An Estimate of Time-Dependent Transmission of COVID-19 Pandemic in Katsina State from June to November 2021
DOI:
https://doi.org/10.56919/usci.1222.023Keywords:
COVID-19 Transmission, Reproduction Number, Infection, Graphical VisualizationAbstract
This paper investigates the spread of COVID-19 pandemic in Katsina state from 23rd June to 27th November, 2021, using graphical tools to visually analyse infection over time and time-dependent reproduction number to quantify the transmissibility of the disease. Study data consist of diagnostic results of reverse transcriptase real-time quantitative polymerase chain reaction assays (RT-PCR) on nine hundred and eighty-nine nasal swab samples from suspected COVID-19 cases, collected from public and private health facilities across Local government areas of the State and analysed by the Molecular Laboratory of the Federal Medical Centre Katsina, recording a total of 137 positive cases. Our investigation revealed that, over the study period, COVID-19 transmission reaches its peak on 17th October 2021 (Epidemic Week 41), with a mean Reproduction number (Rt) of 3.22 and a standard deviation of 0.5976 (95% CI: 2.6193 - 3.8145), culminating in 19 new infections on Wednesday the 27th (Epidemic Week 43). The combined age groups 21-30 and 31-40 constituted the most affected cases with 29 (21.17%) and 19 (13.87%) positive cases, respectively. This was closely followed by age group 51-60 with 19 (13.87%) positive cases. On gender basis, 70 (51%) females tested positive compared to 67 (49%) males. We therefore conclude that for the third wave of COVID-19 pandemic in Katsina State, disease transmission reaches its peak in Epidemic Week 41 in October, then rapidly diminishes to Rt values of less than one, indicating that no new infections were expected by the end of November, with female gender and age groups in the range 21 to 40 years being most infected. We recommend that mitigation strategies that take into consideration features inherent in female gender and more pronounced in young (21 to 40 years) and middle-aged (51-60 years) adults should be adopted in case of future waves.
References
Adeyemi, O. O., Ndodo, N. D., Sulaiman, M. K., Et Al. (2023): SARS-COV-2 Variants-Associated Outbreaks Of COVID-19 In A Tertiary Institution , Nort-Central Nigeria, : Implications For Epidemic Control. PLOS ONE, 18(1), E0280756 [Crossref]
https://doi.org/10.1371/journal.pone.0280756
Aryana, I. G. P. S., Setiati, S., Mulyana, R., Et Al. (2023): Indonesian Geriatrics Society Consensus On COVID-19 Management In Older Adults. Acta Med. Indones - Indones. J. Intern. Med., Vol. 55, No. 1, Pp. 118-131.
Badmus, N. I., Faweya, O. And Ige, S. A. (2023): Parametric Modeling Approach To COVID-19 Pandemic Data, Open Journal Of Statistics, 13, Pp. 61-73. https://doi.org/10.4236/ojs.2023.131005
Chen W., Zhang W. And Li L. (2021): Precise Transmission For COVID-19 Information: Based On China's Experience. International Journal Of Environmental Research And Public Health, 18, 3015 [Crossref] Accessed: 26th June 2022 04:45:28 AM https://doi.org/10.3390/ijerph18063015
Cori A., Ferguson N. M., Fraser C. And Cauchemez S. (2013): A New Framework And Software To Estimate Time-Varying Reproduction Numbers During Epidemics. American Journal Of Epidemiology, 178(9): Pp. 1505-1512.
https://doi.org/10.1093/aje/kwt133
D'Angelo, N., Abruzzo, A. And Adelfio, G. (2021). Spatio-Temporal Spread Pattern Of COVID-19 In Italy. Mathematics, 9, [Crossref] Accessed 29th April, 2022 01:52 AM
https://doi.org/10.3390/math9192454
Elimian K., Musah A., King C., Et Al. (2022): COVID-19 Mortality Rate And Its Associated Factors During The First And Second Waves In Nigeria. PLOS Glob Public Health 2(6), [Crossref] Accessed 04th September, 2022 05:09:05 PM
Elimian K. O., Ochu C. L., Ebhodaghe B., Et Al. (2020): Patient Characteristics Associated With COVID-19 Positivity And Fatality In Nigeria: Retrospective Cohort Study. BMS Open, [Crossref] Accessed: 06th April, 2022 11:55:54 AM
Goldstein E., Lipsitch M. And Cevik M. (2021): On The Effect Of Age On The Transmission Of SARS-COV-2 In Households, Schools And The Community. The Journal Of Infectious Diseases, 223, Pp. 362-369. https://doi.org/10.1093/infdis/jiaa691
Hao X., Cheng S., Wu D., Et Al. (2020): Reconstruction Of The Full Transmission Dynamics Of COVID- 19 In Wuhan. Nature, Vol. 584, Pp. 420-424.
