Community Transmission Research Articles

The impact of the cruise ship coral princess on COVID-19 transmission in regional Western Australia in 2022.

Increased COVID-19 community transmission in regional areas with high Aboriginal populations, limited health infrastructure and low vaccination rates could result in clusters of transmission with increased deaths rates. Pilbara, a regional community with a high Aboriginal population, showed a 34.8% increase in COVID-19 cases in the 4-week post-cruise-ship docking.

Antigen-specific chemokine profiles as biomarkers for detecting Mycobacterium tuberculosis infection.

Latent tuberculosis (TB) infection can progress to active TB, which perpetuates community transmission that undermines global TB control efforts. Clinically, interferon-γ release assays (IGRAs) are commonly used for active TB case detection. However, low IGRA sensitivity rates lead to false-negative results for a high proportion of active TB cases, thus highlighting IGRA ineffectiveness in differentiating MTB-infected individuals from healthy individuals. Participants enrolled at Beijing Chest Hospital from May 2020-April 2022 were assigned to healthy control (HC), LTBI, IGRA-positive TB, and IGRA-negative TB groups. Screening cohort MTB antigen-specific blood plasma chemokine concentrations were measured using Luminex xMAP assays then were verified via testing of validation cohort samples. A total of 302 individuals meeting study inclusion criteria were assigned to screening and validation cohorts. Testing revealed significant differences in blood plasma levels of CXCL9, CXCL10, CXCL16, CXCL21, CCL1, CCL19, CCL27, TNF-α, and IL-4 between IGRA-negative TB and HC groups. Levels of CXCL9, CXCL10, IL-2, and CCL8 biomarkers were predictive for active TB, as reflected by AUC values of ≥0.9. CXCL9-based enzyme-linked immunosorbent assay sensitivity and specificity rates were 95.9% (95%CI: 91.7-98.3) and 100.0% (92.7-100.0), respectively. Statistically similar AUC values were obtained for CXCL9 and CXCL9-CXCL10 assays, thus demonstrating that combined analysis of CXCL10 and CXCL9 levels did not improve active TB diagnostic performance. The MTB antigen stimulation-based CXCL9 assay may compensate for low IGRA diagnostic accuracy when used to diagnose IGRA-negative active TB cases and thus is an accurate and sensitive alternative to IGRAs for detecting MTB infection.

Exploring the syndemic interaction between social, environmental and structural contexts of HIV infection in peri-mining areas in South Africa: a qualitative study

ObjectiveTo explore the syndemic interaction between social, environmental, and structural contexts and HIV infection in peri-mining areas in South Africa.DesignMixed qualitative methods consisting of in-depth interviews (IDIs) and focus group...

A review of bovine tuberculosis transmission risk in European wildlife communities

Abstract Understanding how disease moves through wildlife communities is essential to managing outbreaks of zoonotic diseases across the globe. Bovine tuberculosis is a disease caused by the bacterium Mycobacterium bovis that can threaten domestic and wildlife species. The mechanism by which Mycobacterium bovis is spread between species is still poorly understood. Previous reviews are limited in the breadth of species considered and are primarily concerned with transmission from wildlife to domestic species. We conducted a review and analysis of Mycobacterium bovis prevalence rates in European wildlife species to identify species of concern for the transmission of bovine tuberculosis in a wildlife community. We subsequently conducted a narrative review of these species assessing the risk of Mycobacterium bovis transmission in a wildlife community based on available literature. We calculated weighted mean disease prevalence rates to be highest in fallow deer (Dama dama, 20%), Eurasian badgers (Meles meles, 11%), wild boar (Sus scrofa, 9%) and red foxes (Vulpes vulpes, 4%). We considered these species to be of particular concern for the transmission of Mycobacterium bovis and selected them as the focus of our narrative review and risk assessment. Our risk assessment considered disease pathology, spatiotemporal activity patterns and animal behaviour as factors affecting the likelihood of Mycobacterium bovis transmission between wildlife species. We found that prior research has principally focused on a few individual species, but that Mycobacterium bovis transmission through a wildlife community is likely more complex. We determined that disease transmission between multiple species may compound the severity of an outbreak of bovine tuberculosis. Broad, multi‐species sampling campaigns and standardised Mycobacterium bovis testing protocols should be implemented in future studies. We also determined that an in‐depth analysis of spatiotemporal overlap between species was needed to better assess the risk of transmission between wildlife species.

