Evidence map›Paper›PMID 39593092›Full record

ArticleGlobalization and health2024

Predicting the risk of malaria importation into Jiangsu Province, China: a modeling study.

Kaixuan Liu, Yuanyuan Cao, Enyu Xu, Zeyin Chong, Liying Chai, Yi Wang, Yuhui Xu, Yin Wang, Jun Zhang, Olaf Müller and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Globalization and health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Challenges in postoperative self-management for patients with bladder cancer and urinary stoma: a qualitative study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Kaixuan Liu *Institute of Public Health, Medical School of Yangzhou University, Yangzhou University, Yangzhou, Hanjiang District, 225007, China.
Yuanyuan Cao *National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory On Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China.
Enyu XuInstitute of Public Health, Medical School of Yangzhou University, Yangzhou University, Yangzhou, Hanjiang District, 225007, China.
Zeyin ChongInstitute of Public Health, Medical School of Yangzhou University, Yangzhou University, Yangzhou, Hanjiang District, 225007, China.
Liying ChaiInstitute of Public Health, Medical School of Yangzhou University, Yangzhou University, Yangzhou, Hanjiang District, 225007, China.
Yi WangNational Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory On Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China.
Yuhui XuYangzhou Center for Disease Control and Prevention, Yangzhou, China.
Yin WangYangzhou Center for Disease Control and Prevention, Yangzhou, China.
Jun ZhangYangzhou Center for Disease Control and Prevention, Yangzhou, China.
Olaf MüllerInstitute of Global Health, Medical School, Ruprecht-Karls-University, Heidelberg, Germany.
Jun CaoNational Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory On Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China.
Guoding ZhuNational Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory On Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, China. jipdzhu@hotmail.com.
Guangyu LuInstitute of Public Health, Medical School of Yangzhou University, Yangzhou University, Yangzhou, Hanjiang District, 225007, China. guangyu.lu@yzu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe World Health Organization certified China malaria-free in 2021. Consequently, preventing the risk of malaria re-introduction caused by imported malaria has now become a major challenge. This study aims to characterize the dynamics and predict the risk of malaria importation in Jiangsu Province, where the number of imported malaria cases ranks among the highest in China.

methodsThe annual number of cases with imported malaria in Jiangsu Province, the annual number of travelers from sub-Saharan Africa (SSA) to Jiangsu Province (both Chinese and international travelers), and the annual number of Chinese migrant workers from Jiangsu Province who stayed abroad between 2013 and 2020 were assessed. The spatio-temporal dynamics of malaria importation was characterized with ArcGIS 10.8. A negative binomial model was applied to model malaria importation to Jiangsu Province, China.

resultsA total of 2,221 of imported malaria cases were reported from January 1, 2013, until December 31, 2020. Imported malaria cases into China were mainly from SSA (98%) and P. falciparum (78%), the most common species. A seasonal pattern was observed, with the most cases occurring from December to February. The negative binomial model, which incorporates the number of Chinese migrant workers from Jiangsu Province who stayed abroad as an independent variable, demonstrated better performance (AIC: 96.495, BIC: 94.230) compared to the model based solely on travelers from SSA to Jiangsu Province. The model indicated an estimated 139% increase in imported cases for a 10% increase in Chinese migrant workers from Jiangsu Province who stayed abroad.

conclusionIn conclusion, our study underscores the importance of incorporating data on Chinese migrant workers who have stayed abroad when predicting malaria importation risks. By integrating both international travel patterns and migrant worker data, our findings offer a more robust framework for assessing and managing malaria risk in Jiangsu Province. This approach provides valuable insights for public health officials, enabling more effective resource allocation and targeted interventions to prevent the re-introduction of malaria and improve overall disease management.

Indexed as

Communicable Diseases, ImportedMalariaAfrica South of the SaharaChinaHumansRisk AssessmentTransients and MigrantsTravelImported malariaMalaria eliminationMigrant workersPrevention of malaria reintroductionTravel medicine

Identifiers

PMID39593092
PMCPMC11590227

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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.