IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0102755.html
   My bibliography  Save this article

Predicting Local Dengue Transmission in Guangzhou, China, through the Influence of Imported Cases, Mosquito Density and Climate Variability

Author

Listed:
  • Shaowei Sang
  • Wenwu Yin
  • Peng Bi
  • Honglong Zhang
  • Chenggang Wang
  • Xiaobo Liu
  • Bin Chen
  • Weizhong Yang
  • Qiyong Liu

Abstract

Introduction: Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue’s control and prevention purpose. Methodology and Principal Findings: Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags. Conclusions: Imported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China.

Suggested Citation

  • Shaowei Sang & Wenwu Yin & Peng Bi & Honglong Zhang & Chenggang Wang & Xiaobo Liu & Bin Chen & Weizhong Yang & Qiyong Liu, 2014. "Predicting Local Dengue Transmission in Guangzhou, China, through the Influence of Imported Cases, Mosquito Density and Climate Variability," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-10, July.
    • Handle: RePEc:plo:pone00:0102755
    DOI: 10.1371/journal.pone.0102755
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0102755
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0102755&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0102755?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Miranda Chan & Michael A Johansson, 2012. "The Incubation Periods of Dengue Viruses," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    2. Yien Ling Hii & Huaiping Zhu & Nawi Ng & Lee Ching Ng & Joacim Rocklöv, 2012. "Forecast of Dengue Incidence Using Temperature and Rainfall," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 6(11), pages 1-9, November.
    3. Elodie Descloux & Morgan Mangeas & Christophe Eugène Menkes & Matthieu Lengaigne & Anne Leroy & Temaui Tehei & Laurent Guillaumot & Magali Teurlai & Ann-Claire Gourinat & Justus Benzler & Anne Pfannst, 2012. "Climate-Based Models for Understanding and Forecasting Dengue Epidemics," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 6(2), pages 1-19, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yingtao Zhang & Tao Wang & Kangkang Liu & Yao Xia & Yi Lu & Qinlong Jing & Zhicong Yang & Wenbiao Hu & Jiahai Lu, 2016. "Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 10(2), pages 1-17, February.
    2. Hongyan Ren & Lan Zheng & Qiaoxuan Li & Wu Yuan & Liang Lu, 2017. "Exploring Determinants of Spatial Variations in the Dengue Fever Epidemic Using Geographically Weighted Regression Model: A Case Study in the Joint Guangzhou-Foshan Area, China, 2014," IJERPH, MDPI, vol. 14(12), pages 1-13, December.
    3. Yujuan Yue & Xiaobo Liu & Dongsheng Ren & Haixia Wu & Qiyong Liu, 2021. "Spatial Dynamics of Dengue Fever in Mainland China, 2019," IJERPH, MDPI, vol. 18(6), pages 1-12, March.
    4. Faizul Akmal Abdul Rahim & Mohd Amierul Fikri Mahmud & Mohd Farihan Md Yatim & Mohd Hatta Abdul Mutalip & Hanipah Shahar, 2022. "The Construction Site Provides A Suitable Environment For Vector Mosquitoes In The Federal Territory Of Kuala Lumpur, Malaysia," Environment & Ecosystem Science (EES), Zibeline International Publishing, vol. 6(2), pages 65-70, June.
    5. Sheika Henry & Francisco de Assis Mendonça, 2020. "Past, Present, and Future Vulnerability to Dengue in Jamaica: A Spatial Analysis of Monthly Variations," IJERPH, MDPI, vol. 17(9), pages 1-14, May.
    6. Michael Xiaoliang Tong & Alana Hansen & Scott Hanson-Easey & Scott Cameron & Jianjun Xiang & Qiyong Liu & Yehuan Sun & Philip Weinstein & Gil-Soo Han & Craig Williams & Peng Bi, 2015. "Infectious Diseases, Urbanization and Climate Change: Challenges in Future China," IJERPH, MDPI, vol. 12(9), pages 1-12, September.
    7. Yujuan Yue & Qiyong Liu, 2019. "Exploring Epidemiological Characteristics of Domestic Imported Dengue Fever in Mainland China, 2014–2018," IJERPH, MDPI, vol. 16(20), pages 1-10, October.
    8. Shaowei Sang & Shaohua Gu & Peng Bi & Weizhong Yang & Zhicong Yang & Lei Xu & Jun Yang & Xiaobo Liu & Tong Jiang & Haixia Wu & Cordia Chu & Qiyong Liu, 2015. "Predicting Unprecedented Dengue Outbreak Using Imported Cases and Climatic Factors in Guangzhou, 2014," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(5), pages 1-12, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ting-Wu Chuang & Luis Fernando Chaves & Po-Jiang Chen, 2017. "Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-20, June.
    2. Kraisak Kesorn & Phatsavee Ongruk & Jakkrawarn Chompoosri & Atchara Phumee & Usavadee Thavara & Apiwat Tawatsin & Padet Siriyasatien, 2015. "Morbidity Rate Prediction of Dengue Hemorrhagic Fever (DHF) Using the Support Vector Machine and the Aedes aegypti Infection Rate in Similar Climates and Geographical Areas," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