Lessons Learned from Contact Tracing COVID-19 cases in Dental Settings in East Scotland.

Dental settings were considered high risk settings for COVID-19. A Dental Public Health Team in East Scotland worked to risk assess each situation timeously to break chains of transmission. To present learning from routine data collected from contact tracing COVID-19 cases in the dental setting. Retrospective analysis of a routine data set of COVID-19 cases associated with a dental setting reported via the national contact tracing system for two health board areas in the East of Scotland. Descriptive statistics summarise the data collected over a 13-month period (Oct 2020-Dec 2021) during which all included COVID-19 cases were confirmed by PCR. A narrative presents output from contact tracing of all cases and includes themes identified during contact tracing that led to transmission within a dental setting. A case study illustrates impact of transmission. 752 cases are included. No evidence of staff to patient transmission or vice versa was found in this study. Staff to staff transmission occurred in non-clinical areas contributing to 33% of total staff cases with the remainder assessed to result from community transmission. Transmission of COVID-19 in a dental setting, in the context of this study, appears to be confined to non-clinical areas with the majority of staff cases resulting from community transmission. Future pandemic plans should include tools to aid with implementation of guidance in non-clinical areas.

Underdetected dispersal and extensive local transmission drove the 2022 mpox epidemic

The World Health Organization declared mpox a public health emergency of international concern in July 2022. To investigate global mpox transmission and population-level changes associated with controlling spread, we built phylogeographic and phylodynamic models to analyze MPXV genomes from five global regions together with air traffic and epidemiological data. Our models reveal community transmission prior to detection, changes in case reporting throughout the epidemic, and a large degree of transmission heterogeneity. We find that viral introductions played a limited role in prolonging spread after initial dissemination, suggesting that travel bans would have had only a minor impact. We find that mpox transmission in North America began declining before more than 10% of high-risk individuals in the USA had vaccine-induced immunity. Our findings highlight the importance of broader routine specimen screening surveillance for emerging infectious diseases and of joint integration of genomic and epidemiological information for early outbreak control.

Delay in seeking treatment and associated factors among pulmonary tuberculosis patients attending public health facilities in the Metekel zone, Benishangul Gumuz region, Western Ethiopia.

Tuberculosis is a major global public health problem and a leading cause of morbidity and mortality in Ethiopia. TB prevention and control in low-income countries, such as Ethiopia, face significant challenges, including late detection and treatment initiation. A delay in the initiation of tuberculosis treatment increases the morbidity and mortality of patients and community transmission. Therefore, this study aimed to assess patient delay and associated factors among pulmonary tuberculosis patients attending public health facilities in the Metekel Zone, Benishangul Gumuz Region, Western Ethiopia. An institution-based cross-sectional study was conducted from March to August 2020 among newly diagnosed pulmonary tuberculosis patients. All pulmonary tuberculosis patients (416) who came to all public health facilities of the Metekel zone for treatment during the period were included. Data were collected through face-to-face interviews using a structured and pretested questionnaire. A multivariable logistic regression was fitted to identify independent factors for delay in seeking treatment among PTB patients. Adjusted odds ratios with 95% CIs were determined, and variables with p values <0.05 were considered statistically significant. Nearly three-fourths 302 (72.6, 95% CI: 68.5, 76.7) of the patients were delayed in seeking medical advice, with a median patient delay of 27 days (IQR: 21-31). Age of the patients [above 54 years (AOR = 2.65, 95% CI: 1.30, 5.40), 36-54 years (AOR = 1.86, 95% CI: 1.14,3.02)], family size of 5 members and above (AOR = 1.62, 95% CI: 1.10-3.14), travel time above 60 min (AOR = 3.65, 95% CI: 1.55, 8.60), history of visits to informal care providers (AOR = 1.74, 95% CI: 1.11, 3.14), and poor knowledge about PTB (AOR = 1.64, 95% CI: 1.04-2.44) were statistically significant factors associated with delays in seeking treatment among PTB patients. Most pulmonary tuberculosis patients delay seeking medical advice for their illnesses. Delays in seeking treatment were associated with older age, large household size, longer travel time to reach the nearby health facility, visiting informal care providers, and poor knowledge about pulmonary tuberculosis. Hence, it is crucial to consider community screening programs, enhance public awareness, and ensure the accessibility of TB diagnostic and treatment services.

