COVID-19 BÜYÜK SALGIN DALGASININ İSTATİSTİKSEL YAZILIM YOLUYLA MODELLENMESİ: NİCELİKSEL RİSK DEĞERLENDİRMESİ VE TANIMLAMA ANALİZİ

Year 2022, Volume: 7 Issue: 1, 145 - 161, 31.01.2022

Mostafa Eissa

https://doi.org/10.35232/estudamhsd.1024129

Cited By: 3

Abstract

COVID-19 küresel salgını, son zamanlarda halk sağlığı kriterlerine dayalı etkili bir tehlike indeksi arayışını teşvik etti. Buradaki çalışma, bir ada ülkesindeki seçilmiş salgın vakaları üzerinden sağlık tehlikesi tahmini ve risk analizi için kantitatif teknikleri tartışmaktadır. Vaka araştırması, vakaların ve ölüm paternlerinin kronolojik şekilde görsel olarak izlenmesine ek olarak tanımlayıcı analiz, kontrol grafikleri, Pareto grafikleri, veri modeleme gibi istatistiksel süreç metodolojilerinin bir kombinasyonunu içerir. Trend grafikleri, salgın atağının iki dalga şeklinde olduğunu gösterdi: ilk büyük ve keskin tepe noktası, ardından başka bir minor relaps meydana gelmeden önce düşük seviyeli bir dalga. Morbidite oranı, hastalığın toplam ülke nüfusunun yaklaşık %0,02'lik katkısıyla düşüktü. Dönüştürülmüş enfeksiyon vakaları sayısının dağılımı, ana dalgada Gauss dağılımını takip ederken ölüm sayısı, normal dağılımdan çarpıklık ve basıklık değerlerinin önemli ölçüde kaymasının gösterilmesiyle verilerin normal yayılım belirtilerini gösteremedi. Bununla birlikte, çalışma süresi boyunca bireysel vaka ve ölüm sayılarının genel dağılımı, sıfırın alt değeriyle sınırlı, kesikli bir dağılım göstermiştir. Büyük dalganın kümülatif vakalar ve ölümler olarak matematiksel açıklaması, Richards modelini iyi bir regresyonla izledi (r>0,996). Yerleşik analiz, salgınların incelenmesi için tıp alanında değerli olabilecek basit, ucuz istatistiksel programlar kullanılarak ölüm/hastalığa dayalı pandemi etkisinin hızlı nicel değerlendirmesi için bir kilometre taşı görevi görmektedir.

Keywords

Kontrol grafikleri, COVID-19, morbidite/mortalite, Yeni Zelanda, Pareto grafiği, Richard modeli

MODELING OF COVID-19 MAJOR OUTBREAK WAVE THROUGH STATISTICAL SOFTWARE: QUANTITATIVE RISK EVALUATION AND DESCRIPTION ANALYSIS

Abstract

The recent COVID-19 global pandemic has stimulated a search for an effective hazard index based on public health criteria. The study herein is discussing quantitative techniques for health hazard estimation and analysis of risk through selected epidemic cases in an island country. The case investigation comprises a combination of unique statistical process methodologies of descriptive analysis, control charts, Pareto charts, data modeling, in addition to the visual monitoring of cases and death patterns chronologically. Trending charts showed that the outbreak attack takes the form of two waves: the first major and sharp peak followed by a low noise level before another minor relapse occurs. The morbidity rate was low with the contribution of illness from the total country population of approximately 0.02%. While the dispersion of the number of evolved cases of infection followed Gaussian distribution in the major wave, the mortality number failed to show signs of normal spreading of data indicated by significant drifting of skewness and kurtosis values from the normal distribution. However, the overall dispersion of the individual counts of cases and deaths during the period of the study demonstrated truncated distribution limited by the lower value of zero. Mathematical description of the major wave as cumulative cases and deaths followed the Richards model with good regression (r>0.996). The established analysis serves as a milestone for swift quantitative assessment of the pandemic impact based on mortality/morbidity using simple inexpensive statistical programs which would be valuable in the medical field for the study of outbreaks.

Keywords

Control chart, COVID-19, morbidity/mortality, New Zealand, Pareto diagram, Richard Model

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