Araştırma Makalesi
HİNDİSTAN’DAKİ SARS-COV-2 PREVALANSI VE 2020 YILINDAKİ COVID19 PANDEMİSİYLE İLİŞKİLİ EPİDEMİYOLOJİK ÖZELLİKLERİN BELİRLENMESİ
Öz
Amaç: SARS-CoV-2, COVID-19 pandemisini tetiklemektedir. Çalışmamızda Hindistan eyaletleri ve yakın bölgelerinde COVID-19 hastalığının yükünün izlenmesi, epidemiyolojik özelliklerinin incelenmesi ve COVID-19 hastalığının pandemi yükü açısından Hindistan’ın eşdeğer nüfus büyüklüğüne sahip diğer dünya ülkeleri ile karşılaştırılması amaçlanmıştır.
Gereç ve Yöntemler: 31 Aralık 2020 tarihine kadar bildirilen tüm COVID pozitif vakaları üzerinde nüfus temelli karşılaştırmalı optimizasyon algoritmaları çalışması gerçekleştirilmiştir.
Bulgular: Doğrulanmış vakalar, Hindistan’da dünyanın geri kalanına göre 1:7,2 oranıyla sonuçlanırken, 1:12 oranıyla (100.000 kişi başına CMR) diğer ülkelere göre daha düşük bir ölüm oranı tespit edilmiştir. Hindistan’ın birçok idari bölgesinde, ekonomik durumu iyi ülkelerden daha düşük hastalık oranları (Z-değerleri -2653.7369 ile -11,6403 arasında değişmektedir) ve ölüm oranlarının (Z-değerleri -439.446 ile -4,86 arasında değişmektedir) olduğu görülmüştür. Hindistan’da 184.728.001 test yapıldığı, vakaların %5,6’sının COVID-19 tanısı yönünden doğrulandığı, %96,1’inin iyileştiği ve %1,4’ünün ise COVID-19 nedeniyle öldüğü tespit edilmiştir. COVID-19 erkeklerde ve 25-44 yaş arası hastalarda daha yaygın görülürken, SARSCoV- 2’nin ölüm oranlarının 60 yaş üstü kişilerde en yüksek olduğu saptanmıştır. En çok enfeksiyon vakasının Bihar’da, en çok ölümün ise Punjap’da olduğu bulunmuştur.
Sonuç: SARS-CoV-2 hastalığı Hindistan’da dünyanın geri kalanından daha düşük bir morbidite ve mortalite yüküne yol açmıştır. COVID-19’un pandemi eğrileri en net şekilde günlük piklerle sonuçlanmış ve kümülatif vaka sayısı yükseliş eğilimiyle muazzam bir artış göstermiştir. İklim değişikliğinin etkisi ve ortaya çıkan koronavirüsün epidemiyolojik özellikleriyle korele olan indikatörleri anlamak için analitik, mekânsal ve zamansal araştırma çalışmaları yürütülecektir.
Anahtar Kelimeler
Kaynakça
- Syed A. Coronavirus: a mini-review. Int J Curr Res Med Sci 2020;6(1):8-10. google scholar
- Proenca-Modena JP, Acrani GO, Srinder CB, Arruda E. Respiratory Viral Infections. 3rd ed. Tropical Infectious Diseases: Principles, Pathogens and Practice; 2011.p.379-91. google scholar
- Heesterbeek H, Anderson RM, Andreasen V, Bansal S, Angelis DD, Dye C, et al. Modeling infectious disease dynamics in the complex landscape of global health. Science 2015;347(6227):aaa4339. google scholar
- Bogoch II, Watts A, Thomas-Bachli A, Huber C, Kraemer MUG, Khan K. Pneumonia of unknown aetiology in Wuhan, China: potential for international spread via commercial air travel. J Travel Med 2020;27(2):taaa008. google scholar
- Wang C, Hornby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet 2020;395(10223):470-3. google scholar
- World Health Organization (WHO). Naming the coronavirus disease (COVID-19) and the virus that causes it. Geneva: WHO 2020. google scholar
- Anonymous. Coronavirus-Wikipedia. https://en.wikipedia.org/wiki/ Coronavirus. google scholar
- Paules CI, Marston HD, Fauci AS. Coronavirus infection—more than just the common cold. JAMA 2020;323(8):707-8. google scholar
- Gorbalenya AE, Baker SC, Baric RS, Groot RJD, Drosten C, Gulyaeva AA, et al. The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbio 2020;5(4):536-44. google scholar
- Cohen J, Mining coronavirus genomes for clues to the outbreak’s origins. 2020. https://www.sciencemag.org/news/2020/01/miningcoronavirus- genomes-clues-outbreak-s-origins. google scholar
- Reid D. India confirms its first coronavirus case. CNBC 2020. https:// www.cnbc.com/2020/01/30/india-confirms-first-case-of-the coronavirus.html. google scholar
- Yadav PD, Potdar VA, Choudhary ML, Nyayanit DA, Agrawal M, Jadhav SM, et al. Full-genome sequences of the first two SARS-CoV-2 viruses from India. Indian J Med Res 2020;151(2&3):200-9 google scholar