Leprosy in North India in Post-Elimination Era: A Retrospective Study

Abstract Background: India achieved elimination target for leprosy in December 2005. However, many pockets in the country continue to report significant number of cases. Aim: The aim of the study was to study the profile of leprosy cases presenting to a tertiary care hospital in North India in post-elimination era. Patients and Methods: The study was conducted at Hansen’s disease clinic. The study design was a retrospective observational study. Chart review of treatment naive leprosy patients enrolled between 1st January 2018 and 31st December 2019 was done. Data regarding demographic profile, clinical spectrum of leprosy, slit-skin smears (SSSs) and histopathological findings were analysed. Statistical Analysis: Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) software version 23 (SPSS Inc., Chicago, IL, USA). Data were statistically described in terms of range, mean ± standard deviation, frequency (number of cases), and relative frequency (percentages). Results: Amongst a total of 115 patients, males (68%, n = 79/115) outnumbered females. Children (&lt;15 years) constituted 0.86% cases (n = 1/115) and 26% cases (n = 30/115) were above 50 years of age. Multibacillary leprosy (73%, n = 84/115) was more common. Borderline lepromatous (41.7%, n = 48/115) was the most common clinical type of leprosy, whereas Grade 2 disability was noted amongst 0.05% (n = 6/115) patients at presentation. SSS were positive in 60% (69/115) cases. Conclusions: The present study showed a significant increase in cases in the older age group and decrease in new cases in children. Furthermore, multibacillary cases outnumbered the paucibacillary cases. Similar trends were reported to be an indicator of decreasing incidence of leprosy in countries that eliminated leprosy. We speculate that India may be entering a phase of decreased community transmission of leprosy. Further, multicentric studies across the country may throw more light.

Overestimation of Severe Acute Respiratory Syndrome Coronavirus 2 Household Transmission in Settings of High Community Transmission: Insights From an Informal Settlement Community in Salvador, Brazil.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has spread globally. However, the contribution of community versus household transmission to the overall risk of infection remains unclear. Between November 2021 and March 2022, we conducted an active case-finding study in an urban informal settlement with biweekly visits across 1174 households with 3364 residents. Individuals displaying coronavirus disease 2019 (COVID-19)-related symptoms were identified, interviewed along with household contacts, and defined as index and secondary cases based on reverse-transcription polymerase chain reaction (RT-PCR) and symptom onset. In 61 households, we detected a total of 94 RT-PCR-positive cases. Of 69 sequenced samples, 67 cases (97.1%) were attributed to the Omicron BA.1* variant. Among 35 of their households, the secondary attack rate was 50.0% (95% confidence interval [CI], 37.0%-63.0%). Women (relative risk [RR], 1.6 [95% CI, .9-2.7]), older individuals (median difference, 15 [95% CI, 2-21] years), and those reporting symptoms (RR, 1.73 [95% CI, 1.0-3.0]) had a significantly increased risk for SARS-CoV-2 secondary infection. Genomic analysis revealed substantial acquisition of viruses from the community even among households with other SARS-CoV-2 infections. After excluding community acquisition, we estimated a household secondary attack rate of 24.2% (95% CI, 11.9%-40.9%). These findings underscore the ongoing risk of community acquisition of SARS-CoV-2 among households with current infections. The observed high attack rate necessitates swift booster vaccination, rapid testing availability, and therapeutic options to mitigate the severe outcomes of COVID-19.

