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1.
Influenza Other Respir Viruses ; 18(5): e13300, 2024 May.
Article in English | MEDLINE | ID: mdl-38666359

ABSTRACT

BACKGROUND: Identifying children at risk for severe COVID-19 disease from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may guide future mitigation interventions. Using sentinel surveillance data, we aimed to identify risk factors for SARS-CoV-2-associated hospitalisation among patients aged ≤ 18 years with respiratory illness. METHODS: From April 2020 to March 2022, patients meeting study case definitions were enrolled at four outpatient influenza-like illness (ILI) and five inpatient severe respiratory infection (SRI) surveillance sites and tested for SARS-CoV-2 infection using polymerase chain reaction (PCR). Each ILI clinic shared a catchment area with its corresponding SRI hospital. Potential risk factors for SARS-CoV-2-associated hospitalisation were analysed using multivariable logistic regression by comparing inpatient versus outpatient SARS-CoV-2 cases. RESULTS: Of 4688 participants aged ≤ 18 years, 4556 (97%) with complete PCR and HIV data were included in the analysis. Among patients with ILI and SRI, 92/1145 (8%) and 154/3411 (5%) tested SARS-CoV-2 positive, respectively. Compared to outpatients, hospitalised SARS-CoV-2 cases were associated with age < 6 months ([adjusted odds ratio (aOR) 8.0, 95% confidence interval (CI) 2.7-24.0] versus 1-4 years); underlying medical condition other than HIV [aOR 5.8, 95% CI 2.3-14.6]; laboratory-confirmed Omicron BA.1/BA.2 or Delta variant ([aOR 4.9, 95% CI 1.7-14.2] or [aOR 2.8, 95% CI 1.1-7.3] compared to ancestral SARS-CoV-2); and respiratory syncytial virus coinfection [aOR 6.2, 95% CI 1.0-38.5]. CONCLUSION: Aligning with previous research, we identified age < 6 months or having an underlying condition as risk factors for SARS-CoV-2-associated SRI hospitalisation and demonstrated the potential of sentinel surveillance to monitor COVID-19 in children.


Subject(s)
COVID-19 , Hospitalization , SARS-CoV-2 , Sentinel Surveillance , Humans , COVID-19/epidemiology , COVID-19/diagnosis , Adolescent , Child , Risk Factors , Male , Female , Child, Preschool , Hospitalization/statistics & numerical data , South Africa/epidemiology , Infant , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/virology , Infant, Newborn
2.
PLoS One ; 19(3): e0296810, 2024.
Article in English | MEDLINE | ID: mdl-38483886

ABSTRACT

Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age groups. Their estimation, however, is generally time and effort consuming and model-driven strategies to quantify the contacts are often needed. In this article we focus on household contact matrices, describing the contacts among the members of a family and develop a parametric model to describe them. This model combines demographic and easily quantifiable survey-based data and is tested on high resolution proximity data collected in two sites in South Africa. Given its simplicity and interpretability, we expect our method to be easily applied to other contexts as well and we identify relevant questions that need to be addressed during the data collection procedure.


Subject(s)
Epidemics , Metadata , Surveys and Questionnaires , Epidemiological Models , South Africa , Contact Tracing/methods
3.
J Pediatric Infect Dis Soc ; 12(12): 646-651, 2023 Dec 16.
Article in English | MEDLINE | ID: mdl-37952237

ABSTRACT

We enrolled 1323 hospitalized infants aged <1 year in 2016-2018, and examined the association between HIV status and in-hospital mortality. After controlling for confounders, HIV-exposed uninfected infants did not have an increased risk of mortality, whereas infants living with HIV had 4 times greater risk compared with HIV-uninfected infants.


Subject(s)
HIV Infections , Infant , Humans , HIV Infections/complications , South Africa/epidemiology , Hospital Mortality
4.
Elife ; 122023 07 18.
Article in English | MEDLINE | ID: mdl-37461328

