Öz
Infectious diseases such as measles, morbillivirus, influenza, AIDS have caused millions of infecteds and deaths, great workforce lost and economical cost since the beginning of civilization. The spread dynamics of bacteria and viruses that cause infectious diseases through a population is carefully analysed to be able to effectively use intervention methods such as vaccination, quarantine, medicine, and etc. while considering scarce resources and costs. SIR (Susceptable-Infected-Recovered) compartmental model has been used to model spread dynamics of infectious diseases through a population, to predict total number of infected and death people and to calculate economical cost of diseases for roughly a century. In this study, we develop a software, YAYsim, coded in Python programming language, to be able to help decision makers and interested users to analyse results of an epidemic or pandemic by allowing them to change disease parameters as attack rates, recovery periods, the number of infected people at the beginning. YAYsim includes demografic information of each city in Turkey. Thus, it enables users to see how a pandemic affects on a selected city and to be able to decide based on their working area according to the results. Finally, an example study is carried out to estimate and evaluate rates of infected and death people during a possible H1N1 pandemic in Gaziantep city. It is observed that 35.8% of Gaziantep’s population are affected from the disease and 0.7% of them are death based on the disease parameters of 1918 Spanish Flu.
Anahtar Kelimeler
Kaynakça
- Editorial (2018). How to be ready for the next influenza pandemic. Lancet Infect. Dis., 18(7), 697.
- Hawkey, S. (2019). Overview of ebola virus disease. WHO, https://www.who.int/health-topics/ebola/#tab=tab_1, (01/01/2020).
- Özkaya, H. (2016). Fight against contagious diseases during the period of the republic. Türkiye Aile Hekim. Derg., 20(2), 77–84.
- Kermack, W. O. and McKendrick, A. G. (1927). A Contribution to the Mathematical Theory of Epidemics. Proc. R. Soc. A Math. Phys. Eng. Sci., 115(772), 700–721.
- Walters, C. E., Meslé, M. M. I. and Hall, I. M. (2018). Modelling the global spread of diseases: A review of current practice and capability. Epidemics, 25, 1–8.
- Prieto, D. M., Das, T. K., Savachkin, A. A., Uribe, A., Izurieta, R., and Malavade, S. (2012). A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels,” BMC Public Health, 12(1), 251.
- Chao, D.L., Halloran, M.E., Obenchain, V.J. and Longini Jr, I.M., (2010). FluTE, a publicly available stochastic influenza epidemic simulation model. PLoS computational biology, 6(1), 1–8.
- Hladish, T., Melamud, E., Barrera, L.A., Galvani, A. and Meyers, L.A., (2012). EpiFire: An open source C++ library and application for contact network epidemiology. BMC bioinformatics, 13(1), 76.
- Liu, S., Poccia, S., Candan, K.S., Chowell, G. and Sapino, M.L., (2016). epiDMS: data management and analytics for decision-making from epidemic spread simulation ensembles. The Journal of infectious diseases, 214, 427-432.
- Edlund, S.B., Davis, M.A. and Kaufman, J.H., (2010). The spatiotemporal epidemiological modeler. In Proceedings of the 1st ACM International Health Informatics Symposium, November, 817-820.
- Grefenstette, J.J., Brown, S.T., Rosenfeld, R., DePasse, J., Stone, N.T., Cooley, P.C., Wheaton, W.D., Fyshe, A., Galloway, D.D., Sriram, A. and Guclu, H., (2013). FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations. BMC public health, 13 (1), 940.
- Kuylen, E., Stijven, S., Broeckhove, J. and Willem, L., (2017). Social Contact Patterns in an Individual-based Simulator for the Transmission of Infectious Diseases (Stride). In ICCS, January, 2438-2442.
- Ramírez-Ramírez, L.L., Gel, Y.R., Thompson, M., de Villa, E. and McPherson, M., (2013). A new surveillance and spatio-temporal visualization tool SIMID: SIMulation of Infectious Diseases using random networks and GIS. Computer methods and programs in biomedicine, 110(3), 455-470.
- Hethcote, H.W., (2000). The mathematics of infectious diseases. SIAM review, 42(4), 599-653.
- Zaric, G.S. and Brandeau, M.L., (2001). Resource allocation for epidemic control over short time horizons. Mathematical Biosciences, 171(1), 33-58.
- Medlock, J. and Galvani, A.P., (2009). Optimizing influenza vaccine distribution. Science, 325(5948), 1705-1708.
- Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G.S., Wallinga, J. and Heijne, J., (2008). Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS medicine, 5(3).
- Glezen, W.P., (1996). Emerging infections: pandemic influenza. Epidemiologic reviews, 18(1), 64-76.
