Mathematical modeling and impact analysis of the use of COVID Alert SA app
The human life-threatening novel Severe Acute Respiratory Syndrome Corona-virus-2 (SARS-CoV-2) has lasted for over a year escalating and posing simultaneous anxiety day-by-day globally since its first report in the late December 2019. The scientific arena has been kept animated via continuous invest...
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| Format: | Article |
| Language: | English |
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AIMS Press
2022-01-01
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| Series: | AIMS Public Health |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/publichealth.2022009?viewType=HTML |
| _version_ | 1811309871267577856 |
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| author | Musyoka Kinyili Justin B Munyakazi Abdulaziz YA Mukhtar |
| author_facet | Musyoka Kinyili Justin B Munyakazi Abdulaziz YA Mukhtar |
| author_sort | Musyoka Kinyili |
| collection | DOAJ |
| description | The human life-threatening novel Severe Acute Respiratory Syndrome Corona-virus-2 (SARS-CoV-2) has lasted for over a year escalating and posing simultaneous anxiety day-by-day globally since its first report in the late December 2019. The scientific arena has been kept animated via continuous investigations in an effort to understand the spread dynamics and the impact of various mitigation measures to keep this pandemic diminished. Despite a lot of research works having been accomplished this far, the pandemic is still deep-rooted in many regions worldwide signaling for more scientific investigations. This study joins the field by developing a modified SEIR (Susceptible-Exposed-Infectious-Removed) compartmental deterministic model whose key distinct feature is the incorporation of the COVID Alert SA app use by the general public in prolific intention to control the spread of the epidemic. Validation of the model is performed by fitting the model to the Republic of South Africa's COVID-19 cases reported data using the Maximum Likelihood Estimation algorithm implemented in fitR package. The model's sensitivity analysis and simulations stipulate that gradual to complete use of the app would be perfect in contact tracing and substantially reduce the plateau number of COVID-19 infections. This would consequentially contribute remarkably to the eradication of the SARS-CoV-2 over time. Proportional amalgamation of the app use and test for COVID-19 on individuals not using the app would also reduce the peak number of infections apart from the 50 – 50% ratio which spikes the plateau number beyond any other proportion. The study establishes that at least 30% implementation of the app use with gradual increase in tests conducted for individuals not using the app would suffice to stabilize the disease free equilibrium resulting to gradual eradication of the pandemic. |
| first_indexed | 2024-04-13T09:49:37Z |
| format | Article |
| id | doaj.art-8e1afe86755948499494df93129dab29 |
| institution | Directory Open Access Journal |
| issn | 2327-8994 |
| language | English |
| last_indexed | 2024-04-13T09:49:37Z |
| publishDate | 2022-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Public Health |
| spelling | doaj.art-8e1afe86755948499494df93129dab292022-12-22T02:51:38ZengAIMS PressAIMS Public Health2327-89942022-01-019110612810.3934/publichealth.2022009Mathematical modeling and impact analysis of the use of COVID Alert SA appMusyoka Kinyili 0Justin B Munyakazi 1Abdulaziz YA Mukhtar2Department of Mathematics and Applied Mathematics, Faculty of Natural Sciences, University of the Western Cape, Private Bag X17 Bellville 7535, South AfricaDepartment of Mathematics and Applied Mathematics, Faculty of Natural Sciences, University of the Western Cape, Private Bag X17 Bellville 7535, South Africa Department of Mathematics and Applied Mathematics, Faculty of Natural Sciences, University of the Western Cape, Private Bag X17 Bellville 7535, South AfricaThe human life-threatening novel Severe Acute Respiratory Syndrome Corona-virus-2 (SARS-CoV-2) has lasted for over a year escalating and posing simultaneous anxiety day-by-day globally since its first report in the late December 2019. The scientific arena has been kept animated via continuous investigations in an effort to understand the spread dynamics and the impact of various mitigation measures to keep this pandemic diminished. Despite a lot of research works having been accomplished this far, the pandemic is still deep-rooted in many regions worldwide signaling for more scientific investigations. This study joins the field by developing a modified SEIR (Susceptible-Exposed-Infectious-Removed) compartmental deterministic model whose key distinct feature is the incorporation of the COVID Alert SA app use by the general public in prolific intention to control the spread of the epidemic. Validation of the model is performed by fitting the model to the Republic of South Africa's COVID-19 cases reported data using the Maximum Likelihood Estimation algorithm implemented in fitR package. The model's sensitivity analysis and simulations stipulate that gradual to complete use of the app would be perfect in contact tracing and substantially reduce the plateau number of COVID-19 infections. This would consequentially contribute remarkably to the eradication of the SARS-CoV-2 over time. Proportional amalgamation of the app use and test for COVID-19 on individuals not using the app would also reduce the peak number of infections apart from the 50 – 50% ratio which spikes the plateau number beyond any other proportion. The study establishes that at least 30% implementation of the app use with gradual increase in tests conducted for individuals not using the app would suffice to stabilize the disease free equilibrium resulting to gradual eradication of the pandemic.https://www.aimspress.com/article/doi/10.3934/publichealth.2022009?viewType=HTMLcovid-19covid alert sa appdigital-contact-tracing technologycompartmental deterministic modelsmathematical modelingmitigation measures |
| spellingShingle | Musyoka Kinyili Justin B Munyakazi Abdulaziz YA Mukhtar Mathematical modeling and impact analysis of the use of COVID Alert SA app AIMS Public Health covid-19 covid alert sa app digital-contact-tracing technology compartmental deterministic models mathematical modeling mitigation measures |
| title | Mathematical modeling and impact analysis of the use of COVID Alert SA app |
| title_full | Mathematical modeling and impact analysis of the use of COVID Alert SA app |
| title_fullStr | Mathematical modeling and impact analysis of the use of COVID Alert SA app |
| title_full_unstemmed | Mathematical modeling and impact analysis of the use of COVID Alert SA app |
| title_short | Mathematical modeling and impact analysis of the use of COVID Alert SA app |
| title_sort | mathematical modeling and impact analysis of the use of covid alert sa app |
| topic | covid-19 covid alert sa app digital-contact-tracing technology compartmental deterministic models mathematical modeling mitigation measures |
| url | https://www.aimspress.com/article/doi/10.3934/publichealth.2022009?viewType=HTML |
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