Descriptive Analysis Using R for Age Trend in Dengue Cases

  • Nor Farisha Muhamad Krishnan Faculty of Computer and Mathematical Sciences UiTM Kelantan
  • Zuriani Ahmad Zukarnain Faculty of Computer and Mathematical Sciences UiTM Kelantan
  • Marhainis Jamaludin Faculty of Computer and Mathematical Sciences UiTM Kelantan
  • Noorihan Abdul Rahman Faculty of Computer and Mathematical Sciences UiTM Kelantan
Keywords: Age, Areas, Dengue Cases, Descriptive, R Programming


Dengue is a viral infection disease transmitted by Aedes mosquitoes which can lead to fatality. The case study is conducted for Kota Bharu city which is the capital city of Kelantan State in Malaysia. Different areas in Kota Bharu recorded different number of cases. The aim of this study is to see whether there is a trend in age range for those who are infected by dengue. Data on dengue cases were obtained from Department of Health in Kelantan from 2015 until 2019. We have done descriptive analysis on range of age among the infected victims using R programming. The data visualization presented that the age range between 10 years old and 35 years old were the most common in area Kubang Kerian and Panji with 20.3% and 19.7% respectively. Nevertheless, gender did not have an effect on dengue. The mean age is 30.17 years and 28.38 years old for both areas correspondingly.  Dengue outbreak was also affected by the age of victims and has a significant health problem primarily in adolescents and young adults. Public awareness and proper vector control are needed to keep the dengue cases low and to prevent outbreaks.


