Background: Scientists and development stakeholders argue that health interventions proven
e↵ective in randomized ecacy
trials should be translated into large-scale programs to benefit
public health. Substantive evidence supports the scale-up of numerous health interventions,
such as water, sanitation, and deworming interventions, and since the establishment
of the Millennium Development Goals (MDGs) the funding and motivation for such scale-up
has grown. In the field of water and sanitation, numerous interventions have been demonstrated
to be ecacious
in the reduction of diarrhea and soil-transmitted helminth infection.
However, scaling up these interventions to regional or national levels frequently presents
implementation challenges, and systematically studying the reasons for scale-up success or
failure is essential to refine and sustain public health programs. Another important feature
of scaling up interventions is determining how best to integrate interventions at scale and
whether intervention delivery should be focused at the individual, household, or community
level. Population attributable fraction (PAF) parameters and a new class of parameters
which build upon the PAF can be used to estimate the e↵ect of large-scale programs on
population health. Evaluation of interventions at scale poses unique questions, and epidemiologic
designs and analyses need to be tailored to answer these particular questions. Modern
approaches to PAF estimation allow for parameter definition to be tailored one’s particular
research question and are well suited to the evaluation of population-level e↵ects of largescale
health interventions.