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South Africa was among the first countries to detect the SARS-CoV-2 Omicron variant. Propelled by increased transmissibility and immune escape properties, Omicron displaced other globally circulating variants within 3 months of its emergence. Due to limited testing, Omicrons attenuated clinical severity, and an increased risk of reinfection, the size of the Omicron BA.1 and BA.2 subvariants (BA.1/2) wave remains poorly understood in South Africa and in many other countries. Using South African data from urban and rural cohorts closely monitored since the beginning of the pandemic, we analyzed sequential serum samples collected before, during, and after the Omicron BA.1/2 wave to infer infection rates and monitor changes in the immune histories of participants over time. Omicron BA.1/2 infection attack rates reached 65% (95% CI, 60% - 69%) in the rural cohort and 58% (95% CI, 61% - 74%) in the urban cohort, with repeat infections and vaccine breakthroughs accounting for >60% of all infections at both sites. Combined with previously collected data on pre-Omicron variant infections within the same cohorts, we identified 14 distinct categories of SARS-CoV-2 antigen exposure histories in the aftermath of the Omicron BA.1/2 wave, indicating a particularly fragmented immunologic landscape. Few individuals (<6%) remained naive to SARS-CoV-2 and no exposure history category represented over 25% of the population at either cohort site. Further, cohort participants were more than twice as likely to get infected during the Omicron BA.1/2 wave, compared to the Delta wave. Prior infection with the ancestral strain (with D614G mutation), Beta, and Delta variants provided 13% (95% CI, -21% - 37%), 34% (95% CI, 17% - 48%), and 51% (95% CI, 39% - 60%) protection against Omicron BA.1/2 infection, respectively. Hybrid immunity (prior infection and vaccination) and repeated prior infections (without vaccination) reduced the risks of Omicron BA.1/2 infection by 60% (95% CI, 42% - 72%) and 85% (95% CI, 76% - 92%) respectively. Reinfections and vaccine breakthroughs had 41% (95% CI, 26% - 53%) lower risk of onward transmission than primary infections. Our study sheds light on a rapidly shifting landscape of population immunity, along with the changing characteristics of SARS-CoV-2, and how these factors interact to shape the success of emerging variants. Our findings are especially relevant to populations similar to South Africa with low SARS-CoV-2 vaccine coverage and a dominant contribution of immunity from prior infection. Looking forward, the study provides context for anticipating the long-term circulation of SARS-CoV-2 in populations no longer naive to the virus.
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BackgroundData on risk factors for COVID-19-associated hospitalisation and mortality in high HIV prevalence settings are limited. MethodsUsing existing syndromic surveillance programs for influenza-like-illness and severe respiratory illness at sentinel sites in South Africa, we identified factors associated with COVID-19 hospitalisation and mortality. ResultsFrom April 2020 through March 2022, SARS-CoV-2 was detected in 24.0% (660/2746) of outpatient and 32.5% (2282/7025) of inpatient cases. Factors associated with COVID-19-associated hospitalisation included: older age (25-44 [adjusted odds ratio (aOR) 1.8, 95% confidence interval (CI) 1.1-2.9], 45-64 [aOR 6.8, 95%CI 4.2-11.0] and [≥]65 years [aOR 26.6, 95%CI 14.4-49.1] vs 15-24 years); black race (aOR 3.3, 95%CI 2.2-5.0); obesity (aOR 2.3, 95%CI 1.4-3.9); asthma (aOR 3.5, 95%CI 1.4-8.9); diabetes mellitus (aOR 5.3, 95%CI 3.1-9.3); HIV with CD4 [≥]200/mm3 (aOR 1.5, 95%CI 1.1-2.2) and CD4<200/mm3 (aOR 10.5, 95%CI 5.1-21.6) or tuberculosis (aOR 12.8, 95%CI 2.8-58.5). Infection with Beta (aOR 0.5, 95%CI 0.3-0.7) vs Delta variant and being fully vaccinated (aOR 0.1, 95%CI 0.1-0.3) were less associated with COVID-19 hospitalisation. In-hospital mortality was increased in older age (45-64 years [aOR 2.2, 95%CI 1.6-3.2] and [≥]65 years [aOR 4.0, 95%CI 2.8-5.8] vs 25-44 years) and male sex (aOR1.3, 95%CI 1.0-1.6) and was lower in Omicron -infected (aOR 0.3, 95%CI 0.2-0.6) vs Delta-infected individuals. ConclusionActive syndromic surveillance encompassing clinical, laboratory and genomic data identified setting-specific risk factors associated with COVID-19 severity that will inform prioritization of COVID-19 vaccine distribution. Elderly, people with tuberculosis or people living with HIV, especially severely immunosuppressed should be prioritised for vaccination. Summary of articles viewpointCompared to the Delta variant, the Omicron variant was associated with reduced risk of mortality and Beta associated with decreased risk of hospitalisation. Active syndromic surveillance combining clinical, laboratory and genomic data can be used to describe the epidemic timing, epidemiological characteristics of cases, early detection of variants of concern and how these impact disease severity and outcomes; and presents a viable surveillance approach in settings where national surveillance is not possible.