COVID-19 Vaccine Perspective From Adolescents' Lens in the US.

Introduction The COVID-19 pandemic has presented an unprecedented global health issue. The World Health Organization estimates 773 million confirmed cases and 7 million deaths. Vaccination continues to be the most effective way to prevent COVID-19 and has demonstrated safety and efficacy in all age groups. Though a lot of studies have looked at COVID-19 vaccination acceptance and hesitancy in adults, there is scarce research addressing adolescent vaccination readiness. COVID-19 infection in this age group may result in lost school days, school and community transmission, and loss of productivity for parents. Aim This study aims to determine COVID-19 vaccination rates and factors influencing its acceptance and hesitancy in adolescents in a community setting. Methods A voluntary survey was conducted at a local high school in May 2023. Information was collected about the demographics of adolescents and the educational background of parents/guardians. The survey assessed the COVIDvaccine rate, reasons for COVID-19 vaccine acceptance or refusal, number of doses of COVID-19 vaccine and boosters received, prior history of COVID-19 infection, source of information on COVID-19 vaccine, flu vaccine acceptance by the students, and whether they would be willing to take a COVID-19 vaccine booster. Results Four hundred participants, ranging in age from 13 to 19, were surveyed. The vaccination rate in boys was comparable to that in girls. 72% received at least one COVID-19 vaccine, and 66% were considered completely vaccinated. Of those completely vaccinated, 80% had undergone further updated COVID-19 booster vaccinations. Adolescents whose parents/guardians were college graduates had a higher vaccination rate than those whose parents/guardians were not. Caucasians and Asians had a higher vaccination rate compared to African Americans and mixed races. The vaccination rate was not statistically different in adolescents with prior COVID-19 infection versus no prior infection. Flu vaccination was associated with higher COVID-19 vaccination rates. Lack of trust was an important reason for vaccine hesitancy, along with questions about efficacy, concerns about side effects, parent/guardian decisions, and religious reasons. Protecting oneself, family/friends, and community were the major reasons to take the vaccine. Parents/guardians, physicians, peers, television, social media, flyers, and schools were the primary sources that adolescents relied on for information about the COVID-19 vaccination. Conclusion Lower education attainment among parents/guardians, African Americans, and mixed races was associated with lower vaccination rates. Lack of trust in the vaccine, questions about efficacy, and fear of side effects were the most frequently cited reasons for vaccine hesitancy. Parent/guardian influence and religious reasons were other significant reasons for vaccine hesitancy. Flu vaccination was associated with higher COVID-19 vaccination rates. Understanding factors influencing COVID-19 vaccination will allow us to address barriers to COVID-19 vaccination and other vaccinations appropriate for this age group. Educating adolescents in schools, involving local and state health departments to increase awareness about the vaccine, and educating parents and guardians along with the teenagers can help increase the acceptance of the vaccine. These interventions will also positively affect the acceptance of the booster and prepare us for any future pandemics.

Infectious Disease in the Workplace: Quantifying Uncertainty in Transmission

Understanding disease transmission in the workplace is essential for protecting workers. To model disease outbreaks, the small populations in many workplaces require that stochastic effects are considered, which results in higher uncertainty. The aim of this study was to quantify and interpret the uncertainty inherent in such circumstances. We assessed how uncertainty of an outbreak in workplaces depends on i) the infection dynamics in the community, ii) the workforce size, iii) spatial structure in the workplace, iv) heterogeneity in susceptibility of workers, and v) heterogeneity in infectiousness of workers. To address these questions, we developed a multiscale model: A deterministic model to predict community transmission, and a stochastic model to predict workplace transmission. We extended this basic workplace model to allow for spatial structure, and heterogeneity in susceptibility and infectiousness in workers. We found a non-monotonic relationship between the workplace transmission rate and the coefficient of variation (CV), which we use as a measure of uncertainty. Increasing community transmission, workforce size and heterogeneity in susceptibility decreased the CV. Conversely, increasing the level of spatial structure and heterogeneity in infectiousness increased the CV. However, when the model predicts bimodal distributions, for example when community transmission is low and workplace transmission is high, the CV fails to capture this uncertainty. Overall, our work informs modellers and policy makers on how model complexity impacts outbreak uncertainty. In particular: workforce size, community and workplace transmission, spatial structure and individual heterogeneity contribute in a specific and individual manner to the predicted workplace outbreak size distribution.