ABSTRACT

Background: Households are an important location for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, especially during periods when travel and work was restricted to essential services. We aimed to assess the association of close-range contact patterns with SARS-CoV-2 transmission. Methods: We deployed proximity sensors for two weeks to measure face-to-face interactions between household members after SARS-CoV-2 was identified in the household, in South Africa, 2020-2021. We calculated the duration, frequency, and average duration of close-range proximity events with SARS-CoV-2 index cases. We assessed the association of contact parameters with SARS-CoV-2 transmission using mixed effects logistic regression accounting for index and household member characteristics. Results: We included 340 individuals (88 SARS-CoV-2 index cases and 252 household members). On multivariable analysis, factors associated with SARS-CoV-2 acquisition were index cases with minimum Ct value <30 (aOR 16.8 95% CI 3.1-93.1) vs >35, and female contacts (aOR 2.5 95% CI 1.3-5.0). No contact parameters were associated with acquisition (aOR 1.0-1.1) for any of the duration, frequency, cumulative time in contact, or average duration parameters. Conclusions: We did not find an association between close-range proximity events and SARS-CoV-2 household transmission. Our findings may be due to study limitations, that droplet-mediated transmission during close-proximity contacts plays a smaller role than airborne transmission of SARS-CoV-2 in the household, or due to high contact rates in households. Funding: Wellcome Trust (Grant number 221003/Z/20/Z) in collaboration with the Foreign, Commonwealth, and Development Office, United Kingdom.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Female , COVID-19/epidemiology , Family Characteristics , Travel , South Africa/epidemiology
5.
Open Forum Infect Dis ; 9(12): ofac578, 2022 Dec.
Article in English | MEDLINE | ID: mdl-36570970

ABSTRACT

Background: Data on risk factors for coronavirus disease 2019 (COVID-19)-associated hospitalization and mortality in high human immunodeficiency virus (HIV) prevalence settings are limited. Methods: Using 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 hospitalization and mortality. Results: From April 2020 through March 2022, severe acute respiratory syndrome coronavirus 2 was detected in 24.0% (660 of 2746) of outpatient and 32.5% (2282 of 7025) of inpatient cases. Factors associated with COVID-19-associated hospitalization included the following: 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, .3-.7) vs Delta variant and being fully vaccinated (aOR, 0.1; 95% CI, .1-.3) were less associated with COVID-19 hospitalization. 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 (aOR, 1.3; 95% CI, 1.0-1.6) and was lower in Omicron-infected (aOR, 0.3; 95% CI, .2-.6) vs Delta-infected individuals. Conclusions: Active 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 with HIV, especially severely immunosuppressed, should be prioritized for vaccination.

6.
Clin Infect Dis ; 75(1): e144-e156, 2022 08 24.
Article in English | MEDLINE | ID: mdl-35134129

ABSTRACT

BACKGROUND: We assessed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA shedding duration and magnitude among persons living with human immunodeficiency virus (HIV, PLHIV). METHODS: From May through December 2020, we conducted a prospective cohort study at 20 hospitals in South Africa. Adults hospitalized with symptomatic coronavirus disease 2019 (COVID-19) were enrolled and followed every 2 days with nasopharyngeal/oropharyngeal (NP/OP) swabs until documentation of cessation of SARS-CoV-2 shedding (2 consecutive negative NP/OP swabs). Real-time reverse transcription-polymerase chain reaction testing for SARS-CoV-2 was performed, and cycle-threshold (Ct) values < 30 were considered a proxy for high SARS-CoV-2 viral load. Factors associated with prolonged shedding were assessed using accelerated time-failure Weibull regression models. RESULTS: Of 2175 COVID-19 patients screened, 300 were enrolled, and 257 individuals (155 HIV-uninfected and 102 PLHIV) had > 1 swabbing visit (median 5 visits [range 2-21]). Median time to cessation of shedding was 13 days (interquartile range [IQR] 6-25) and did not differ significantly by HIV infection. Among a subset of 94 patients (41 PLHIV and 53 HIV-uninfected) with initial respiratory sample Ct-value < 30, median time of shedding at high SARS-CoV-2 viral load was 8 days (IQR 4-17). This was significantly longer in PLHIV with CD4 count < 200 cells/µL, compared to HIV-uninfected persons (median 27 days [IQR 8-43] vs 7 days [IQR 4-13]; adjusted hazard ratio [aHR] 0.14, 95% confidence interval [CI] .07-.28, P < .001), as well as in unsuppressed-HIV versus HIV-uninfected persons. CONCLUSIONS: Although SARS-CoV-2 shedding duration did not differ significantly by HIV infection, among a subset with high initial SARS-CoV-2 viral loads, immunocompromised PLHIV shed SARS-CoV-2 at high viral loads for longer than HIV-uninfected persons. Better HIV control may potentially decrease transmission time of SARS-CoV-2.


Subject(s)
COVID-19 , HIV Infections , Adult , HIV , HIV Infections/complications , HIV Infections/epidemiology , Humans , Prospective Studies , RNA, Viral , SARS-CoV-2 , South Africa/epidemiology , Viral Load , Virus Shedding
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