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

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

OBJECTIVE

Mathematical 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.

METHODS

We 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.

RESULTS

The 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.

CONCLUSIONS

While 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.

Notional Spread of Cholera in Haiti Following a Natural Disaster: Considerations for Military and Disaster Relief Personnel

INTRODUCTION

Cholera remains a significant public health threat for many countries, and the severity largely varies by the population and local conditions that drive disease spread, especially in endemic areas prone to natural disasters and flooding. Epidemiological models can provide useful information to military planners for understanding disease spread within populations and the effectiveness of response options for preventing the transmission among deployed and stationed personnel. This study demonstrates the use of epidemiological modeling to understand the dynamics of cholera transmission to inform emergency planning and military preparedness in areas with highly communicable diseases.

MATERIALS AND METHODS

Areas with higher probability for a potential cholera outbreak in Haiti followed by a natural disaster were identified. The hotspots were then used to seed an extended compartmental model, EpiGrid, to simulate notional spread scenarios of cholera originating in three distinct areas in Haiti. Disease parameters were derived from the 2010 cholera outbreak in Haiti, and disease spread was simulated over a 12-week period under uncontrolled and controlled spread.

RESULTS

For each model location, scenarios of mitigated (intervention with 30% transmission reduction via international aid) and unmitigated (without intervention) are simulated. The results depict the geographical spread and estimate the cumulative cholera infection for each notional scenario over the course of 3 months. Disease transmission differs considerably across origin site with an outbreak originating in the department of Nippes spanning the largest geographic area and resulting in the largest number of cumulative cases after 12 weeks under unmitigated (79,518 cases) and mitigated (35,667 cases) spread scenarios.

CONCLUSIONS

We modeled the notional re-emergence and spread of cholera following the August 2021 earthquake in Haiti while in the midst of the global COVID-19 pandemic. This information can help guide military and emergency response decision-making during an infectious disease outbreak and considerations for protecting military personnel in the midst of a humanitarian response. Military planners should consider the use of epidemiological models to assess the health risk posed to deployed and stationed personnel in high-risk areas.

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

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.