- World Health Organization. Novel Coronavirus (2019-nCoV) Situation Report-11. https://www.who.int/docs/default-source/coronaviruse/ situation-reports/20200131-sitrep-11-ncov.pdf?sfvrsn=de7c0f7_4. google scholar
- Centers for Disease Control and Prevention (CDC). Coronavirus Disease 2019 (COVID-19): Symptoms of Coronavirus. CDC 2020. https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/ symptoms.html. google scholar
- Guo YR, Cao QD, Hong Z, Tan YY, Chen SD, Jin HJ, et al. The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak - an update on the status. Mil Med Res 2020;7(1):11. google scholar
- Zou L, Ruan F, Huang M, Liang L, Huang H, Hong Z, et al. SARS-CoV-2 viral load in upper respiratory specimens of infected patients. N Engl J Med 2020;382(12) :1177-9 google scholar
- Tucker JD, Day S, Tang W, Bayus B. Crowdsourcing in medical research: concepts and applications. Peer J 2019;7:e6762. google scholar
- Bai Y, Yao L, Wei T, Tian F, Jin DY, Chen L, Wang M. Presumed asymptomatic carrier transmission of COVID-19. JAMA 2020;323(14):1406-7. google scholar
- Morse SS. Pandemic influenza: studying the lessons of history. Proc Natl Acad Sci USA 2007;104(18):7313-4 google scholar
- Abraham R. Why does India have so few COVID-19 cases and deaths? IDFC Institute 2020. http://www.idfcinstitute.org/knowledge/ publications/op-eds/why-does-india-have-so-few-covid-19-casesand- deaths/. google scholar
- Anonymous. Is India running too few coronavirus tests? The Hindu business line, New Delhi; India 17.03.2020. https://www. thehindubusinessline.com/news/national/is-india-running-too-fewcoronavirus- tests/article31074309.ece. google scholar
- Battegay M, Kuehl R, Tschudin-Sutter S, Hirsch HH, Widmer AF, Neher RA. 2019-Novel coronavirus (2019-nCoV): estimating the case fatality rate: a word of caution. Swiss Med Wkly 2020;150:w20203. google scholar
- Anonymous. What Explains India’s Low COVID-19 Death Rate. Fit Connect, 04.05.2020. https://fit.thequint.com/coronavirus/ explained-indias-low-covid-19-fatality-rate. google scholar
- Editorial. India under COVID-19 lockdown. Lancet 2020;395(10233):1315. google scholar
- Miller A, Reandelar MJ, Fasciglione K, Roumenova V, Li Y, Otazu GH. Correlation between universal BCG vaccination policy and reduced morbidity and mortality for COVID-19: an epidemiological study. MedRxiv 2020. doi: https://doi.org/10.1101/2020.03.24.20042937. google scholar
- Anonymous. Coronavirus | Preventive drug for healthcare workers cleared. The Hindu. New Delhi. 24.03.2020. https://www.thehindu. com/sci-tech/health/coronavirus-icmr-prescribes-anti-malarialdrug- for-high-risk-covid-19-cases/article31142391.ece. google scholar
- Anonymous. In India, most deaths go unregistered. How reliable is its COVID-19 mortality data? Scroll. in. 16.06.2020. https://scroll.in/ article/961081/in-india-most-deaths-go-unregistered-how-reliableis- its-covid-19-mortality-data. google scholar
- Anonymous. Report on medical certification of cause of death 2017. Office of the registrar general, India. Government of India, Ministry of home affairs 2017. https://censusindia.gov.in/2011-Documents/mccd_Report1/MCCD_Report-2017.pdf. google scholar
- Rocklov J, Sjodin H, Wilder-Smith A. COVID-19 outbreak on the Diamond Princess cruise ship: estimating the epidemic potential and effectiveness of public health countermeasures. J Trave Med 2020;18(27)(3):taaa 030. google scholar
- Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395(10223):497-506. google scholar
- Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382(18):1708-20. google scholar
- Wit ED, Doremalen NV, Falzarano D, Munster VJ. SARS and MERS: recent insights into emerging coronaviruses. Na. Rev Microbio 2016;14(8):523-34. google scholar
- Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) Outbreak in China: Summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention. JAMA 2020;323(13):1239-42. google scholar