https://doi.org/10.1038/s41586-020-2554-8
Hu, D., Lou, X., Meng, N., Et Al. (2021): Influence Of Age And Gender On The Epidemic Of COVID-19 Evidence From 177 Countries And Territories- An Explanatory, Ecological Study. Wien Klin Wochenschr, 133, Pp. 321-330.
https://doi.org/10.1007/s00508-021-01816-z
Hwang, H., Lim, S-K, Song, S-A, Et Al. (2022), Transmission Dynamics Of The Delta Variant Of SARS-Cov-2 Infections In South Korea. The Journal Of Infectious Diseases, Academic.Oup.Com Accessed 26th June 2022 09:07 AM
Isere E. E., Adejugbagbe M. M., Fagbemi A. T., Et Al. (2021): Outcome Of Epidemiological Investigation Of COVID-19 Outbreak In A South-West State Of Nigeria, March To August 2020. Open Journal Of Epidemiology, 11, Pp 163-177.
https://doi.org/10.4236/ojepi.2021.112015
Jameel, I. J., Mohammed, H. J., Shawkat, M. A. And Ahmed, H. J. (2023): Relation Between Some Of Risk Factors And COVID-19 Infection. Journal Of Genetic And Environmental Resources Conservation, 11(1), Pp. 33-43.
Ladan S. I. (2020): Preventive Measures Adopted Against Spread Of Corona Virus Disease By Katsina State Government, Nigeria. Direct Research Journal Of Public Health And Environmental Technology, Vol. 5(5), Pp. 92-101.
Li, X And Dey, D. K. (2022). Estimation Of COVID-19 Mortality In The United States Using Spatio- Temporal Conway Maxwell Poisson Model, Spatial Statistics, [Crossref] Accessed 26th June 2022 06:56 AM
https://doi.org/10.1016/j.spasta.2021.100542
Li X-P., Ullah S., Zahir H., Et Al. (2022a): Modeling The Dynamics Of Corona Virus With Super- Spreader Class: A Fractal-Fractional Approach. Results In Physics, [Crossref] Accessed: 04th September, 2022 05:15:22 PM.
Li W., Bulekova K., Gregor B., Et Al. (2022b): Estimation Of Local Time-Varying Reproduction Number In Noisy Surveillance Data. Phil. Trans. R. Soc., A380: 20210303 [Crossref]
https://doi.org/10.1098/rsta.2021.0303
Mitra, S., Muley, A., Bavish, A., Patel, G. And Bhattacharya, A. (2023): Characteristics An Outcomes Of COVID-19 During The Third Wave Of COVID-19 Pandemic: A Single-Center Descriptive Study. Journal Of The Association Of Physicians Of India, Vol. 71, Issue 2, Pp. 37-40.
