SARS-CoV-2 superspreading occurs when transmission is highly efficient and/or an individual infects many others, contributing to rapid spread. To better quantify heterogeneity in SARS-CoV-2 transmission, particularly superspreading, we performed a systematic review of transmission events with data on secondary attack rates or contact tracing of individual index cases published before September 2021 prior to the emergence of variants of concern and widespread vaccination. We reviewed 592 distinct events and 9,883 index cases from 491 papers. A meta-analysis of secondary attack rates identified substantial heterogeneity across 12 chosen event types/settings, with the highest transmission (25–35%) in co-living situations including households, nursing homes, and other congregate housing. Among index cases, 67% reported zero secondary cases and only 3% (287) infected >5 secondary cases (“superspreaders”). Index case demographic data were limited, with only 55% of individuals reporting age, sex, symptoms, real-time polymerase chain reaction (PCR) cycle threshold values, or total contacts. With the data available, we identified a higher percentage of superspreaders among symptomatic individuals, individuals aged 49–64 years, and individuals with over 100 total contacts. Addressing gaps in the literature regarding transmission events and contact tracing is needed to properly explain the heterogeneity in transmission and facilitate control efforts for SARS-CoV-2 and other infections.

Nontuberculous mycobacteria (NTM) is a large group of mycobacteria other than the Mycobacterium tuberculosis complex and Mycobacterium leprae. Epidemiological investigations have found that the incidence of NTM infections is increasing in China, and it is naturally resistant to many antibiotics. Therefore, studies of NTM species in clinical isolates are useful for understanding the epidemiology of NTM infections. The present study aimed to investigate the incidence of NTM infections and types of NTM species. Of the 420 samples collected, 285 were positive for M. tuberculosis, 62 samples were negative, and the remaining 73 samples contained NTM, including 35 (8.3%) only NTM and 38 (9%) mixed (M. tuberculosis and NTM). The most prevalent NTM species were Mycobacterium intracellulare (30.1%), followed by Mycobacterium abscessus (15%) and M. triviale (12%). M. gordonae infection was detected in 9.5% of total NTM-positive cases. Moreover, this study reports the presence of Mycobacterium nonchromogenicum infection and a high prevalence of M. triviale for the first time in Henan. M. intracellulare is the most prevalent, accompanied by some emerging NTM species, including M. nonchromogenicum and a high prevalence of M. triviale in Henan Province. Monitoring NTM transmission and epidemiology could enhance mycobacteriosis management in future.

During the COVID-19 pandemic in Germany, a variety of societal activities were restricted to minimize direct personal interactions and, consequently, reduce SARS-CoV-2 transmission. The aim of the CoViRiS study was to investigate whether certain behaviours and societal factors were associated with the risk of sporadic symptomatic SARS-CoV-2 infections. Adult COVID-19 cases and frequency-matched population controls were interviewed by telephone regarding activities that involved contact with other people during the 10 days before illness onset (cases) or before the interview (controls). Associations between activities and symptomatic SARS-CoV-2 infection were analysed using logistic regression models adjusted for potential confounding variables. Data of 859 cases and 1 971 controls were available for analysis. The risk of symptomatic SARS-CoV-2 infection was lower for individuals who worked from home (adjusted odds ratio (aOR) 0.5; 95% confidence interval (CI) 0.3–0.6). Working in a health care setting was associated with a higher risk (aOR: 1.5; 95% CI: 1.1–2.1) as were private indoor contacts, personal contacts that involved shaking hands or hugging, and overnight travelling within Germany. Our results are in line with some of the public health recommendations aimed at reducing interpersonal contacts during the COVID-19 pandemic.

Malaria is endemic in Guinea; however, the extent and role in transmission of asymptomatic malaria are not well understood. In May 2023, we conducted a rapid community survey to determine Plasmodium falciparum (P. falciparum) prevalence among asymptomatic individuals in Middle Guinea (Prefecture Dalaba) and Forest Guinea (Prefecture Guéckédou). In Dalaba, 6 of 239 (2.1%, confidence interval (CI) 0.9–4.8%) individuals tested positive for P. falciparum by a rapid diagnostic test (RDT), while in Guéckédou, 147 of 235 (60.9%, CI 54.5–66.9%) participants tested positive. Asymptomatic malaria needs to be considered more strongly as a driver of transmission when designing control strategies, especially in Forest Guinea and potentially other hyper-endemic settings.

