Modeling Dynamic System for Prediction of Dengue Hemorrhagic Fever in Maros District

Authors

  • Ilham Salam Public Health Study Program, Faculty of Sports Science, Manado State University, Manado, Indonesia; Doctoral Study Program, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia
  • A. Arsunan Arsin Department of Epidemiology, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia
  • Atjo Wahyu Department of Occupational Safety and Health, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia
  • Agus Bintara Birawida Department of Environmental Health, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia
  • Aminuddin Syam Nutrition Study Program, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia
  • Anwar Mallongi Department of Environmental Health, Faculty of Public Health, Hasanuddin University, Indonesia
  • Sukri Palutturi Department of Health Policy Administration, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia
  • Farid Agushybana Public Health Study Program, Faculty of Public Health, Diponegoro University, Semarang, Indonesia
  • Aisyah Aisyah Department of Agribusiness, Pangkajene Islands State Agricultural Polytechnic, Pangkep, Indonesia
  • Ahmad Yani Department of Health Promotion and Behavioral Sciences, Faculty of Public Health, University of Muhammadiyah Palu, Palu, Indonesia
  • Muhammad Akbar Nurdin Public Health Study Program, Faculty of Public Health, Cenderawasih University, Jayapura, Indonesia
  • Rezki Elisafitri Department of Epidemiology, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia

DOI:

https://doi.org/10.3889/oamjms.2021.7098

Keywords:

DHF, Dynamic Model, ISM

Abstract

BACKGROUND: Efforts to control the incidence of dengue hemorrhagic fever (DHF) have been carried out intensively, however, there is no significant reduction in the number of DHF sufferers. Meanwhile, the predictive model is expected to be an early warning to anticipate the incidence of DHF.

AIM: Therefore, this study aims to determine the dynamic model for predicting dengue fever incidence in Maros Regency from 2020 to 2040.

METHODS: This study used the research and development (R and D) method with a dynamic systems approach. The study was conducted in Maros Regency and the data on dengue cases in Maros Regency from 2014 to 2018 were used as samples. Meanwhile, interpretive structural modeling (ISM) was used to determine policy scenarios in reducing dengue cases while the analysis of the dynamic model of dengue fever was conducted using the Powersim program.

RESULTS: The critical elements of DHF prevention in the Maros Regency include the Jumantik program, 3M Plus, early warning systems, and outreach. Furthermore, the prediction of the average incidence of dengue fever from 2020 to 2040 has decreased based on dynamic model simulations by applying the Jumantik scenario (46.8%), 3M Plus (61.17%), early warning systems (74.4%), counseling (52.12%), and the combined scenario (97.87%).

CONCLUSIONS: The incidence of dengue fever in the Maros Regency is prevented and controlled by the combination of the Jumantik program, 3M Plus, early warning systems, and counseling.

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References

Salam I, Arsin AA, Wahyu A, Syam A, Birawida AB, Mallongi A, et al. Eco-epidemiological analysis of dengue hemorrhagic fever (DHF) in Makassar city. Indian J Public Health Res Dev. 2019;10(12):1246-50. https://doi.org/10.37506/v10/i12/2019/ijphrd/192217

Noor N, Arsunan A, Marleni N, Mallongi A. Algorithm malaria diagnosis as a result of the comparison between clinical symptoms and microscopy test in the population central Sulawesi Province. Asian J Epidemiol. 2017;10(1):32-6. https://doi.org/10.3923/aje.2017.32.36

Amelia AR, Amiruddin R, Arsunan AA, Bahar B, Hasnik S, Rahardjo SP. Environmental analysis related to pulmonary TB incidence in work area of puskesmas kaluku bodoa Makassar city. Indian J Public Health Res Dev. 2018;9(8):1512-7. https://doi.org/10.5958/0976-5506.2018.00947.6

Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013;496(7446):504-7. https://doi.org/10.1038/nature12060 PMid:23563266

World Health Organization. Dengue and Severe Dengue. Geneva: World Health Organization; 2021c. Available from: https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue. [Last accessed on 2021 May 19].

Arsin AA. Epidemiologi Demam Berdarah Dengue (DBD) di Indonesia. 1st ed. Makassar: Masagena Press; 2013.

Bachtiar SP, Arusnan AA, Arsyad DS. Factors toward dengue haemorrhagic fever occurrence in Patte’ne village, North Wara district, Palopo city. Indian J Public Health Res Dev. 2019;10(7):1085-9. https://doi.org/10.5958/0976-5506.2019.01726.1

Arsin AA, Istiqamah SN, Elisafitri R, Nurdin MA, Sirajuddin S, Pulubuhu DA, et al. Correlational study of climate factor, mobility and the incidence of dengue hemorrhagic fever in Kendari, Indonesia. Enferm Clín. 2020;30:280-4.

