About this Research Topic
Evaluating and understanding the effectiveness of a policy or a program is imperative when implementing a population-level intervention, whether it be in the realm of public health, public policy, or economics.
Alongside the advancement of causal inference methods in the past few decades, we have also seen various developments in methods to quantify population-level intervention effects, including approaches such as difference-in-difference methods, comparative interrupted time series, and synthetic control methods. These natural experiment methods offer an important alternative to randomized controlled trials, which may not be feasible or ethical to conduct in the context of population-level intervention implementation.
As these modern methods are being applied to individual studies in different fields, cross-disciplinary exchanges of advantages as well as challenges with specific methodological aspects and required assumptions should be galvanized in order to facilitate further methodological advancements.
The aim of this Research Topic is to collect and highlight methods quantifying the impact of population-level interventions and their applications within and across a range of disciplines, in order to stimulate interdisciplinary discourse on emerging approaches and their transferability.
We welcome contributions to original and innovative methodological approaches, as well as applications of a method(s) with an interdisciplinary aspect. We also welcome contributions that review and synthesize the state of the art in quantifying population-level intervention effects.
Possible submission themes include but not limited to:
● Novel methodological approach in estimating effects of a policy or program
● Comparative study of current methods
● Data infrastructure and requirements
● Feasibility of required methodological assumptions
Alongside the advancement of causal inference methods in the past few decades, we have also seen various developments in methods to quantify population-level intervention effects, including approaches such as difference-in-difference methods, comparative interrupted time series, and synthetic control methods. These natural experiment methods offer an important alternative to randomized controlled trials, which may not be feasible or ethical to conduct in the context of population-level intervention implementation.
As these modern methods are being applied to individual studies in different fields, cross-disciplinary exchanges of advantages as well as challenges with specific methodological aspects and required assumptions should be galvanized in order to facilitate further methodological advancements.
The aim of this Research Topic is to collect and highlight methods quantifying the impact of population-level interventions and their applications within and across a range of disciplines, in order to stimulate interdisciplinary discourse on emerging approaches and their transferability.
We welcome contributions to original and innovative methodological approaches, as well as applications of a method(s) with an interdisciplinary aspect. We also welcome contributions that review and synthesize the state of the art in quantifying population-level intervention effects.
Possible submission themes include but not limited to:
● Novel methodological approach in estimating effects of a policy or program
● Comparative study of current methods
● Data infrastructure and requirements
● Feasibility of required methodological assumptions
Keywords: population-level intervention, methods, public health, public policy, economics
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