Genomic epidemiology is routinely used worldwide to interrogate infectious disease dynamics. Multiple computational tools exist that reconstruct transmission networks by coupling genomic data with epidemiological models. Resulting inferences can improve our understanding of pathogen transmission dynamics, and yet the performance of these tools has not been evaluated for tuberculosis (TB), a disease process with complex epidemiology including variable latency and within-host heterogeneity. Here, we performed a systematic comparison of six publicly available transmission reconstruction models, evaluating their accuracy when predicting transmission events in simulated and real-world Mycobacterium tuberculosis outbreaks. We observed variability in the number of transmission links that were predicted with high probability (P ≥ 0.5) and low accuracy of these predictions against known transmission in simulated outbreaks. We also found a low proportion of epidemiologically supported case–contact pairs were identified in our real-world TB clusters. The specificity of all models was high, and a relatively high proportion of the total transmission events predicted by some models were true links, notably with TransPhylo, Outbreaker2, and Phybreak. Our findings may inform the choice of tools in TB transmission analyses and underscore the need for caution when interpreting transmission networks produced using probabilistic approaches.

Severe infections and psychiatric disorders have a large impact on both society and the individual. Studies investigating these conditions and the links between them are therefore important. Most past studies have focused on binary phenotypes of particular infections or overall infection, thereby losing some information regarding susceptibility to infection as reflected in the number of specific infection types, or sites, which we term infection load. In this study we found that infection load was associated with increased risk for attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, schizophrenia and overall psychiatric diagnosis. We obtained a modest but significant heritability for infection load (h2 = 0.0221), and a high degree of genetic correlation between it and overall psychiatric diagnosis (rg = 0.4298). We also found evidence supporting a genetic causality for overall infection on overall psychiatric diagnosis. Our genome-wide association study for infection load identified 138 suggestive associations. Our study provides further evidence for genetic links between susceptibility to infection and psychiatric disorders, and suggests that a higher infection load may have a cumulative association with psychiatric disorders, beyond what has been described for individual infections.

Surveillance is a key public health function to enable early detection of infectious disease events and inform public health action. Data linkage may improve the depth of data for response to infectious disease events. This study aimed to describe the uses of linked data for infectious disease events. A systematic review was conducted using Pubmed, CINAHL and Web of Science. Studies were included if they used data linkage for an acute infectious disease event (e.g. outbreak of disease). We summarised the event, study aims and designs; data sets; linkage methods; outcomes reported; and benefits and limitations. Fifty-four studies were included. Uses of linkage for infectious disease events included assessment of severity of disease and risk factors; improved case finding and contact tracing; and vaccine uptake, safety and effectiveness. The ability to conduct larger scale population level studies was identified as a benefit, in particular for rarer exposures, risk factors or outcomes. Limitations included timeliness, data quality and inability to collect additional variables. This review demonstrated multiple uses of data linkage for infectious disease events. As infectious disease events occur without warning, there is a need to establish pre-approved protocols and the infrastructure for data-linkage to enhance information available during an event.

Our study population consisted of all children and adolescents, with laboratory-confirmed SARS-Co-V-2 infection, hospitalised from February 2020 through February 2022, among residents of the Tel Aviv (TA) District, Israel. There were 491 children and adolescents hospitalised with Sars-CoV-2 infection. Among them, 281 (57%) admitted with coronavirus disease 2019 (COVID-19) as the primary cause of admission (rate of 39 per 100 000). Among all children and adolescents in the TA District, the highest hospitalisation rates were observed among infants and children below the age of 4 years (rate of 311 per 100 000 population). Severe disease was observed mostly among children with multiple underlying medical conditions. Admission rates were also elevated among residents of the ultra-orthodox community (rate ratio (RR) compared to the rest of the district; 95% confidence interval (CI) 2.38–3.82). Admission rates with COVID-19 as primary cause of admission were higher during Omicron compared to Delta predominance period (RR 1.7; 95% CI 1.22–2.32). Targeted social and public health policies should be put in place when rates of disease start to increase, such as encouraging vaccine uptake for eligible children and social distancing when necessary, taking into account already existing social and learning gaps, in order to reduce the burden of disease.

