An extreme value analysis of daily new cases of COVID-19 in Africa
Modeling COVID-19 cases in Africa is crucial for developing effective public health strategies, allocating resources efficiently, and mitigating the impact of the pandemic on vulnerable populations. A recent paper by the first author provided an extreme value analysis of daily new cases of COVID-19...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
|
| Series: | Frontiers in Public Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1546404/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832576374459596800 |
|---|---|
| author | Saralees Nadarajah Adamu Abubakar Umar Adamu Abubakar Umar |
| author_facet | Saralees Nadarajah Adamu Abubakar Umar Adamu Abubakar Umar |
| author_sort | Saralees Nadarajah |
| collection | DOAJ |
| description | Modeling COVID-19 cases in Africa is crucial for developing effective public health strategies, allocating resources efficiently, and mitigating the impact of the pandemic on vulnerable populations. A recent paper by the first author provided an extreme value analysis of daily new cases of COVID-19 from sixteen countries in west Africa. In this paper, we broaden our analysis to encompass data spanning all fifty four African nations over a period of forty four months. We identified extreme values as the monthly maximums of daily new cases. Utilizing the generalized extreme value distribution, we fitted the data, allowing two of its three parameters to vary linearly or quadratically in relation to the month number. Twenty six countries demonstrated significant downward trends in monthly maximums. Two countries demonstrated significant upward trends in monthly maximums. Nineteen countries demonstrated significant quadratic trends where monthly maximums initially increased before decreasing. The sharpest and weakest of the downward trends with respect to location were for Mali and Liberia, respectively. The sharpest and weakest of the downward trends with respect to scale were for Egypt and Libya, respectively. Recommendations are given for each country. We evaluated the adequacy of fits through probability plots and the Kolmogorov-Smirnov test. Subsequently, the fitted models were employed to determine quantiles of the monthly maximum of new cases, as well as their limits extrapolated to infinite month numbers. |
| format | Article |
| id | doaj-art-e103058d50a541d2a80e6d763468898d |
| institution | Kabale University |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-e103058d50a541d2a80e6d763468898d2025-01-31T06:40:04ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-01-011310.3389/fpubh.2025.15464041546404An extreme value analysis of daily new cases of COVID-19 in AfricaSaralees Nadarajah0Adamu Abubakar Umar1Adamu Abubakar Umar2Department of Mathematics, University of Manchester, Manchester, United KingdomDepartment of Mathematics, University of Manchester, Manchester, United KingdomDepartment of Statistics, Ahmadu Bello University, Zaria, NigeriaModeling COVID-19 cases in Africa is crucial for developing effective public health strategies, allocating resources efficiently, and mitigating the impact of the pandemic on vulnerable populations. A recent paper by the first author provided an extreme value analysis of daily new cases of COVID-19 from sixteen countries in west Africa. In this paper, we broaden our analysis to encompass data spanning all fifty four African nations over a period of forty four months. We identified extreme values as the monthly maximums of daily new cases. Utilizing the generalized extreme value distribution, we fitted the data, allowing two of its three parameters to vary linearly or quadratically in relation to the month number. Twenty six countries demonstrated significant downward trends in monthly maximums. Two countries demonstrated significant upward trends in monthly maximums. Nineteen countries demonstrated significant quadratic trends where monthly maximums initially increased before decreasing. The sharpest and weakest of the downward trends with respect to location were for Mali and Liberia, respectively. The sharpest and weakest of the downward trends with respect to scale were for Egypt and Libya, respectively. Recommendations are given for each country. We evaluated the adequacy of fits through probability plots and the Kolmogorov-Smirnov test. Subsequently, the fitted models were employed to determine quantiles of the monthly maximum of new cases, as well as their limits extrapolated to infinite month numbers.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1546404/fullgeneralized extreme value distributionKolmogorov-Smirnov testlinear trendquadratic trendestimation |
| spellingShingle | Saralees Nadarajah Adamu Abubakar Umar Adamu Abubakar Umar An extreme value analysis of daily new cases of COVID-19 in Africa Frontiers in Public Health generalized extreme value distribution Kolmogorov-Smirnov test linear trend quadratic trend estimation |
| title | An extreme value analysis of daily new cases of COVID-19 in Africa |
| title_full | An extreme value analysis of daily new cases of COVID-19 in Africa |
| title_fullStr | An extreme value analysis of daily new cases of COVID-19 in Africa |
| title_full_unstemmed | An extreme value analysis of daily new cases of COVID-19 in Africa |
| title_short | An extreme value analysis of daily new cases of COVID-19 in Africa |
| title_sort | extreme value analysis of daily new cases of covid 19 in africa |
| topic | generalized extreme value distribution Kolmogorov-Smirnov test linear trend quadratic trend estimation |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1546404/full |
| work_keys_str_mv | AT saraleesnadarajah anextremevalueanalysisofdailynewcasesofcovid19inafrica AT adamuabubakarumar anextremevalueanalysisofdailynewcasesofcovid19inafrica AT adamuabubakarumar anextremevalueanalysisofdailynewcasesofcovid19inafrica AT saraleesnadarajah extremevalueanalysisofdailynewcasesofcovid19inafrica AT adamuabubakarumar extremevalueanalysisofdailynewcasesofcovid19inafrica AT adamuabubakarumar extremevalueanalysisofdailynewcasesofcovid19inafrica |