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In response to the COVID-19 pandemic, the South African government employed various nonpharmaceutical interventions (NPIs) in order to reduce the spread of SARS-CoV-2. In addition to mitigating transmission of SARS-CoV-2, these public health measures have also functioned in slowing the spread of other endemic respiratory pathogens. Surveillance data from South Africa indicates low circulation of respiratory syncytial virus (RSV) throughout the 2020-2021 Southern Hemisphere winter seasons. Here we fit age-structured epidemiological models to national surveillance data to predict the 2022 RSV outbreak following two suppressed seasons. We project a 32% increase in the peak number of monthly hospitalizations among infants [≤] 2 years, with older infants (6-23 month olds) experiencing a larger portion of severe disease burden than typical. Our results suggest that hospital system readiness should be prepared for an intense RSV season in early 2022.
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By November 2021, after the third SARS-CoV-2 wave in South Africa, seroprevalence was 60% (95%CrI 56%-64%) in a rural and 70% (95%CrI 56%-64%) in an urban community; highest in individuals aged 13-18 years. High seroprevalence prior to Omicron emergence may have contributed to reduced severity observed in the 4th wave. Article Summary LineIn South Africa, after a third wave of SARS-CoV-2 infections, seroprevalence was 60% in a rural and 70% in an urban community, with case-to-infection, - hospitalization and -fatality ratios similar to the second wave.
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Understanding the build-up of immunity with successive SARS-CoV-2 variants and the epidemiological conditions that favor rapidly expanding epidemics will facilitate future pandemic control. High-resolution infection and serology data from longitudinal household cohorts in South Africa reveal high cumulative infection rates and durable cross-protective immunity conferred by prior infection in the pre-Omicron era. Building on the cohorts history of past exposures to different SARS-CoV-2 variants and vaccination, we use mathematical models to explore the fitness advantage of the Omicron variant and its epidemic trajectory. Modelling suggests the Omicron wave infected a large fraction of the population, leaving a complex landscape of population immunity primed and boosted with antigenically distinct variants. Future SARS-CoV-2 resurgences are likely under a range of scenarios of viral characteristics, population contacts, and residual cross-protection. One Sentence SummaryClosely monitored population in South Africa reveal high cumulative infection rates and durable protection by prior infection against pre-Omicron variants. Modelling indicates that a large fraction of the population has been infected with Omicron; yet epidemic resurgences are plausible under a wide range of epidemiologic scenarios.
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BackgroundBy August 2021, South Africa experienced three SARS-CoV-2 waves; the second and third associated with emergence of Beta and Delta variants respectively. MethodsWe conducted a prospective cohort study during July 2020-August 2021 in one rural and one urban community. Mid-turbinate nasal swabs were collected twice-weekly from household members irrespective of symptoms and tested for SARS-CoV-2 using real-time reverse transcription polymerase chain reaction (rRT-PCR). Serum was collected every two months and tested for anti-SARS-CoV-2 antibodies. ResultsAmong 115,759 nasal specimens from 1,200 members (follow-up rate 93%), 1976 (2%) were SARS-CoV-2-positive. By rRT-PCR and serology combined, 62% (749/1200) of individuals experienced [≥]1 SARS-CoV-2 infection episode, and 12% (87/749) experienced reinfection. Of 662 PCR-confirmed episodes with available data, 15% (n=97) were associated with [≥]1 symptom. Among 222 households, 200 (90%) had [≥]1 SARS-CoV-2-positive individual. Household cumulative infection risk (HCIR) was 25% (213/856). On multivariable analysis, accounting for age and sex, index case lower cycle threshold value (OR 3.9, 95%CI 1.7-8.8), urban community (OR 2.0,95%CI 1.1-3.9), Beta (OR 4.2, 95%CI 1.7-10.1) and Delta (OR 14.6, 95%CI 5.7-37.5) variant infection were associated with increased HCIR. HCIR was similar for symptomatic (21/110, 19%) and asymptomatic (195/775, 25%) index cases (p=0.165). Attack rates were highest in individuals aged 13-18 years and individuals in this age group were more likely to experience repeat infections and to acquire SARS-CoV-2 infection. People living with HIV who were not virally supressed were more likely to develop symptomatic illness, and shed SARS-CoV-2 for longer compared to HIV-uninfected individuals. ConclusionsIn this study, 85% of SARS-CoV-2 infections were asymptomatic and index case symptom status did not affect HCIR, suggesting a limited role for control measures targeting symptomatic individuals. Increased household transmission of Beta and Delta variants, likely contributed to successive waves, with >60% of individuals infected by the end of follow-up. