ABSTRACT
Household transmission studies are useful to quantify SARS-CoV-2 transmission dynamics. We conducted a remote prospective household study to quantify transmission, and the effects of subject characteristics, household characteristics, and implemented infection control measures on transmission. Households with a laboratory-confirmed SARS-CoV-2 index case were enrolled < 48 h following test result. Follow-up included digitally daily symptom recording, regular nose-throat self-sampling and paired dried blood spots from all household members. Samples were tested for virus detection and SARS-CoV-2 antibodies. Secondary attack rates (SARs) and associated factors were estimated using logistic regression. In 276 households with 920 participants (276 index cases and 644 household members) daily symptom diaries and questionnaires were completed by 95%, and > 85% completed sample collection. 200 secondary SARS-CoV-2 infections were detected, yielding a household SAR of 45.7% (95% CI 39.7-51.7%) and per-person SAR of 32.6% (95%CI: 28.1-37.4%). 126 (63%) secondary cases were detected at enrollment. Mild (aRR = 0.57) and asymptomatic index cases (aRR = 0.29) were less likely to transmit SARS-CoV-2, compared to index cases with an acute respiratory illness (p = 0.03 for trend), and child index cases (< 12 years aRR = 0.60 and 12-18 years aRR = 0.85) compared to adults (p = 0.03 for trend). Infection control interventions in households had no significant effect on transmission. We found high SARs with the majority of transmissions occuring early after SARS-CoV-2 introduction into the household. This may explain the futile effect of implemented household measures. Age and symptom status of the index case influence secondary transmission. Remote, digitally-supported study designs with self-sampling are feasible for studying transmission under pandemic restrictions.
Subject(s)
COVID-19 , SARS-CoV-2 , Adult , COVID-19/epidemiology , Child , Family Characteristics , Humans , Pandemics/prevention & control , Prospective StudiesABSTRACT
BACKGROUND: Clinical findings do not accurately predict laboratory diagnosis of influenza. Early identification of influenza is considered useful for proper management decisions in primary care. OBJECTIVE: We evaluated the diagnostic value of the presence and the severity of symptoms for the diagnosis of laboratory-confirmed influenza infection among adults presenting with influenza-like illness (ILI) in primary care. METHODS: Secondary analysis of patients with ILI who participated in a clinical trial from 2015 to 2018 in 15 European countries. Patients rated signs and symptoms as absent, minor, moderate, or major problem. A nasopharyngeal swab was taken for microbiological identification of influenza and other microorganisms. Models were generated considering (i) the presence of individual symptoms and (ii) the severity rating of symptoms. RESULTS: A total of 2,639 patients aged 18 or older were included in the analysis. The mean age was 41.8 ± 14.7 years, and 1,099 were men (42.1%). Influenza was microbiologically confirmed in 1,337 patients (51.1%). The area under the curve (AUC) of the model for the presence of any of seven symptoms for detecting influenza was 0.66 (95% confidence interval [CI]: 0.65-0.68), whereas the AUC of the symptom severity model, which included eight variables-cough, fever, muscle aches, sweating and/or chills, moderate to severe overall disease, age, abdominal pain, and sore throat-was 0.70 (95% CI: 0.69-0.72). CONCLUSION: Clinical prediction of microbiologically confirmed influenza in adults with ILI is slightly more accurate when based on patient reported symptom severity than when based on the presence or absence of symptoms.
Influenza is usually diagnosed clinically. However, the accuracy of a diagnosis of influenza based on clinical features is limited because symptoms overlap considerably with those caused by other microorganisms. This study examined whether identification of the severity rather than the presence of key signs and symptoms could aid in the diagnosis of influenza, thereby helping clinicians to determine when antiviral agent use is appropriate. The authors used the database of a previous randomized clinical trial on the effectiveness of an antiviral carried out in primary care centers in 15 countries in Europe during three epidemic periods from 2015/2016 to 2017/2018. Participants with influenza symptoms were included and they were asked about the presence and severity of different symptoms during the baseline visit with their doctors and a nasopharyngeal swab was taken for microbiological analysis. Overall, only 51% of the patients aged 18 or older had a confirmed influenza infection. Clinical findings are not particularly useful for confirming or excluding the diagnosis of influenza. However, the results of our study recommend considering how intense the different symptoms are, since key symptoms rated as moderate or severe are slightly better for predicting flu rather than the presence or absence of these symptoms.
Subject(s)
Influenza, Human , Adult , Clinical Laboratory Techniques , Cough , Female , Fever , Humans , Influenza, Human/diagnosis , Influenza, Human/epidemiology , Male , Middle Aged , Primary Health CareABSTRACT
BACKGROUND: Achromobacter xylosoxidans is increasingly being recognized as an emerging pathogen in cystic fibrosis. Recent severe infections with A. xylosoxidans in some of our cystic fibrosis (CF) patients led to a re-evaluation of the epidemiology of CF-associated A. xylosoxidans infections in two Belgian reference centres (Antwerp and Ghent). Several of these patients also stayed at the Rehabilitation Centre De Haan (RHC). In total, 59 A. xylosoxidans isolates from 31 patients (including 26 CF patients), collected between 2001 and 2014, were studied. We evaluated Matrix Assisted Laser Desorption Ionisation -Time of Flight mass spectrometry (MALDI-TOF) as an alternative for McRAPD typing. RESULTS: Both typing approaches established the presence of a major cluster, comprising isolates, all from 21 CF patients, including from two patients sampled when staying at the RHC a decade ago. This major cluster was the same as the cluster established already a decade ago at the RHC. A minor cluster consisted of 13 isolates from miscellaneous origin. A further seven isolates, including one from a non-CF patient who had stayed recently at the RHC, were singletons. CONCLUSIONS: Typing results of both methods were similar, indicating transmission of a single clone of A. xylosoxidans among several CF patients from at least two reference centres. Isolates of the same clone were already observed at the RHC, a decade ago. It is difficult to establish to what extent the RHC is the source of transmission, because the epidemic strain was already present when the first epidemiological study in the RHC was carried out. This study also documents the applicability of MALDI-TOF for typing of strains within the species A. xylosoxidans and the need to use the dynamic cutoff algorithm of the BioNumerics® software for correct clustering of the fingerprints.