Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches
<i>Background and Objectives:</i> Coronavirus disease 19 (COVID-19) has emerged as the most devastating syndemic of the 21st century, with worrisome and sustained consequences for the entire society. Despite the relative success of vaccination programs, the global threat of the novel cor...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Medicina |
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| Online Access: | https://www.mdpi.com/1648-9144/58/2/253 |
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| author | Antonio Sarría-Santamera Nurlan Abdukadyrov Natalya Glushkova David Russell Peck Paolo Colet Alua Yeskendir Angel Asúnsolo Miguel A. Ortega |
| author_facet | Antonio Sarría-Santamera Nurlan Abdukadyrov Natalya Glushkova David Russell Peck Paolo Colet Alua Yeskendir Angel Asúnsolo Miguel A. Ortega |
| author_sort | Antonio Sarría-Santamera |
| collection | DOAJ |
| description | <i>Background and Objectives:</i> Coronavirus disease 19 (COVID-19) has emerged as the most devastating syndemic of the 21st century, with worrisome and sustained consequences for the entire society. Despite the relative success of vaccination programs, the global threat of the novel coronavirus SARS-CoV-2 is still present and further efforts are needed for its containment and control. Essential for its control and containment is getting closer to understanding the actual extent of SARS-CoV-2 infections. <i>Material and Methods:</i> We present a model based on the mortality data of Kazakhstan for the estimation of the underlying epidemic dynamic—with both the lag time from infection to death and the infection fatality rate. For the estimation of the actual number of infected individuals in Kazakhstan, we used both back-casting and capture–recapture methods. <i>Results:</i> Our results suggest that despite the increased testing capabilities in Kazakhstan, official case reporting undercounts the number of infections by at least 60%. Even though our count of deaths may be either over or underestimated, our methodology could be a more accurate approach for the following: the estimation of the actual magnitude of the pandemic; aiding the identification of different epidemiological values; and reducing data bias. <i>Conclusions:</i> For optimal epidemiological surveillance and control efforts, our study may lead to an increased awareness of the effect of COVID-19 in this region and globally, and aid in the implementation of more effective screening and diagnostic measures. |
| first_indexed | 2024-03-09T21:29:24Z |
| format | Article |
| id | doaj.art-49720e4dfd894119b52b08ce10b16c47 |
| institution | Directory Open Access Journal |
| issn | 1010-660X 1648-9144 |
| language | English |
| last_indexed | 2024-03-09T21:29:24Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Medicina |
| spelling | doaj.art-49720e4dfd894119b52b08ce10b16c472023-11-23T21:00:26ZengMDPI AGMedicina1010-660X1648-91442022-02-0158225310.3390/medicina58020253Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture ApproachesAntonio Sarría-Santamera0Nurlan Abdukadyrov1Natalya Glushkova2David Russell Peck3Paolo Colet4Alua Yeskendir5Angel Asúnsolo6Miguel A. Ortega7Department of Medicine, School of Medicine, Nazarbayev University, Nur-Sultan 020000, KazakhstanDepartement of Mathematics, Statistics and Computer Sciences, University of Illinois at Chicago, Chicago, IL 60607, USADepartment of Epidemiology, Biostatistics and Evidence-Based Medicine, Al-Farabi Kazakh National University, Almaty 050040, KazakhstanIndependent Researcher, 28410 Madrid, SpainDepartment of Medicine, School of Medicine, Nazarbayev University, Nur-Sultan 020000, KazakhstanDepartment of Medicine, School of Medicine, Nazarbayev University, Nur-Sultan 020000, KazakhstanDepartment of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Alcalá de Henares, 28801 Madrid, SpainRamón y Cajal Institute of Health Research (IRYCIS), 28034 Madrid, Spain<i>Background and Objectives:</i> Coronavirus disease 19 (COVID-19) has emerged as the most devastating syndemic of the 21st century, with worrisome and sustained consequences for the entire society. Despite the relative success of vaccination programs, the global threat of the novel coronavirus SARS-CoV-2 is still present and further efforts are needed for its containment and control. Essential for its control and containment is getting closer to understanding the actual extent of SARS-CoV-2 infections. <i>Material and Methods:</i> We present a model based on the mortality data of Kazakhstan for the estimation of the underlying epidemic dynamic—with both the lag time from infection to death and the infection fatality rate. For the estimation of the actual number of infected individuals in Kazakhstan, we used both back-casting and capture–recapture methods. <i>Results:</i> Our results suggest that despite the increased testing capabilities in Kazakhstan, official case reporting undercounts the number of infections by at least 60%. Even though our count of deaths may be either over or underestimated, our methodology could be a more accurate approach for the following: the estimation of the actual magnitude of the pandemic; aiding the identification of different epidemiological values; and reducing data bias. <i>Conclusions:</i> For optimal epidemiological surveillance and control efforts, our study may lead to an increased awareness of the effect of COVID-19 in this region and globally, and aid in the implementation of more effective screening and diagnostic measures.https://www.mdpi.com/1648-9144/58/2/253COVID-19SARS-CoV-2back-casting approachcapture–recapture method |
| spellingShingle | Antonio Sarría-Santamera Nurlan Abdukadyrov Natalya Glushkova David Russell Peck Paolo Colet Alua Yeskendir Angel Asúnsolo Miguel A. Ortega Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches Medicina COVID-19 SARS-CoV-2 back-casting approach capture–recapture method |
| title | Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches |
| title_full | Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches |
| title_fullStr | Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches |
| title_full_unstemmed | Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches |
| title_short | Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches |
| title_sort | towards an accurate estimation of covid 19 cases in kazakhstan back casting and capture recapture approaches |
| topic | COVID-19 SARS-CoV-2 back-casting approach capture–recapture method |
| url | https://www.mdpi.com/1648-9144/58/2/253 |
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