[Stoves] How are DALYs and GBD numbers created?

Crispin Pemberton-Pigott crispinpigott at outlook.com
Fri May 19 15:24:11 CDT 2017


Dear Nikhil

I felt that with that advice in hand (yours) people reading this list should familiarize themselves with the root documents to understand how model-based this is, and where the limitations lie.

One limitation is trying to take a population statistic and project onto an individual a specific ‘countable’ better outcome. If such a projection is not true for one person, it is also not true for a thousand people counted individually.  If we can understand that, we have a chance of seeing between other lines.

Independent investigation of truth. It is a founding principle.

Regards
Crispin



Crispin:

I repeat - DALYs and risk factors for household fuel use in developing countries are cooked.

Do not bother looking for emissions, concentrations, exposures, or for that matter even deaths and disability statistics with any physical counterparts -- THESE people, THIS area, THESE fuels and stoves, THIS moment.

Let me spell out simply - they are all lies.

Official lies. In officious publications.

Nikhil

------------------------------------------------------------------------
Nikhil Desai
(India +91) 909 995 2080
Skype: nikhildesai888

On Sat, May 20, 2017 at 12:29 AM, Crispin Pemberton-Pigott <crispinpigott at outlook.com<mailto:crispinpigott at outlook.com>> wrote:
Dear Friends

If you have wondered how the GBD and DALY numbers are generated, have a look at these two documents linked below.

Note the clear distinction maintained between exposure and emissions. When it comes to cooking stoves there is a big difference. If the emissions go outside and do not result in exposure, the indoor exposure problem is solved. If emissions go outside and elevate an ambient level to a higher one, exposures increase a bit for everyone.

We have the interesting case of upland Kyrgyzstan where dung and wood are primarily burned for cooking and heating. If the current situation is heavily polluted indoor air (leaky stoves etc) and pristine outdoor air, is it enough to put 100% of the emissions outside (seal the stoves)? Is it enough to reduce emissions by ½ and put all the it outside where it is diluted into insignificance? When is ‘enough’ an adequate response?

How about in a crowded valley where it is 500 µg/m3 indoors and 100 µg/m3 outside? The indoor pollution goes outside anyway, sooner or later, so putting it up a chimney would make nearly no difference to anything. Not even 100.01.

My point is that reducing emissions is great, but that putting it in the right place is a Good Start, while working on absolute reductions. Thoughts, anyone?

Regards
Crispin

Models of death and disability:

http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)30505-6/fulltext

Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000–422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015.

And

http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(16)31012-1/fulltext

We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes…



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