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Omicron variant was first found in Botswana, southern Africa, on November 9, 2021. The variant has many mutations and spreads quickly. It also has immune escape to existing COVID-19 vaccines, and the infection rate and repeated infection rate have increased worldwide. For such variant, at this stage, foreign countries mainly adopt three strategies to prevent and control the epidemic. First, big data is used to track the potential infection of the epidemic, trace the spread of the epidemic, screen close contacts, and control the scope of infection. The second is to maximum the coverage rate of vaccination, especially the coverage rate of the third injection, so as to reduce the infection level of Omicron variant. At last, they are developing a general coronavirus vaccine to prevent infection caused by SARS-CoV-2 variants, including the Omicron variant, so as to fundamentally eliminate the potential threat of variants to human beings. In this paper, three major epidemic prevention strategies of Omicron variant abroad were summarized in detail. [ABSTRACT FROM AUTHOR]

Due to the high transmission rate and mortality index of the current coronavirus pandemic, many settings in Africa instituted lockdowns to reduce its rate of spread and avert exponential growth rate. At the early stage, this measure seemed to heighten awareness of the virus and subsequently minimized exponential growth of cases. However, these lockdowns have had great consequences on the weak health systems and frail economy in place in many African countries. In this paper, we examine the impact of lockdown measures in these countries and provides key recommendations in dealing with present and future pandemics. [ABSTRACT FROM AUTHOR]

The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31–4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions. [ABSTRACT FROM AUTHOR]

Self-medication is an important initial response to illness in Africa. This mode of medication is often done with the help of African traditional medicines. Because of the misconception that African traditional medicines can cure/prevent all diseases, some Africans may opt for COVID-19 prevention and management by self-medicating. Thus to efficiently predict the dynamics of COVID-19 in Africa, the role of the self-medicated population needs to be taken into account. In this paper, we formulate and analyse a mathematical model for the dynamics of COVID-19 in Cameroon. The model is represented by a system of compartmental age-structured ODEs that takes into account the self-medicated population and subdivides the human population into two age classes relative to their current immune system strength. We use our model to propose policy measures that could be implemented in the course of an epidemic in order to better handle cases of self-medication. [ABSTRACT FROM AUTHOR]

• Morbidity and mortality in children due to COVID-19 remained low • Adolescents had higher reported cases than younger children • Reported cases were lower in pediatric population than adult population • Testing protocols vary between countries; reflects bias in reported cases Few data on the COVID-19 epidemiological characteristics among the pediatric population in Africa exists. This paper examines the age and sex distribution of the morbidity and mortality rate in children with COVID-19 and compares it to the adult population in 15 Sub-Saharan African countries. A merge line listing dataset shared by countries within the Regional Office for Africa was analyzed. Patients diagnosed within 1 March and 1 September 2020 with a confirmed positive RT-PCR test for SARS-CoV-2 were analyzed. Children's data were stratified into three age groups: 0-4 years, 5-11 years, and 12-17 years, while adults were combined. The cumulative incidence of cases, its medians, and 95% confidence intervals were calculated. 9% of the total confirmed cases and 2.4% of the reported deaths were pediatric cases. The 12-17 age group in all 15 countries showed the highest cumulative incidence proportion in children. Adults had a higher case incidence per 100,000 people than children. The cases and deaths within the children's population were smaller than the adult population. These differences may reflect biases in COVID-19 testing protocols and reporting implemented by countries, highlighting the need for more extensive investigation and focus on the effects of COVID-19 in children. [ABSTRACT FROM AUTHOR]