ArticlePLoS computational biology2020
Immunization strategies in networks with missing data.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 26 citations in OpenAlex.
- Sensitivity analysis of epidemic forecasting and spreading on networks with probability generating functions.Journal of the Royal Society, Interface · 2026Article
- Quantifying edge relevance for epidemic spreading via the semi-metric topology of complex networks.Journal of physics. Complexity · 2025Article
- Current trends and challenges in the management of foot and mouth disease in Saudi Arabia: A review.Open veterinary journal · 2025Review
- Temporal and Probabilistic Comparisons of Epidemic Interventions.Bulletin of mathematical biology · 2023Article
- TRACE-Omicron: Policy Counterfactuals to Inform Mitigation of COVID-19 Spread in the United States.Advanced theory and simulations · 2023Article
- Modeling the effectiveness of targeting Rift Valley fever virus vaccination using imperfect network information.Frontiers in veterinary science · 2023Article
- Non-selective distribution of infectious disease prevention may outperform risk-based targeting.Nature communications · 2022Article
- A sampling-guided unsupervised learning method to capture percolation in complex networks.Scientific reports · 2022Article
- Network sampling coverage III: Imputation of missing network data under different network and missing data conditions.Social networks · 2022Article
- A review and agenda for integrated disease models including social and behavioural factors.Nature human behaviour · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Network-based intervention strategies can be effective and cost-efficient approaches to curtailing harmful contagions in myriad settings. As studied, these strategies are often impractical to implement, as they typically assume complete knowledge of the network structure, which is unusual in practice. In this paper, we investigate how different immunization strategies perform under realistic conditions-where the strategies are informed by partially-observed network data. Our results suggest that global immunization strategies, like degree immunization, are optimal in most cases; the exception is at very high levels of missing data, where stochastic strategies, like acquaintance immunization, begin to outstrip them in minimizing outbreaks. Stochastic strategies are more robust in some cases due to the different ways in which they can be affected by missing data. In fact, one of our proposed variants of acquaintance immunization leverages a logistically-realistic ongoing survey-intervention process as a form of targeted data-recovery to improve with increasing levels of missing data. These results support the effectiveness of targeted immunization as a general practice. They also highlight the risks of considering networks as idealized mathematical objects: overestimating the accuracy of network data and foregoing the rewards of additional inquiry.
Indexed as
Identifiers
What OpenQuestion holds
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.