |
| title | Modelling stillbirth mortality reduction with the Lives Saved Tool |
| title_full | Modelling stillbirth mortality reduction with the Lives Saved Tool |
| title_fullStr | Modelling stillbirth mortality reduction with the Lives Saved Tool |
| title_full_unstemmed | Modelling stillbirth mortality reduction with the Lives Saved Tool |
| title_short | Modelling stillbirth mortality reduction with the Lives Saved Tool |
| title_sort | modelling stillbirth mortality reduction with the lives saved tool |
| topic | Stillbirths Lives saved tool Mortality modelling |
| url | http://link.springer.com/article/10.1186/s12889-017-4742-5 |
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