New SARS-CoV-2 variants causing COVID-19 are a major risk to public health worldwide due to the potential for phenotypic change and increases in pathogenicity, transmissibility and/or vaccine escape. Recognising signatures of new variants in terms of replacing growth and severity are key to informing the public health response. To assess this, we aimed to investigate key time periods in the course of infection, hospitalisation and death, by variant. We linked datasets on contact tracing (Contact Tracing Advisory Service), testing (the Second-Generation Surveillance System) and hospitalisation (the Admitted Patient Care dataset) for the entire length of contact tracing in the England – from March 2020 to March 2022. We modelled, for England, time delay distributions using a Bayesian doubly interval censored modelling approach for the SARS-CoV-2 variants Alpha, Delta, Delta Plus (AY.4.2), Omicron BA.1 and Omicron BA.2. This was conducted for the incubation period, the time from infection to hospitalisation and hospitalisation to death. We further modelled the growth of novel variant replacement using a generalised additive model with a negative binomial error structure and the relationship between incubation period length and the risk of a fatality using a Bernoulli generalised linear model with a logit link. The mean incubation periods for each variant were: Alpha 4.19 (95% credible interval (CrI) 4.13–4.26) days; Delta 3.87 (95% CrI 3.82–3.93) days; Delta Plus 3.92 (95% CrI 3.87–3.98) days; Omicron BA.1 3.67 (95% CrI 3.61–3.72) days and Omicron BA.2 3.48 (95% CrI 3.43–3.53) days. The mean time from infection to hospitalisation was for Alpha 11.31 (95% CrI 11.20–11.41) days, Delta 10.36 (95% CrI 10.26–10.45) days and Omicron BA.1 11.54 (95% CrI 11.38–11.70) days. The mean time from hospitalisation to death was, for Alpha 14.31 (95% CrI 14.00–14.62) days; Delta 12.81 (95% CrI 12.62–13.00) days and Omicron BA.2 16.02 (95% CrI 15.46–16.60) days. The 95th percentile of the incubation periods were: Alpha 11.19 (95% CrI 10.92–11.48) days; Delta 9.97 (95% CrI 9.73–10.21) days; Delta Plus 9.99 (95% CrI 9.78–10.24) days; Omicron BA.1 9.45 (95% CrI 9.23–9.67) days and Omicron BA.2 8.83 (95% CrI 8.62–9.05) days. Shorter incubation periods were associated with greater fatality risk when adjusted for age, sex, variant, vaccination status, vaccination manufacturer and time since last dose with an odds ratio of 0.83 (95% confidence interval 0.82–0.83) (P value < 0.05). Variants of SARS-CoV-2 that have replaced previously dominant variants have had shorter incubation periods. Conversely co-existing variants have had very similar and non-distinct incubation period distributions. Shorter incubation periods reflect generation time advantage, with a reduction in the time to the peak infectious period, and may be a significant factor in novel variant replacing growth. Shorter times for admission to hospital and death were associated with variant severity – the most severe variant, Delta, led to significantly earlier hospitalisation, and death. These measures are likely important for future risk assessment of new variants, and their potential impact on population health.

The rubella disease burden in Zambia may be under-estimated. Using models, we describe the transmission dynamics, determine the incidence estimates and assess the level of underestimation of the real burden of rubella infection in Zambia during the pre-vaccination period 2005–2016. This study used both the deterministic compartmental model and likelihood-based method using a Bayesian framework to describe the epidemiology of rubella. A total of 1313 cases of rubella were confirmed with the highest annual number of 255 new cases recorded in 2008. However, 2014 recorded the highest monthly median positivity rate of 9.0%. The observed median rubella cases were 5.5. There was a seasonal pattern in the occurrence of laboratory-confirmed rubella, with higher test positivity rates of rubella infection usually recorded in the months of September, October and November. The modelled monthly median incidence of rubella infection among the general population was 76 and 20 among pregnant women. The incidence of rubella among the non-pregnant women was 44. The average effective reproductive number (Rt) between 2005 and 2016 was estimated as 1.2 with the peak of infection occurring in 2016. The measles surveillance system underestimates the observed burden of rubella. A mass vaccination campaign conducted between January and July is recommended.

Previous studies have suggested that a hospital patient's risk of developing healthcare facility-onset (HCFO) Clostridioides difficile infections (CDIs) increases with the number of concurrent spatially proximate patients with CDI, termed CDI pressure. However, these studies were performed either in a single institution or in a single state with a very coarse measure of concurrence. We conducted a retrospective case-control study involving over 17.5 million inpatient visits across 700 hospitals in eight US states. We built a weighted, directed network connecting overlapping inpatient visits to measure facility-level CDI pressure. We then matched HCFO-CDIs with non-CDI controls on facility, comorbidities and demographics and performed a conditional logistic regression to determine the odds of developing HCFO-CDI given the number of coincident patient visits with CDI. On average, cases' visits coincided with 9.2 CDI cases, which for an individual with an average length of stay corresponded to an estimated 17.7% (95% CI 12.9–22.7%) increase in the odds of acquiring HCFO-CDI compared to an inpatient visit without concurrent CDI cases or fully isolated from both direct and indirect risks from concurrent CDI cases. These results suggest that, either directly or indirectly, hospital patients with CDI lead to CDIs in non-infected patients with temporally overlapping visits.