    3. Maneerat, Somsakun & Daudé, Eric, 2016. "A spatial agent-based simulation model of the dengue vector Aedes aegypti to explore its population dynamics in urban areas," Ecological Modelling, Elsevier, vol. 333(C), pages 66-78.
    4. Teerawad Sriklin & Siriwan Kajornkasirat & Supattra Puttinaovarat, 2021. "Dengue Transmission Mapping with Weather-Based Predictive Model in Three Southernmost Provinces of Thailand," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
    5. Paul C. Fenema & A. Georges L. Romme, 2020. "Latent organizing for responding to emergencies: foundations for research," Journal of Organization Design, Springer;Organizational Design Community, vol. 9(1), pages 1-16, December.
    6. Pablo Méndez-Lázaro & Frank E. Muller-Karger & Daniel Otis & Matthew J. McCarthy & Marisol Peña-Orellana, 2014. "Assessing Climate Variability Effects on Dengue Incidence in San Juan, Puerto Rico," IJERPH, MDPI, vol. 11(9), pages 1-20, September.
    7. Tay, Chai Jian & Fakhruddin, Muhammad & Fauzi, Ilham Saiful & Teh, Su Yean & Syamsuddin, Muhammad & Nuraini, Nuning & Soewono, Edy, 2022. "Dengue epidemiological characteristic in Kuala Lumpur and Selangor, Malaysia," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 489-504.
    8. Víctor Hugo Peña-García & Omar Triana-Chávez & Ana María Mejía-Jaramillo & Francisco J. Díaz & Andrés Gómez-Palacio & Sair Arboleda-Sánchez, 2016. "Infection Rates by Dengue Virus in Mosquitoes and the Influence of Temperature May Be Related to Different Endemicity Patterns in Three Colombian Cities," IJERPH, MDPI, vol. 13(7), pages 1-16, July.
    9. Baharuddin Baharuddin & Suhariningsih Suhariningsih & Brodjol Ulama, 2014. "Geographically Weighted Regression Modeling for Analyzing Spatial Heterogeneity on Relationship between Dengue Hemorrhagic Fever Incidence and Rainfall in Surabaya, Indonesia," Modern Applied Science, Canadian Center of Science and Education, vol. 8(3), pages 1-85, June.
    10. Abidemi, A. & Abd Aziz, M.I. & Ahmad, R., 2020. "Vaccination and vector control effect on dengue virus transmission dynamics: Modelling and simulation," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    11. Brito da Cruz, Artur M.C. & Rodrigues, Helena Sofia, 2021. "Personal protective strategies for dengue disease: Simulations in two coexisting virus serotypes scenarios," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 254-267.
    12. Judicaël Obame-Nkoghe & Boris Kevin Makanga & Sylvie Brizard Zongo & Aubin Armel Koumba & Prune Komba & Neil-Michel Longo-Pendy & Franck Mounioko & Rodolphe Akone-Ella & Lynda Chancelya Nkoghe-Nkoghe , 2023. "Urban Green Spaces and Vector-Borne Disease Risk in Africa: The Case of an Unclean Forested Park in Libreville (Gabon, Central Africa)," IJERPH, MDPI, vol. 20(10), pages 1-17, May.
    13. Yoon Ling Cheong & Katrin Burkart & Pedro J. Leitão & Tobia Lakes, 2013. "Assessing Weather Effects on Dengue Disease in Malaysia," IJERPH, MDPI, vol. 10(12), pages 1-16, November.
    14. Abdalgader, Tarteel & Banerjee, Malay & Zhang, Lai, 2022. "Spatially weak syncronization of spreading pattern between Aedes Albopictus and dengue fever," Ecological Modelling, Elsevier, vol. 473(C).
    15. Villela, Daniel A.M., 2016. "Analysis of the vectorial capacity of vector-borne diseases using moment-generating functions," Applied Mathematics and Computation, Elsevier, vol. 290(C), pages 1-8.
    16. Jue Tao Lim & Borame Sue Dickens & Sun Haoyang & Ng Lee Ching & Alex R Cook, 2020. "Inference on dengue epidemics with Bayesian regime switching models," PLOS Computational Biology, Public Library of Science, vol. 16(5), pages 1-15, May.
    17. Kazi Mizanur Rahman & Yushuf Sharker & Reza Ali Rumi & Mahboob-Ul Islam Khan & Mohammad Sohel Shomik & Muhammad Waliur Rahman & Sk Masum Billah & Mahmudur Rahman & Peter Kim Streatfield & David Harley, 2020. "An Association between Rainy Days with Clinical Dengue Fever in Dhaka, Bangladesh: Findings from a Hospital Based Study," IJERPH, MDPI, vol. 17(24), pages 1-9, December.
    18. Mateus C, Rafael & Zuluaga, Susana Alvarez & Orozco, Mariajose Franco & Marín, Paula Alejandra Escudero, 2021. "Modeling the propagation of the Dengue, Zika and Chikungunya virus in the city of Bello using Agent-Based Modeling and Simulation," OSF Preprints wmxzd, Center for Open Science.
    19. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    20. Ayu Rahayu & Utari Saraswati & Endah Supriyati & Dian Aruni Kumalawati & Rio Hermantara & Anwar Rovik & Edwin Widyanto Daniwijaya & Iva Fitriana & Sigit Setyawan & Riris Andono Ahmad & Dwi Satria Ward, 2019. "Prevalence and Distribution of Dengue Virus in Aedes aegypti in Yogyakarta City before Deployment of Wolbachia Infected Aedes aegypti," IJERPH, MDPI, vol. 16(10), pages 1-12, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0102755. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.