Evidence map›Paper›PMID 21504239›Full record

ReviewPharmacoEconomics2011

Modelling the epidemiology of infectious diseases for decision analysis: a primer.

Mark Jit, Marc Brisson

Open access · bronzeAbstract readReview
In one paragraph

Review in PharmacoEconomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 13 pooled it
7.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

53 citing papers in PubMed, 13 syntheses or guidelines pooled it, 123 citations in OpenAlex.

  1. Incorporating Social Determinants of Health in Infectious Disease Models: A Systematic Review of Guidelines.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
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  17. Cost-Effectiveness of the Second COVID-19 Booster Vaccination in the USA.Applied health economics and health policy · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 3 countries.

Mark JitModelling and Economics Unit, Centre for Infections, Health Protection Agency, London, UK. mark.jit@hpa.org.uk
Marc Brisson
Centre hospitalier universitaire de Québec · CAHealth Protection Agency · MV

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number of economic evaluations related to infectious disease topics has increased over the last 2 decades. However, many such evaluations rely on models that do not take into account unique features of infectious diseases that can affect the estimated value of interventions against them. These include their transmissibility from infected to susceptible individuals, the possibility of acquiring natural immunity following recovery from infection and the uncertainties that arise as a result of their complex natural history and epidemiology. Modellers conducting economic evaluations of infectious disease interventions need to know the main features of different types of infectious disease models, the situations in which they should be applied and the effects of model choices on the cost effectiveness of interventions.

Indexed as

Decision Support TechniquesModels, EconometricCommunicable Disease ControlCommunicable DiseasesEconomics, PharmaceuticalHumansMarkov Chains

Identifiers

PMID21504239
PMCPMC7100690
OpenAlexW2011259658

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.