Zamli Z, Syafar M, Palutturi S, Suriah S, Arsunan AA, Hatta H, Amiruddin R. Potential of rainfall, humidity and temperature, against the increasing of larvae in Makassar city, Indonesia. Int J Innov Technol Exp Eng. 2019;9(1):1485-7. https://doi.org/10.35940/ijitee.a4296.119119

Arsunan AA, Muis M, Ansar J, Amiruddin R, Dwinata I, Nurdin MA, et al. Positive deviance approach; an efforts to reduce the incidence of dengue hemorrhagic fever (DHF) in pangkep regency. Eur J Mol Clin Med. 2020;7(8):160-7.

Madjid A, Muhammad S, Arsunan AA, Maria IL, Abdullah T, Russeng R. Effect of knowledge and attitude factors on tuberculosis incidents in Mandar ethnic in the district of Majene West Sulawesi. Indian J Public Health Res Dev. 2019;10(8):1935-9. https://doi.org/10.5958/0976-5506.2019.02135.1

Nuddin A, Asiah N, Dangnga MS, Arsunan AA, Yusriani Y, Handayani S. Institutional strengthening as an anticipatory measure for dengue virus transmission to reduce the incidence of dengue fever. Enferm Clín. 2020;30(2):424-8. https://doi.org/10.1016/j.enfcli.2019.07.129 PMid:32204203

Taslim M, Arsunan A, Ishak H, Nasir S, Usman AN. Diversity of dengue virus serotype in endemic region of South Sulawesi Province. J Trop Med. 2018;2018:1-4. https://doi.org/10.1155/2018/9682784

Dinkes Kabupaten Maros. Profil Kesehatan Kabupaten Maros. Maros: Dinas Kesehatan Kabupaten Maros; 2017. https://doi.org/10.31850/jdm.v2i1.359

Rahayu Y, Budi IS, Yeni Y. Analysis of the participation of Jumantik cadres in efforts to combat dengue hemorrhagic fever (DHF) in the work area of indralaya puskesmas. J Ilmu Kesehatan Masyarakat (JIKM). 2017;8(3):200-7. https://doi.org/10.26553/jikm.2017.8.3.200-207

Supriyana S, Saptiwi B, Rimbyastuti H, Warijan W. Establishment of the One House One Jumantik Program in Order to Control Dengue Fever (DF). Link. 2016;12(2):83-5. https://doi.org/10.31983/link.v12i2.1274

Moreira ZD, Setyobudi A, Ndun HJ. The correlation between 3M+ behavior and the incidence of dengue hemorrhagic fever in Kupang city. Lontar J Community Health. 2020;2(1):34-43. https://doi.org/10.35508/ljch.v2i1.2824

Marlinae L, Ulfah N, Mahardika SR, Dewi SL, Rahmayani S, Zubaidah T. Study of environmental management on the event of dengue hemorrhagic fever (DHF) in Banjarbaru city, Kalimantan Selatan. Indian J Public Health Res Dev. 2019;10(12):1867-71. https://doi.org/10.37506/v10/i12/2019/ijphrd/192139

Zaki R, Roffeei SN, Hii YL, Yahya A, Appannan M, Said MA, et al. Public perception and attitude towards dengue prevention activity and response to dengue early warning in Malaysia. PLoS One. 2019;14(2):e0212497. https://doi.org/10.1371/journal.pone.0212497 PMid:30818394

Utama B, Abdullah AZ, Amqam H, Saleh LM, Elisafitri R, Usman AN, et al. The influence of interpersonal communication toward knowledge and attitude prevention of dengue fever (DHF) in the work area of the Meo-Meo public health center in Baubau city. Eur J Mol Clin Med. 2020;7(3):1318-25. https://doi.org/10.37506/ijfmt.v15i1.13529

Lee JS, Carabali M, Lim JK, Herrera VM, Park IY, Villar L, et al. Early warning signal for dengue outbreaks and identification of high risk areas for dengue fever in Colombia using climate and non-climate datasets. BMC Infect Dis. 2017;17(1):480. https://doi.org/10.1186/s12879-017-2577-4

Hasanah N. Health Education in Increasing Prevention Behavior of Dengue Hemorrhagic Fever in Families at Gubeng Village, Surabaya, Indonesia. Indian J Public Health Res Dev. 2019;10(11):1977-81. https://doi.org/10.5958/0976-5506.2019.03845.2

Baequni, Nasir MN, Adhiyanto C. Attitude and preventive behavior of dengue hemorrhagic fever among elementary school students in Jakarta, Indonesia. Asian J Microbiol Biotechnol Environ Sci. 2019;21(4):1028-32.

Rasmanto MF, Sakka A, Ainurafiq A. Prediction model of dengue hemorrhagic fever (DHF) based on climate elements in Kendari city 2000-2015. JIMKESMAS. 2016;1(3):1-14.

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Published

2021-10-11

How to Cite

1.
Salam I, Arsunan Arsin A, Wahyu A, Bintara Birawida A, Syam A, Mallongi A, Palutturi S, Agushybana F, Aisyah A, Yani A, Akbar Nurdin M, Elisafitri R. Modeling Dynamic System for Prediction of Dengue Hemorrhagic Fever in Maros District. Open Access Maced J Med Sci [Internet]. 2021 Oct. 11 [cited 2021 Dec. 4];9(E):901-5. Available from: https://oamjms.eu/index.php/mjms/article/view/7098

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Public Health Epidemiology

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