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have generated wide-ranging estimates of the proportion of SARS-CoV-2 infections which are asymptomatic. A recent systematic review found that 20% (95% CI 3%-67%) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections remained asymptomatic throughout infection and that transmission from asymptomatic individuals was reduced. A systematic review and meta-analysis of 87 household transmission studies of SARS-CoV-2 found an estimated secondary attack rate of 19% (95% CI 16-22). The review also found that household secondary attack rates were increased from symptomatic index cases and that adults were more likely to acquire infection. As of December 2021, South Africa experienced three waves of SARS-CoV-2 infections; the second and third waves were associated with circulation of Beta and Delta variants respectively. SARS-CoV-2 vaccines became available in February 2021, but uptake was low in study sites reaching 5% fully vaccinated at the end of follow up. Studies to quantify the burden of asymptomatic infections, symptomatic fraction, reinfection frequency, duration of shedding and household transmission of SARS-CoV-2 from asymptomatically infected individuals have mostly been conducted as part of outbreak investigations or in specific settings. Comprehensive systematic community studies of SARS-CoV-2 burden and transmission including for the Beta and Delta variants are lacking, especially in low vaccination settings. Added value of this studyWe conducted a unique detailed COVID-19 household cohort study over a 13 month period in South Africa, with real time reverse transcriptase polymerase chain reaction (rRT-PCR) testing twice a week irrespective of symptoms and bimonthly serology. By the end of the study in August 2021, 749 (62%) of 1200 individuals from 222 randomly sampled households in a rural and an urban community in South Africa had at least one confirmed SARS-CoV-2 infection, detected on rRT-PCR and/or serology, and 12% (87/749) experienced reinfection. Symptom data were analysed for 662 rRT-PCR-confirmed infection episodes that occurred >14 days after the start of follow-up (of a total of 718 rRT-PCR-confirmed episodes), of these, 15% (n=97) were associated with one or more symptoms. Among symptomatic indvidiausl, 9% (n=9) were hospitalised and 2% (n=2) died. Ninety percent (200/222) of included households, had one or more individual infected with SARS-CoV-2 on rRT-PCR and/or serology within the household. SARS-CoV-2 infected index cases transmitted the infection to 25% (213/856) of susceptible household contacts. Index case ribonucleic acid (RNA) viral load proxied by rRT-PCR cycle threshold value was strongly predictive of household transmission. Presence of symptoms in the index case was not associated with household transmission. Household transmission was four times greater from index cases infected with Beta variant and fifteen times greater from index cases infected with Delta variant compared to wild-type infection. Attack rates were highest in individuals aged 13-18 years and individuals in this age group were more likely to experience repeat infections and to acquire SARS-CoV-2 infection within households. People living with HIV (PLHIV) who were not virally supressed were more likely to develop symptomatic illness when infected with SARS-CoV-2, and shed SARS-CoV-2 for longer when compared to HIV-uninfected individuals. Implications of all the available evidenceWe found a high rate of SARS-CoV-2 infection in households in a rural community and an urban community in South Africa, with the majority of infections being asymptomatic in individuals of all ages. Asymptomatic individuals transmitted SARS-CoV-2 at similar levels to symptomatic individuals suggesting that interventions targeting symptomatic individuals such as symptom-based testing and contact tracing of individuals tested because they report symptoms may have a limited impact as control measures. Increased household transmission of Beta and Delta variants, likely contributed to recurrent waves of COVID-19, with >60% of individuals infected by the end of follow-up. Higher attack rates, reinfection and acquisition in adolescents and prolonged SARS-CoV-2 shedding in PLHIV who were not virally suppressed suggests that prioritised vaccination of individuals in these groups could impact community transmission.