The objectives of this study were to define risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in University of Cambridge (UoC) students during a period of increased incidence in October and November 2020. The study design was a survey.

Routine public health surveillance identified an increase in the numbers of UoC students with confirmed SARS-CoV-2 positivity in the 10 days after a national lockdown was announced in the UK on 5th November 2020. Cases were identified both through symptom-triggered testing and a universal asymptomatic testing programme. An online questionnaire was sent to all UoC students on 25 November to investigate risk factors for testing positive in the period after 30th October 2020. This asked about symptoms, SARS-CoV-2 test results, aspects of university life, and attendance at social events in the week prior to lockdown. Univariate and multivariable analyses were undertaken evaluating potential risk factors for SARS-CoV-2 positivity.

Among 3980 students responding to the questionnaire, 99 (2.5%) reported testing SARS-CoV-2 positive in the period studied; 28 (28%) were asymptomatic. We found strong independent associations with SARS-CoV-2 positivity and attendance at two social settings in the City of Cambridge (adjusted odds ratio favouring disease 13.0 (95% CI 6.2–26.9) and 14.2 (95% CI 2.9–70)), with weaker evidence of association with three further social settings. By contrast, we did not observe strong independent associations between disease risk and accommodation type or attendance at a range of activities associated with the university curriculum.

To conclude attendance at social settings can facilitate widespread SARS-CoV-2 transmission in university students. Constraint of transmission in higher education settings needs to emphasise risks outside university premises, as well as a COVID-safe environment within university premises.

Household transmission plays a key role in the spread of COVID-19 through populations. In this paper, we report on the transmission of COVID-19 within households in a metropolitan area in Australia, examine the impact of various factors and highlight priority areas for future public health responses. We collected and reviewed retrospective case report data and follow-up interview responses from households with a positive case of the Delta COVID-19 variant in Queensland in 2021. The overall secondary attack rate (SAR) among household contacts was 29.6% and the mean incubation period for secondary cases was 4.3 days. SAR was higher where the index case was male (57.9% vs. 14.3%) or aged ≤12 years (38.7% vs. 17.4%) but similar for adult contacts that were double vaccinated (35.7%) and unvaccinated (33.3%). Most interview participants emphasised the importance of clear, consistent and compassionate health advice as a key priority for managing outbreaks in the home. The overall rate of household transmission was slightly higher than that reported in previous studies on the wild COVID-19 variant and secondary infections developed more rapidly. While vaccination did not appear to affect the risk of transmission to adult subjects, uptake in the sample was ultimately high.

Prisons are susceptible to outbreaks. Control measures focusing on isolation and cohorting negatively affect wellbeing. We present an outbreak of coronavirus disease 2019 (COVID-19) in a large male prison in Wales, UK, October 2020 to April 2021, and discuss control measures.

We gathered case-information, including demographics, staff-residence postcode, resident cell number, work areas/dates, test results, staff interview dates/notes and resident prison-transfer dates. Epidemiological curves were mapped by prison location. Control measures included isolation (exclusion from work or cell-isolation), cohorting (new admissions and work-area groups), asymptomatic testing (case-finding), removal of communal dining and movement restrictions. Facemask use and enhanced hygiene were already in place. Whole-genome sequencing (WGS) and interviews determined the genetic relationship between cases plausibility of transmission.

Of 453 cases, 53% (n = 242) were staff, most aged 25–34 years (11.5% females, 27.15% males) and symptomatic (64%). Crude attack-rate was higher in staff (29%, 95% CI 26–64%) than in residents (12%, 95% CI 9–15%).

Whole-genome sequencing can help differentiate multiple introductions from person-to-person transmission in prisons. It should be introduced alongside asymptomatic testing as soon as possible to control prison outbreaks. Timely epidemiological investigation, including data visualisation, allowed dynamic risk assessment and proportionate control measures, minimising the reduction in resident welfare.

