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Table 3 Details of scenarios considered for LiST modelling

From: LiST modelling with monitoring data to estimate impact on child mortality of an ORS and zinc programme with public sector providers in Bihar, India

Models Descriptions
Scenario 1
ORS and zinc (A intersection with C, i.e., B))
i. ORS coverage rate = Numerator is (Numbers treated with ORS only + Numbers treated with ORS and zinc) and
ii. Zinc coverage rate = Numerator is (Numbers treated with ORS and zinc)
Scenario 2
ORS and zinc; ORS alone; zinc alone (A + C; A union with C, which includes B)
i. ORS coverage rate = Numerator is (Numbers treated with ORS only + Numbers treated with ORS and zinc) and
ii. Zinc coverage rate = Numerator is (Numbers treated with ORS and zinc + those who received zinc alone)
Scenario 3
To achieve the 2010 CIFF estimate of 4200 additional number of deaths averted (cumulatively)
(B set to 4200)
By working backwards, to achieve the 2010 CIFF estimate of 4200 additional cumulative number of deaths averted, what coverage rates for ORS and zinc would have been necessary after five years of programme intervention?
Scenario 4a
(Scenario 1 with 40% and 60% higher coverage rates)
This model will estimate the effect of larger coverage rates calculated from MIS data (greatly improved coverage) for ORS and zinc, with a “worst case” diarrhoea incidence scenario of 2.20 episodes/child/year.
Note All scenarios have a denominator of total number of diarrhoea incidences/episodes in the population (among 2–59 month old children)
  1. aThis model doesn’t use JHSPH & SAS’s 2013 measured coverage rates but purely depends on MIS data, whereas, all other models inherently used JHSPH & SAS’s coverage rates