Evidence map›Paper›PMID 30107824›Full record

ArticleBMC infectious diseases2018

Epidemiology of measles in the metropolitan setting, Addis Ababa, Ethiopia, 2005-2014: a retrospective descriptive surveillance data analysis.

Munira Nasser Hassen, Abyot Bekele Woyessa, Mekonen Getahun, Berhane Beyene, Lucy Buluanger, Ayesheshem Ademe, Alemayehu Bekele, Adamu Addissie, Amha Kebede, Daddi Jima

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 18% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
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

10 authors at 5 institutions in 1 country.

Munira Nasser HassenAddis Ababa Health Bureau, Addis Ababa, Ethiopia.
Abyot Bekele WoyessaCenter for Public Health Emergency Management, Ethiopian Public Health Institute, PO BOX 1242, Addis Ababa, Ethiopia. abyotbekelephem@gmail.com.
Mekonen GetahunCenter for Public Health Emergency Management, Ethiopian Public Health Institute, PO BOX 1242, Addis Ababa, Ethiopia.
Berhane BeyeneCenter for Public Health Emergency Management, Ethiopian Public Health Institute, PO BOX 1242, Addis Ababa, Ethiopia.
Lucy BuluangerCDC, Addis Ababa, Ethiopia.
Ayesheshem AdemeWHO, Addis Ababa, Ethiopia.
Alemayehu BekeleCenter for Public Health Emergency Management, Ethiopian Public Health Institute, PO BOX 1242, Addis Ababa, Ethiopia.
Adamu AddissieAddis Ababa University, Addis Ababa, Ethiopia.
Amha KebedeCenter for Public Health Emergency Management, Ethiopian Public Health Institute, PO BOX 1242, Addis Ababa, Ethiopia.
Daddi JimaCenter for Public Health Emergency Management, Ethiopian Public Health Institute, PO BOX 1242, Addis Ababa, Ethiopia.
Ethiopian Public Health Institute · ETAddis Ababa City Administration Health Bureau · ETAddis Ababa University · ETAfrica Centres for Disease Control and Prevention · ETEthiopian Public Health Association · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeasles is a highly infectious and serious respiratory viral disease which caused by a virus. It is a significant cause of illness and death worldwide. This data analysis was conducted to describe the trend and determine the reporting rate of measles cases in Addis Ababa to make recommendation for the government of the city to strengthening measles control interventions.

methodsWe obtained and extracted ten years (2005-2014) Addis Ababa city's measles surveillance data from national database. We carried out retrospective descriptive data analysis by time, place and person variables. We calculated cumulative and specific reporting rates by dividing measles cases (lab confirmed, epidemiologically linked and compatible cases) to respective population and multiplying by 100,000. We divided average of ten years measles cases to midyear population and multiplied by 100,000 to calculate annualized reporting rate. We analyzed non-measles febrile rash rate by dividing laboratory negative cases to total population and multiplying by 100,000.

resultsA total of 4203 suspected measles cases were identified. Among them 1154 (27.5%) were laboratory confirmed, 512 (12.2%) were clinically compatible, 52 (1.2%) were epidemiologically linked cases and the rest 2485 (59.1%) were IgM negative for measles which makes total measles cases 1718 (40.9%). Median age was 5 years with 2-18 years interquartile-range. The annualized measles reporting rate was 5.9, which was 40.2 among > 1 year, 11.5 among 1-4 years, 6.0 among 5-14 years, 4.1 among 15-44 years and 0.01 among ≥ 45 years per 100,000 population. Among the total measles cases; 380 (22%) were received at least one dose of measles containing vaccine (MCV) while 415 (24%) cases were not vaccinated and the vaccination status of 923 (54%) cases were not known.

conclusionOur analysis revealed that the reporting rate was higher among young children than older age group. Among all the patients 22% were received at least one dose of measles vaccine whereas 13% were not vaccinated against measles antigen. Routine immunization should be strengthened to reach all children through well monitored vaccine cold chain management.

Indexed as

AdolescentAdultChildChild, PreschoolDatabases, FactualDisease OutbreaksEthiopiaFemaleHumansIncidenceInfantMaleMeaslesMeasles VaccineMiddle AgedRetrospective StudiesMeasles VaccineAddis AbabaEthiopiaMeaslesOutbreakSurveillanceVaccination

Identifiers

PMID30107824
PMCPMC6092798
OpenAlexW2886522864

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.