Evidence map›Paper›PMID 31931793›Full record

ArticleBMC health services research2020

An evaluation of the Zambia influenza sentinel surveillance system, 2011-2017.

Paul Simusika, Stefano Tempia, Edward Chentulo, Lauren Polansky, Mazyanga Lucy Mazaba, Idah Ndumba, Quinn K Mbewe, Mwaka Monze

Abstract readEvaluation Study
In one paragraph

Article in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  10. First COVID-19 case in Zambia - Comparative phylogenomic analyses of SARS-CoV-2 detected in African countries.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021
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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

8 authors.

Paul SimusikaNational Influenza Center, Virology Laboratory, University Teaching Hospital, Lusaka, Zambia. psimusika@yahoo.co.uk.ORCID http://orcid.org/0000-0001-5755-6163
Stefano TempiaInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Edward ChentuloNational Influenza Center, Virology Laboratory, University Teaching Hospital, Lusaka, Zambia.
Lauren PolanskyInfluenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa.
Mazyanga Lucy MazabaNational Influenza Center, Virology Laboratory, University Teaching Hospital, Lusaka, Zambia.
Idah NdumbaNational Influenza Center, Virology Laboratory, University Teaching Hospital, Lusaka, Zambia.
Quinn K MbeweNational Influenza Center, Virology Laboratory, University Teaching Hospital, Lusaka, Zambia.
Mwaka MonzeNational Influenza Center, Virology Laboratory, University Teaching Hospital, Lusaka, Zambia. mwakamonze@hotmail.com.

Funding

CDC,US NU511P000828-05-02).
6 · The paper itself

Abstract

backgroundOver the past decade, influenza surveillance has been established in several African countries including Zambia. However, information on the on data quality and reliability of established influenza surveillance systems in Africa are limited. Such information would enable countries to assess the performance of their surveillance systems, identify shortfalls for improvement and provide evidence of data reliability for policy making and public health interventions.

methodsWe used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza surveillance system (ISS) in Zambia during 2011-2017 using 9 attributes: (i) data quality and completeness, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability, (viii) utility, and (ix) sustainability. Each attribute was evaluated using pre-defined indicators. For each indicator we obtained the proportion (expressed as percentage) of the outcome of interest over the total. A scale from 1 to 3 was used to provide a score for each attribute as follows: < 60% (as obtained in the calculation above) scored 1 (weak performance); 60-79% scored 2 (moderate performance); ≥80% scored 3 (good performance). An overall score for each attribute and the ISS was obtained by averaging the scores of all evaluated attributes.

resultsThe overall mean score for the ISS in Zambia was 2.6. Key strengths of the system were the quality of data generated (score: 2.9), its flexibility (score: 3.0) especially to monitor viral pathogens other than influenza viruses, its simplicity (score: 2.8), acceptability (score: 3.0) and stability (score: 2.6) over the review period and its relatively low cost ($310,000 per annum). Identified weaknesses related mainly to geographic representativeness (score: 2.0), timeliness (score: 2.5), especially in shipment of samples from remote sites, and sustainability (score: 1.0) in the absence of external funds.

conclusionsThe system performed moderately well in our evaluation. Key improvements would include improvements in the timeliness of samples shipments and geographical coverage. However, these improvements would result in increased cost and logistical complexity. The ISSS in Zambia is largely reliant on external funds and the acceptability of maintaining the surveillance system through national funds would require evaluation.

Indexed as

Sentinel SurveillanceData AccuracyHumansInfluenza, HumanReproducibility of ResultsZambiaEvaluationInfluenzaSurveillanceZambia

Identifiers

PMID31931793
PMCPMC6958603

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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.