Evidence map›Paper›PMID 23849433›Full record

ArticleInfectious diseases of poverty2013

Elimination of tropical disease through surveillance and response.

Xiao-Nong Zhou, Robert Bergquist, Marcel Tanner

Open access · goldAbstract read
In one paragraph

Article in Infectious diseases of poverty, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 1 pooled it
21.9field-weighted citation impact, top 1% 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

61 citing papers in PubMed, 1 synthesis or guideline pooled it, 168 citations in OpenAlex.

  1. Pooled it
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  13. NTD Diagnostics for Disease Elimination: A Review.Diagnostics (Basel, Switzerland) · 2020
    Review
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1 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 2 countries.

Xiao-Nong ZhouNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, 200025, People's Republic of China. zhouxn1@chinacdc.cn.
Robert Bergquist
Marcel Tanner
National Institute for Parasitic Diseases · CNSwiss Tropical and Public Health Institute · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surveillance and response represent the final crucial steps in achieving effective control and particularly elimination of communicable diseases as recognized in the area of neglected tropical diseases (NTDs), applied in increasing numbers in endemic countries with ongoing control and elimination programmers. More and more national NTD elimination initiatives are scheduled based on the innovative and effective One world-One health perspective to detect pockets of transmission and disease reintroduction. Resource-constrained countries, which carry the heaviest NTD burdens, face various challenges how to strengthen the health system as well as developing effective and novel tools for surveillance and response tailored to local settings. Surveillance-response approaches take place in two different stages corralling the basic components of the surveillance-response system for NTD elimination. Six different research priorities have been identified:1)dynamic mapping of transmission, 2) near real-time capture of population dynamics, 3) modelling based on a minimum essential database/dataset, 4) implementation of mobile health (m-health) and sensitive diagnostics, 5) design of effective response packages tailored to different transmission settings and levels, and 6) validation of approaches and responses packages.

Identifiers

PMID23849433
PMCPMC3707090
OpenAlexW2135155742

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.