Characterising social contacts under COVID-19 control measures in Africa.

BACKGROUND: Early in the COVID-19 pandemic, countries adopted non-pharmaceutical interventions (NPIs) such as lockdowns to limit SARS-CoV-2 transmission. Social contact studies help measure the effectiveness of NPIs and estimate parameters for modelling SARS-CoV-2 transmission. However, few contact studies have been conducted in Africa. METHODS: We analysed nationally representative cross-sectional survey data from 19 African Union Member States, collected by the Partnership for Evidence-based Responses to COVID-19 (PERC) via telephone interviews at two time points (August 2020 and February 2021). Adult respondents reported contacts made in the previous day by age group, demographic characteristics, and their attitudes towards COVID-19. We described mean and median contacts across these characteristics and related contacts to Google Mobility reports and the Oxford Government Response Stringency Index for each country at the two time points. RESULTS: Mean reported contacts varied across countries with the lowest reported in Ethiopia (9, SD=16, median = 4, IQR = 8) in August 2020 and the highest in Sudan (50, SD=53, median = 33, IQR = 40) in February 2021. Contacts of people aged 18-55 represented 50% of total contacts, with most contacts in household and work or study settings for both surveys. Mean contacts increased for Ethiopia, Ghana, Liberia, Nigeria, Sudan, and Uganda and decreased for Cameroon, the Democratic Republic of Congo (DRC), and Tunisia between the two time points. Men had more contacts than women and contacts were consistent across urban or rural settings (except in Cameroon and Kenya, where urban respondents had more contacts than rural ones, and in Senegal and Zambia, where the opposite was the case). There were no strong and consistent variations in the number of mean or median contacts by education level, self-reported health, perceived self-reported risk of infection, vaccine acceptance, mask ownership, and perceived risk of COVID-19 to health. Mean contacts were correlated with Google mobility (coefficient 0.57, p=0.051 and coefficient 0.28, p=0.291 in August 2020 and February 2021, respectively) and Stringency Index (coefficient -0.12, p = 0.304 and coefficient -0.33, p=0.005 in August 2020 and February 2021, respectively). CONCLUSIONS: These are the first COVID-19 social contact data collected for 16 of the 19 countries surveyed. We find a high reported number of daily contacts in all countries and substantial variations in mean contacts across countries and by gender. Increased stringency and decreased mobility were associated with a reduction in the number of contacts. These data may be useful to understand transmission patterns, model infection transmission, and for pandemic planning.

Psychosocial determinants of adherence to public health and social measures (PHSMs) in 18 African Union Member States during the early phase of the COVID-19 pandemic: results of a cross-sectional survey.

OBJECTIVE: The 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. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: Nationally 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 MEASURES: Information 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. RESULTS: Adherence to PHSMs was high, with better adherence to personal than community PHSMs (65.5% vs 30.2%, p<0.05). Psychosocial measures were significantly associated with personal and community PHSMs (p<0.05). Women and older adults demonstrated better adherence to personal PHSMs (adjusted OR (aOR): women=1.43, age=1.01, p<0.05) and community PHSMs (aOR: women=1.57, age=1.01, p<0.05). Secondary education was associated with better adherence only to personal PHSMs (aOR=1.22, p<0.05). Rural residence and access to running water were associated with better adherence to community PHSMs (aOR=1.12 and 1.18, respectively, 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. CONCLUSIONS: Psychosocial 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.

Infodemics: A new challenge for public health.

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.

The first and second waves of the COVID-19 pandemic in Africa: a cross-sectional study.

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.

Healthcare seeking behaviour for common infectious syndromes among people in three administrative regions of Johannesburg, South Africa, 2015: a cross-sectional study.

INTRODUCTION: Hospital-based surveillance programs only capture people presenting to facilities and may underestimate disease burden. We conducted a healthcare utilisation survey to characterise healthcare-seeking behaviour among people with common infectious syndromes in the catchment areas of two sentinel surveillance hospitals in Johannesburg, South Africa. METHODS: A cross-sectional survey was conducted within three regions of Johannesburg from August to November 2015. Premises were randomly selected from an enumerated list with data collected on household demographics and selected syndromes using a structured questionnaire. Fisher's exact or chi-square tests were used to determine association of characteristics among different regions. RESULTS: Of 3650 selected coordinates, 3358 were eligible dwellings and 2930 (87%) households with 9850 individuals participated. Four percent of participants (431/9850) reported influenza-like illness (ILI) in the last 30 days; equal numbers of participants (0.2%, 20/9850) reported pneumonia or tuberculosis symptoms in the last year and <1% reported diarrhoea or meningitis symptoms. Sixty eight percent (295/431) of participants who reported ILI, 75% (6/8) of children with diarrhoea and all participants who reported pneumonia (20), tuberculosis (20) or meningitis (6) sought healthcare. For all syndromes most sought care at registered healthcare providers. Of these only 10% (24/237) attended sentinel hospitals, predominantly those that lived closer to the hospitals. In contrast, of patients with meningitis, 50% (3/6) sought care at sentinel hospitals. CONCLUSION: Patterns of seeking healthcare differed by syndrome and distance from facilities. Surveillance programs are still relevant in collecting information on infectious syndromes and reflect a proportion of the hospital's catchment area.