- Sue K. The science behind “man flu”. BMJ 2017;359:j5560. google scholar
- Schurz H, Salie M, Tromp G, Hoal EG, Kinnearet CJ, Moller M. The X chromosome and sex-specific effects in infectious disease susceptibility. Hum Genomics 2019;13(1):2. google scholar
- Voor A. Men’s blood contains greater concentrations of enzyme that helps COVID-19 infect cells. European Society of Cardiology 2020. https://www.sciencedaily.com/releases/2020/05/200510193241. htm. google scholar
- Harris CR, Jenkins M, Glader D. Gender differences in risk assessment: Why do women take fewer risks than men? Judgm Decis Mak 2006;1(1):48-63. google scholar
- Lv J, Ren ZY, Zhang YY. Study on age-dependent pre-existing 2009 pandemic influenza virus T and B cell responses from Chinese population. BMC Infect Dis 2017;17(1):136. google scholar
- Greenbaum AH, Chen J, Reed C, Beavers S, Callahan D, Christensen D, et al. Hospitalizations for severe lower respiratory tract infections. Pediatrics 2014;134(3):546-54 google scholar
- Yi Y, Lagniton PNP, Ye S, Li E, Xu RH. COVID-19: what has been learned and to be learned about the novel coronavirus disease. Int J Biol Sci 2020;16(10):1753-66. google scholar
- Arino J, Bauch C, Brauer F, Driedger SM, Greer AL, Moghadas SM, et al. Pandemic influenza modeling and public health perspectives. Math Biosci Eng 2011;8(1):1-20. google scholar
- Royal Society. Infectious diseases in livestock, 2002. The Royal Society policy document 19/02. www.royalsoc.ac.uk. google scholar
- Ray D, Salvatore M, Bhattacharyya R, Wang L, Du J, Mohammed S, et al. Predictions, role of interventions, and effects of a historic national lockdown in India’s response to the COVID-19 pandemic: Data Science Call to Arms. Harv Data Sci Rev 2020;2020(Suppl 1):10.1162/99608f92.60e08ed5. google scholar
- Anonymous. Covid-19: Omicron’s XBB variant emerges as dominant in India. The India Post, India 31.10.2022. Covid-19: Omicron’s XBB variant emerges as dominant in India, TN tops, India Post News Paper. google scholar
SARS-COV-2 PREVALENCE IN INDIA COMPARED TO THE REST OF THE GLOBE AND ASCERTAINS EPIDEMIOLOGICAL CHARACTERISTICS ASSOCIATED WITH THE COVID-19 PANDEMIC DURING 2020 IN INDIA
Öz
Objectives: SARS-CoV-2 triggers a pandemic of COVID-19. We ascertain the pandemic burden of COVID-19 disease between India and the rest of the world; monitor the burden of COVID-19 disease in Indian states and union territories compared to other countries with nearly equivalent population sizes, and study the epidemiological characteristics.
Material and Methods: A population-based comparative optimization algorithms study was conducted on all COVID positive cases reported by 31st December 2020.
Results: Confirmed cases resulted in India with a ratio of 1:7.2 to the rest of the world, with a lower mortality rate with a ratio of 1:12 (CMR per 100,000 people) than other countries. Many Indian administrative regions have lower morbidity rates (Z-values range from -2653.7369 to -11.6403) and mortality (Z-values range from -439.446 to -4.86) than the countries selected. In India, 184,728,001 tests were done, with 5.6% cases confirmed, 96.1% recovered, and 1.4% dying due to COVID-19. COVID-19 was more prevalent in males and patients aged 25–44, whereas SARSCoV- n2 killed the most people over the age of 60. Bihar had the most cases of infection, while Punjab had the most deaths.
Conclusion: SARS-CoV-2 disease led India to have a lower morbidity and mortality burden than the rest of the world. The pandemic curves of COVID-19 resulted in daily peaks most significantly, and the cumulativennumber of cases increased tremendously with an upward trend. Analytical, spatial, and temporal research studies will be carried out to understand the effect of climate change and indicators that correlate with the epidemiological characteristics of the emerging coronavirus.
