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

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.

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.