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1.
Clin Infect Dis ; 73(4): e976-e980, 2021 08 16.
Article in English | MEDLINE | ID: mdl-33575791

ABSTRACT

BACKGROUND: The Democratic Republic of the Congo (DRC) has one of the highest neonatal death rates (between 14% and 28%) in the world. In the DRC, neonatal sepsis causes 15.6% of this mortality, but data on the bacterial etiology and associated drug susceptibility are lacking. METHODS: Hemocultures of 150 neonates with possible early-onset neonatal sepsis (pEOS) were obtained at the Hôpital Provincial Général de Référence de Bukavu (Bukavu, DRC). The newborns with pEOS received an empirical first-line antimicrobial treatment (ampicillin, cefotaxime, and gentamicin) based on the synopsis of international guidelines for the management of EOS that are in line with World Health Organization (WHO) recommendations. Isolates were identified using matrix-assisted laser desorption/ ionization time-of-flight mass spectrophotometry. Antibiotic resistance was assessed using the disk diffusion method. RESULTS: Fifty strains were obtained from 48 patients and identified. The 3 most prevalent species were Enterobacter cloacae complex (42%), Klebsiella pneumoniae (18%), and Serratia marcescens (12%). Enterobacter cloacae isolates were resistant to all first-line antibiotics. All K. pneumoniae and S. marcescens isolates were resistant to ampicillin, and the majority of the K. pneumoniae and half of the S. marcescens isolates were resistant to both cefotaxime and gentamicin. All E. cloacae complex strains, 89% of K. pneumoniae, and half of S. marcescens had an extended-spectrum ß-lactamase phenotype. CONCLUSIONS: The most prevalent pathogens causing EOS in Bukavu were E. cloacae complex, K. pneumoniae, and S. marcescens. Most of these isolates were resistant to the WHO-recommended antibiotics.


Subject(s)
Neonatal Sepsis , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Democratic Republic of the Congo/epidemiology , Drug Resistance, Microbial , Humans , Infant, Newborn , Klebsiella pneumoniae , Microbial Sensitivity Tests , Neonatal Sepsis/drug therapy , Neonatal Sepsis/epidemiology , beta-Lactamases
2.
Viruses ; 16(9)2024 Sep 14.
Article in English | MEDLINE | ID: mdl-39339937

ABSTRACT

(1) Background: early in the COVID-19 pandemic, reverse transcription polymerase chain reaction (RT-PCR) testing was limited. Assessing seroprevalence helps understand prevalence and reinfection risk. However, such data are lacking for the first epidemic wave in Belgian nursing homes. Therefore, we assessed SARS-CoV-2 seroprevalence and cumulative RT-PCR positivity in Belgian nursing homes and evaluated reinfection risk. (2) Methods: we performed a cross-sectional study in nine nursing homes in April and May 2020. Odds ratios (ORs) were calculated to compare the odds of (re)infection between seropositive and seronegative participants. (3) Results: seroprevalence was 21% (95% CI: 18-23): 22% (95% CI: 18-25) in residents and 20% (95% CI: 17-24) in staff. By 20 May 2020, cumulative RT-PCR positivity was 16% (95% CI: 13-21) in residents and 8% (95% CI: 6-12) in staff. ORs for (re)infection in seropositive (compared to seronegative) residents and staff were 0.22 (95% CI: 0.06-0.72) and 3.15 (95% CI: 1.56-6.63), respectively. (4) Conclusion: during the first wave, RT-PCR test programmes underestimated the number of COVID-19 cases. The reinfection rate in residents was 3%, indicating protection, while it was 21% in staff, potentially due to less cautious health behaviour. Future outbreaks should use both RT-PCR and serological testing for complementary insights into transmission dynamics.


Subject(s)
COVID-19 , Nursing Homes , SARS-CoV-2 , Humans , Belgium/epidemiology , COVID-19/epidemiology , COVID-19/transmission , COVID-19/virology , Nursing Homes/statistics & numerical data , Seroepidemiologic Studies , SARS-CoV-2/immunology , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Female , Male , Cross-Sectional Studies , Aged , Middle Aged , Aged, 80 and over , Antibodies, Viral/blood , Adult , Reinfection/epidemiology , Reinfection/virology , Health Personnel/statistics & numerical data , COVID-19 Serological Testing , Prevalence
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