Anahtar Kelimeler
Kaynakça
- Syed A. Coronavirus: a mini-review. Int J Curr Res Med Sci 2020;6(1):8-10. google scholar
- Proenca-Modena JP, Acrani GO, Srinder CB, Arruda E. Respiratory Viral Infections. 3rd ed. Tropical Infectious Diseases: Principles, Pathogens and Practice; 2011.p.379-91. google scholar
- Heesterbeek H, Anderson RM, Andreasen V, Bansal S, Angelis DD, Dye C, et al. Modeling infectious disease dynamics in the complex landscape of global health. Science 2015;347(6227):aaa4339. google scholar
- Bogoch II, Watts A, Thomas-Bachli A, Huber C, Kraemer MUG, Khan K. Pneumonia of unknown aetiology in Wuhan, China: potential for international spread via commercial air travel. J Travel Med 2020;27(2):taaa008. google scholar
- Wang C, Hornby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet 2020;395(10223):470-3. google scholar
- World Health Organization (WHO). Naming the coronavirus disease (COVID-19) and the virus that causes it. Geneva: WHO 2020. google scholar
- Anonymous. Coronavirus-Wikipedia. https://en.wikipedia.org/wiki/ Coronavirus. google scholar
- Paules CI, Marston HD, Fauci AS. Coronavirus infection—more than just the common cold. JAMA 2020;323(8):707-8. google scholar
- Gorbalenya AE, Baker SC, Baric RS, Groot RJD, Drosten C, Gulyaeva AA, et al. The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbio 2020;5(4):536-44. google scholar
- Cohen J, Mining coronavirus genomes for clues to the outbreak’s origins. 2020. https://www.sciencemag.org/news/2020/01/miningcoronavirus- genomes-clues-outbreak-s-origins. google scholar
- Reid D. India confirms its first coronavirus case. CNBC 2020. https:// www.cnbc.com/2020/01/30/india-confirms-first-case-of-the coronavirus.html. google scholar
- Yadav PD, Potdar VA, Choudhary ML, Nyayanit DA, Agrawal M, Jadhav SM, et al. Full-genome sequences of the first two SARS-CoV-2 viruses from India. Indian J Med Res 2020;151(2&3):200-9 google scholar
- World Health Organization. Novel Coronavirus (2019-nCoV) Situation Report-11. https://www.who.int/docs/default-source/coronaviruse/ situation-reports/20200131-sitrep-11-ncov.pdf?sfvrsn=de7c0f7_4. google scholar
- Centers for Disease Control and Prevention (CDC). Coronavirus Disease 2019 (COVID-19): Symptoms of Coronavirus. CDC 2020. https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/ symptoms.html. google scholar
- Guo YR, Cao QD, Hong Z, Tan YY, Chen SD, Jin HJ, et al. The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak - an update on the status. Mil Med Res 2020;7(1):11. google scholar
- Zou L, Ruan F, Huang M, Liang L, Huang H, Hong Z, et al. SARS-CoV-2 viral load in upper respiratory specimens of infected patients. N Engl J Med 2020;382(12) :1177-9 google scholar
- Tucker JD, Day S, Tang W, Bayus B. Crowdsourcing in medical research: concepts and applications. Peer J 2019;7:e6762. google scholar
- Bai Y, Yao L, Wei T, Tian F, Jin DY, Chen L, Wang M. Presumed asymptomatic carrier transmission of COVID-19. JAMA 2020;323(14):1406-7. google scholar
- Morse SS. Pandemic influenza: studying the lessons of history. Proc Natl Acad Sci USA 2007;104(18):7313-4 google scholar
- Abraham R. Why does India have so few COVID-19 cases and deaths? IDFC Institute 2020. http://www.idfcinstitute.org/knowledge/ publications/op-eds/why-does-india-have-so-few-covid-19-casesand- deaths/. google scholar
- Anonymous. Is India running too few coronavirus tests? The Hindu business line, New Delhi; India 17.03.2020. https://www. thehindubusinessline.com/news/national/is-india-running-too-fewcoronavirus- tests/article31074309.ece. google scholar
- Battegay M, Kuehl R, Tschudin-Sutter S, Hirsch HH, Widmer AF, Neher RA. 2019-Novel coronavirus (2019-nCoV): estimating the case fatality rate: a word of caution. Swiss Med Wkly 2020;150:w20203. google scholar
- Anonymous. What Explains India’s Low COVID-19 Death Rate. Fit Connect, 04.05.2020. https://fit.thequint.com/coronavirus/ explained-indias-low-covid-19-fatality-rate. google scholar
- Editorial. India under COVID-19 lockdown. Lancet 2020;395(10233):1315. google scholar
