@article{f935afa1200a44859c54a81a110ec092,
title = "Comparing modelled predictions of neonatal mortality impacts using list with observed results of community-based intervention trials in South Asia",
abstract = "Background: There is an increasing body of evidence from trials suggesting that major reductions in neonatal mortality are possible through community-based interventions. Since these trials involve packages of varying content, determining how much of the observed mortality reduction is due to specific interventions is problematic. The Lives Saved Tool (LiST) is designed to facilitate programmatic prioritization by modelling mortality reductions related to increasing coverage of specific interventions which may be combined into packages. Methods: To assess the validity of LiST outputs, we compared predictions generated by LiST with observed neonatal mortality reductions in trials of packages which met inclusion criteria but were not used as evidence inputs for LiST. Results: Four trials, all from South Asia, met the inclusion criteria. The neonatal mortality rate (NMR) predicted by LiST matched the observed rate very closely in two effectiveness-type trials. LiST predicted NMR reduction was close (absolute difference <5/1000 live births) in a third study. The NMR at the end of the fourth study (Shivgarh, India) was overestimated by 39% or 16/1000 live births. Conclusions: These results suggest that LiST is a reasonably reliable tool for use by policymakers to prioritize interventions to reduce neonatal deaths, at least in South Asia and where empirical data are unavailable. Reasons for the underestimated reduction in one trial likely include the inability of LiST to model all effective interventions.",
keywords = "Bangladesh, Child survival, India, Lives saved tool, Modelling, Neonatal mortality, Pakistan",
author = "Friberg, {Ingrid K.} and Bhutta, {Zulfiqar A.} and Darmstadt, {Gary L.} and Abhay Bang and Simon Cousens and Baqui, {Abdullah H.} and Vishwajeet Kumar and Neff Walker and Lawn, {Joy E.}",
note = "Funding Information: This analysis was funded by the US Fund for UNICEF through a grant from the Bill & Melinda Gates Foundation to {\textquoteleft}Promote evidence-based decision making in designing maternal, neonatal and child health interventions in low-and middle-income countries{\textquoteright} (No. 43386); and Save The Children-US through a grant from the Bill & Melinda Gates Foundation for {\textquoteleft}Saving Newborn Lives{\textquoteright} (No. 50124). Funding Information: The individual studies were supported by the United States Agency for International Development (USAID), through cooperative agreements with the Johns Hopkins Bloomberg School of Public Health and the International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B), and by the Saving Newborn Lives program of Save the Children-US through a grant from the Bill & Melinda Gates Foundation (Sylhet); The John D. and Catherine T. MacArthur Foundation, The Ford Foundation, Saving Newborn Lives, Save the Children-US, The Bill & Melinda Gates Foundation, the International Women{\textquoteright}s Health Coalition, Oxfam and the Indian Council of Medical Research (SEARCH); WHO and the Saving Newborn Lives program of Save the Children-US, funded by the Bill & Melinda Gates Foundation (Hala); and the USAID, Delhi Mission and the Saving Newborn Lives program of Save the Children-US through a grant from the Bill & Melinda Gates Foundation (Shivgarh).",
year = "2010",
month = apr,
day = "1",
doi = "10.1093/ije/dyq017",
language = "English (US)",
volume = "39",
pages = "i11--i20",
journal = "International journal of epidemiology",
issn = "0300-5771",
publisher = "Oxford University Press",
number = "SUPPL. 1",
}