Household Transmission of Seasonal Influenza From HIV-Infected and HIV-Uninfected Individuals in South Africa, 2013-2014.

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.

Risk Factors for Influenza-Associated Severe Acute Respiratory Illness Hospitalization in South Africa, 2012-2015.

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 (<6 months [adjusted odds ratio {aOR}, 37.6], 6-11 months [aOR, 31.9], 12-23 months [aOR, 22.1], 24-59 months [aOR, 7.1], and ≥65 years [aOR, 40.7] compared with 5-24 years of age), underlying medical conditions (aOR, 4.5), human immunodeficiency virus infection (aOR, 4.3), and Streptococcus pneumoniae colonization density ≥1000 deoxyribonucleic acid copies/mL (aOR, 4.8). Underlying medical conditions in children aged <5 years included asthma (aOR, 22.7), malnutrition (aOR, 2.4), and prematurity (aOR, 4.8); in persons aged ≥5 years, conditions included asthma (aOR, 3.6), diabetes (aOR, 7.1), chronic lung diseases (aOR, 10.7), chronic heart diseases (aOR, 9.6), and obesity (aOR, 21.3). Mine workers (aOR, 13.8) and pregnant women (aOR, 12.5) were also at increased risk for influenza-associated hospitalization. CONCLUSIONS: The risk groups identified in this study may benefit most from annual influenza immunization, and children <6 months of age may be protected through vaccination of their mothers during pregnancy.

Determining the Provincial and National Burden of Influenza-Associated Severe Acute Respiratory Illness in South Africa Using a Rapid Assessment Methodology.

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 <5 years and was higher in HIV-infected than HIV-uninfected persons in all age groups. Influenza virus was associated with a substantial amount of severe disease, especially in young children and HIV-infected populations in South Africa.

Epidemiology of severe acute respiratory illness (SARI) among adults and children aged ≥5 years in a high HIV-prevalence setting, 2009-2012.

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 (p<0.001). On multivariable analysis, compared to HIV-uninfected individuals, HIV-infected individuals were more likely to be receiving tuberculosis treatment (odds ratio (OR):1.7; 95%CI:1.1-2.7), have pneumococcal infection (OR 2.4; 95%CI:1.7-3.3) be hospitalised for >7 days rather than <2 days (OR1.7; 95%CI:1.2-2.2) and had a higher case-fatality ratio (8% vs 5%;OR1.7; 95%CI:1.2-2.3), but were less likely to be infected with influenza (OR 0.6; 95%CI:0.5-0.8). On multivariable analysis, independent risk indicators associated with death included HIV infection (OR 1.8;95%CI:1.3-2.4), increasing age-group, receiving mechanical ventilation (OR 6.5; 95%CI:1.3-32.0) and supplemental-oxygen therapy (OR 2.6; 95%CI:2.1-3.2). CONCLUSION: The burden of hospitalized SARI amongst individuals aged ≥5 years is high in South Africa. HIV-infected individuals are the most important risk group for SARI hospitalization and mortality in this setting.

Epidemiology of viral-associated acute lower respiratory tract infection among children <5 years of age in a high HIV prevalence setting, South Africa, 2009-2012.

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 <5 years. METHODS: We prospectively enrolled hospitalized children with physician-diagnosed LRTI from 5 sites in 4 provinces from 2009 to 2012. Using polymerase chain reaction (PCR), nasopharyngeal aspirates were tested for 10 viruses and blood for pneumococcal DNA. Incidence was estimated at 1 site with available population denominators. RESULTS: We enrolled 8723 children aged <5 years with LRTI, including 64% <12 months. The case-fatality ratio was 2% (150/8512). HIV prevalence among tested children was 12% (705/5964). The overall prevalence of respiratory viruses identified was 78% (6517/8393), including 37% rhinovirus, 26% respiratory syncytial virus (RSV), 7% influenza and 5% human metapneumovirus. Four percent (253/6612) tested positive for pneumococcus. The annual incidence of LRTI hospitalization ranged from 2530 to 3173/100,000 population and was highest in infants (8446-10532/100,000). LRTI incidence was 1.1 to 3.0-fold greater in HIV-infected than HIV-uninfected children. In multivariable analysis, compared to HIV-uninfected children, HIV-infected children were more likely to require supplemental-oxygen [odds ratio (OR): 1.3, 95% confidence interval (CI): 1.1-1.7)], be hospitalized >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.

Severe influenza-associated respiratory infection in high HIV prevalence setting, South Africa, 2009-2011.

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.