ArticleEcoHealth2014
Merging economics and epidemiology to improve the prediction and management of infectious disease.
Article in EcoHealth, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 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
45 citing papers in PubMed.
- Social, mobility and contact networks in shaping health behaviours and infectious disease dynamics: a scoping review.Infectious diseases of poverty · 2025Article
- Improving policy design and epidemic response using integrated models of economic choice and disease dynamics with behavioral feedback.PLoS computational biology · 2025Article
- Adaptive human behavior and delays in information availability autonomously modulate epidemic waves.PNAS nexus · 2025Article
- Physical distancing versus testing with self-isolation for controlling an emerging epidemic.Scientific reports · 2023Article
- Dengue as a Disease Threatening Global Health: A Narrative Review Focusing on Latin America and Brazil.Tropical medicine and infectious disease · 2023Review
- A missing behavioural feedback in COVID-19 models is the key to several puzzles.BMJ global health · 2022Article
- Heterogeneous adaptive behavioral responses may increase epidemic burden.Scientific reports · 2022Article
- Disease-economy trade-offs under alternative epidemic control strategies.Nature communications · 2022Article
- Analytical estimation of maximum fraction of infected individuals with one-shot non-pharmaceutical intervention in a hybrid epidemic model.BMC infectious diseases · 2022Article
- Challenges of integrating economics into epidemiological analysis of and policy responses to emerging infectious diseases.Epidemics · 2022Article
- Enhancing long-term forecasting: Learning from COVID-19 models.PLoS computational biology · 2022Article
- COVID-19 pandemic and economic scenarios for Ontario.The Canadian journal of economics. Revue canadienne d'economique · 2022Article
- Asymptomatic individuals can increase the final epidemic size under adaptive human behavior.Scientific reports · 2021Article
- Modeling and controlling the spread of epidemic with various social and economic scenarios.Chaos, solitons, and fractals · 2021Article
- A review and agenda for integrated disease models including social and behavioural factors.Nature human behaviour · 2021Review
- Is the 2003 SARS epidemic over? Long-term effects of epidemic exposure on mortality among older adults.China economic review · 2021Article
- Accounting for farmers' control decisions in a model of pathogen spread through animal trade.Scientific reports · 2021Article
- Adaptive Human Behavior in Epidemics: the Impact of Risk Misperception on the Spread of Epidemics.Research square · 2021Article
- Adaptive social contact rates induce complex dynamics during epidemics.PLoS computational biology · 2021Article
- The impact of social distancing on box-office revenue: Evidence from the COVID-19 pandemic.Quantitative marketing and economics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as "economic epidemiology" or "epidemiological economics," the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
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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.