Kenya has experienced five COVID-19 surges driven by Alpha, Beta, Delta (2x), and Omicron. These waves are accurately
predicted by the OTOI-NARIMA model. Consequently, in Kenyan Lake Region
Economic Bloc (LREB), private sector and NGO partnerships have been forged to
strengthen regional health systems and prepare effectively for epidemic
resurgence. The co-development and implementation of the so-called “LREB COVID-Dx” digital platform enable efficient epidemic monitoring in semi-real time,
referral of patients, optimal use of limited resources, and community of
practice among regional health practitioners. In this paper, we describe the
practical implementation of the OTOI-NARIMA model and COVID-Dx digitized
platform in Kenyan COVID-19 reality, with emphasis on the latest Omicron wave. In
estimating the trajectory of Omicron wave, 612 data points of daily case
infections are used. The order of moving
average is calculated and corresponds to reproduction number, R0. The series are normalized, superimposed, and used to derive OTOI-NARIMA
model. The model is estimated and interpreted. Test statistics including Ljung-Box test, ACF, and PACF are conducted. The
COVID-Dx data digitization is used to
inform epidemic preparedness. The OTOI-NARIMA model in
References
[1]
Orangi, S., et al. (2021) Assessing the Level and Determinants of COVID-19 Vaccine Confidence in Kenya. Vaccines (Basel), 9, 936.
[2]
Petersen, E., et al. (2021) Emergence of New SARS-CoV-2 Variant of Concern Omicron (B.1.1.529)—Highlights Africa’s Research Capabilities, But Exposes Major Knowledge Gaps, Inequities of Vaccine Distribution, Inadequacies in Global COVID-19 Response and Control Efforts. International Journal of Infectious Diseases, 114, 268-272.
[3]
Sam, S.O., Pokhariyal, G.P., Rogo, K. and Ndhine, E.O. (2021) Otoi-NARIMA Model for Forecast Seasonality of COVID-19 Waves: Case of Kenya. International Journal of Statistics and Applied Mathematics, 6, 48-58. https://doi.org/10.22271/maths.2021.v6.i2a.675
[4]
van Duijn, S., et al. (2021) Strengthening Public COVID-19 Response with Private Facilities in Kisumu, Kenya.
[5]
Rae, M. (2020) Omicron: A Failure to Act with a Global Focus Will Continue the Proliferation of New Variants of COVID-19. BMJ, 375, n3095. https://doi.org/10.1136/bmj.n3095
[6]
Christie, B. (2021) COVID-19: Early Studies Give Hope Omicron Is Milder than Other. BMJ, 375, n3144. https://doi.org/10.1136/bmj.n3144
[7]
Bentley, E., Kirby, K., Sharma, P., Kipar, A., et al. (2021) SARS-CoV-2 Omicron-B.1.1.529 Variant Leads to Less Severe Disease than Pango B and Delta Variants Strains in a Mouse Model of Severe COVID-19. https://doi.org/10.1101/2021.12.26.474085
[8]
Jefferson, S., da Silva, R. and Pena, L. (2021) Collapse of the Public Health System and the Emergence of New Variants during the Second Wave of the COVID-19 Pandemic in Brazil. One Health, 13, Article ID: 100287.
[9]
Saha, S., Tanmoy, A.M., et al. (2021) New Waves, New Variants, Old Inequity: A Continuing COVID-19 Crisis. BMJ Global Health, 6, e007031. https://doi.org/10.1136/bmjgh-2021-007031
[10]
Chen, Z.G., Chong, K.C., Ng, R.W.Y., Lai, C.K.C., et al. (2021) A Global Analysis of Replacement of Genetic Variants of SARS-CoV-2 in Association with Containment Capacity and Changes in Disease Severity. Clinical Microbiology and Infection, 27, 750-757. https://doi.org/10.1016/j.cmi.2021.01.018
[11]
Sam, S.O. and Ndhine, E.O. (2020) Prediction and Forecasting COVID-19 Cases, Fatalities, and Morbidity in Kenya. International Journal of Statistics and Applied Mathematics, 5, 249-257.
[12]
Kalpakis, K., Gada, D. and Puttagunta, V. (2001) Distance Measures for Effective Clustering of ARIMA Time-Series. Proceedings 2001 IEEE International Conference on Data Mining, San Jose, 29 November-2 December 2001, 273-280.
[13]
Sam, S.O., Sewe, S., Kimathi, G., Wainaina, M., et al. (2021) Antecedents of Patients COVID-19 Management Outcomes. International Journal of Statistics and Applied Mathematics, 6, 109-117. https://doi.org/10.22271/maths.2021.v6.i5b.730
[14]
Wangari, I.M., et al. (2021) Mathematical Modelling of COVID-19 Transmission in Kenya: A Model with Reinfection Transmission Mechaism. Computational Mathematics in Medicine, 2021, Article ID: 5384481. https://doi.org/10.1155/2021/5384481
[15]
Sam, S.O. (2020) Exploring the Statistical Significance of Africa COVID-19 Data. International Journal of Statistics and Applied Mathematics, 5, 34-42.
