Evidence map›Paper›PMID 36537137›Full record

ArticleEpidemiology and infection2022

Estimated incidence and transmission intensity of rubella infection in Zambia pre-vaccine era 2005-2016.

Mazyanga L Mazaba, Samuel Bosomprah, Daniel Cohen, Mwaka Monze, Seter Siziya

Abstract read
In one paragraph

Article in Epidemiology and infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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.

Mazyanga L MazabaMichael Chilufya Sata School of Medicine, Copperbelt University, Ndola, Zambia.ORCID 0000-0002-5465-5710
Samuel BosomprahDepartment of Biostatistics, School of Public Health, University of Ghana, Legon, Accra.
Daniel CohenSchool of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Mwaka MonzeVirology Unit, University Teaching Hospital, Ministry of Health, Lusaka, Zambia.
Seter SiziyaMichael Chilufya Sata School of Medicine, Copperbelt University, Ndola, Zambia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rubella disease burden in Zambia may be under-estimated. Using models, we describe the transmission dynamics, determine the incidence estimates and assess the level of underestimation of the real burden of rubella infection in Zambia during the pre-vaccination period 2005-2016. This study used both the deterministic compartmental model and likelihood-based method using a Bayesian framework to describe the epidemiology of rubella. A total of 1313 cases of rubella were confirmed with the highest annual number of 255 new cases recorded in 2008. However, 2014 recorded the highest monthly median positivity rate of 9.0%. The observed median rubella cases were 5.5. There was a seasonal pattern in the occurrence of laboratory-confirmed rubella, with higher test positivity rates of rubella infection usually recorded in the months of September, October and November. The modelled monthly median incidence of rubella infection among the general population was 76 and 20 among pregnant women. The incidence of rubella among the non-pregnant women was 44. The average effective reproductive number (Rt) between 2005 and 2016 was estimated as 1.2 with the peak of infection occurring in 2016. The measles surveillance system underestimates the observed burden of rubella. A mass vaccination campaign conducted between January and July is recommended.

Indexed as

MeaslesRubellaBayes TheoremFemaleHumansIncidenceInfantLikelihood FunctionsMeasles-Mumps-Rubella VaccineRubella VaccineVaccinationZambiaMeasles-Mumps-Rubella VaccineRubella Vaccineinfectious diseaseInfectious disease epidemiologymodellingoutbreaksrubella

Identifiers

PMID36537137
PMCPMC9990411

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Registered trials

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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.