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BackgroundSARS-CoV-2 infections may be underestimated due to limited testing access, particularly in sub-Saharan Africa. South Africa experienced two SARS-CoV-2 waves, the second associated with emergence of variant 501Y.V2. In this study, we report longitudinal SARS-CoV-2 seroprevalence in cohorts in two communities in South Africa. MethodsWe measured SARS-CoV-2 seroprevalence two monthly in randomly selected household cohorts in a rural and an urban community (July 2020-March 2021). We compared seroprevalence to laboratory-confirmed infections, hospitalisations and deaths reported in the districts to calculate infection-case (ICR), infection-hospitalisation (IHR) and infection-fatality ratio (IFR) in the two waves of infection. FindingsSeroprevalence after the second wave ranged from 18% (95%CrI 10-26%) and 28% (95%CrI 17-41%) in children <5 years to 37% (95%CrI 28-47%) in adults aged 19-34 years and 59% (95%CrI 49-68%) in adults aged 35-59 years in the rural and urban community respectively. Individuals infected in the second wave were more likely to be from the rural site (aOR 4.7, 95%CI 2.9-7.6), and 5-12 years (aOR 2.1, 95%CI 1.1-4.2) or [≥]60 years (aOR 2.8, 95%CI 1.1-7.0), compared to 35-59 years. The in-hospital IFR in the urban site was significantly increased in the second wave 0.36% (95%CI 0.28-0.57%) compared to the first wave 0.17% (95%CI 0.15-0.20%). ICR ranged from 3.69% (95%CI 2.59-6.40%) in second wave at urban community, to 5.55% (95%CI 3.40-11.23%) in first wave in rural community. InterpretationThe second wave was associated with a shift in age distribution of cases from individuals aged to 35-59 to individuals at the extremes of age, higher attack rates in the rural community and a higher IFR in the urban community. Approximately 95% of SARS-CoV-2 infections in these two communities were not reported to the national surveillance system, which has implications for contact tracing and infection containment. FundingUS Centers for Disease Control and Prevention Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSeroprevalence studies provide better estimates of SARS-CoV-2 burden than laboratory-confirmed cases because many infections may be missed due to restricted access to care and testing, or differences in disease severity and health-care seeking behaviour. This underestimation may be amplified in African countries, where testing access may be limited. Seroprevalence data from sub-Saharan Africa are limited, and comparing seroprevalence estimates between countries can be challenging because populations studied and timing of the study relative to country-specific epidemics differs. During the first wave of infections in each country, seroprevalence was estimated at 4% in Kenya and 11% in Zambia. Seroprevalence estimates in South African blood donors is estimated to range between 32% to 63%. South Africa has experienced two waves of infection, with the emergence of the B.1.351/501Y.V2 variant of concern after the first wave. Reported SARS-CoV-2 cases may not be a true reflection of SARS-CoV-2 burden and specifically the differential impact of the first and second waves of infection. Added value of this studyWe collected longitudinal blood samples from prospectively followed rural and urban communities, randomly selected, household cohorts in South Africa between July 2020 and March 2021. From 668 and 598 individuals included from the rural and urban communities, respectively, seroprevalence was found to be 7% (95%CrI 5-9%) and 27% (95%CrI 23-31%), after the first wave of infection, and 26% (95%CrI 22-29%) and 41% (95%CrI 37-45%) after the second wave, in rural and urban study districts, respectively. After standardising for age, we estimated that only 5% of SARS-CoV-2 infections were laboratory-confirmed and reported. Infection-hospitalisation ratios in the urban community were higher in the first (2.01%, 95%CI 1.57-2.57%) and second (2.29%, 95%CI 1.63-3.94%) wave than the rural community where there was a 0.75% (95%CI 0.49-1.41%) and 0.66% (95%CI 0.50-0.98%) infection-hospitalisation ratio in the first and second wave, respectively. When comparing the infection fatality ratios for the first and second SARS-CoV-2 waves, at the urban site, the ratios for both in-hospital and excess deaths to cases were significantly higher in the second wave (0.36%, 95%CI 0.28-0.57% in-hospital and 0.51%, 95%CI 0.34-0.93% excess deaths), compared to the first wave in-hospital (0.17%, 95%CI 0.15-0.20%) and excess (0.13%, 95%CI 0.10-0.17%) fatality ratios, p<0.001 and p<0.001, respectively). In the rural community, the point estimates for infection-fatality ratios also increased in the second wave compared to the first wave for in-hospital deaths, 0.13% (95%CI 0.10-0.23%) first wave vs 0.20% (95%CI 0.13%-0.28%) second wave, and excess deaths (0.51%, 95%CI 0.30-1.06% vs 0.70%, 95%CI 0.49-1.12%), although neither change was statistically significant. Implications of all the available evidenceIn South Africa, the overall prevalence of SARS-CoV-2 infections is substantially underestimated, resulting in many cases being undiagnosed and without the necessary public health action to isolate and trace contacts to prevent further transmission. There were more infections during the first wave in the urban community, and the second wave in the rural community. Although there were less infections during the second wave in the urban community, the infection-fatality ratios were significantly higher compared to the first wave. The lower infection-hospitalisation ratio and higher excess infection-fatality ratio in the rural community likely reflect differences in access to care or prevalence of risk factors for progression to severe disease in these two communities. In-hospital infection-fatality ratios for both communities during the first wave were comparable with what was experienced during the first wave in India (0.15%) for SARS-CoV-2 confirmed deaths. To our knowledge, these are the first longitudinal seroprevalence data from a sub-Saharan Africa cohort, and provide a more accurate understanding of the pandemic, allowing for serial comparisons of antibody responses in relation to reported laboratory-confirmed SARS-CoV-2 infections within diverse communities.