Evidence map›Paper›PMID 29155668›Full record

ArticleEmerging infectious diseases2017

Responding to Communicable Diseases in Internationally Mobile Populations at Points of Entry and along Porous Borders, Nigeria, Benin, and Togo.

Rebecca D Merrill, Kimberly Rogers, Sarah Ward, Olubumni Ojo, Clement Glele Kakaī, Tamekloe Tsidi Agbeko, Hassan Garba, Amanda MacGurn, Marydale Oppert, Idrissa Kone and 3 more

Abstract read
In one paragraph

Article in Emerging infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

13 authors.

Rebecca D Merrill
Kimberly Rogers
Sarah Ward
Olubumni Ojo
Clement Glele Kakaī
Tamekloe Tsidi Agbeko
Hassan Garba
Amanda MacGurn
Marydale Oppert
Idrissa Kone
Olutola Bamsa
Dana Schneider
Clive Brown

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent multinational disease outbreaks demonstrate the risk of disease spreading globally before public health systems can respond to an event. To ensure global health security, countries need robust multisectoral systems to rapidly detect and respond to domestic or imported communicable diseases. The US Centers for Disease Control and Prevention International Border Team works with the governments of Nigeria, Togo, and Benin, along with Pro-Health International and the Abidjan-Lagos Corridor Organization, to build sustainable International Health Regulations capacities at points of entry (POEs) and along border regions. Together, we strengthen comprehensive national and regional border health systems by developing public health emergency response plans for POEs, conducting qualitative assessments of public health preparedness and response capacities at ground crossings, integrating internationally mobile populations into national health surveillance systems, and formalizing cross-border public health coordination. Achieving comprehensive national and regional border health capacity, which advances overall global health security, necessitates multisectoral dedication to the aforementioned components.

Indexed as

Communicable Disease ControlPopulation SurveillanceCommunicable DiseasesDisease OutbreaksEmigration and ImmigrationGlobal HealthHumansInternational CooperationNigeriaPublic Health SurveillanceTogoBeninborder crossingglobal healthglobal health securityNigeriapublic health surveillanceTogo

Identifiers

PMID29155668
PMCPMC5711311

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.