- Miller A, Reandelar MJ, Fasciglione K, Roumenova V, Li Y, Otazu GH. Correlation between universal BCG vaccination policy and reduced morbidity and mortality for COVID-19: an epidemiological study. MedRxiv 2020. doi: https://doi.org/10.1101/2020.03.24.20042937. google scholar
- Anonymous. Coronavirus | Preventive drug for healthcare workers cleared. The Hindu. New Delhi. 24.03.2020. https://www.thehindu. com/sci-tech/health/coronavirus-icmr-prescribes-anti-malarialdrug- for-high-risk-covid-19-cases/article31142391.ece. google scholar
- Anonymous. In India, most deaths go unregistered. How reliable is its COVID-19 mortality data? Scroll. in. 16.06.2020. https://scroll.in/ article/961081/in-india-most-deaths-go-unregistered-how-reliableis- its-covid-19-mortality-data. google scholar
- Anonymous. Report on medical certification of cause of death 2017. Office of the registrar general, India. Government of India, Ministry of home affairs 2017. https://censusindia.gov.in/2011-Documents/mccd_Report1/MCCD_Report-2017.pdf. google scholar
- Rocklov J, Sjodin H, Wilder-Smith A. COVID-19 outbreak on the Diamond Princess cruise ship: estimating the epidemic potential and effectiveness of public health countermeasures. J Trave Med 2020;18(27)(3):taaa 030. google scholar
- Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395(10223):497-506. google scholar
- Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382(18):1708-20. google scholar
- Wit ED, Doremalen NV, Falzarano D, Munster VJ. SARS and MERS: recent insights into emerging coronaviruses. Na. Rev Microbio 2016;14(8):523-34. google scholar
- Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) Outbreak in China: Summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention. JAMA 2020;323(13):1239-42. google scholar
- Sue K. The science behind “man flu”. BMJ 2017;359:j5560. google scholar
- Schurz H, Salie M, Tromp G, Hoal EG, Kinnearet CJ, Moller M. The X chromosome and sex-specific effects in infectious disease susceptibility. Hum Genomics 2019;13(1):2. google scholar
- Voor A. Men’s blood contains greater concentrations of enzyme that helps COVID-19 infect cells. European Society of Cardiology 2020. https://www.sciencedaily.com/releases/2020/05/200510193241. htm. google scholar
- Harris CR, Jenkins M, Glader D. Gender differences in risk assessment: Why do women take fewer risks than men? Judgm Decis Mak 2006;1(1):48-63. google scholar
- Lv J, Ren ZY, Zhang YY. Study on age-dependent pre-existing 2009 pandemic influenza virus T and B cell responses from Chinese population. BMC Infect Dis 2017;17(1):136. google scholar
- Greenbaum AH, Chen J, Reed C, Beavers S, Callahan D, Christensen D, et al. Hospitalizations for severe lower respiratory tract infections. Pediatrics 2014;134(3):546-54 google scholar
- Yi Y, Lagniton PNP, Ye S, Li E, Xu RH. COVID-19: what has been learned and to be learned about the novel coronavirus disease. Int J Biol Sci 2020;16(10):1753-66. google scholar
- Arino J, Bauch C, Brauer F, Driedger SM, Greer AL, Moghadas SM, et al. Pandemic influenza modeling and public health perspectives. Math Biosci Eng 2011;8(1):1-20. google scholar
- Royal Society. Infectious diseases in livestock, 2002. The Royal Society policy document 19/02. www.royalsoc.ac.uk. google scholar
- Ray D, Salvatore M, Bhattacharyya R, Wang L, Du J, Mohammed S, et al. Predictions, role of interventions, and effects of a historic national lockdown in India’s response to the COVID-19 pandemic: Data Science Call to Arms. Harv Data Sci Rev 2020;2020(Suppl 1):10.1162/99608f92.60e08ed5. google scholar
- Anonymous. Covid-19: Omicron’s XBB variant emerges as dominant in India. The India Post, India 31.10.2022. Covid-19: Omicron’s XBB variant emerges as dominant in India, TN tops, India Post News Paper. google scholar
Toplam 44 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Klinik Tıp Bilimleri (Diğer) |
| Bölüm | Araştırma Makaleleri |
| Yazarlar | |
| Yayımlanma Tarihi | 24 Ekim 2023 |
| Gönderilme Tarihi | 8 Mayıs 2023 |
| Yayımlandığı Sayı | Yıl 2023 Cilt: 6 Sayı: 3 |
