Predicting epidemic diseases using mathematical modelling of SIR

Epidemic diseases such as Tuberculosis (TB), AIDS (Acquired Immune Deficiency Syndrome) and CCHF (Crimean-Congo Hemorrhagic Fever) remain as a major global health problem. For example, in 2012, an estimated 8.6 million people developed TB and 1.3 million died from the disease reported by WHO (including 320 000 deaths among HIV (human immunodeficiency virus) positive people) in the world. However, the presence of immunodeficiency such as in HIV positive cases helps TB to occur and to be contagious. Hence, to decrease the number of patients with TB lessens the socioeconomical burden, and, to prevent the people from TB as well as TB/HIV and MDR-TB (multi-drug-resistant tuberculosis) are of importance. Taking appropriate precautions in fighting epidemic diseases begins primarily with making predictions. In this respect, although the diagnosis and cure are known for some epidemic diseases, it is evident that a fighting program must depend on predictable cases. Therefore an investigation on an epidemic disease in framework of the mathematical modelling is indispensable and can potentially lead to better ways to analyze, forecast, and prevent epidemics. In this study, to help with all these concerns, we aimed to predict the effects of epidemic of TB including HIV positive patients, as well as of AIDS and CCHF in terms of number of infected people in Turkey by using the mathematical modelling of SIR. Here, we showed that SIR (susceptible-infected-recovered) Model can be used for such epidemic diseases.

Yazar Ergen K.
Çilli A.
Yahnioglu N.
Yayın Türü Conference Object
Tek Biçim Adres https://hdl.handle.net/20.500.12628/7101
Tek Biçim Adres 10.12693/APhysPolA.128.B-273
Koleksiyonlar Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed | SOBİAD
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Dergi Adı Acta Physica Polonica A
Dergi Cilt Bilgisi 128
Dergi Sayısı 2
Sayfalar 273 - 275
Yayın Yılı 2015
Eser Adı
[dc.title]
Predicting epidemic diseases using mathematical modelling of SIR
Yayıncı
[dc.publisher]
Polish Academy of Sciences
Yayın Türü
[dc.type]
conferenceObject
Özet
[dc.description.abstract]
Epidemic diseases such as Tuberculosis (TB), AIDS (Acquired Immune Deficiency Syndrome) and CCHF (Crimean-Congo Hemorrhagic Fever) remain as a major global health problem. For example, in 2012, an estimated 8.6 million people developed TB and 1.3 million died from the disease reported by WHO (including 320 000 deaths among HIV (human immunodeficiency virus) positive people) in the world. However, the presence of immunodeficiency such as in HIV positive cases helps TB to occur and to be contagious. Hence, to decrease the number of patients with TB lessens the socioeconomical burden, and, to prevent the people from TB as well as TB/HIV and MDR-TB (multi-drug-resistant tuberculosis) are of importance. Taking appropriate precautions in fighting epidemic diseases begins primarily with making predictions. In this respect, although the diagnosis and cure are known for some epidemic diseases, it is evident that a fighting program must depend on predictable cases. Therefore an investigation on an epidemic disease in framework of the mathematical modelling is indispensable and can potentially lead to better ways to analyze, forecast, and prevent epidemics. In this study, to help with all these concerns, we aimed to predict the effects of epidemic of TB including HIV positive patients, as well as of AIDS and CCHF in terms of number of infected people in Turkey by using the mathematical modelling of SIR. Here, we showed that SIR (susceptible-infected-recovered) Model can be used for such epidemic diseases.
Kayıt Giriş Tarihi
[dc.date.accessioned]
2019-12-23
Açık Erişim Tarihi
[dc.date.available]
2019-12-23
Yayın Yılı
[dc.date.issued]
2015
Tek Biçim Adres
[dc.identifier.uri]
https://dx.doi.org/10.12693/APhysPolA.128.B-273
Tek Biçim Adres
[dc.identifier.uri]
https://hdl.handle.net/20.500.12628/7101
Yayın Dili
[dc.language.iso]
eng
Yazar
[dc.contributor.author]
Ergen K.
Yazar
[dc.contributor.author]
Çilli A.
Yazar
[dc.contributor.author]
Yahnioglu N.
Haklar
[dc.rights]
info:eu-repo/semantics/openAccess
ISSN
[dc.identifier.issn]
0587-4246
Yazar Departmanı
[dc.contributor.department]
Zonguldak Bülent Ecevit Üniversitesi
İlk Sayfa Sayısı
[dc.identifier.startpage]
273
Son Sayfa Sayısı
[dc.identifier.endpage]
275
Dergi Adı
[dc.relation.journal]
Acta Physica Polonica A
Dergi Sayısı
[dc.identifier.issue]
2
Dergi Cilt Bilgisi
[dc.identifier.volume]
128
Görüntülenme Sayısı ( Şehir )
Görüntülenme Sayısı ( Ülke )
Görüntülenme Sayısı ( Zaman Dağılımı )
Görüntülenme
80
09.12.2022 tarihinden bu yana
İndirme
1
09.12.2022 tarihinden bu yana
Son Erişim Tarihi
06 Haziran 2024 01:22
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Tıklayınız
epidemic diseases people positive number disease million patients modelling prevent fighting mathematical immunodeficiency Epidemic program evident diagnosis although respect depend predictable concerns (susceptible-infected-recovered) showed Turkey infected including effects predict Therefore epidemics forecast analyze better making
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