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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]

Background: The public health response to the global COVID-19 pandemic has varied widely by region. In Africa, uptake of effective COVID-19 vaccines has been limited by accessibility and vaccine hesitancy. The aim of this study was to compare perceptions of COVID-19 infection and vaccination between pregnant women and non-pregnant adults in four regions of Cameroon, located in Central Africa. Methods: A cross-sectional survey study was conducted at urban and suburban hospital facilities in Cameroon. Participants were randomly selected from a convenience sample of adult pregnant and non-pregnant adults in outpatient clinical settings between June 1st and July 14th, 2021. A confidential survey was administered in person by trained research nurses after obtaining written informed consent. Participants were asked about self-reported sociodemographics, medical comorbidities, perceptions of COVID-19 infection, and vaccination. Descriptive statistics were used for survey responses and univariate and multivariable logistic regression models were created to explore factors associated with COVID-19 vaccine acceptability. Results: Fewer than one-third of participants were interested in receiving the COVID-19 vaccine (31%, 257/835) and rates did not differ by pregnancy status. Overall, 43% of participants doubted vaccine efficacy, and 85% stated that the vaccine available in Africa was less effective than vaccine available in Europe. Factors independently associated with vaccine acceptability included having children (aOR = 1.5; p = 0.04) and higher education (aOR = 1.6 for secondary school vs primary/none; p = 0.03). Perceived risks of vaccination ranged from death (33%) to fetal harm (31%) to genetic changes (1%). Health care professionals were cited as the most trusted source for health information (82%, n = 681). Conclusion: COVID-19 vaccine hesitancy and misinformation in Cameroon was highly prevalent among pregnant and non-pregnant adults in 2021 while vaccine was available but not recommended for use in pregnancy. Based on study findings, consistent public health messaging from medical professionals about vaccine safety and efficacy and local production of vaccine are likely to improve acceptability. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused over 500 million cases and over six million deaths globally. From these numbers, over 12 million cases and over 250 thousand deaths have occurred on the African continent as of May 2022. Prevention and surveillance remains the cornerstone of interventions to halt the further spread of COVID-19. Google Health Trends (GHT), a free Internet tool, may be valuable to help anticipate outbreaks, identify disease hotspots, or understand the patterns of disease surveillance. We collected COVID-19 case and death incidence for 54 African countries and obtained averages for four, five-month study periods in 2020–2021. Average case and death incidences were calculated during these four time periods to measure disease severity. We used GHT to characterize COVID-19 incidence across Africa, collecting numbers of searches from GHT related to COVID-19 using four terms: 'coronavirus', 'coronavirus symptoms', 'COVID19', and 'pandemic'. The terms were related to weekly COVID-19 case incidences for the entire study period via multiple linear and weighted linear regression analyses. We also assembled 72 variables assessing Internet accessibility, demographics, economics, health, and others, for each country, to summarize potential mechanisms linking GHT searches and COVID-19 incidence. COVID-19 burden in Africa increased steadily during the study period. Important increases for COVID-19 death incidence were observed for Seychelles and Tunisia. Our study demonstrated a weak correlation between GHT and COVID-19 incidence for most African countries. Several variables seemed useful in explaining the pattern of GHT statistics and their relationship to COVID-19 including: log of average weekly cases, log of cumulative total deaths, and log of fixed total number of broadband subscriptions in a country. Apparently, GHT may best be used for surveillance of diseases that are diagnosed more consistently. Overall, GHT-based surveillance showed little applicability in the studied countries. GHT for an ongoing epidemic might be useful in specific situations, such as when countries have significant levels of infection with low variability. Future studies might assess the algorithm in different epidemic contexts. [ABSTRACT FROM AUTHOR]