Non-pharmaceutical interventions and their relevance in the COVID-19 vaccine rollout in Saudi Arabia and Arab Gulf countries

COVID-19 dynamic modeling of immune variability and multistage vaccination strategies: A case study in Malaysia

Hybrid-immune and immunodeficient individuals have been identified by the World Health Organization as two vulnerable groups in the context of COVID-19, but their distinct characteristics remain underexplored. To address this gap, we developed an extended SIVS compartmental model that simulates the spread of COVID-19 and the impact of administering three doses of the vaccine (first, second, and booster). This study aims to provide insights into how these vulnerable populations respond to vaccination and the dynamics of waning immunity. Using real-time data from the Ministry of Health of Malaysia (May 2023-April 2024), we estimated key parameters through numerical methods and fitted the model to the data using MATLAB's lsqcurvefit package. We carried out stability and equilibrium analyses, computed the basic reproduction number (R 0), and identified conditions for Hopf bifurcation. Sensitivity analysis highlights the parameters with the greatest impact on infection dynamics. The calculated basic reproduction number and stability results suggest that with current vaccination rates, COVID-19 will persist in the population over an extended period. Our findings provide valuable information for public health agencies, offering recommendations for vaccination strategies targeting hybrid-immune and immunodeficient groups. These insights can inform decisions about vaccine booster schedules and resource allocation to better manage the pandemic.

Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models

As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.

A systematic literature review on public health and healthcare resources for pandemic preparedness planning

BACKGROUND

Generating insights into resource demands during outbreaks is an important aspect of pandemic preparedness. The EU PANDEM-2 project used resource modelling to explore the demand profile for key resources during pandemic scenarios. This review aimed to identify public health and healthcare resources needed to respond to pandemic threats and the ranges of parameter values on the use of these resources for pandemic influenza (including the novel influenza A(H1N1)pdm09 pandemic) and the COVID-19 pandemic, to support modelling activities.

METHODS

We conducted a systematic literature review and searched Embase and Medline databases (1995 - June 2023) for articles that included a model, scenario, or simulation of pandemic resources and/or describe resource parameters, for example personal protective equipment (PPE) usage, length of stay (LoS) in intensive care unit (ICU), or vaccine efficacy. Papers with data on resource parameters from all countries were included.

RESULTS

We identified 2754 articles of which 147 were included in the final review. Forty-six different resource parameters with values related to non-ICU beds (n = 43 articles), ICU beds (n = 57), mechanical ventilation (n = 39), healthcare workers (n = 12), pharmaceuticals (n = 21), PPE (n = 8), vaccines (n = 26), and testing and tracing (n = 19). Differences between resource types related to pandemic influenza and COVID-19 were observed, for example on mechanical ventilation (mostly for COVID-19) and testing & tracing (all for COVID-19).

CONCLUSION

This review provides an overview of public health and healthcare resources with associated parameters in the context of pandemic influenza and the COVID-19 pandemic. Providing insight into the ranges of plausible parameter values on the use of public health and healthcare resources improves the accuracy of results of modelling different scenarios, and thus decision-making by policy makers and hospital planners. This review also highlights a scarcity of published data on important public health resources.

Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.

Assessment of willingness and determinants to receive the COVID-19 vaccine among the general population of the Somali region, Eastern Ethiopia: a 2021 cross-sectional study

OBJECTIVE

This research aimed to assess COVID-19 vaccine acceptance and the factors influencing it among the population of the Somali region in Ethiopia through a cross-sectional COVID-19 survey.

DESIGN

Community-based cross-sectional study.

SETTING

The survey was conducted in eight selected districts of the Somali region in Ethiopia from 20 October 2021 to 30 October 2021.

PARTICIPANTS

Participants were chosen using simple random sampling and data analysis used Stata V.14. Both bivariable and multivariable binary logistic regression methods were applied, with variables having a p value below 0.2 considered for inclusion in the final model, where statistically significant factors were identified at p<0.5.

PRIMARY OUTCOME MEASURE

Willingness to take the vaccine.

RESULTS

A total of 1010 respondents participated in this study. The proportion of people's willingness to take the vaccine was 65% (95% CI 62 to 68). When you believe moderately or highly that getting a COVID-19 vaccine will protect others (AOR=6.2, 95% CI 1.43 to 26.6) and (AOR=7.2, 95% CI 1.7 to 29.7), then you will protect others as well. Whereas, a desire to get vaccinated little, moderately and highly (AOR=4.3, 95% CI 1.77 to 10.4), (AOR=20, 95% CI 8.5 to 47) and (AOR=147, 95% CI 55 to 392), respectively, was significantly associated with willingness to take the vaccine. Moreover having close family and friends who want them to get a COVID-19 vaccine (AOR=2, 95% CI 1.2 to 3.57) and religious leaders or community leaders (AOR=1.8, 95% CI 1 to 3.1) were significant factors in the multivariable logistic regression model.

CONCLUSION

This study found that COVID-19 vaccine acceptance was low in the Somali region. Factors positively linked to one's willingness to get vaccinated included the belief that it protects others, personal desire for vaccination and support from family, friends, community and religious leaders.