Search

International audience; The COVID-19 information epidemic, or "infodemic," demonstrates how unlimited access to information may confuse and influence behaviors during a health emergency. However, the study of infodemics is relatively new, and little is known about their relationship with epidemics management. Here, we discuss unresolved issues and propose research directions to enhance preparedness for future health crises.

ObjectiveThe objective of this study was to gain a better understanding of the psychosocial and sociodemographic factors that affected adherence to COVID-19 public health and social measures (PHSMs), and to identify the factors that most strongly related to whether citizens followed public health guidance.DesignCross-sectional study.Setting and participantsNationally representative telephone surveys were conducted from 4–17 August 2020 in 18 African Union Member States. A total of 21 600 adults (mean age=32.7 years, SD=11.4) were interviewed (1200 in each country).Outcome measuresInformation including sociodemographics, adherence to PHSMs and psychosocial variables was collected. Logistic regression models examined the association between PHSM adherence (eg, physical distancing, gathering restrictions) and sociodemographic and psychosocial characteristics (eg, risk perception, trust). Factors affecting adherence were ranked using the Shapley regression decomposition method.ResultsAdherence to PHSMs was high, with better adherence to personal than community PHSMs (65.5% vs 30.2%, p<0.05) and community PHSMs (aOR: women=1.57, age=1.01, p<0.05). The factors that most affected adherence to personal PHSMs were: self-efficacy; trust in hospitals/health centres; knowledge about face masks; trust in the president; and gender. For community PHSMs they were: gender; trust in the president; access to running water; trust in hospitals/health centres; and risk perception.ConclusionsPsychosocial factors, particularly trust in authorities and institutions, played a critical role in PHSM adherence. Adherence to community PHSMs was lower than personal PHSMs since they can impose significant burdens, particularly on the socially vulnerable.

Given the current trends in incidence and underlying healthcare systems vulnerabilities, Africa could become the next epicenter of the COVID-19 pandemic. As the pandemic transitions to more widespread community transmission, how can the lessons learned thus far be consolidated to effectively curb the spread of COVID-19 while minimizing social disruption and negative humanitarian and economic consequences?

Summary Background Although the first wave of the COVID-19 pandemic progressed more slowly in Africa than the rest of the world, by December, 2020, the second wave appeared to be much more aggressive with many more cases. To date, the pandemic situation in all 55 African Union (AU) Member States has not been comprehensively reviewed. We aimed to evaluate reported COVID-19 epidemiology data to better understand the pandemic's progression in Africa. Methods We did a cross-sectional analysis between Feb 14 and Dec 31, 2020, using COVID-19 epidemiological, testing, and mitigation strategy data reported by AU Member States to assess trends and identify the response and mitigation efforts at the country, regional, and continent levels. We did descriptive analyses on the variables of interest including cumulative and weekly incidence rates, case fatality ratios (CFRs), tests per case ratios, growth rates, and public health and social measures in place. Findings As of Dec 31, 2020, African countries had reported 2 763 421 COVID-19 cases and 65 602 deaths, accounting for 3·4% of the 82 312 150 cases and 3·6% of the 1 798 994 deaths reported globally. Nine of the 55 countries accounted for more than 82·6% (2 283 613) of reported cases. 18 countries reported CFRs greater than the global CFR (2·2%). 17 countries reported test per case ratios less than the recommended ten to 30 tests per case ratio range. At the peak of the first wave in Africa in July, 2020, the mean daily number of new cases was 18 273. As of Dec 31, 2020, 40 (73%) countries had experienced or were experiencing their second wave of cases with the continent reporting a mean of 23 790 daily new cases for epidemiological week 53. 48 (96%) of 50 Member States had five or more stringent public health and social measures in place by April 15, 2020, but this number had decreased to 36 (72%) as of Dec 31, 2020, despite an increase in cases in the preceding month. Interpretation Our analysis showed that the African continent had a more severe second wave of the COVID-19 pandemic than the first, and highlights the importance of examining multiple epidemiological variables down to the regional and country levels over time. These country-specific and regional results informed the implementation of continent-wide initiatives and supported equitable distribution of supplies and technical assistance. Monitoring and analysis of these data over time are essential for continued situational awareness, especially as Member States attempt to balance controlling COVID-19 transmission with ensuring stable economies and livelihoods. Funding None.

