Evidence map›Paper›PMID 18331978›Full record

ArticleJournal of the Royal Society, Interface2008

Modelling heterogeneity and the impact of chemotherapy and vaccination against human hookworm.

L Sabatelli, A C Ghani, L C Rodrigues, P J Hotez, S Brooker

Open access · greenAbstract readComparative Study
In one paragraph

Article in Journal of the Royal Society, Interface, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

10 citing papers in PubMed, 15 citations in OpenAlex.

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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

5 authors at 4 institutions in 2 countries.

L SabatelliLondon School of Hygiene and Tropical Medicine, Keppel Street, London, UK. simon.brooker@lshtm.ac.uk
A C Ghani
L C Rodrigues
P J Hotez
S Brooker
London School of Hygiene & Tropical Medicine · GBGeorge Washington University · USImperial College London · GBUniversity of London · GB

Funding

Wellcome Trust 081673
6 · The paper itself

Abstract

There is a growing emphasis on the development of vaccines against helminths (worms), and mathematical models provide a useful tool to assess the impact of new vaccines under a range of scenarios. The present study describes a stochastic individual-based model to assess the relative impact of chemotherapy and vaccination against human hookworm infection and investigates the implications of potential correlations between risk of infection and vaccine efficacy. Vaccination is simulated as a reduction in susceptibility to infection and the model includes population heterogeneities and dynamical waning of protection. To help identify appropriate measures of vaccine impact, we present a novel framework to quantify the vaccine impact on the infection-associated morbidity and introduce a measure of symmetry to study the correspondence between reduction in intensity and reduction in morbidity. Our modelling shows that, in high-transmission settings, the greatest impact of vaccination will be attained when vaccine efficacy is the greatest among individuals harbouring the heaviest worm burdens, and that the decline of morbidity primarily depends on the level of protection attained in the most at risk 8-12% of the population. We also demonstrate that if risk of infection and vaccine protection are correlated, there is not always a direct correspondence between the reduction in worm burden and in morbidity, with the precise relationship varying according to transmission setting.

Indexed as

Models, TheoreticalAnimalsComputer SimulationHookworm InfectionsHumansVaccinesVaccines

Identifiers

PMID18331978
PMCPMC2607437
OpenAlexW2096796853

What OpenQuestion holds

Textmetadata
LicenceTDM
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.