A call to invest in post-TB lung disease to halt TB transmission in communities.

A call to invest in post-TB lung disease to halt TB transmission in communities.

Impact of the COVID-19 related border restrictions on influenza and other common respiratory viral infections in New Zealand.

New Zealand's (NZ) complete absence of community transmission of influenza and respiratory syncytial virus (RSV) after May 2020, likely due to COVID-19 elimination measures, provided a rare opportunity to assess the impact of border restrictions on common respiratory viral infections over the ensuing 2 years. We collected the data from multiple surveillance systems, including hospital-based severe acute respiratory infection surveillance, SHIVERS-II, -III and -IV community cohorts for acute respiratory infection (ARI) surveillance, HealthStat sentinel general practice (GP) based influenza-like illness surveillance and SHIVERS-V sentinel GP-based ARI surveillance, SHIVERS-V traveller ARI surveillance and laboratory-based surveillance. We described the data on influenza, RSV and other respiratory viral infections in NZ before, during and after various stages of the COVID related border restrictions. We observed that border closure to most people, and mandatory government-managed isolation and quarantine on arrival for those allowed to enter, appeared to be effective in keeping influenza and RSV infections out of the NZ community. Border restrictions did not affect community transmission of other respiratory viruses such as rhinovirus and parainfluenza virus type-1. Partial border relaxations through quarantine-free travel with Australia and other countries were quickly followed by importation of RSV in 2021 and influenza in 2022. Our findings inform future pandemic preparedness and strategies to model and manage the impact of influenza and other respiratory viral threats.

Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey

Key epidemiological parameters, including the effective reproduction number, R(t), and the instantaneous growth rate, r(t), generated from an ensemble of models, have been informing public health policy throughout the COVID-19 pandemic in the four nations of the United Kingdom of Great Britain and Northern Ireland (UK). However, estimation of these quantities became challenging with the scaling down of surveillance systems as part of the transition from the “emergency” to “endemic” phase of the pandemic.The Office for National Statistics (ONS) COVID-19 Infection Survey (CIS) provided an opportunity to continue estimating these parameters in the absence of other data streams. We used a penalised spline model fitted to the publicly-available ONS CIS test positivity estimates to produce a smoothed estimate of the prevalence of SARS-CoV-2 positivity over time. The resulting fitted curve was used to estimate the “ONS-based” R(t) and r(t) across the four nations of the UK. Estimates produced under this model are compared to government-published estimates with particular consideration given to the contribution that this single data stream can offer in the estimation of these parameters.Depending on the nation and parameter, we found that up to 77% of the variance in the government-published estimates can be explained by the ONS-based estimates, demonstrating the value of this singular data stream to track the epidemic in each of the four nations. We additionally find that the ONS-based estimates uncover epidemic trends earlier than the corresponding government-published estimates.Our work shows that the ONS CIS can be used to generate key COVID-19 epidemiological parameters across the four UK nations, further underlining the enormous value of such population-level studies of infection. This is not intended as an alternative to ensemble modelling, rather it is intended as a potential solution to the aforementioned challenge faced by public health officials in the UK in early 2022.