https://doi.org/10.5005/japi-11001-0173
Moroh, J. E., Innocent, D. C., Chukwuocha, U. M., Et Al. (2023): Seasonal Variation And Geographical Distribution Of COVID-19 Across Nigeria (March 2020 - July 2021). Vaccines,11,[Crossref] https://doi.org/10.3390/vaccines11020298
Nash R. K., Nouvellet P. And Cori A. (2022): Real-Time Estimation Of The Epidemic Reproduction Number: Scoping Review Of The Applications And Challenges. PLOS Digital Health 1
https://doi.org/10.1371/journal.pdig.0000052
(6) [Crossref] Accessed: 04th September 2022 02:58:56 PM
https://doi.org/10.52314/tjima.2022.v2i1.65
NCDC (2021): Weekly Epidemiological Report, Week 28: 12th -18th July, 2021. Vol.2, No. 28 Reliefweb.Int Accessed: 05th June 2022 07:05:49 AM
NCDC (2023): Official Statement Following The Declaration F COVID-19 As No Longer A Public Health Emergency Of International Concern. Accessed 29th May, 2023, 5:52 AM Ncdc.Gov.Ng
Ofori S. K., Schwind J. S., Sullivan K. L., Et Al. (2022): Transmission Dynamics Of COVID-19 In Ghana And The Impact Of Public Health Interventions. Am. J. Trop. Med. Hyg., 107 (1), Pp. 175-179. https://doi.org/10.4269/ajtmh.21-0718
Olawa, B., Lawal, A., Odoh, I., Et Al. (2023): Mistrust In Government And COVID-19 Vaccination Acceptance In Nigeria: Investigating The Indirect Roles Of Attitudes Towards Vaccination. Journal Of The Egyptian Public Health Society, 98(1), [Crossref] Accessed 29th May 2023; 06:52:52 AM
https://doi.org/10.1186/s42506-023-00129-5
Olusola, A., Olusola, B., Onafeso, O., Et Al. (2020). Early Geography Of The Coronavirus Disease Outbreak In Nigeria. Geojournal, [Crossref] Accessed 12th July 2021 03:49 PM
Omede B. I., Odionyenma U. B., Ibrahim A. A. And Bolaji B. (2023): Third Wave Of COVID-19: Mathematical Model With Optimal Control Strategy For Reducing The Disease Burden In Nigeria. International Journal Of Dynamics And Control, 11, Pp. 411-427.
https://doi.org/10.1007/s40435-022-00982-w
Onwube, O., Ohalete, P. And Yakubu, J. A. (2023): The Coronavirus Disease Pandemic And The Basic Reproduction Number (R0) In Nigeria: What Does The Data Real? Ibom Medical Journal, Vol. 16, No. 1, Pp. 35-44.
Otovwe A., Roli A. T., Nneka O. C., Et Al. (2022): Predictors Of COVID-19 Positivity In Ndokwa- West District In Nigeria: A Retrospective Cohort Study. Afro-Egypt J. Infect. Endem. Dis., 12(1), Pp 85-91. https://doi.org/10.21608/aeji.2022.102216.1190
Permata A. D., Murti B. And Tamtomo D. G. (2021): Hypertension, Gender, Older Age And Their Relationships With COVID-19 Mortality: Meta-Analysis. Journal Of Epidemiology And Public Health, 06(01), Pp. 98-111.
https://doi.org/10.26911/jepublichealth.2021.06.01.10
Petri, O., Abazaj, E., Huti, A. D. G., Et Al. (2022): The Epidemiological Situation And Clinical Characteristic Aspect Cause By COVID-19 In Albania. Open Access Maced. J. Med. Sci.,10(B), Pp. 1062-1067.
https://doi.org/10.3889/oamjms.2022.8824
Politis M. D., Hua X., Ogwara C. A., Et Al. (2022): Spatially Refined Time-Varying Reproduction Number Of SARS-COV-2 In Arkansas And Kentucky And Their Relationship To Population Size And Public Health Policy, March-November, 2020. Annals Of Epidemiology, 68, Pp. 37-44.
