ArticleCurrent epidemiology reports2016
Dependent Happenings: A Recent Methodological Review.
Article in Current epidemiology reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed.
- Disseminated Effects in Agent-Based Models: A Potential Outcomes Framework and Application to Inform Preexposure Prophylaxis Coverage Levels for HIV Prevention.American journal of epidemiology · 2021Trial
- Are arms-based methods required to test the stable unit treatment value assumption (SUTVA) among Cochrane reviews of contagious infection prevention interventions?Global epidemiology · 2026Article
- Proposed study design for estimating COVID-19 vaccine effectiveness in post-pandemic Taiwan.Journal of the Chinese Medical Association : JCMA · 2026Article
- Institutional spillover effects of antimicrobial use on antimicrobial resistance andAntimicrobial stewardship & healthcare epidemiology : ASHE · 2026Article
- HK-DeepIV: heat-kernel geometric diagnostics and early-warning signals for curvature-induced interference in financial correlation networks.Frontiers in big data · 2026Article
- Design of egocentric network-based studies to estimate causal effects under interference.Statistical methods in medical research · 2025Article
- Design of field trials for the evaluation of transmissible vaccines in animal populations.PLoS computational biology · 2025Article
- Unraveling the 'community effects' of interventions against malaria endemicity: a systematic scoping review.BMJ public health · 2024Article
- Article
- Identifying and estimating effects of sustained interventions under parallel trends assumptions.Biometrics · 2023Article
- Framework for converting mechanistic network models to probabilistic models.Journal of complex networks · 2023Article
- Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs.Pathogens (Basel, Switzerland) · 2023Article
- Randomization, design and analysis for interdependency in aging research: no person or mouse is an island.Nature aging · 2022Article
- Targeted maximum likelihood estimation of causal effects with interference: A simulation study.Statistics in medicine · 2022Article
- Estimating vaccine effectiveness against SARS-CoV-2 infection, hospitalization and death from ecologic data in Costa Rica.BMC infectious diseases · 2022Article
- Toward evaluation of disseminated effects of medications for opioid use disorder within provider-based clusters using routinely-collected health data.Statistics in medicine · 2022Article
- A compelling demonstration of why traditional statistical regression models cannot be used to identify risk factors from case data on infectious diseases: a simulation study.BMC medical research methodology · 2022Article
- Estimating sibling spillover effects with unobserved confounding using gain-scores.Annals of epidemiology · 2022Article
- Using social contact data to improve the overall effect estimate of a cluster-randomized influenza vaccination program in Senegal.Journal of the Royal Statistical Society. Series C, Applied statistics · 2022Article
- Dynamical Modeling as a Tool for Inferring Causation.American journal of epidemiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
One hundred years ago Sir Ronald Ross published his treatise on a general Theory of Happenings. Dependent happenings are those in which the frequency depends on the number already affected. When there is dependency of events, interventions can have different types of effects. Interventions such as vaccination can have direct protective effects for the person receiving the treatment, as well as indirect/spillover effects for others in the population. Causal inference is a framework for carefully defining the causal effect of a treatment, exposure, or policy, and then determining conditions under which such effects can be estimated from the observed data. We consider here scenarios in which the potential outcomes of an individual can depend on the treatment of other individuals in the population, known as causal inference with interference. Much of the research so far has assumed the population is divided into groups or clusters, and individuals can interfere with others within their clusters but not across clusters. Recent developments have assumed more general forms of interference. We review some of the different types of effects that have been defined for dependent happenings, particularly using the methods of causal inference with interference. Many of the methods are applicable across disciplines, such as infectious diseases, social sciences, and economics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.