History must not repeat itself — global and continental cooperation are essential. History must not repeat itself — global and continental cooperation are essential.

The heterogeneous epidemiological picture for COVID-19 in Africa continues to generate debate. Modelling projections raise speculation about the phases and trends of SARS-CoV-2 outbreaks across the continent and how these differ from outbreaks elsewhere.[1–4][1] Continental efforts drew praise in

Background We estimated the household secondary infection risk (SIR) and serial interval (SI) for influenza transmission from HIV-infected and HIV-uninfected index cases. Methods Index cases were the first symptomatic person in a household with influenza-like illness, testing influenza positive on real-time reverse transcription polymerase chain reaction (rRT-PCR). Nasopharyngeal swabs collected from household contacts every 4 days were tested by rRT-PCR. Factors associated with SIR were evaluated using logistic regression. Results We enrolled 28 HIV-infected and 57 HIV-uninfected index cases. On multivariable analysis, HIV-infected index cases were less likely to transmit influenza to household contacts (odds ratio [OR] 0.2; 95% confidence interval [CI], 0.1-0.6; SIR 16%, 18/113 vs 27%, 59/220). Factors associated with increased SIR included index age group 1-4 years (OR 3.6; 95% CI, 1.2-11.3) and 25-44 years (OR 8.0; 95% CI, 1.8-36.7), and contact age group 1-4 years (OR 3.5; 95% CI, 1.2-10.3) compared to 5-14 years, and sleeping with index case (OR 2.7; 95% CI, 1.3-5.5). HIV infection of index case was not associated with SI. Conclusions HIV-infection was not associated with SI. Increased infectiousness of HIV-infected individuals is likely not an important driver of community influenza transmission.

Background: Mathematical models have been used throughout the COVID-19 pandemic to inform policymaking decisions. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was established to provide country governments, particularly low- and middle-income countries (LMICs), and other model users with an overview of the aims, capabilities and limits of the main multi-country COVID-19 models to optimise their usefulness in the COVID-19 response. Methods: Seven models were identified that satisfied the inclusion criteria for the model comparison and had creators that were willing to participate in this analysis. A questionnaire, extraction tables and interview structure were developed to be used for each model, these tools had the aim of capturing the model characteristics deemed of greatest importance based on discussions with the Policy Group. The questionnaires were first completed by the CMCC Technical group using publicly available information, before further clarification and verification was obtained during interviews with the model developers. The fitness-for-purpose flow chart for assessing the appropriateness for use of different COVID-19 models was developed jointly by the CMCC Technical Group and Policy Group. Results: A flow chart of key questions to assess the fitness-for-purpose of commonly used COVID-19 epidemiological models was developed, with focus placed on their use in LMICs. Furthermore, each model was summarised with a description of the main characteristics, as well as the level of engagement and expertise required to use or adapt these models to LMIC settings. Conclusions: This work formalises a process for engagement with models, which is often done on an ad-hoc basis, with recommendations for both policymakers and model developers and should improve modelling use in policy decision making.

Supplemental Digital Content is available in the text., Background: Data on the epidemiology of viral-associated acute lower respiratory tract infection (LRTI) from high HIV prevalence settings are limited. We aimed to describe LRTI hospitalizations among South African children aged 7 days (OR: 3.8, 95% CI: 2.8–5.0) and had a higher case-fatality ratio (OR: 4.2, 95% CI: 2.6–6.8). In multivariable analysis, HIV-infection (OR: 3.7, 95% CI: 2.2–6.1), pneumococcal coinfection (OR: 2.4, 95% CI: 1.1–5.6), mechanical ventilation (OR: 6.9, 95% CI: 2.7–17.6) and receipt of supplemental-oxygen (OR: 27.3, 95% CI: 13.2–55.9) were associated with death. Conclusions: HIV-infection was associated with an increased risk of LRTI hospitalization and death. A viral pathogen, commonly RSV, was identified in a high proportion of LRTI cases.