The duration of immunity after first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the extent to which prior immunity prevents reinfection is uncertain and remains an important question within the context of new variants. This is a retrospective population-based matched observational study where we identified the first polymerase chain reaction (PCR) positive of primary SARS-CoV-2 infection case tests between 1 March 2020 and 30 September 2020. Each case was matched by age, sex, upper tier local authority of residence and testing route to one individual testing negative in the same week (controls) by PCR. After a 90-day pre-follow-up period for cases and controls, any subsequent positive tests up to 31 December 2020 and deaths within 28 days of testing positive were identified, this encompassed an essentially vaccine-free period. We used a conditional logistic regression to analyse the results. There were 517 870 individuals in the matched cohort with 2815 reinfection cases and 12 098 first infections. The protective effect of a prior SARS-CoV-2 PCR-positive episode was 78% (odds ratio (OR) 0.22, 0.21–0.23). Protection rose to 82% (OR 0.18, 0.17–0.19) after a sensitivity analysis excluded 933 individuals with a first test between March and May and a subsequent positive test between June and September 2020. Amongst individuals testing positive by PCR during follow-up, reinfection cases had 77% lower odds of symptoms at the second episode (adjusted OR 0.23, 0.20–0.26) and 45% lower odds of dying in the 28 days after reinfection (adjusted OR 0.55, 0.42–0.71). Prior SARS-CoV-2 infection offered protection against reinfection in this population. There was some evidence that reinfections increased with the alpha variant compared to the wild-type SARS-CoV-2 variant highlighting the importance of continued monitoring as new variants emerge.

The coronavirus disease 2019 (COVID-19) pandemic had an uneven development in different countries. In Argentina, the pandemic began in March 2020 and, during the first 3 months, the vast majority of cases were concentrated in a densely populated region that includes the city of Buenos Aires (country capital) and the Greater Buenos Aires (GBA) area that surrounds it. This work focuses on the spread of COVID-19 between June and November 2020 in GBA. Within this period of time there was no vaccine, basically only the early wild strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was present, and the official restriction and distancing measures in this region remained more or less constant. Under these particular conditions, the incidences show a sharp rise from June 2020 and begin to decrease towards the end of August until the end of November 2020. In this work we study, through mathematical modelling and available epidemiological information, the spread of COVID-19 in this region and period of time. We show that a coherent explanation of the evolution of incidences can be obtained assuming that only a minority fraction of the population got involved in the spread process, so that the incidences decreased as this group of people was becoming immune. The observed evolution of the incidences could then be a consequence at the population level of lasting immunity conferred by SARS-CoV-2.

In general, mass gatherings might pose a risk to the public health (PH). The UEFA EURO 2020 tournament (EURO 2020) was one of the first mass gathering events since the start of the coronavirus disease 2019 (COVID-19) pandemic in Germany. To allow early detection and response to any EURO 2020-associated impact on the COVID-19-related epidemiological situation, we initiated enhanced surveillance activities using the routine surveillance system in collaboration with the regional PH authority of Bavaria. Several preventive measures regarding the attendance of football matches and public viewing were implemented according to state regulations. We describe the results from the enhanced surveillance during the EURO 2020. In total, five cases who had attended a football match in the stadium of Munich, nine cases, who attended a football match in a stadium outside of Germany, and 123 cases in association with public viewing events were identified by enhanced surveillance. Concluding, the EURO 2020 seems to not have had a major impact on the COVID-19 pandemic development in Germany. Health measures for stadium visitors and the restriction of large public viewing events may have potentially contributed to the low case numbers detected, emphasising the need of appropriate PH surveillance and regulations to limit the potential risk to PH during mass gathering events.

Shiga toxin-producing Escherichia coli (STEC) serogroup O157 is a zoonotic, foodborne gastrointestinal pathogen of major public health concern. We describe the epidemiology of STEC O157 infection in England by exploring the microbiological and clinical characteristics, the demographic and geographical distribution of cases, and examining changes in environmental exposures over 11 years of enhanced surveillance. Enhanced surveillance data including microbiological subtyping, clinical presentations and exposures were extracted for all cases resident in England with evidence of STEC O157 infection, either due to faecal culture or serology detection. Incidence rates were calculated based on mid-year population estimates from the Office of National Statistics (ONS). Demographics, geography, severity and environmental exposures were compared across the time periods 2009–2014 and 2015–2019. The number of cases reported to national surveillance decreased, with the mean cases per year dropping from 887 for the period 2009–2014 to 595 for the period 2015–2019. The decline in STEC O157 infections appears to be mirrored by the decrease in cases infected with phage type 21/28. Although the percentage of cases that developed HUS decreased, the percentage of cases reporting bloody diarrhoea and hospitalisation remained stable. The number of outbreaks declined over time, although more refined typing methods linked more cases to each outbreak. Integration of epidemiological data with microbiological typing data is essential to understanding the changes in the burden of STEC infection, assessment of the risks to public health, and the prediction and mitigation of emerging threats.