https://doi.org/10.1016/j.annepidem.2021.12.012
R Core Team (2023): R - A Language And Environment For Statistical Computing. R Foundation For Statistical Computing, Vienna, Austria. URL R-Project.Org
Rahimi E., Nazari S. S. H., Mokhayeri Y., Et Al. (2021): Nine-Month Trend Of Time-Varying Reproduction Numbers Of COVID-19 In West Of Iran. Journal Of Research In Health Sciences, 21(2), E00517. Doi: 10.34172/Jrhs.2021.54
https://doi.org/10.34172/jrhs.2021.54
Rambo A. P. S., Goncalves L. F., Gonzales A. I., Et Al. (2021): Impact Of Super-Spreaders On COVID-19: Systematic Review. Sao Paulo Med. J., 139(2), Pp 163-169. https://doi.org/10.1590/1516-3180.2020.0618.r1.10122020
.Slater, J. J., Brown, P. E., Rosenthal, J. S. And Mateu, J. (2022). Capturing The Spatial Dependence Of COVID-19 Case Counts With Cell Phone Mobility Data. Spatial Statistics, 49 100540 [Crossref] Accessed 26th June 2022 06:56 AM
https://doi.org/10.1016/j.spasta.2021.100540
Sokunbi, T. O., Oluyedun, A. T., Adegboye, E. A., Et Al (2023): COVID-19 Vaccination In Nigeria:Challenges And Recommendations For Future Vaccination Initiatives. Vaccines,10, [Crossref]. Accessed 05 June 2023 07:01:51 AM
https://doi.org/10.1002/puh2.57
Taiwo, O., Addie, O. And Seun-Addie, K. (2023): A Local Government Area Based COVID-19 Vulnerability Analysis In Nigeria. Geojournal, [Crossref]Https://Doi.Org/10.1007/S10708-023-10857-Y https://doi.org/10.1007/s10708-023-10857-y
Tandon, P., Leibner, E. S., Hackett, A., Et Al. (2021): The Third Wave: Comparing Seasonal Trends In COVID-19 Patient Data At A Large Hospital System In New York City. Critical Care Exploration. Vol. 4, No. 3, [Crossref] Accessed 4th June 2023. https://doi.org/10.1097/CCE.0000000000000653
Thompson R. N., Stockwin J. E., Van Gaalen R. D., Et Al (2019): Improved Inference Of Time-Varying Reproduction Numbers During Infectious Diseases Outbreaks. Epidemics, 29 [Crossref] Accessed: 04th September 2022 02:59:31PM
https://doi.org/10.1016/j.epidem.2019.100356
Triambak, S., Mahapatra, D. P., Barik, N. And Chutjian, A. (2023): Plausible Explanation For The Third COVID-19 Wave In India And Its Implications. Infectious Disease Modelling, 8, Pp. 183-191. https://doi.org/10.1016/j.idm.2023.01.001
Turasie A. A. (2020): Temporal Dynamics In COVID-19 Transmission: Case Of Some African Countries. Advances In Infectious Diseases, 10, Pp. 110-122. https://doi.org/10.4236/aid.2020.103011
Utulu R., Ajayi I. O., Bello S., Et Al. (2022): Risk Factors For COVID-19 Infection And Disease Severity In Nigeria: A Case-Control Study. Panafrican Medical Journal, 41(317) Panafrican-Med-Journal.Com Accessed: 04th September 2022 07:16:42:PM
https://doi.org/10.11604/pamj.2022.41.317.34307
Wilasang, C., Jitsuk, N. C., Sararat, C. And Modchang C. (2022). Reconstruction Of The Transmission Dynamics Of The First COVID-19 Epidemic Wave In Thailand. Scientific Reports, 12: 2002. [Crossref] Accessed 3rd April, 2022 08:50 AM https://doi.org/10.1038/s41598-022-06008-x
World Health Organization. (2020a): Novel Coronavirus (2019-Ncov): Situation Report, 1 World Health Organization. Apps.Who.Int Accessed 26th June 2021
World Health Organization (2020b): Novel Corona Virus (2019-Ncov): Situation Report, 22 World Health Organization Apps.Who.Int
World Health Organization (2020c): COVID-19 Public Health Emergency Of International Concern (PHEIC) Global Research An Innovation Forum, 12th February 2020 Publication. Who.Int Accessed 26th June 2021.
World Health Organization. (2020d): WHO Director-General's Opening Remarks At The Media Briefing On COVID-19-11 March 2020. WHO Director General's Speeches. Geneva. Who.Int Accessed 26th June 2021
World Health Organization. (2023): Statement On The Fifteenth Meeting Of The IHR (2005) Emergency Committee On The COVID-19 Pandemic Who.Int. Accessed 29th May, 2023, 05:32 AM
You C., Deng Y., Hu W., Et Al. (2020): Estimation Of The Time-Varying Reproduction Number Of COVID-19 Outbreak In China. International Journal Of Hygiene And Environmental Health, 228, [Crossref] https://doi.org/10.1016/j.ijheh.2020.113555
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