Evidence map›Paper›PMID 39553340›Full record

ArticleChina CDC weekly2024

Application of an Integrated Risk Matrix and the Borda Count Method on Lassa Fever in Assessing the Importation Risk of EID - 9 African Countries, 1996-2023.

Weijing Shang, Yu Wu, Jue Liu, Wannian Liang, Min Liu

Abstract read
In one paragraph

Article in China CDC weekly, 2024. 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.

Weijing ShangSchool of Public Health, Peking University, Beijing, China.
Yu WuSchool of Public Health, Peking University, Beijing, China.
Jue LiuSchool of Public Health, Peking University, Beijing, China.
Wannian LiangVanke School of Public Health, Tsinghua University, Beijing, China.
Min LiuSchool of Public Health, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Common methods for assessing and responding to outbreaks of emerging infectious diseases (EIDs) are usually applied in isolation and have limitations. This study aimed to integrate the risk matrix and Borda count methods to assess the importation risk of EIDs to China, using Lassa fever (LF) as an example. Methods: This study used a mixed-methods approach combining multi-source data with an integrated risk matrix and Borda count method. Data were obtained from the World Health Organization, the Concise Statistics of International Students dataset, the United Nations World Tourism Organization, and the Statistical Yearbook. Importation risk was assessed across two dimensions: possibility and severity. Total importation risk was then categorized into 4 levels (low, moderate, high, and extremely high), corresponding to green, yellow, orange, and red zones, respectively, in the risk matrix assessment index. The Borda count method was used to rank the risks. Results: The importation risk for 9 countries that experienced LF outbreaks from 1996 to 2023 was scored and ranked by importation possibility and severity to derive overall importation risks. This study determined that Nigeria posed the highest LF importation risk to China, ranking first among West African countries with the highest Borda points. Countries with moderate importation risk included Sierra Leone, Burkina Faso, and Ghana. Discussion: An integrated risk matrix and Borda count method presented in this study may serve as a significant supplement to other risk assessment methods and enrich the current toolbox of public health countermeasures and inform future risk management of the importation of EIDs.

Indexed as

Borda count methodEmerging infectious diseaseLassa FeverRisk assessmentRisk matrix

Identifiers

PMID39553340
PMCPMC11561373

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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.