Pooling sputum samples for the Xpert MTB/RIF assay: a practical screening strategy for highly infectious tuberculosis cases

The Xpert MTB/RIF test (Xpert) can help in the accurate screening of tuberculosis, however, its widespread use is limited by its high cost and lack of accessibility. Pooling of sputum samples for testing is a strategy to cut expenses and enhance population coverage but may result in a decrease in detection sensitivity due to the dilution of Mycobacterium tuberculosis (Mtb) by sample mixing. We investigated how the mixing ratio affected the detection performance of Xpert. We used frozen sputum samples that had been kept after individual Xpert assays of the sputa from Mtb-confirmed TB patients and non-TB patients. Our results showed that the overall sensitivity of the Xpert pooling assay remained higher than 80% when the mixing ratio was between 1/2 and 1/8. When the mixing ratio was raised to 1/16, the positive detection rate fell to 69.0%. For patients with either a high sputum Mtb smear score ≥ 2+, a time-to-positive culture ≤ 10 days, or an Xpert test indicating a high or medium abundance of bacteria, the pooling assay positivity rates were 93.3%, 96.8%, and 100% respectively, even at a 1/16 mixing ratio. For participants with cavities and cough, the pooling assay positivity rates were 86.2% and 90.0% at a 1/8 ratio, higher than for those without these signs. Our results show that the Xpert pooled assay has a high overall sensitivity, especially for highly infectious patients. This pooling strategy with lower reagent and labor costs could support TB screening in communities with limited resources, thereby facilitating reductions in the community transmission and incidence of TB worldwide.

Hospital outbreak of Carbapenem-resistant acinetobacter baumannii in the context of local facility transmission

Carbapenem-resistant Acinetobacter baumannii are of increasing concern in the health care setting. We describe a cluster of 9 cases in hospitalized patients over a 3-month period that reflected ongoing community transmission from high-risk facilities. Robust surveillance and knowledge of local epidemiology are critical to mitigating onward transmission in the health care setting.

Road networks and socio-demographic factors to explore COVID-19 infection during its different waves

The COVID-19 pandemic triggered an unprecedented level of restrictive measures globally. Most countries resorted to lockdowns at some point to buy the much-needed time for flattening the curve and scaling up vaccination and treatment capacity. Although lockdowns, social distancing and business closures generally slowed the case growth, there is a growing concern about these restrictions' social, economic and psychological impact, especially on the disadvantaged and poorer segments of society. While we are all in this together, these segments often take the heavier toll of the pandemic and face harsher restrictions or get blamed for community transmission. This study proposes a road-network-based networked approach to model mobility patterns between localities during lockdown stages. It utilises a panel regression method to analyse the effects of mobility in transmitting COVID-19 in an Australian context, together with a close look at a suburban population’s characteristics like their age, income and education. Firstly, we attempt to model how the local road networks between the neighbouring suburbs (i.e., neighbourhood measure) and current infection count affect the case growth and how they differ between delta and omicron variants. We use a geographic information system, population and infection data to measure road connections, mobility and transmission probability across the suburbs. We then looked at three socio-demographic variables: age, education and income and explored how they moderate independent and dependent variables (infection rates and neighbourhood measures). The result shows strong model performance to predict infection rate based on neighbourhood road connection. However, apart from age in the delta variant context, the other variables (income and education level) do not seem to moderate the relationship between infection rate and neighbourhood measure. The results indicate that suburbs with a more socio-economically disadvantaged population do not necessarily contribute to more community transmission. The study findings could be potentially helpful for stakeholders in tailoring any health decision for future pandemics.

SARS-CoV-2 Delta and Omicron community transmission networks as added value to contact tracing

Calculations of SARS-CoV-2 transmission networks at a population level have been limited. Networks that estimate infections between individuals and whether this results in a mutation, can be a way to evaluate fitness of a mutational clone by how much it expands in number as well as determining the likelihood a transmission results in a new variant. Australian Delta and Omicron SARS-CoV-2 sequences were downloaded from GISAID. Transmission networks of infection between individuals were estimated using a novel mathematical method. Many of the sequences were identical, with clone sizes following power law distributions driven by negative binomial probability distributions for both the number of infections per individual and the number of mutations per transmission (median 0.74 nucleotide changes for Delta and 0.71 for Omicron). Using these distributions, an agent-based model was able to replicate the observed clonal network structure, providing a basis for more detailed COVID-19 modelling. Possible recombination events, tracked by insertion/deletion (indel) patterns, were identified for each variant in these outbreaks. This modelling approach reveals key transmission characteristics of SARS-CoV-2 and may complement traditional contact tracing. This methodology can also be applied to other diseases as genetic sequencing of viruses becomes more commonplace.

