Evidence map›Paper›PMID 35421123›Full record

ArticlePloS one2022

Performance of COVID-19 case-based surveillance system in FCT, Nigeria, March 2020 -January 2021.

Chikodi Modesta Umeozuru, Aishat Bukola Usman, Abdulhakeem Abayomi Olorukooba, Idris Nasir Abdullahi, Doris Japhet John, Lukman Ademola Lawal, Charles Chukwudi Uwazie, Muhammad Shakir Balogun

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. 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

8 authors.

Chikodi Modesta UmeozuruNigeria Field Epidemiology and Laboratory Training Program, Abuja, Nigeria.ORCID 0000-0001-9081-9148
Aishat Bukola UsmanAfrican Field Epidemiology Network (AFENET), Abuja, Nigeria.
Abdulhakeem Abayomi OlorukoobaDepartment of Community Medicine, Ahmadu Bello University, Zaria, Kaduna, Nigeria.
Idris Nasir AbdullahiDepartment of Medical Laboratory Science, Ahmadu Bello University, Zaria, Kaduna State, Nigeria.
Doris Japhet JohnDepartment of Public Health, Federal Capital Territory Administration, Abuja, Nigeria.
Lukman Ademola LawalDepartment of Public Health, Federal Capital Territory Administration, Abuja, Nigeria.ORCID 0000-0002-6961-580X
Charles Chukwudi UwazieNigeria Field Epidemiology and Laboratory Training Program, Abuja, Nigeria.
Muhammad Shakir BalogunAfrican Field Epidemiology Network (AFENET), Abuja, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe emergence of novel SARS-CoV-2 has caused a pandemic of Coronavirus Disease 19 (COVID-19) which has spread exponentially worldwide. A robust surveillance system is essential for correct estimation of the disease burden and containment of the pandemic. We evaluated the performance of COVID-19 case-based surveillance system in FCT, Nigeria and assessed its key attributes.

methodsWe used a cross-sectional study design, comprising a survey, key informant interview, record review and secondary data analysis. A self-administered, semi-structured questionnaire was administered to key stakeholders to assess the attributes and process of operation of the surveillance system using CDC's Updated Guidelines for Evaluation of Public Health Surveillance System 2001. Data collected alongside surveillance data from March 2020 to January 2021 were analyzed and summarized using descriptive statistics.

resultsOut of 69,338 suspected cases, 12,595 tested positive with RT-PCR with a positive predictive value (PPV) of 18%. Healthcare workers were identified as high-risk group with a prevalence of 23.5%. About 82% respondents perceived the system to be simple, 85.5% posited that the system was flexible and easily accommodates changes, 71.4% reported that the system was acceptable and expressed willingness to continue participation. Representativeness of the system was 93%, stability 40%, data quality 56.2% and timeliness 45.5%, estimated result turnaround time (TAT) was suboptimal.

conclusionThe system was found to be useful, simple, flexible, sensitive, acceptable, with good representativeness but the stability, data quality and timeliness was poor. The system meets initial surveillance objectives but rapid expansion of sample collection and testing sites, improvement of TAT, sustainable funding, improvement of electronic database, continuous provision of logistics, supplies and additional trainings are needed to address identified weaknesses, optimize the system performance and meet increasing need of case detection in the wake of rapidly spreading pandemic. More risk-group persons should be tested to improve surveillance effectiveness.

Indexed as

COVID-19Cross-Sectional StudiesHumansNigeriaPublic Health SurveillanceSARS-CoV-2

Identifiers

PMID35421123
PMCPMC9009682

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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.