Background Data on risk factors for influenza-associated hospitalizations in low- and middle-income countries are limited. Methods We conducted active syndromic surveillance for hospitalized severe acute respiratory illness (SARI) and outpatient influenza-like illness (ILI) in 2 provinces of South Africa during 2012–2015. We compared the characteristics of influenza-positive patients with SARI to those with ILI to identify factors associated with severe disease requiring hospitalization, using unconditional logistic regression. Results During the study period, influenza virus was detected in 5.9% (110 of 1861) and 15.8% (577 of 3652) of SARI and ILI cases, respectively. On multivariable analysis factors significantly associated with increased risk of influenza-associated SARI hospitalization were as follows: younger and older age ( Conclusions The risk groups identified in this study may benefit most from annual influenza immunization, and children

Local disease burden data are necessary to set national influenza vaccination policy. In 2010 the population of South Africa was 50 million and the HIV prevalence was 11%. We used a previously developed methodology to determine severe influenza burden in South Africa. Hospitalized severe acute respiratory illness (SARI) incidence was calculated, stratified by HIV status, for four age groups using data from population-based surveillance in one site situated in Gauteng Province for 2009-2011. These rates were adjusted for each of the remaining 8 provinces based on their prevalence of risk factors for pneumonia and healthcare-seeking behavior. We estimated non-hospitalized influenza-associated SARI from healthcare utilization surveys at two sites and used the percent of SARI cases positive for influenza from sentinel surveillance to derive the influenza-associated SARI rate. We applied rates of hospitalized and non-hospitalized influenza-associated SARI to census data to calculate the national number of cases. The percent of SARI cases that tested positive for influenza ranged from 7-17% depending on age group, year, province and HIV status. In 2010, there were an estimated 21,555 total severe influenza cases in HIV-uninfected individuals and 13,876 in HIV-infected individuals. In 2011, there were an estimated 29,892 total severe influenza cases in HIV-uninfected individuals and 17,289 in HIV-infected individuals. The incidence of influenza-associated SARI was highest in children

Objective There are few published studies describing severe acute respiratory illness ( SARI) epidemiology amongst older children and adults from high HIV-prevalence settings. We aimed to describe SARI epidemiology amongst individuals aged >= 5 years in South Africa. Methods We conducted prospective surveillance for individuals with SARI from 2009-2012. Using polymerase chain reaction, respiratory samples were tested for ten viruses, and blood for pneumococcal DNA. Cumulative annual SARI incidence was estimated at one site with population denominators. Findings We enrolled 7193 individuals, 9% (621/7067) tested positive for influenza and 9%(600/6519) for pneumococcus. HIV-prevalence was 74% (4663/6334). Among HIV-infected individuals with available data, 41% of 2629 were receiving antiretroviral therapy (ART). The annual SARI hospitalisation incidence ranged from 325-617/100,000 population. HIV-infected individuals experienced a 13-19 times greater SARI incidence than HIV-uninfected individuals (p7 days rather than = 5 years is high in South Africa. HIV-infected individuals are the most important risk group for SARI hospitalization and mortality in this setting.

Data on influenza epidemiology in HIV-infected persons are limited, particularly for sub-Saharan Africa, where HIV infection is widespread. We tested respiratory and blood samples from patients with acute lower respiratory tract infections hospitalized in South Africa during 2009-2011 for viral and pneumococcal infections. Influenza was identified in 9% (1,056/11,925) of patients enrolled; among influenza case-patients, 358 (44%) of the 819 who were tested were infected with HIV. Influenza-associated acute lower respiratory tract infection incidence was 4-8 times greater for HIV-infected (186-228/100,000) than for HIV-uninfected persons (26-54/100,000). Furthermore, multivariable analysis showed HIV-infected patients were more likely to have pneumococcal co-infection; to be infected with influenza type B compared with type A; to be hospitalized for 2-7 days or >7 days; and to die from their illness. These findings indicate that HIV-infected persons are at greater risk for severe illnesses related to influenza and thus should be prioritized for influenza vaccination.