Predictors of later COVID-19 test seeking.

Delays in COVID-19 testing may increase the risk of secondary household and community transmission. Little is known about what patient characteristics and symptom profiles are associated with delays in test seeking. We conducted a retrospective cohort study of all symptomatic patients diagnosed with COVID-19 and assessed in a COVID Expansion to Outpatients (COVIDEO) virtual care program between March 2020 and June 2021. The primary outcome was later test seeking more than 3 days from symptom onset. Multivariable logistic regression was used to examine predictors of later testing including patient characteristics and symptoms (30 individual symptoms or 7 symptom clusters). Of 5,363 COVIDEO patients, 4,607 were eligible and 2,155/4,607 (46.8%) underwent later testing. Older age was associated with increased odds of late testing (adjusted odds ratio [aOR] 1.007/year; 95% CI 1.00 to 1.01), as was history of recent travel (aOR 1.4; 95% CI 1.01 to 1.95). Health care workers had lower odds of late testing (aOR 0.50; 95% CI 0.39 to 0.62). Late testing was associated with symptoms in the cardiorespiratory (aOR 1.2; 95% CI 1.05, 1.36), gastrointestinal (aOR = 1.2; 95% CI 1.04, 1.4), neurological (aOR 1.1; 95% CI 1.003, 1.3) and psychiatric (aOR 1.3; 95% CI 1.1, 1.5) symptom clusters. Among individual symptoms, dyspnea, anosmia, dysgeusia, sputum, and anorexia were associated with late testing; pharyngitis, myalgia, and headache were associated with early testing. Certain patient characteristics and symptoms are associated with later testing, and warrant further efforts to encourage earlier testing to minimize transmission.

Changing genomic epidemiology of COVID-19 in long-term care facilities during the 2020–2022 pandemic, Washington State

BackgroundLong-term care facilities (LTCFs) are vulnerable to disease outbreaks. Here, we jointly analyze SARS-CoV-2 genomic and paired epidemiologic data from LTCFs and surrounding communities in Washington state (WA) to assess transmission patterns during 2020–2022, in a setting of changing policy. We describe sequencing efforts and genomic epidemiologic findings across LTCFs and perform in-depth analysis in a single county.MethodsWe assessed genomic data representativeness, built phylogenetic trees, and conducted discrete trait analysis to estimate introduction sizes over time, and explored selected outbreaks to further characterize transmission events.ResultsWe found that transmission dynamics among cases associated with LTCFs in WA changed over the course of the COVID-19 pandemic, with variable introduction rates into LTCFs, but decreasing amplification within LTCFs. SARS-CoV-2 lineages circulating in LTCFs were similar to those circulating in communities at the same time. Transmission between staff and residents was bi-directional.ConclusionsUnderstanding transmission dynamics within and between LTCFs using genomic epidemiology on a broad scale can assist in targeting policies and prevention efforts. Tracking facility-level outbreaks can help differentiate intra-facility outbreaks from high community transmission with repeated introduction events. Based on our study findings, methods for routine tree building and overlay of epidemiologic data for hypothesis generation by public health practitioners are recommended. Discrete trait analysis added valuable insight and can be considered when representative sequencing is performed. Cluster detection tools, especially those that rely on distance thresholds, may be of more limited use given current data capture and timeliness. Importantly, we noted a decrease in data capture from LTCFs over time. Depending on goals for use of genomic data, sentinel surveillance should be increased or targeted surveillance implemented to ensure available data for analysis.