Count Every Newborn: EN-INDEPTH study to improve pregnancy outcome measurement in population-based surveys
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Main Authors: | , , , , , |
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Format: | Book |
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BMC,
2021-02-01T00:00:00Z.
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001 | doaj_c9500fa9c8cb41a3a3150503c29f8a5a | ||
042 | |a dc | ||
100 | 1 | 0 | |a Stephen M. Tollman |e author |
700 | 1 | 0 | |a Peter Byass |e author |
700 | 1 | 0 | |a Peter Waiswa |e author |
700 | 1 | 0 | |a Hannah Blencowe |e author |
700 | 1 | 0 | |a Judith Yargawa |e author |
700 | 1 | 0 | |a Joy E. Lawn |e author |
245 | 0 | 0 | |a Count Every Newborn: EN-INDEPTH study to improve pregnancy outcome measurement in population-based surveys |
260 | |b BMC, |c 2021-02-01T00:00:00Z. | ||
500 | |a 10.1186/s12963-020-00243-y | ||
500 | |a 1478-7954 | ||
546 | |a EN | ||
690 | |a Computer applications to medicine. Medical informatics | ||
690 | |a R858-859.7 | ||
690 | |a Public aspects of medicine | ||
690 | |a RA1-1270 | ||
655 | 7 | |a article |2 local | |
786 | 0 | |n Population Health Metrics, Vol 19, Iss S1, Pp 1-7 (2021) | |
787 | 0 | |n https://doi.org/10.1186/s12963-020-00243-y | |
787 | 0 | |n https://doaj.org/toc/1478-7954 | |
856 | 4 | 1 | |u https://doaj.org/article/c9500fa9c8cb41a3a3150503c29f8a5a |z Connect to this object online. |