Abdullah, S. M. (2019, September 1). Dengue cases in Kelantan record downward trend. New Straits Times.
Abu-soud, S. M. (2019). A Novel Approach for Dealing with Missing Values in Machine Learning Datasets with Discrete Values. July.
Abu Hassan Shaari, A. H. S. B., Mohamed, M. S. B., & Rahman, J. A. (2015). Dengue in Malaysia - A commentary. International Medical Journal Malaysia, 14(1), 3–4.
Acuña, E., & Rodriguez, C. (2004). The Treatment of Missing Values and its Effect on Classifier Accuracy. In Classification, Clustering, and Data Mining Applications.
Ahmad Nizal, M. G., Rozita, H., Mazrura, S., Zainudin, M. A., Hidayatulfathi, O., Faridah, M. A., Noor Artika, I., & Er, A. C. (2012). Dengue infections and circulating serotypes in Negeri Sembilan, Malaysia. Malaysian Journal of Public Health Medicine, 12(1), 21–30.
Angelov, B. (2017). Working with Missing Data in Machine Learning. Towards Data Science Websites.
Asnis, D. S., & Crupi, R. (2005). Flaviviridae. In Emerging Neurological Infections.
Chau, N. V. V., Ph, D., & Wills, B. (2012). Review article: Dengue. 1423–1432.
Chew, C. H., Woon, Y. L., Amin, F., Adnan, T. H., Hani, A., Wahab, A., Ahmad, Z. E., Bujang, M. A., Muneer, A., Hamid, A., Jamal, R., Chen, W. S., Hor, C. P., Yeap, L., Hoo, L. P., Goh, P. P., & Lim, T. O. (2016). Rural-urban comparisons of dengue seroprevalence in Malaysia. BMC Public Health, 1–9.
Chew, M. H., & Rahman, M. (2012). Dengue in Malaysia : An epidemiological perspective study. 28(4), 643–647.
Dong, Y., & Peng, C. J. (2013). Principled missing data methods for researchers. 2004, 1–17.
Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37–53.
Gullo, F. (2015). From patterns in data to knowledge discovery: What data mining can do. Physics Procedia, 62, 18–22.
Guo, C., Zhou, Z., Wen, Z., Liu, Y., Zeng, C., Xiao, D., Ou, M., Han, Y., Huang, S., Liu, D., Ye, X., Zou, X., Wu, J., Wang, H., Zeng, E. Y., Jing, C., & Yang, G. (2017). Global epidemiology of dengue outbreaks in 1990–2015: A systematic review and meta-analysis. Frontiers in Cellular and Infection Microbiology, 7(JUL), 1–11.
Huy, B. V., Hoa, L. N. M., Thuy, D. T., Van Kinh, N., Ngan, T. T. D., Duyet, L. Van, Hung, N. T., Minh, N. N. Q., Truong, N. T., Chau, N. V. V., & Tran, B. X. (2019). Epidemiological and Clinical Features of Dengue Infection in Adults in the 2017 Outbreak in Vietnam. BioMed Research International, 2019.
Ibrahim, N., Akhir, N. S., & Hassan, F. H. (n.d.). Using Clustering and Predictive Analysis of Infected Area on Dengue Outbreaks in Malaysia. 9(2), 51–58.
Liew, S. M., Khoo, E. M., Ho, B. K., Lee, Y. K., & Omar, M. (2016). Dengue in Malaysia : Factors Associated with Dengue Mortality from a National Registry. 1–14.
Lo, J. (2006). The R -computing language : Potential for Asian economists. 17, 1066–1081.
Low, W. L., Lee, M. L., & Ling, T. W. (2001). A knowledge-based approach for duplicate elimination in data cleaning. Information Systems.
Luís, S. (2017). Analysis of dengue cases according to clinical severity, São Luís, Maranhão, Brazil. August, 1–10.
Mudin, R. N. (2015). Dengue incidence and the prevention and control program in Malaysia. International Medical Journal Malaysia.
Nepal, H. P. (2014). Detection of IgM against Dengue Virus in Clinically Suspected Patients Presenting at a Tertiary Care Centre, Narayani Zone, Nepal. Journal of Tropical Diseases, 02(03), 1–7.
Nur Fatini H, Mangantig E, S. L. . (2017). Factors Associated With Dengue Knowledge of Behavior Among Community in a Dengue. International Journal of Public Health and Clinical Sciences.
Peng, L., & Lei, L. (n.d.). A Review of Missing Data Treatment Methods. 1–8.
Singh Rathore, M., Vohra, R., Nath Sharma, B., Prakash Pankaj, J., Lal Bhardwaj, S., & Singh, L. (2015). Clinico-Epidemiological Study of Dengue in a Tertiary Care Hospital in Jaipur, Rajasthan. International Journal of Scientific Study, 3(9), 32–35.
Velasco, J. M. S., Alera, M. T. P., Ypil-cardenas, C. A., Dimaano, E. M., Jarman, R. G., Chinnawirotpisan, P., Thaisomboonsuk, B., Yoon, I., & Cummings, D. A. (2014). Demographic , clinical and laboratory findings among adult and pediatric patients hospitalized with dengue in the philippines. 337–345.
Wan-Norafikah, O., Nazni, W. A., Noramiza, S., Shafa’ar-Ko’ohar, S., Heah, S. K., Nor-Azlina, A. H., Khairul-Asuad, M., & Lee, H. L. (2012). Distribution of Aedes mosquitoes in three selected localities in Malaysia. Sains Malaysiana.
Woon, Yuan Liang; Wan Ng, Chiu; Nani Mudin, Rose; Suli, Z. (2019). Health facility use by dengue patients in the Klang Valley, Malaysia: a secondary analysis of dengue surveillance data. 10(2), 39–45.
World Health Organisation. (2014). Dengue and severe dengue. WHO Fact Sheet.
Yousaf, M., Junaid, K., Iqbal, M. S., Aslam, I., Ahmad, S., Aqeel, M., Ashfaq, U. A., Khaliq, S., Ghani, M. U., & Waqar, N. (2018). Analysis of dengue virus burden and serotypes pattern in Faisalabad, 2016-2017. Future Virology, 13(4), 245–251.
Yung, C. F., Chan, S. P., Thein, T. L., Chai, S. C., & Leo, Y. S. (2016). Epidemiological risk factors for adult dengue in Singapore: An 8-year nested test negative case control study. BMC Infectious Diseases, 16(1), 1–9.