Öz
İnsanlık tarihinin başlangıcından itibaren kızıl, kızamık, grip, AIDS gibi bulaşıcı hastalıklar milyonlarca insanın hastalanmasına ve ölmesine, büyük iş gücü kayıplarına ve çok yüksek ekonomik maliyetlere sebep olmuştur. Aşı, karantina ve ilaç gibi müdahale yöntemlerinin, kıt kaynaklar ve maliyetler düşünüldüğünde etkili bir şekilde kullanılmaları için bulaşıcı hastalıklara neden olan bakteri ve virüslerin bir topluluk içinde yayılma dinamiklerinin iyi analiz edilmiş olması gerekmektedir. SIR (Susceptable-Infected-Recovered) bölmeli modelleme yöntemi yaklaşık bir asırdır bulaşıcı hastalıkların bir populasyon içinde yayılma dinamiklerinin modellemesinde ve toplam hasta ve ölü sayısının, hastalığın ekonomik boyutlarının tahmininde kullanılmaktadır. Bu makalede, karar vericilerin ve ilgili kullanıcıların, hastalık şiddeti, iyileşme periyodu, başlangıçtaki hasta sayısı gibi salgın parametrelerini değiştirebilmesine izin vererek, salgının sonuçlarını analiz edebilmelerine yardım edecek, python programlama dilinde kodlanan, YAYsim isimli karar destek programı geliştirilmiştir. YAYsim, Türkiye’deki her şehrin nüfus bilgilerini içermektedir. Bu sayede kullanıcıların, seçilmiş bir şehirde yaşanabilecek bir salgının sonuçlarını görebilmelerine ve bu sonuçlara göre çalıştıkları disiplinler çerçevesinde karar verebilmelerine olanak sağlamaktadır. Son olarak Gaziantep ilinde yaşanabilecek olası bir H1N1 salgını sırasında oluşabilecek hasta ve ölü oranlarını tahmin etmek ve değerlendirmek için örnek bir çalışma yapılmıştır. 1918 İspanyol Gribi yayılma parametreleri baz alınarak yapılan modellemede, Gaziantep nüfusunun %35.8’inin hastalıktan etkilendiği ve %0.7’sinin hayatını kaybettiği gözlenmiştir.
Anahtar Kelimeler
Kaynakça
- Editorial (2018). How to be ready for the next influenza pandemic. Lancet Infect. Dis., 18(7), 697.
- Hawkey, S. (2019). Overview of ebola virus disease. WHO, https://www.who.int/health-topics/ebola/#tab=tab_1, (01/01/2020).
- Özkaya, H. (2016). Fight against contagious diseases during the period of the republic. Türkiye Aile Hekim. Derg., 20(2), 77–84.
- Kermack, W. O. and McKendrick, A. G. (1927). A Contribution to the Mathematical Theory of Epidemics. Proc. R. Soc. A Math. Phys. Eng. Sci., 115(772), 700–721.
- Walters, C. E., Meslé, M. M. I. and Hall, I. M. (2018). Modelling the global spread of diseases: A review of current practice and capability. Epidemics, 25, 1–8.
- Prieto, D. M., Das, T. K., Savachkin, A. A., Uribe, A., Izurieta, R., and Malavade, S. (2012). A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels,” BMC Public Health, 12(1), 251.
- Chao, D.L., Halloran, M.E., Obenchain, V.J. and Longini Jr, I.M., (2010). FluTE, a publicly available stochastic influenza epidemic simulation model. PLoS computational biology, 6(1), 1–8.
- Hladish, T., Melamud, E., Barrera, L.A., Galvani, A. and Meyers, L.A., (2012). EpiFire: An open source C++ library and application for contact network epidemiology. BMC bioinformatics, 13(1), 76.
- Liu, S., Poccia, S., Candan, K.S., Chowell, G. and Sapino, M.L., (2016). epiDMS: data management and analytics for decision-making from epidemic spread simulation ensembles. The Journal of infectious diseases, 214, 427-432.
- Edlund, S.B., Davis, M.A. and Kaufman, J.H., (2010). The spatiotemporal epidemiological modeler. In Proceedings of the 1st ACM International Health Informatics Symposium, November, 817-820.
- Grefenstette, J.J., Brown, S.T., Rosenfeld, R., DePasse, J., Stone, N.T., Cooley, P.C., Wheaton, W.D., Fyshe, A., Galloway, D.D., Sriram, A. and Guclu, H., (2013). FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations. BMC public health, 13 (1), 940.
- Kuylen, E., Stijven, S., Broeckhove, J. and Willem, L., (2017). Social Contact Patterns in an Individual-based Simulator for the Transmission of Infectious Diseases (Stride). In ICCS, January, 2438-2442.
- Ramírez-Ramírez, L.L., Gel, Y.R., Thompson, M., de Villa, E. and McPherson, M., (2013). A new surveillance and spatio-temporal visualization tool SIMID: SIMulation of Infectious Diseases using random networks and GIS. Computer methods and programs in biomedicine, 110(3), 455-470.
- Hethcote, H.W., (2000). The mathematics of infectious diseases. SIAM review, 42(4), 599-653.
- Zaric, G.S. and Brandeau, M.L., (2001). Resource allocation for epidemic control over short time horizons. Mathematical Biosciences, 171(1), 33-58.
- Medlock, J. and Galvani, A.P., (2009). Optimizing influenza vaccine distribution. Science, 325(5948), 1705-1708.
- Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G.S., Wallinga, J. and Heijne, J., (2008). Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS medicine, 5(3).
- Glezen, W.P., (1996). Emerging infections: pandemic influenza. Epidemiologic reviews, 18(1), 64-76.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Mühendislik |
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 28 Haziran 2020 |
| Gönderilme Tarihi | 16 Ocak 2020 |
| Kabul Tarihi | 22 Nisan 2020 |
| Yayımlandığı Sayı | Yıl 2020 Cilt: 7 Sayı: 1 |