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- biological and social lie of being born
- difference in where you are born
- improper ANC (neonatal care) of mother compromises
- maternal education contributes to knowledge to seek care (women have less education as
the goal of women is to find a good husband/family)
- habits of mother to child
- genetics is important contributor but difficult to modify/change survival
- maternal nutrition
- we are never at the same odds of surviving (programmed in our genes but also influenced
by the behaviour our families have, education, nutritional characteristics, and any
modifications)
- every baby born has a heavy burden of risks that they do not have the choice of
- 41% of child births = neonatal
Æ will change depending on how developed regions are
- the more developed the area, the higher the share of neonatal deaths BECAUSE less deaths
in older ages than younger ages [boys are more fragile than girls - but also depending on
where you are born]
- families usually do not prefer girls - health affected
- of the world, only 40% of deaths are recorded [births were probably unregistered as well]
- uncertainty of the effects/patterns of death
- statistical arthritis -- do not have data, and the accessible data are too old
Challenges
- measure real-time mortality trends
- improve coverage indicators
- mainstream equity in epidemiological research [where the action is happening]
- delivery channel research [only 10% of the global investment in health research is directed
at 90% of the global burden of the disease]
- how to make technology to evidence
- improve large-scale evaluation designs
- balance advocacy with evidence [to prove]
- inaccurate/outdated data -- overestimates and underestimates
- 2.3 million out of 9 million of child mortality in India
- WHO/UNICEF estimated 7000 of malarial deaths >5yo, but 50 000 in India
* if you have endless resources, it would be better to overestimate, but limited
resources and redirecting expenditures to tackle disease is harmful to the society
Æ challenges of large-scale evaluations
- vaccine trials may be unethical -- test medications that already work, only treat half of the
population but not the other
- efficacy-effectiveness gap
- in large countries, an average does not represent the country as vast range/spectrum of
rich/poor
Imbalances in health research
- problems and researchers are in different places
- 1090 gap, do not have enough people working in the public health sector
- DALY - # of years of life you lose due to a health condition
- global R&D investments per DALY
global average of all diseases = US$72 - funds in WRONG areas that do not
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