Coronavirus Disease 2019 on the Heels of Ebola Virus Disease in West Africa

Dembek, Zygmunt F.; Schwartz-Watjen, Kierstyn T; Swiatecka, Anna L; Broadway, Katherine M; Hadeed, Steven J; Mothershead, Jerry L.; Chekol, Tesema; Owens, Akeisha N; Wu, Aiguo

doi:10.3390/pathogens10101266

Cited by 5 publications

(11 citation statements)

References 25 publications

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“…The first limitation of our study is that our model was age-stratified only. Other demographic variables (e.g., occupation and comorbidity) might change a person’s COVID-19 infection risk and clinical prognosis ( 45 ). Second, our model did not include a hospitalization compartment.…”

Section: Discussionmentioning

confidence: 99%

Age-Stratified Model to Assess Health Outcomes of COVID-19 Vaccination Strategies, Ghana

Ofori¹,

Schwind²,

Sullivan³

et al. 2023

Emerg. Infect. Dis.

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We assessed the effect of various COVID-19 vaccination strategies on health outcomes in Ghana by using an age-stratified compartmental model. We stratified the population into 3 age groups: <25 years, 25–64 years, and ≥65 years. We explored 5 vaccination optimization scenarios using 2 contact matrices, assuming that 1 million persons could be vaccinated in either 3 or 6 months. We assessed these vaccine optimization strategies for the initial strain, followed by a sensitivity analysis for the Delta variant. We found that vaccinating persons <25 years of age was associated with the lowest cumulative infections for the main matrix, for both the initial strain and the Delta variant. Prioritizing the elderly (≥65 years of age) was associated with the lowest cumulative deaths for both strains in all scenarios. The consensus between the findings of both contact matrices depended on the vaccine rollout period and the objective of the vaccination program.

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Section: Discussionmentioning

confidence: 99%

Age-Stratified Model to Assess Health Outcomes of COVID-19 Vaccination Strategies, Ghana

Ofori¹,

Schwind²,

Sullivan³

et al. 2023

Emerg. Infect. Dis.

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show abstract

“…First, our model was age-stratified only. Other demographic variables (e.g., occupation and comorbidity) may change one’s COVID-19 infection risk and clinical prognosis ( 41 ). Second, the model did not include a hospitalization compartment.…”

Section: Discussionmentioning

confidence: 99%

Modeling infections and deaths averted due to COVID-19 vaccination strategies in Ghana

Ofori

Schwind

Sullivan

et al. 2022

Preprint

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This study assessed the impact of various COVID-19 vaccination strategies on health outcomes in Ghana using an age-stratified compartmental model. The population was stratified into three age groups: <25 years, 25-64 years, and 65+ years. Five vaccination optimization scenarios were explored, assuming that one million persons could be vaccinated in three versus six months. We also performed uncertainty analysis by assuming that the available doses were halved and doubled. The vaccine optimization strategies were assessed for the initial strain, followed by a sensitivity analysis for the delta variant by varying the reproduction number and vaccine efficacy. The results showed that vaccinating individuals <65 years was associated with the lowest cumulative infections when one million persons were vaccinated over three months for both the initial strain and the delta variant. On the contrary, prioritizing the elderly (65+) was associated with the lowest cumulative deaths for both strains.

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“…North Africa had the most studies (n = 13, 41%) and Central Africa (n = 2, 6%) was the least represented region in Africa. Five of the studies focused on more than one African country [18][19][20][21][22] and one study was on the WHO African region [23]. By country, most studies were about or included South Africa (n = 12, 37%), followed by Morocco (n = 6, 19%) and Ethiopia (n = 5, 16%) (Figure 2, Table 1).…”

Section: Spatial Distribution Of Included Studies and Author Affiliat...mentioning

confidence: 99%

“…Nine of the included studies compared the effectiveness of vaccination and NPIs on health outcomes while five studies (16%) assessed post-vaccination dynamics, for example, the impact of imperfect vaccines on transmission dynamics. Two studies calibrated their transmission rates to vary over time to account for public health measures without directly modelling specific NPIs due to inconsistencies in implementation and compliance across countries [20,43]. The NPIs explored in these studies were mainly social distancing, face masks, quarantine, travel restrictions, isolation and testing [21,25,34,39,43,45].…”

Section: Key Vaccination Questionsmentioning

confidence: 99%

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COVID‐19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy

Ofori,

Dankwa,

Estrada

et al. 2024

Tropical Med Int Health

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ObjectiveMathematical models are vital tools to understand transmission dynamics and assess the impact of interventions to mitigate COVID‐19. However, historically, their use in Africa has been limited. In this scoping review, we assess how mathematical models were used to study COVID‐19 vaccination to potentially inform pandemic planning and response in Africa.MethodsWe searched six electronic databases: MEDLINE, Embase, Web of Science, Global Health, MathSciNet and Africa‐Wide NiPAD, using keywords to identify articles focused on the use of mathematical modelling studies of COVID‐19 vaccination in Africa that were published as of October 2022. We extracted the details on the country, author affiliation, characteristics of models, policy intent and heterogeneity factors. We assessed quality using 21‐point scale criteria on model characteristics and content of the studies.ResultsThe literature search yielded 462 articles, of which 32 were included based on the eligibility criteria. Nineteen (59%) studies had a first author affiliated with an African country. Of the 32 included studies, 30 (94%) were compartmental models. By country, most studies were about or included South Africa (n = 12, 37%), followed by Morocco (n = 6, 19%) and Ethiopia (n = 5, 16%). Most studies (n = 19, 59%) assessed the impact of increasing vaccination coverage on COVID‐19 burden. Half (n = 16, 50%) had policy intent: prioritising or selecting interventions, pandemic planning and response, vaccine distribution and optimisation strategies and understanding transmission dynamics of COVID‐19. Fourteen studies (44%) were of medium quality and eight (25%) were of high quality.ConclusionsWhile decision‐makers could draw vital insights from the evidence generated from mathematical modelling to inform policy, we found that there was limited use of such models exploring vaccination impacts for COVID‐19 in Africa. The disparity can be addressed by scaling up mathematical modelling training, increasing collaborative opportunities between modellers and policymakers, and increasing access to funding.

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Coronavirus Disease 2019 on the Heels of Ebola Virus Disease in West Africa

Cited by 5 publications

References 25 publications

Age-Stratified Model to Assess Health Outcomes of COVID-19 Vaccination Strategies, Ghana

Age-Stratified Model to Assess Health Outcomes of COVID-19 Vaccination Strategies, Ghana

Modeling infections and deaths averted due to COVID-19 vaccination strategies in Ghana

COVID‐19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy

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